Survival Of Breast Cancer Patients Research Articles

The therapeutic effect and targets of herba Sarcandrae on breast cancer and the construction of a prognostic signature consisting of inflammation-related genes

BackgroundThe prevalence of breast cancer (BRCA), which is common among women, is on the rise. This study applied network pharmacology to explore the potential mechanism of action of herba sarcandrae in BRCA and construct a prognostic signature composed of inflammation-related genes. MethodsThe active ingredients of herba sarcandrae were screened using the SymMap, TCMID, and TCMSP platforms, and the molecular targets were determined in the UniProt database. The “drug-active compound-potential target” network was established with Cytoscape 3.7.2. The molecular targets were subjected to disease ontology, gene ontology (GO), and Kyoto Encyclopedia of Genes (KEGG) analyses. AutoDock software was used for molecular docking. Differentially expressed genes (DEGs) related to inflammation were obtained from the BRCA Cancer Genome Atlas (TCGA) database. In the training cohort, the univariate Cox regression model was applied to preliminarily screen prognostic genes. A multigene signature was built by the least absolute shrinkage and selection operator (LASSO) regression model, followed by validation through Kaplan‒Meier, Cox, and receiver operating characteristic (ROC) analyses. ResultsForty-one active compounds were identified, and 265 therapeutic targets for herba sarcandrae were predicted. GO enrichment results revealed significant enrichment of biological processes, such as response to xenobiotic stimuli, response to nutrient levels, and response to lipopolysaccharide. KEGG analysis revealed significant enrichment of pathways such as AGE-RAGE and chemical carcinogenesis receptor activation signaling pathways. In addition, the herbs Marc-Andre and rutin were shown to mediate BRCA cell proliferation and apoptosis via the interferon regulatory factor 1 (IRF1)/signal transducer and activator of transcription 3 (STAT3)/programmed death-ligand 1 (PD-L1) pathway. Sixteen inflammatory signatures, including BST2, GPR132, IL12B, IL18, IL1R1, IL2RB, IRF1, and others, were constructed, and the risk score was found to be a strong independent prognostic factor for overall survival in BRCA patients. The 16-inflammation signature was associated with several clinical features (age, clinical stage, T, and N classifications) and could reflect immune cell infiltration in tumor microenvironments with different immune cells. ConclusionsHerba sarcandrae and rutin were shown to mediate BRCA cell proliferation and apoptosis via the IRF1/STAT3/PD-L1 pathway, and the 16-member inflammatory signature might be a novel biomarker for predicting BRCA patient prognosis, providing more accurate guidance for clinical treatment prognosis evaluation and having important reference value for individualized treatment selection.

Unraveling breast cancer prognosis: a novel model based on coagulation-related genes.

Breast cancer is highly heterogeneous, presenting challenges in prognostic assessment. Developing a universally applicable prognostic model could simplify clinical decision-making. This study aims to develop and validate a novel breast cancer prognosis model using coagulation-related genes with broad clinical applicability. A total of 203 genes related to coagulation were obtained from the KEGG database, and the mRNA data of 1,099 tumor tissue samples and 572 samples of normal tissue were retrieved from the TCGA-BRCA cohort and GTEx databases. The R package "limma" was utilized to detect variations in gene expression related to coagulation between the malignancies and normal tissue. A model was constructed in the TCGA cohort through a multivariable Cox regression analysis, followed by validation using the GSE42568 dataset as the testing set. Constructing a nomogram incorporating clinical factors to enhance the predictive capacity of the model. Utilizing the ESTIMATE algorithm to investigate the immune infiltration levels in groups with deferent risk. Performing drug sensitivity analysis using the "oncoPredict" package. A risk model consisting of six coagulation-associated genes (SERPINA1, SERPINF2, C1S, CFB, RASGRP1, and TLN2) was created and successfully tested for validation. Identified were 6 genes that serve as protective factors in the model's development. Kaplan-Meier curves revealed a worse prognosis in the high-risk group compared to the low-risk group. The ROC analysis showed that the model accurately forecasted the overall survival (OS) of breast cancer patients at 1, 3, and 5 years. Nomogram accompanied by calibration curves can also provide better guidance for clinical decision-making. The low-risk group is more likely to respond well to immunotherapy, whereas the high-risk group may show improved responses to Gemcitabine treatment. Furthermore, individuals in distinct risk categories displayed different responses to various medications within the identical therapeutic category. We established a breast cancer prognostic model incorporating six coagulation-associated genes and explored its clinical utility. This model offers valuable insights for clinical decision-making and drug selection in breast cancer patients, contributing to personalized and precise treatment advancements.

