119 research outputs found
Endocrine therapy and related issues in hormone receptor-positive early breast cancer: a roundtable discussion by the breast cancer therapy expert group (BCTEG)
Purpose: Management of breast cancer is a rapidly evolving field, and, although evidence-based guidelines are available for clinicians to provide direction on critical issues in patient care, clinicians often left to address these issues in the context of community practice situations with their patients. These include the patient’s comorbid conditions, actual versus perceived benefit of treatments, patient’s compliance as well as financial/reimbursement issues, and long-term tolerability of therapy. Methods: A meeting of global oncology experts was convened in January 2017 with the belief that there is a gap in clinical practice guidance on several fundamental issues in breast cancer care, particularly in the community setting, where oncologists may encounter multiple tumor types. The goal was to discuss some of the most important questions in this area and provide some guidance for practicing oncologists. Results: Topics addressed included risk of contralateral breast cancer recurrence in patients with estrogen receptor-positive early breast cancer who have undergone 5 years of adjuvant endocrine therapy, adverse events associated with endocrine therapy and their management, emergent data on adjuvant bisphosphonate therapy and its apparent benefit in reducing breast cancer recurrence, recent findings of extended adjuvant endocrine therapy trials, and the use of currently available genomic biomarker tests as a means of further informing treatment decisions. Conclusions: A summary of the discussion on these topics and several ‘expert opinion statements’ are provided herein in an effort to convey the collective insights of the panel as it relates to current standard practice
Markers for the identification of late breast cancer recurrence
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited
The promise of microarrays in the management and treatment of breast cancer
Breast cancer is the most common malignancy afflicting women from Western cultures. Developments in breast cancer molecular and cellular biology research have brought us closer to understanding the genetic basis of this disease. Recent advances in microarray technology hold the promise of further increasing our understanding of the complexity and heterogeneity of this disease, and providing new avenues for the prognostication and prediction of breast cancer outcomes. These new technologies have some limitations and have yet to be incorporated into clinical use, for both the diagnosis and treatment of women with breast cancer. The most recent application of microarray genomic technologies to studying breast cancer is the focus of this review
Evaluation of applying IHC4 as a prognostic model in the translational study of Intergroup Exemestane Study (IES): PathIES
Background: Intergroup Exemestane Study (IES) was a randomised study that showed a survival benefit of switching adjuvant endocrine therapy after 2–3 years from tamoxifen to exemestane. This PathIES aimed to assess the role of immunohistochemical (IHC)4 score in determining the relative sensitivity to either tamoxifen or sequential treatment with tamoxifen and exemestane. Patients and methods: Primary tumour samples were available for 1274 patients (27% of IES population). Only patients for whom the IHC4 score could be calculated (based on oestrogen receptor, progesterone receptor, HER2 and Ki67) were included in this analysis (N = 430 patients). The clinical score (C) was based on age, grade, tumour size and nodal status. The association of clinicopathological parameters, IHC4(+C) scores and treatment effect with time to distant recurrence-free survival (TTDR) was assessed in univariable and multivariable Cox regression analyses. A modified clinical score (PathIEscore) (N = 350) was also estimated. Results: Our results confirm the prognostic importance of the original IHC4, alone and in conjunction with clinical scores, but no significant difference with treatment effects was observed. The combined IHC4 + Clinical PathIES score was prognostic for TTDR (P < 0.001) with a hazard ratio (HR) of 5.54 (95% CI 1.29–23.70) for a change from 1st quartile (Q1) to Q1–Q3 and HR of 15.54 (95% CI 3.70–65.24) for a change from Q1 to Q4. Conclusion: In the PathIES population, the IHC4 score is useful in predicting long-term relapse in patients who remain disease-free after 2–3 years. This is a first trial to suggest the extending use of IHC4+C score for prognostic indication for patients who have switched endocrine therapies at 2–3 years and who remain disease-free after 2–3 years
Multigene prognostic tests in breast cancer: past, present, future
There is growing consensus that multigene prognostic tests provide useful complementary information to tumor size and grade in estrogen receptor (ER)-positive breast cancers. The tests primarily rely on quantification of ER and proliferation-related genes and combine these into multivariate prediction models. Since ER-negative cancers tend to have higher proliferation rates, the prognostic value of current multigene tests in these cancers is limited. First-generation prognostic signatures (Oncotype DX, MammaPrint, Genomic Grade Index) are substantially more accurate to predict recurrence within the first 5 years than in later years. This has become a limitation with the availability of effective extended adjuvant endocrine therapies. Newer tests (Prosigna, EndoPredict, Breast Cancer Index) appear to possess better prognostic value for late recurrences while also remaining predictive of early relapse. Some clinical prediction problems are more difficult to solve than others: there are no clinically useful prognostic signatures for ER-negative cancers, and drug-specific treatment response predictors also remain elusive. Emerging areas of research involve the development of immune gene signatures that carry modest but significant prognostic value independent of proliferation and ER status and represent candidate predictive markers for immune-targeted therapies. Overall metrics of tumor heterogeneity and genome integrity (for example, homologue recombination deficiency score) are emerging as potential new predictive markers for platinum agents. The recent expansion of high-throughput technology platforms including low-cost sequencing of circulating and tumor-derived DNA and RNA and rapid reliable quantification of microRNA offers new opportunities to build extended prediction models across multiplatform data
