Computational toxicology models have been successfully implemented to prioritize and screen chemicals. There are numerous in silico (quantitative) structure-activity relationship ([Q]SAR) models for the prediction of a range of human-relevant toxicological endpoints, but for a given endpoint and chemical, not all predictions are identical due to differences in their training sets, algorithms, and methodology. This poses an issue for high-throughput screening of a large chemical inventory as it necessitates several models to cover diverse chemistries but will then generate data conflicts. To address this challenge, we developed a consensus modeling strategy to combine predictions obtained from different existing in silico (Q)SAR models into a single predictive value while also expanding chemical space coverage. This study developed consensus models for nine toxicological endpoints relating to estrogen receptor (ER) and androgen receptor (AR) interactions (i.e., binding, agonism, and antagonism) and genotoxicity (i.e., bacterial mutation, in vitro chromosomal aberration, and in vivo micronucleus). Consensus models were created by combining different (Q)SAR models using various weighting schemes. As a multi-objective optimization problem, there is no single best consensus model, and therefore, Pareto fronts were determined for each endpoint to identify the consensus models that optimize the multiple-criterion decisions simultaneously. Accordingly, this work presents sets of solutions for each endpoint that contain the optimal combination, regardless of the trade-off, with the results demonstrating that the consensus models improved both the predictive power and chemical space coverage. These solutions were further analyzed to find trends between the best consensus models and their components. Here, we demonstrate the development of a flexible and adaptable approach for in silico consensus modeling and its application across nine toxicological endpoints related to ER activity, AR activity, and genotoxicity. These consensus models are developed to be integrated into a larger multi-tier NAM-based framework to prioritize chemicals for further investigation and support the transition to a non-animal approach to risk assessment in Canada.

Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors have led transformative breakthrough of clinical therapy for hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER-2)-negative breast cancer patients. CDK4/6 inhibitors that have been marketed in China include Ribociclib, Palbociclib, Abemaciclib and Dalpiciclib. For HR-positive HER-2-negative locally advanced and metastatic breast cancer, CDK4/6 inhibitors combined with endocrine therapy have become standard regimen, which can prolong the survival of patients. In the adjuvant treatment stage of early breast cancer, CDK4/6 inhibitors have also achieved positive results and been approved for indications. At present, CDK4/6 inhibitors have been widely used in clinical practice in China. In order to further improve the standardized application of CDK4/6 inhibitors in China, the Breast Cancer Expert Committee of the National Center for Cancer Quality Control and the Professional Committee of Clinical Research of Cancer Drugs of the Chinese Anti-Cancer Association organized the related expert to update the consensus based on the \"CDK4/6 inhibitor consensus on clinical application of in the treatment of hormone receptor positive human epidermal growth factor receptor 2 negative advanced breast cancer (2021 edition)\" . The updated consensus systematically introduces the pharmacological characteristics, drug monitoring and adverse event management, etc., of CDK4/6 inhibitors to promote the accuracy of clinical decision-making with the ultimate goal to prolong the overall survival of patients and improve the quality of life.
细胞周期蛋白依赖性激酶4/6 (CDK4/6)抑制剂为激素受体(HR)阳性、人表皮生长因子受体2(HER-2)阴性乳腺癌患者的临床治疗模式带来变革性的突破。中国已上市的CDK4/6抑制剂包括瑞波西利、哌柏西利、阿贝西利和达尔西利。对于HR阳性HER-2阴性局部晚期和转移性乳腺癌，CDK4/6抑制剂联合内分泌治疗已经成为标准方案，能够延长患者的生存。在早期乳腺癌辅助治疗阶段，也已有CDK4/6抑制剂取得阳性结果并获批适应证。目前，CDK4/6抑制剂广泛进入中国临床实践，为进一步提高CDK4/6抑制剂在中国的规范化应用，国家肿瘤质控中心乳腺癌专家委员会和中国抗癌协会肿瘤药物临床研究专业委员会在2021版《CDK4/6抑制剂治疗激素受体阳性人表皮生长因子受体2阴性晚期乳腺癌的临床应用共识》基础上，组织相关领域专家，对该共识进行更新，系统性介绍CDK4/6抑制剂的药理学特征、在晚期及早期乳腺癌中的适应证、患者用药监测以及不良事件管理等，以期推进临床决策的精准性，达到延长患者生存时间和提高生活质量的最终目标。.