The A986S calcium sensing receptor variant supports the adaptation of breast cancer cells to high calcium — a novel paradigm in breast cancer progression

Breast cancer and other solid tumors that metastasize to bone are frequently accompanied by a progressive increase in circulating calcium as the disease becomes more malignant. The increase in circulating calcium not only disrupts systemic calcium homeostasis but also alters the ability of cells to sense slight changes in extracellular Ca2+ via the ubiquitous calcium sensing receptor (CaSR). Of the CASR polymorphisms at rs1801725 (p.A986S), rs1801726 (p.Q1011E), and rs1042636 (p.R990G) in exon 7 of the receptor, previous studies have shown that only the A986S CaSR variant is associated with calcium in breast, prostate and skin cancers. In this study, we assessed if exon 7 inactivating A986S (AS-CaSR) and Q1011E (QE-CaSR) variants of the receptor influence the survival of breast tumor cells at higher Ca2+. We generated isogenic HEK293T and BT-549 cells expressing these CaSR variants and carried out bulk RNA sequencing of high Ca2+ adapted control and breast cancer cells. CaSR expression was detected by western blotting using anti-flag M2 (Sigma) antibody. By using phospho-ERK1/2 as the readout, the activation of AS-CaSR required higher concentrations of Ca2+ (EC50 ~5.28 mM) compared to the QE-CaSR (EC50 of ~3.81 mM) and the wild type (WT-CaSR; EC50 ~3.69 mM) receptor. When the CaSR variants transfected cells initially cultured at 7.5 mM for 6 days, and then sub-cultured in medium containing 7.5 to 20 mM Ca2+, the viability of empty vector control and WT-CaSR transfected cells strongly decreased at Ca2+ levels beyond 7.5 mM and these cells were mostly necrotic at ≥15 mM Ca2+. The QE-CaSR variant transfected cells on the other hand exhibited limited cell death beyond 10 mM Ca2+, while the surviving colonies of the AS-CaSR variant were viable at up to 15 mM Ca2+ with invasive tendencies. Analysis of differentially expressed genes in high Ca2+ adapted mesenchymal-like BT-549 and epithelial MDA-MB-468 breast cancer cells compared to MCF10A control cells revealed a small set of differentially expressed genes that were significantly associated with relapse free survival of basal-like breast cancer patients. Among these genes are ligands and negative regulators of the WNT/FZD pathway. Our data suggest that the A986S-CaSR variant with reduced sensitivity to Ca2+ supported adaptation of TNBC cells at high Ca2+, and that high Ca2+ adaptation of breast cancer cells may be mediated via a panel of high Ca2+ inducible genes with implications in bone metastasis. This study is supported by NIH SC1GM139814, T32AI007281, T32GM144927, T32HL007737; and the American Cancer Society. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

SiRNA treatment targeting integrin α11 overexpressed via EZH2-driven axis inhibits drug-resistant breast cancer progression

BackgroundBreast cancer, the most prevalent cancer in women worldwide, faces treatment challenges due to drug resistance, posing a serious threat to patient survival. The present study aimed to identify the key molecules that drive drug resistance and aggressiveness in breast cancer cells and validate them as therapeutic targets.MethodsTranscriptome microarray and analysis using PANTHER pathway and StemChecker were performed to identify the most significantly expressed genes in tamoxifen-resistant and adriamycin-resistant MCF-7 breast cancer cells. Clinical relevance of the key genes was determined using Kaplan-Meier survival analyses on The Cancer Genome Atlas dataset of breast cancer patients. Gene overexpression/knockdown, spheroid formation, flow cytometric analysis, chromatin immunoprecipitation, immunocytochemistry, wound healing/transwell migration assays, and cancer stem cell transcription factor activation profiling array were used to elucidate the regulatory mechanism of integrin α11 expression. Tumour-bearing xenograft models were used to demonstrate integrin α11 is a potential therapeutic target.ResultsIntegrin α11 was consistently upregulated in drug-resistant breast cancer cells, and its silencing inhibited cancer stem cells (CSCs) and epithelial-mesenchymal transition (EMT) while restoring sensitivity to anticancer drugs. HIF1α, GLI-1, and EZH2 contributed the most to the regulation of integrin α11 and EZH2 expression, with EZH2 being more necessary for EZH2 autoinduction than HIF1α and GLI-1. Additionally, unlike HIF1α or EZH2, GLI-1 was the sole transcription factor activated by integrin-linked focal adhesion kinase, indicating GLI-1 as a key driver of the EZH2-integrin α11 axis operating for cancer stem cell survival and EMT. Kaplan-Meier survival analysis using The Cancer Genome Atlas (TCGA) dataset also revealed both EZH2 and integrin α11 could be strong prognostic factors of relapse-free and overall survival in breast cancer patients. However, the superior efficacy of integrin α11 siRNA therapy over EZH2 siRNA treatment was demonstrated by enhanced inhibition of tumour growth and prolonged survival in murine models bearing tumours.ConclusionOur findings elucidate that integrin α11 is upregulated by EZH2, forming a positive feedback circuit involving FAK-GLI-1 and contributing to drug resistance, cancer stem cell survival and EMT. Taken together, the results suggest integrin α11 as a promising prognostic marker and a powerful therapeutic target for drug-resistant breast cancer.

