Background Breast Cancer Patients Research Articles

Minimally Invasive Breast Biopsy After Neoadjuvant Systemic Treatment to Identify Breast Cancer Patients with Residual Disease for Extended Neoadjuvant Treatment: A New Concept

BackgroundBreast cancer patients with residual disease after neoadjuvant systemic treatment (NAST) have a worse prognosis compared with those achieving a pathologic complete response (pCR). Earlier identification of these patients might allow timely, extended neoadjuvant treatment strategies. We explored the feasibility of a vacuum-assisted biopsy (VAB) after NAST to identify patients with residual disease (ypT+ or ypN+) prior to surgery.MethodsWe used data from a multicenter trial, collected at 21 study sites (NCT02948764). The trial included women with cT1-3, cN0/+ breast cancer undergoing routine post-neoadjuvant imaging (ultrasound, MRI, mammography) and VAB prior to surgery. We compared the findings of VAB and routine imaging with the histopathologic evaluation of the surgical specimen.ResultsOf 398 patients, 34 patients with missing ypN status and 127 patients with luminal tumors were excluded. Among the remaining 237 patients, tumor cells in the VAB indicated a surgical non-pCR in all patients (73/73, positive predictive value [PPV] 100%), whereas PPV of routine imaging after NAST was 56.0% (75/134). Sensitivity of the VAB was 72.3% (73/101), and 74.3% for sensitivity of imaging (75/101).ConclusionResidual cancer found in a VAB specimen after NAST always corresponds to non-pCR. Residual cancer assumed on routine imaging after NAST corresponds to actual residual cancer in about half of patients. Response assessment by VAB is not safe for the exclusion of residual cancer. Response assessment by biopsies after NAST may allow studying the new concept of extended neoadjuvant treatment for patients with residual disease in future trials.

Comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer

BackgroundBreast cancer (BRCA) ranks first among cancers in terms of incidence and mortality rates in women, primarily owing to metastasis, chemo-resistance, and heterogeneity. To predict long-term prognosis and design novel therapies for BRCA, more sensitive markers need to be explored. MethodsData from 1089 BRCA patients were downloaded from TCGA database. Pearson's correlation analysis and univariate and multivariate Cox regression analyses were performed to assess the role of cell death-related genes (CDGs) in predicting BRCA prognosis. Kaplan–Meier survival curves were generated to compare the overall survival in the two subgroups. A nomogram was constructed using risk scores based on the five CDGs and other clinicopathological features. CCK-8, EdU incorporation, and colony formation assays were performed to verify the inhibitory effect of NFKBIA on BRCA cell proliferation. Transwell assay, flow cytometry, and immunohistochemistry analyses were performed to ascertain the biological function of NFKBIA. ResultsFive differentially expressed CDGs were detected among 156 CDGs. The risk score for each patient was then calculated based on the expression levels of the five CDGs. Distinct differences in immune infiltration, expression of immune-oncological targets, mutation status, and half-maximal inhibitory concentration values of some targeted drugs were observed between the high- and low-risk groups. Finally, in vitro cell experiments verified that NFKBIA overexpression suppresses the proliferation and migration of BRCA cells. ConclusionsOur study revealed that some CDGs, especially NFKBIA, could serve as sensitive markers for predicting the prognosis of patients with BRCA and designing more personalized clinical therapies.

Exosomal Linc00969 induces trastuzumab resistance in breast cancer by increasing HER-2 protein expression and mRNA stability by binding to HUR

BackgroundBreast cancer (BC) is the most common malignant disease in female patients worldwide. In HER-2+ BC patients, trastuzumab therapy is associated with a better prognosis. However, many HER-2+ BC patients experience recurrence or metastasis because of trastuzumab resistance. The mechanisms underlying trastuzumab resistance remain unclear. Recently, substantial evidence has suggested that exosomes are associated with drug resistance, and lncRNAs have attracted increasing attention due to their potential role in the regulation of trastuzumab resistance.MethodsWe collected the exosomes from the plasma of BC patients with and without trastuzumab resistance, sequenced the whole transcriptomes, identified differentially expressed lncRNAs, and identified lncRNA Linc00969, which was overexpressed in trastuzumab-resistant patients. Then, we established trastuzumab-resistant BC cell lines and explored the role of exosomal Linc00969 in trastuzumab resistance in vitro and in vivo by silencing or overexpressing Linc00969 and performing a series of functional analyses. Furthermore, to explore the mechanism by which exosomal Linc00969 contributes to trastuzumab resistance, we measured changes in HER-2, HUR and autophagy-related protein expression levels after regulating Linc00969 expression. In addition, we investigated the interaction between Linc00969 and HUR via pull-down and RIP assays and the effect of HUR on HER-2 expression and trastuzumab resistance after blocking HUR.ResultsWe first found that exosomal lncRNA Linc00969 was overexpressed in trastuzumab-resistant BC patients and that exosome-mediated Linc00969 transfer could disseminate trastuzumab resistance in BC. Then, we found that silencing Linc00969 could reduce trastuzumab resistance and that overexpressing Linc00969 could enhance trastuzumab resistance. Furthermore, our results showed that Linc00969 could upregulate HER-2 expression at the protein level and maintain the stability of HER-2 mRNA by binding to HUR. Additionally, we found that exosomal Linc00969 could regulate trastuzumab resistance by inducing autophagy.ConclusionsIn this study, we first identified that exosomal lncRNA Linc00969 could induce trastuzumab resistance by increasing HER-2 protein expression and mRNA stability by binding to HUR, and Linc00969 might also be involved in trastuzumab resistance by inducing autophagy. Our results elucidate a novel mechanism underlying trastuzumab resistance, and Linc00969 might be a new target for improving the treatment of HER-2+ BC patients.