This study aimed to evaluate the impacts of 21-gene recurrence score (RS) and St. Gallen International Expert Consensus on treatment decision and prognosis of patients with invasive breast cancer. We retrospectively analyzed the therapy protocol and outcome of 134 cases based on age, body mass index (BMI), menopause, pathological types, tumor-node-metastasis (TNM) stages, percentage of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER2), Ki-67, molecular subtype, and tumor biomarkers. RS was calculated based on 21-gene assay following traditional (old RS cutoff) and updated (new RS cutoff) National Comprehensive Cancer Network (NCCN) guideline. In addition, we also compared treatment protocol of NCCN guidelines with St. Gallen International Expert Consensus. The results showed that BMI, PR, Ki-67, and molecular subtype are critical for the evaluation of risk factors. Based on the new cutoff, low, middle, and high RS were 18%, 66%, and 16%, respectively. In contrast, based on the old cutoff, low, middle, and high RS were 60%, 29%, and 11%, respectively. The agreement rate of NCCN guidelines and St. Gallen International Expert Consensus for adjuvant treatment was 50. However, there is minimal agreement (0.151, 0.071) in kappa coefficient of old and new cutoff. This study revealed that the combination of NCCN guidelines and St. Gallen International Expert Consensus might improve the benefits of adjuvant treatment in patients with early invasive breast cancer.

We describe the first targeted validation of fFLASH, a molecular similarity program from IBM that has been previously proposed as suitable for the virtual screening (VS) of compound libraries based on explicit 3D flexible superimpositions, as part of its deployment within a novel consensus ligand-based virtual screening cascade. A virtual screening protocol using fFLASH for the human estrogen receptor alpha (ERα) was advanced and benchmarked against screens completed using established commercial screening softwares - Catalyst and ROCS. The optimised protocol was applied to a ∼6000 member physical screening collection and virtual \'hits\' sourced and biologically assayed. The approach identified a novel, potent and highly selective partial antagonist of the ERα. This study firstly validates the clique detection algorithm utilised by fFLASH and secondly, emphasises the benefits of the consensus approach of employing more than one program in a VS protocol.

Although there have been several studies on the use of immunohistochemical biomarkers of canine mammary tumors (CMTs), the results are difficult to compare. This article provides guidelines on the most useful immunohistochemical markers to standardize their use and understand how outcomes are measured, thus ensuring reproducibility of results. We have reviewed the biomarkers of canine mammary epithelial and myoepithelial cells and identified those biomarkers that are most useful and those biomarkers for invasion and lymph node micrometastatic disease. A 10% threshold for positive reaction for most of these markers is recommended. Guidelines on immunolabeling for HER2, estrogen receptors (ERs), and progesterone receptors (PRs) are provided along with the specific recommendations for interpretation of the results for each of these biomarkers in CMTs. Only 3+ HER2-positive tumors should be considered positive, as found in human breast cancer. The lack of any known response to adjuvant endocrine therapy of ER- and PR-positive CMTs prevents the use of the biological positive/negative threshold used in human breast cancer. Immunohistochemistry results of ER and PR in CMTs should be reported as the sum of the percentage of positive cells and the intensity of immunolabeling (Allred score). Incorporation of these recommendations in future studies, either prospective or retrospective, will provide a mechanism for the direct comparison of studies and will help to determine whether these biomarkers have prognostic significance. Finally, these biomarkers may ascertain the most appropriate treatment(s) for canine malignant mammary neoplasms.