The relationship of changes in molecular subtypes with metastases and progression-free survival in breast cancer.

Molecular subtyping of breast cancer cells is increasingly being developed as an initial step in selecting therapy and predicting the prognosis of breast cancer patients. During breast cancer, the molecular subtype of cancer cells can change. This study aimed to analyze the relationship between changes in the intrinsic subtype of breast cancer with metastasis and progression-free survival in breast cancer patients. This was a retrospective cohort study of patients diagnosed with breast cancer from 2016 to 2021. The molecular subtypes from the immunohistochemical examination results were recorded twice, and metastasis and progression-free survival (PFS) were recorded. The data were analyzed using the chi-square test and SPSS 26. Of the 44 patients, 19 (43.2%) experienced a change in molecular subtype, and 25 (56.8%) did not. No significant relationship existed between changes in molecular subtype and metastasis (p =0.405). No significant relationship existed between changes in molecular subtype and PFS (p =0.900). A significant relationship was found between changes in the molecular subtype and PFS in the patients with changes in the molecular subtype (p =0.022). Changes in the intrinsic subtype were associated with PFS in breast cancer patients. Patients with an intrinsic subtype that changed to triple-negative showed worse PFS.

Extended Deep-Learning Network for Histopathological Image-Based Multiclass Breast Cancer Classification Using Residual Features

Autonomy of breast cancer classification is a challenging problem, and early diagnosis is highly important. Histopathology images provide microscopic-level details of tissue samples and play a crucial role in the accurate diagnosis and classification of breast cancer. Moreover, advancements in deep learning play an essential role in early cancer diagnosis. However, existing techniques involve unique models for each classification based on the magnification factor and require training numerous models or using a hierarchical approach combining multiple models irrespective of the focus of the cell features. This may lead to lower performance for multiclass categorization. This paper adopts the DenseNet161 network by adding a learnable residual layer. The learnable residual layer enhances the features, providing low-level information. In addition, residual features are obtained from the convolution features of the preceding layer, which ensures that the future size is consistent with the number of channels in DenseNet’s layer. The concatenation of spatial features with residual features helps better learn texture classification without the need for an additional texture feature extraction module. The model was validated for both binary and multiclass categorization of malignant images. The proposed model’s classification accuracy ranges from 94.65% to 100% for binary and multiclass classification, and the error rate is 2.78%. Overall, the suggested model has the potential to improve the survival of breast cancer patients by allowing precise diagnosis and therapy.

Toxoplasma gondii suppresses proliferation and migration of breast cancer cells by regulating their transcriptome

BackgroundBreast cancer is the most common cancer in women worldwide. Toxoplasma gondii (T. gondii) has shown anticancer activity in breast cancer mouse models, and exerted beneficial effect on the survival of breast cancer patients, but the mechanism was unclear.MethodsThe effect of tachyzoites of T. gondii (RH and ME49 strains) on human breast cancer cells (MCF-7 and MDA-MB-231 cells) proliferation and migration was assessed using cell growth curve and wound healing assays. Dual RNA-seq was performed for T. gondii-infected and non-infected cells to determine the differentially expressed genes (DEGs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein–Protein Interaction Networks analysis (PPI) were performed to explore the related signaling pathway and hub genes. Hub genes were validated using the Kaplan–Meier plotter database, and Pathogen Host Interaction (PHI-base) database. The results were verified by qRT-PCR.ResultsThe tachyzoites of T. gondii decreased the expression of Ki67 and increased the expression of E-cadherin, resulting in suppressing the proliferation and migration of infected human breast cancer cells. The inhibitory effect of T. gondii on breast cancer cells showed a significant dose–response relationship. Compared with the control group, 2321 genes were transcriptionally regulated in MCF-7 cells infected with T. gondii, while 169 genes were transcriptionally regulated in infected MDA-MB-231 cells. Among these genes, 698 genes in infected MCF-7 cells and 67 genes in infected MDA-MB-231 cells were validated by the publicly available database. GO and KEGG analyses suggested that several pathways were involved in anticancer function of T. gondii, such as ribosome, interleukin-17 signaling, coronavirus disease pathway, and breast cancer pathway. BRCA1, MYC and IL-6 were identified as the top three hub genes in infected-breast cancer cells based on the connectivity of PPI analysis. In addition, after interacting with breast cancer cells, the expression of ROP16 and ROP18 in T. gondii increased, while the expression of crt, TgIST, GRA15, GRA24 and MIC13 decreased.ConclusionsT. gondii transcriptionally regulates several signaling pathways by altering the hub genes such as BRCA1, MYC and IL-6, which can inhibit the breast tumor growth and migration, hinting at a potential therapeutic strategy.