Development and testing of a random forest-based machine learning model for predicting events among breast cancer patients with a poor response to neoadjuvant chemotherapy

BackgroundBreast cancer (BC) is the most common malignant tumor around the world. Timely detection of the tumor progression after treatment could improve the survival outcome of patients. This study aimed to develop machine learning models to predict events (defined as either (1) the first tumor relapse locally, regionally, or distantly; (2) a diagnosis of secondary malignant tumor; or (3) death because of any reason.) in BC patients post-treatment.MethodsThe patients with the response of stable disease (SD) and progressive disease (PD) after neoadjuvant chemotherapy (NAC) were selected. The clinicopathological features and the survival data were recorded in 1 year and 5 years, respectively. Patients were randomly divided into the training set and test set in the ratio of 8:2. A random forest (RF) and a logistic regression were established in both of 1-year cohort and the 5-year cohort. The performance was compared between the two models. The models were validated using data from the Surveillance, Epidemiology, and End Results (SEER) database.ResultsA total of 315 patients were included. In the 1-year cohort, 197 patients were divided into a training set while 87 were into a test set. The specificity, sensitivity, and AUC were 0.800, 0.833, and 0.810 in the RF model. And 0.520, 0.833, and 0.653 of the logistic regression. In the 5-year cohort, 132 patients were divided into the training set while 33 were into the test set. The specificity, sensitivity, and AUC were 0.882, 0.750, and 0.829 in the RF model. And 0.882, 0.688, and 0.752 of the logistic regression. In the external validation set, of the RF model, the specificity, sensitivity, and AUC were 0.765, 0.812, and 0.779. Of the logistics regression model, the specificity, sensitivity, and AUC were 0.833, 0.376, and 0.619.ConclusionThe RF model has a good performance in predicting events among BC patients with SD and PD post-NAC. It may be beneficial to BC patients, assisting in detecting tumor recurrence.

Identification of a novel five ferroptosis-related gene signature as a promising prognostic model for breast cancer

BackgroundBreast cancer (BCa) is a major challenge for women’s health worldwide. Ferroptosis is closely related to tumorigenesis and cancer progression. However, the prognostic value of ferroptosis-related genes in BCa remains unclear, and more accurate prognostic models are urgently needed.MethodsGene expression profiles and clinical information of BCa patients were collected from public databases. LASSO and multivariate Cox regression analysis were utilized to construct the prognostic gene signature. Kaplan–Meier plotter, receiver operating characteristic (ROC) curves, and nomogram were used to validate the prognostic value of the gene signature. Gene set enrichment analysis was performed to explore the molecular functions and signaling pathways.ResultsDifferentially expressed ferroptosis-related genes between BCa samples and normal tissues were obtained. A novel five-gene signature including BCL2, SLC40A1, TFF1, APOOL, and PRAME was established for prognosis prediction. Patients stratified into high-risk or low-risk group displayed significantly different survival. Kaplan–Meier and ROC curves showed a good performance for survival prediction in different cohorts. Biological function analysis revealed that the five-gene signature was associated with cancer progression, immune infiltration, immune response, and drug resistance. Nomogram including the five-gene signature was established.ConclusionA novel five ferroptosis-related gene signature and nomogram could be used for prognostic prediction in BCa.