ASPP: a new family of oncogenes and tumour suppressor genes
The apoptosis stimulating proteins of p53 (ASPP) family consists of three members, ASPP1, ASPP2 and iASPP. They bind to proteins that are key players in controlling apoptosis (p53, Bcl-2 and RelA/p65) and cell growth (APCL, PP1). So far, the best-known function of the ASPP family members is their ability to regulate the apoptotic function of p53 and its family members, p63 and p73. Biochemical and genetic evidence has shown that ASPP1 and ASPP2 activate, whereas iASPP inhibits, the apoptotic but not the cell-cycle arrest function of p53. The p53 tumour suppressor gene, one of the most frequently mutated genes in human cancer, is capable of suppressing tumour growth through its ability to induce apoptosis or cell-cycle arrest. Thus, the ASPP family of proteins helps to determine how cells choose to die and may therefore be a novel target for cancer therapy
Genomic approaches in the management and treatment of breast cancer
Breast cancer is the most common malignancy afflicting women from Western cultures. It has been estimated that approximately 211 000 women will be diagnosed with breast cancer in 2003 in the United States alone, and each year over 40 000 women will die of this disease. Developments in breast cancer molecular and cellular biology research have brought us closer to understanding the genetic basis of this disease. Unfortunately, this information has not yet been incorporated into the routine diagnosis and treatment of breast cancer in the clinic. Recent advancements in microarray technology hold the promise of further increasing our understanding of the complexity and heterogeneity of this disease, and providing new avenues for the prognostication and prediction of breast cancer outcomes. The most recent application of microarray genomic technologies to studying breast cancer will be the focus of this review
Prospective assessment of the decision-making impact of the Breast Cancer Index in recommending extended adjuvant endocrine therapy for patients with early-stage ER-positive breast cancer
c-Myc overexpression sensitises colon cancer cells to camptothecin-induced apoptosis
The proto-oncogene c-Myc is overexpressed in 70% of colorectal tumours and can modulate proliferation and apoptosis after cytotoxic insult. Using an isogenic cell system, we demonstrate that c-Myc overexpression in colon carcinoma LoVo cells resulted in sensitisation to camptothecin-induced apoptosis, thus identifying c-Myc as a potential marker predicting response of colorectal tumour cells to camptothecin. Both camptothecin exposure and c-Myc overexpression in LoVo cells resulted in elevation of p53 protein levels, suggesting a role of p53 in the c-Myc-imposed sensitisation to the apoptotic effects of camptothecin. This was confirmed by the ability of PFT-alpha, a specific inhibitor of p53, to attenuate camptothecin-induced apoptosis. p53 can induce the expression of p21(Waf1/Cip1), an antiproliferative protein that can facilitate DNA repair and drug resistance. Importantly, although camptothecin treatment markedly increased p21(Waf1/Cip1) levels in parental LoVo cells, this effect was abrogated in c-Myc-overexpressing derivatives. Targeted inactivation of p21(Waf1/Cip1) in HCT116 colon cancer cells resulted in significantly increased levels of apoptosis following treatment with camptothecin, demonstrating the importance of p21(Waf1/Cip1) in the response to this agent. Finally, cDNA microarray analysis was used to identify genes that are modulated in expression by c-Myc upregulation that could serve as additional markers predicting response to camptothecin. Thirty-four sequences were altered in expression over four-fold in two isogenic c-Myc-overexpressing clones compared to parental LoVo cells. Moreover, the expression of 10 of these genes was confirmed to be significantly correlated with response to camptothecin in a panel of 30 colorectal cancer cell lines
Improvement in the Reproducibility and Accuracy of DNA Microarray Quantification by Optimizing Hybridization Conditions
BACKGROUND: DNA microarrays, which have been increasingly used to monitor mRNA transcripts at a global level, can provide detailed insight into cellular processes involved in response to drugs and toxins. This is leading to new understandings of signaling networks that operate in the cell, and the molecular basis of diseases. Custom printed oligonucleotide arrays have proven to be an effective way to facilitate the applications of DNA microarray technology. A successful microarray experiment, however, involves many steps: well-designed oligonucleotide probes, printing, RNA extraction and labeling, hybridization, and imaging. Optimization is essential to generate reliable microarray data. RESULTS: Hybridization and washing steps are crucial for a successful microarray experiment. By following the hybridization and washing conditions recommended by an oligonucleotide provider, it was found that the expression ratios were compressed greater than expected and data analysis revealed a high degree of non-specific binding. A series of experiments was conducted using rat mixed tissue RNA reference material (MTRRM) and other RNA samples to optimize the hybridization and washing conditions. The optimized hybridization and washing conditions greatly reduced the non-specific binding and improved the accuracy of spot intensity measurements. CONCLUSION: The results from the optimized hybridization and washing conditions greatly improved the reproducibility and accuracy of expression ratios. These experiments also suggested the importance of probe designs using better bioinformatics approaches and the need for common reference RNA samples for platform performance evaluation in order to fulfill the potential of DNA microarray technology
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