A Quantitative Bias Analysis Approach to Informative Presence Bias in Electronic Health Records.

Accurate outcome and exposure ascertainment in electronic health record (EHR) data, referred to as EHR phenotyping, relies on the completeness and accuracy of EHR data for each individual. However, some individuals, such as those with a greater comorbidity burden, visit the health care system more frequently and thus have more complete data, compared with others. Ignoring such dependence of exposure and outcome misclassification on visit frequency can bias estimates of associations in EHR analysis. We developed a framework for describing the structure of outcome and exposure misclassification due to informative visit processes in EHR data and assessed the utility of a quantitative bias analysis approach to adjusting for bias induced by informative visit patterns. Using simulations, we found that this method produced unbiased estimates across all informative visit structures, if the phenotype sensitivity and specificity were correctly specified. We applied this method in an example where the association between diabetes and progression-free survival in metastatic breast cancer patients may be subject to informative presence bias. The quantitative bias analysis approach allowed us to evaluate robustness of results to informative presence bias and indicated that findings were unlikely to change across a range of plausible values for phenotype sensitivity and specificity. Researchers using EHR data should carefully consider the informative visit structure reflected in their data and use appropriate approaches such as the quantitative bias analysis approach described here to evaluate robustness of study findings.

Early Stage Breast Cancer: Does Histologic Subtype (Ductal vs. Lobular) Impact 5 Year Overall Survival?

Histology is an important predictor of the behavior of breast cancer. We aim to study the impact of histology on the overall survival (OS) of breast cancer patients. We studied 11,085 breast cancer patients diagnosed with T1-T2 tumors, clinically node-negative and non-metastatic, from 2004 to 2019 included in the National Cancer Database. Kaplan-Meier curves, log-rank tests and Cox regression models were used to study the impact of histology and other variables on OS. In our patient population, 8678 (78.28%) had ductal cancer (IDC), while 2407 (21.71%) had lobular cancer (ILC). ILC patients were significantly more likely to be older, Caucasian, have a lower grade at diagnosis and be hormone receptor-positive compared to IDC patients. There was no statistically significant difference in the 5-year OS of early stage ductal (16.8%) and lobular cancer patients (16.7%) (p = 0.200). Patients of Hispanic and African American origin had worse OS rates compared to non-Hispanic and Caucasian patients, respectively. For node-positive disease, HER2+ tumors and triple-negative tumors, chemotherapy had a positive influence on OS (HR 0.85, 95% CI 0.77-0.93, p = 0.0012). Histology did not have a significant impact on the 5-year OS of early stage breast cancer patients.

RNA-seq-based elucidation of lactylation in breast cancer

IntroductionLactylation is the covalent modification of histones using lactate as a small molecule precursor, playing a role in epigenetic regulation. As a novel protein post-translational modification, it has demonstrated significant relevance in the field of cancer diagnosis and therapy. However, the interaction between lactylation and tumor cells in breast cancer has not been extensively investigated.Material and methodsWe acquired breast cancer-related data from the GEO and TCGA databases. Lactylation-related genes were identified from the differentially expressed genes. We utilized COX and LASSO regression to identify genes with significant prognostic value for constructing a prognostic model and assessing its predictive performance. This model was integrated with clinical parameters to create a nomogram. Finally, we conducted immune infiltration analysis, analyzed differences in biological functions, and assessed drug sensitivity.ResultsWe ultimately identified 3 lactylation-related genes significantly associated with prognosis. These genes were used to construct a prognostic model and calculate a risk score. Using the median score, patients were divided into high-risk and low-risk groups. Notably, the low-risk group patients exhibited better prognosis and higher levels of immune infiltration. GO/KEGG enrichment analysis revealed that PGK1, the gene with the highest HR among these genes, is widely involved in immune, metabolic, and proliferative signaling pathways. Its high expression also correlates with increased sensitivity to anti-tumor drugs.ConclusionsWe showcased the potential of lactylation-based molecular clustering and prognostic profiling for predicting survival, immune status, and treatment response in breast cancer patients. Additionally, we envision the utilization of PGK1 as a diagnostic marker and therapeutic target in the cancer.