Interplay of Mendelian and polygenic risk factors in Arab breast cancer patients

BackgroundBreast cancer patients from the indigenous Arab population present much earlier than patients from Western countries and have traditionally been underrepresented in cancer genomics studies. The contribution of polygenic and Mendelian risk toward the earlier onset of breast cancer in the population remains elusive.MethodsWe performed low-pass whole genome sequencing (lpWGS) and whole-exome sequencing (WES) from 220 female breast cancer patients unselected for positive family history from the indigenous Arab population. Using publicly available resources, we imputed population-specific variants and calculated breast cancer burden-sensitive polygenic risk scores (PRS). Variant pathogenicity was also evaluated on exome variants with high coverage.ResultsVariants imputed from lpWGS showed high concordance with paired exome (median dosage correlation: 0.9459, Interquartile range: 0.9410–0.9490). After adjusting the PRS to the Arab population, we found significant associations between PRS performance in risk prediction and first-degree relative breast cancer history prediction (Spearman rho=0.43, p = 0.03), where breast cancer patients in the top PRS decile are 5.53 (95% CI 1.76–17.97, p = 0.003) times more likely also to have a first-degree relative diagnosed with breast cancer compared to those in the middle deciles. In addition, we found evidence for the genetic liability threshold model of breast cancer where among patients with a family history of breast cancer, pathogenic rare variant carriers had significantly lower PRS than non-carriers (p = 0.0205, Mann-Whitney U test) while for non-carriers every standard deviation increase in PRS corresponded to 4.52 years (95% CI 8.88–0.17, p = 0.042) earlier age of presentation.ConclusionsOverall, our study provides a framework to assess polygenic risk in an understudied population using lpWGS and identifies common variant risk as a factor independent of pathogenic variant carrier status for earlier age of onset of breast cancer among indigenous Arab breast cancer patients.

Effectiveness of home-based exercise in breast cancer survivors: a randomized clinical trial

BackgroundBreast cancer patients are recommended to engage in regular exercise. In developing countries, where there is a lack of facilities to offer specialized, supervised exercise for this population, regularly exercising might be a challenge. We aimed to evaluate the effectiveness of a home-based intervention in this population.MethodsBreast cancer survivors were randomly assigned to either the home-based exercise program or the usual care group. Exercise intervention included walking, balance, and stretch exercises, along with weekly follow-up telephone calls. Quality of life (QOL) was evaluated using EORTC QLQ-C30 and EORTC QLQ-BR23 questionnaires and the predicted VO2 peak was measured using the Ebbeling submaximal treadmill test.ResultsEighty-nine patients were enrolled in the study. Reported minutes of exercise gradually increased from 40.7 min per week in week 1 to 116.9 min per week in week 12. This intervention improved global QOL (P = 0.001), social functioning (P = 0.04), and the predicted VO2 peak (P = 0.01).ConclusionThis home-based exercise regime effectively increased quality of life and physical activity levels.Trial registryIranian Registry of Clinical Trials identifier: IRCT20140810018746N1, prospectively registered 08/01/2018, https://en.irct.ir/trial/27959.

GSG2 facilitates the progression of human breast cancer through MDM2-mediated ubiquitination of E2F1

BackgroundBreast cancer (BC) has posed a great threat to world health as the leading cause of cancer death among women. Previous evidence demonstrated that germ cell-specific gene 2 (GSG2) was involved in the regulation of multiple cancers. Thus, the clinical value, biological function and underlying mechanism of GSG2 in BC were investigated in this study.MethodsThe expression of GSG2 in BC was revealed by immunohistochemistry (IHC), qPCR and western blotting. Secondly, the biological function of GSG2 in BC was evaluated by MTT assay, flow cytometry, Transwell assay and wound healing assay. Furthermore, the potential molecular mechanism of GSG2 regulating the progression of BC by co-immunoprecipitation (Co-IP) and protein stability detection.ResultsOur data indicated that GSG2 was frequently overexpressed in BC. Moreover, there was a significant correlation between the GSG2 expression and the poor prognosis of BC patients. Functionally, GSG2 knockdown inhibited the malignant progression of BC characterized by reduced proliferation, enhanced apoptosis and attenuated tumor growth. Migration inhibition of GSG2 knockdown BC cells via epithelial-mesenchymal transition (EMT), such as downregulation of Vimentin and Snail. In addition, E2F transcription factor 1 (E2F1) was regarded as a target protein of GSG2. Downregulation of E2F1 attenuated the promoting role of GSG2 on BC cells. Mechanistically, knockdown of GSG2 accelerated the ubiquitination of E2F1 protein, which was mediated by E3 ubiquitin ligase MDM2.ConclusionsGSG2 facilitated the development and progression of BC through MDM2-mediated ubiquitination of E2F1, which may be a promising candidate target with potential therapeutic value.