A Novel Class of Human ADAM8 Inhibitory Antibodies for Treatment of Triple-Negative Breast Cancer.

New targeted treatments are urgently needed to improve triple-negative breast cancer (TNBC) patient survival. Previously, we identified the cell surface protein A Disintegrin And Metalloprotease 8 (ADAM8) as a driver of TNBC tumor growth and spread via its metalloproteinase and disintegrin (MP and DI) domains. In proof-of-concept studies, we demonstrated that a monoclonal antibody (mAb) that simultaneously inhibits both domains represents a promising therapeutic approach. Here, we screened a hybridoma library using a multistep selection strategy, including flow cytometry for Ab binding to native conformation protein and in vitro cell-based functional assays to isolate a novel panel of highly specific human ADAM8 dual MP and DI inhibitory mAbs, called ADPs. The screening of four top candidates for in vivo anti-cancer activity in an orthotopic MDA-MB-231 TNBC model of ADAM8-driven primary growth identified two lead mAbs, ADP2 and ADP13. Flow cytometry, hydrogen/deuterium exchange-mass spectrometry (HDX-MS) and alanine (ALA) scanning mutagenesis revealed that dual MP and DI inhibition was mediated via binding to the DI. Further testing in mice showed ADP2 and ADP13 reduce aggressive TNBC characteristics, including locoregional regrowth and metastasis, and improve survival, demonstrating strong therapeutic potential. The continued development of these mAbs into an ADAM8-targeted therapy could revolutionize TNBC treatment.

Utilization of Denosumab on Survival in Breast Cancer Patients with Bone Metastasis: A short literature review.

Utilization of Denosumab on Survival in Breast Cancer Patients with Bone Metastasis: A short literature review.

Drug repositioning for immunotherapy in breast cancer using single-cell analysis.

Immunomodulatory peptides, while exhibiting potential antimicrobial, antifungal, and/or antiviral properties, can play a role in stimulating or suppressing the immune system, especially in pathological conditions like breast cancer (BC). Thus, deregulation of these peptides may serve as an immunotherapeutic strategy to enhance the immune response. In this meta-analysis, we utilized single-cell RNA sequencing data and known therapeutic peptides to investigate the deregulation of these peptides in malignant versus normal human breast epithelial cells. We corroborated our findings at the chromatin level using ATAC-seq. Additionally, we assessed the protein levels in various BC cell lines. Moreover, our in-house drug repositioning approach was employed to identify potential drugs that could positively impact the relapse-free survival of BC patients. Considering significantly deregulated therapeutic peptides and their role in BC pathology, our approach aims to downregulate B2M and SLPI, while upregulating PIGR, DEFB1, LTF, CLU, S100A7, and SCGB2A1 in BC epithelial cells through our drug repositioning pipeline. Leveraging the LINCS L1000 database, we propose BRD-A06641369 for B2M downregulation and ST-4070043 and BRD-K97926541 for SLPI downregulation without negatively affecting the MHC complex as a significantly correlated pathway with these two genes. Furthermore, we have compiled a comprehensive list of drugs for the upregulation of other selected immunomodulatory peptides. Employing an immunotherapeutic approach by integrating our drug repositioning pipeline with single-cell analysis, we proposed potential drugs and drug targets to fortify the immune system against BC.

Abstract LB009: Unveiling the significance of DARPP-32 and its partners, including GRB7 and DKK1, in breast cancer: Integrative insights from patient data and cell line transcriptomics

Abstract DARPP-32 plays a crucial role in regulating both protein-phosphatase-1 (PP-1) and protein kinase A (PKA), its function being reliant on its phosphorylation status. We have previously demonstrated that low DARPP-32 expression is associated with adverse survival of breast cancer patients, particularly those with oestrogen receptor (ER) positive disease; however, there is limited information on how DARPP-32 may alter breast cancer cell behaviour. We have recently published an integrative approach using patient data and cell line transcriptomics to understand the role of DARPP-32 in breast cancer. We analysed the transcriptome of T47D ER positive breast cancer cells following DARPP-32 knockdown, including treatments in combination with 17β-estradiol or PKA inhibitor fragment (6-22) amide. 202 differentially expressed transcripts were identified in DARPP-32 knock down cells and treatment of these cells with 17β-estradiol or PKA inhibitor fragment (6-22) amide led to the differential expression of 193 and 181 transcripts respectively. Differentially expressed transcripts were compared with genes identified as associated with DARPP-32 expression in 1980 breast cancer patients within the METABRIC cohort using an Artificial Neural Network approach (ANN). Several genes overlapped with those identified from cell line transcriptomics, including PTK7, TRAF5, and KLK6. Both DKK1 and GRB7 were identified as genes associated with DARPP-32 expression in patients using ANN, therefore protein expression was determined in a large cohort of early-stage breast cancer patients (n>1000). We demonstrated that DKK1 and GRB7 protein expression was significantly correlated with DARPP-32 Threonine-34 phosphorylation levels within the same samples (all P<0.05). We have now applied an ANN-based integrative data mining approach to identify genes with the largest effect on other genes resulting in an interactome map, which was based on genes identified within the cell line transcriptomics and original ANN. 1878 genes were identified for inclusion within an interactome map in the total patient cohort, whereas 1003 were identified in ER negative disease alone and 2144 in ER positive disease alone. Pathway enrichment analysis identified the ubiquitin proteosome pathway, the insulin pathway-protein kinase B signalling cascade and the RAS pathway. This study underscores the significance of DARPP-32, a central molecular switch, in breast cancer, elucidating its impact on patient prognosis and highlighting potential molecular targets for therapeutic intervention. The integrative approach combining patient data with cell line transcriptomics provides insights into the complex mechanisms underlying breast cancer progression and opens avenues for further research and targeted interventions. Citation Format: Behnaz Saidy, Richa Vasan, Megan-Rose Greener, Rosie Durrant, Adelynn Immanuel, Andrew Green, Emad Rakha, Ian Ellis, Graham Ball, Stewart Martin, Sarah J. Storr. Unveiling the significance of DARPP-32 and its partners, including GRB7 and DKK1, in breast cancer: Integrative insights from patient data and cell line transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB009.

An Optimal Framework Based on the GentleBoost Algorithm and Bayesian Optimization for the Prediction of Breast Cancer Patients' Survivability

Breast cancer is a primary cause of cancer-associated mortality among women globally, and early detection and personalized treatment are critical for improving patient outcomes. In this study, we propose an optimal framework for predicting breast cancer patient survivability using the GentleBoost algorithm and Bayesian optimization. The proposed framework combines the strengths of the GentleBoost algorithm, which is a powerful machine-learning algorithm for classification, and Bayesian optimization, which is a powerful optimization technique for hyperparameter tuning. We evaluated the proposed framework using the publicly available breast cancer dataset provided by The Surveillance, Epidemiology, and End Results (SEER) program and compared its performance with several popular single algorithms, including support vector machine (SVM), artificial neural network (ANN), and k-nearest neighbors (KNN). The experimental results demonstrate that the proposed framework outperforms these methods in terms of accuracy (mean= 95.16%, best = 95.35, worst = 95.1%, and SD = 0.008). The values of precision, recall, and f1-score of the best experiment were 92.3 %, 98.2 %, and 95.2 %, respectively, with hyperparameters of (number of learners = 246, learning rate = 0.0011, and maximum number of splits = 1240). The proposed framework has the potential to improve breast cancer patient survival predictions and personalized treatment plans, leading to the improved patient outcomes and reduced healthcare costs.

Prevalence of depressive disorders in breast cancer patients

IntroductionBreast cancer is the most common type of cancer and the leading cause of death from malignant neoplasms in women in Russia and in most countries in the world (Lima et al. EClinicalMedicine 2021; 38 100985). According to an analysis of the incidence and mortality from 36 cancers in 185 countries (Sung et al. CA Cancer J Clin 2021. 3 209-249) in 2020, 2261419 new cases of breast cancer were identified in the world in both sexes, which is accounted for 11.7% of the total cancer incidence. Mortality from breast cancer in 2020 amounted to 684996 cases. Patients with comorbid depression and anxiety disorders experience more severe symptoms, have longer recovery time, use more healthcare resources and have poorer outcome compare to those with cancer alone (Katon et al. Gen Hosp Psychiatry 2007; 2 147-155).ObjectivesAnalytical review of data on the impact of depressive spectrum disorders as comorbid conditions on the survival of breast cancer patients and their quality of life.MethodsThe following databases were searched for publications: PubMed, Embase, CINAHL, PsycINFO, Scopus, Science Citation Index/Social Sciences Citation Index, Cochrane Evidence Based Medicine database. The searches were limited to English language and studies with more than 100 subjects with diagnosed breast cancer where this information was mentioned. The analyzed period is between 1977 and 2018.ResultsThe reported prevalence of depression in breast cancer patients, according to researches, varies 4,5 to 38%. In patients with I-III stage breast cancer depression increased hazards of all-cause mortality by 50% compared to non-depressed patients. Stage-specific analyses demonstrated a 2–2.5 fold increase in breast cancer-specific and all-cause mortality in patients with stage I and II disease (Vodermaier et al. Breast Cancer Res Treat 2014; 2 373-384.). Women with non-metastatic breast cancer who report mild to moderate depressive symptoms in the weeks after surgery have approximately 2.5 times greater risk of death 8–15 years later than women who report little or no depressive symptoms post-surgery (Antoni et al. Gen Hosp Psychiatry 2017; 44 16-21). Depression in advanced cancer not only reduces quality of life but is also an independent predictor of poorer survival (Lloyd-Williams et al. J Affect Disord 2009; 113 127-132.).ConclusionsDepression and anxiety both have adverse effects on recurrence and all-cause mortality in patients with breast cancer. Untreated depression leads to significant increase in incidence and mortality. Depression can debut at any stage of cancer, including the stage of diagnosis. It proves the necessity for affective disorders screening in patients with cancer on the stage of diagnosis. Patients with diagnosed affective disorders should be observed not only by oncologist, but also by a psychotherapist in order to receive the necessary treatment to improve the quality of life and reduce the risk of mortality.Disclosure of InterestNone Declared

Do breast cancer patients have increased risk of complications after primary total hip and total knee arthroplasty?

Breast cancer survivors have known risk factors that might influence the results of total hip arthroplasty (THA) or total knee arthroplasty (TKA). This study evaluated clinical outcomes of patients with breast cancer history after primary THA and TKA. Our total joint registry identified patients with breast cancer history undergoing primary THA (n = 423) and TKA (n = 540). Patients were matched 1:1 based upon age, sex, BMI, procedure (hip or knee), and surgical year to non-breast cancer controls. Mortality, implant survival, and complications were assessed via Kaplan-Meier methods. Clinical outcomes were evaluated via Harris Hip Scores (HHSs) or Knee Society Scores (KSSs). Mean follow-up was six years (2 to 15). Breast cancer patient survival at five years was 92% (95% confidence interval (CI) 89% to 95%) after THA and 94% (95% CI 92% to 97%) after TKA. Breast and non-breast cancer patients had similar five-year implant survival free of any reoperation or revision after THA (p ≥ 0.412) and TKA (p ≥ 0.271). Breast cancer patients demonstrated significantly lower survival free of any complications after THA (91% vs 96%, respectively; hazard ratio = 2 (95% CI 1.1 to 3.4); p = 0.017). Specifically, the rate of intraoperative fracture was 2.4% vs 1.4%, and venous thromboembolism (VTE) was 1.4% and 0.5% for breast cancer and controls, respectively, after THA. No significant difference was noted in any complications after TKA (p ≥ 0.323). Both breast and non-breast cancer patients experienced similar improvements in HHSs (p = 0.514) and KSSs (p = 0.132). Breast cancer survivors did not have a significantly increased risk of mortality or reoperation after primary THA and TKA. However, there was a two-fold increased risk of complications after THA, including intraoperative fracture and VTE.

Pioglitazone enhances cisplatin’s impact on triple-negative breast cancer: Role of PPARγ in cell apoptosis

Peroxisome proliferator-activated receptor-gamma (PPARγ) has been recently shown to play a role in many cancers. The breast tissue of triple-negative breast cancer (TNBC) patients were found to have a significantly lower expression of PPARγ than the other subtypes. Furthermore, PPARγ activation was found to exert anti-tumor effects by inhibiting cell proliferation, differentiation, cell growth, cell cycle, and inducing apoptosis. To start with, we performed a bioinformatic analysis of data from OncoDB, which showed a lower expression pattern of PPARγ in different cancer types. In addition, high expression of PPARγ was associated with better breast cancer patient survival. Therefore, we tested the impact of pioglitazone, a PPARγ ligand, on the cytotoxic activity of cisplatin in the TNBC cell line. MDA-MB-231 cells were treated with either cisplatin (40 μM) with or without pioglitazone (30 or 60 μM) for 72 h. The MTT results showed a significant dose-dependent decrease in cell viability as a result of using cisplatin and pioglitazone combination compared with cisplatin alone. In addition, the protein expression of Bcl-2, a known antiapoptotic marker, decreased in the cells treated with cisplatin and pioglitazone combination at doses of 40 and 30 μM, respectively. On the other hand, cleaved- poly-ADP ribose polymerase (PARP) and -caspase-9, which are known as pro-apoptotic markers, were upregulated in the combination group compared with the solo treatments. Taken together, the addition of pioglitazone to cisplatin further reduced the viability of MDA-MB-231 cells and enhanced apoptosis compared with chemotherapy alone.

Traditional Clinicopathological Biomarkers Still Determine Disease-Free and Overall Survival in Invasive Breast Cancer Patients: A Pilot Study.

Background: Molecular classification, tumor diameter, Ki67 expression, and brachytherapy administration still act as the most potent potential predictors of breast cancer recurrence and overall survival. Methods: Over the period of 23 months, we included in the study 92 invasive breast cancer (IBrC) patients initially diagnosed at the Clinical Ward of Breast Cancer and Reconstructive Surgery, Oncology Center in Bydgoszcz, Poland. The probability of disease-free survival (DFS) and overall survival (OS) in relation to potential prognostic factors for the patients were determined using a Kaplan-Meier analysis, and univariate and multivariate Cox regression analyses evaluated the predictive factors of IBrC patients. The investigation of the potential prognostic model's accuracy was analyzed using the ROC curve. Results: Patients with tumor size < 2 cm, Ki67 expression < 20%, luminal-A molecular subtype, and extra-dose brachytherapy boost administration displayed the most favorable prognosis according to breast cancer disease-free survival and overall survival. The estimated 5 year probability of DFS and OS rates in women with tumor diameter < 2 cm were 89% and 90%, respectively. In tumor diameter > 2 cm, the estimated 5 year probability of DFS was 73% and OS was 76%. Interestingly, the tumor diameter of 1.6 cm with a specificity of 60.5% and a sensitivity of 75% occurred as the best threshold point to differentiate patients with cancer recurrence from those without cancer progression. Conclusions: Our study provides essential information on the clinicopathological profile and future outcomes of early stage IBrC patients. Furthermore, the tumor diameter cut-off value of 1.6 cm discriminating between disease recurrence and those without disease progression patients represents an innovative direction for further research.

Multicenter Study on Breast Cancer in the Geriatric Population: Insights for Effective Treatment Strategies.

Breast cancer is common among women aged 65 and over. There is a significant lack of evidence regarding the treatment of breast cancer in patients in this age group due to the rare inclusion of these patients in clinical studies. However, it is known that survival in elderly patients with breast cancer is significantly reduced in those not receiving standard therapy. Several factors, including patients' comorbidities, performance status, life expectancy, and tumor pathological and molecular characteristics, can affect the outcomes of treatment. In this study, we aimed to update the knowledge in this field by assessing these factors among the geriatric population in our multicenter dataset. This retrospective study analyzed data from 335 breast cancer patients aged 65 and over who received adjuvant radiotherapy at five oncology centers (Kartal Dr. Lutfi Kirdar Training and Research Hospital, Istanbul,Meram Medical Faculty - Necmettin Erbakan University, Konya,Prof. Dr. Cemil Tascioglu City Hospital, Istanbul,Umraniye Training and Research Hospital, Istanbul, andIstanbul Oncology Hospital, Istanbul) between May 2010 and September 2022. Demographic, clinical, and pathological data were collected, including age, gender, clinical symptoms, tumor characteristics, treatment approaches, and outcomes. Statistical analyses, including descriptive statistics, Kaplan-Meier analysis, log-rank test, and Cox regression analysis, were performed using IBMSPSSStatistics for Windows, Version 22 (Released 2013; IBM Corp., Armonk, New York, United States), with a significance level of p < 0.05. The tumor characteristics and survival time of 335 breast cancer patients were examined. In the results, performance status, T stage, and perineural invasion were found to be factors affecting the survival of elderly breast cancer patients. In multivariate analysis, it was seen that performance status played an important role as an independent prognostic factor. The treatment of breast cancer in the geriatric age group necessitates a personalized approach, taking into account the patient's overall health status, life expectancy, and comorbidities.