Comprehensive research into prognostic and immune signatures of transcription factor family in breast cancer

BackgroundBreast cancer (BRCA) is the most common malignancy with high morbidity and mortality in women, and transcription factor (TF) is closely related to the occurrence and development of BRCA. This study was designed to identify a prognostic gene signature based on TF family to reveal immune characteristics and prognostic survival of BRCA.MethodsIn this study, RNA-sequence with corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and GSE42568. Prognostic differentially expressed transcription factor family genes (TFDEGs) were screened to construct a risk score model, after which BRCA patients were stratified into low-risk and high-risk groups based on their corresponding risk scores. Kaplan–Meier (KM) analysis was applied to evaluate the prognostic implication of risk score model, and a nomogram model was developed and validated with the TCGA and GSE20685. Furthermore, the GSEA revealed pathological processes and signaling pathways enriched in the low-risk and high-risk groups. Finally, analyses regarding levels of immune infiltration, immune checkpoints and chemotactic factors were all completed to investigate the correlation between the risk score and tumor immune microenvironment (TIME).ResultsA prognostic 9-gene signature based on TFDEGs was selected to establish a risk score model. According to KM analyses, high-risk group witnessed a significantly worse overall survival (OS) than low-risk group in both TCGA-BRCA and GSE20685. Furthermore, the nomogram model proved great possibility in predicting the OS of BRCA patients. As indicted in GSEA analysis, tumor-associated pathological processes and pathways were relatively enriched in high-risk group, and the risk score was negatively correlated with ESTIMATE score, infiltration levels of CD4+ and CD8+T cells, as well as expression levels of immune checkpoints and chemotactic factors.ConclusionsThe prognostic model based on TFDEGs could distinguish as a novel biomarker for predicting prognosis of BRCA patients; in addition, it may also be utilized to identify potential benefit population from immunotherapy in different TIME and predict potential drug targets.

Loss of TTC17 promotes breast cancer metastasis through RAP1/CDC42 signaling and sensitizes it to rapamycin and paclitaxel

BackgroundBreast cancer (BC) metastasis is the leading cause of poor prognosis and therapeutic failure. However, the mechanisms underlying cancer metastasis are far from clear.MethodsWe screened candidate genes related to metastasis through genome-wide CRISPR screening and high-throughput sequencing of patients with metastatic BC, followed by a panel of metastatic model assays. The effects of tetratricopeptide repeat domain 17 (TTC17) on migration, invasion, and colony formation ability together with the responses to anticancer drugs were investigated in vitro and in vivo. The mechanism mediated by TTC17 was determined by RNA sequencing, Western blotting, immunohistochemistry, and immunofluorescence. The clinical significance of TTC17 was evaluated using BC tissue samples combined with clinicopathological data.ResultsWe identified the loss of TTC17 as a metastasis driver in BC, and its expression was negatively correlated with malignancy and positively correlated with patient prognosis. TTC17 loss in BC cells promoted their migration, invasion, and colony formation capacity in vitro and lung metastasis in vivo. Conversely, overexpressing TTC17 suppressed these aggressive phenotypes. Mechanistically, TTC17 knockdown in BC cells resulted in the activation of the RAP1/CDC42 pathway along with a disordered cytoskeleton in BC cells, and pharmacological blockade of CDC42 abolished the potentiation of motility and invasiveness caused by TTC17 silencing. Research on BC specimens demonstrated reduced TTC17 and increased CDC42 in metastatic tumors and lymph nodes, and low TTC17 expression was linked to more aggressive clinicopathologic characteristics. Through screening the anticancer drug library, the CDC42 inhibitor rapamycin and the microtubule-stabilizing drug paclitaxel showed stronger inhibition of TTC17-silenced BC cells, which was confirmed by more favorable efficacy in BC patients and tumor-bearing mice receiving rapamycin or paclitaxel in the TTC17Low arm.ConclusionsTTC17 loss is a novel factor promoting BC metastasis, that enhances migration and invasion by activating RAP1/CDC42 signaling and sensitizes BC to rapamycin and paclitaxel, which may improve stratified treatment strategies under the concept of molecular phenotyping-based precision therapy of BC.

CircDNAJC11 interacts with TAF15 to promote breast cancer progression via enhancing MAPK6 expression and activating the MAPK signaling pathway

BackgroundBreast cancer (BC) is a common malignant tumor in women worldwide. Circular RNA (circRNA) has been proven to play a critical role in BC progression. However, the exact biological functions and underlying mechanisms of circRNAs in BC remain largely unknown.MethodsHere, we first screened for differentially expressed circRNAs in 4 pairs of BC tissues and adjacent non-tumor tissues using a circRNA microarray. Functionally, gain- and loss-of-function experiments in vitro and in vivo showed that circDNAJC11 promoted BC cell proliferation, migration, invasion, and tumor growth. Mechanistically, RNA pull-down, mass spectrum, RNA immunoprecipitation, fluorescence in situ hybridization assays, and rescue experiments were executed.ResultsWe found that circDNAJC11 was significantly upregulated in triple-negative breast cancer tissues and cells. Clinical data revealed that the high expression of circDNAJC11 was closely correlated with a poor prognosis of BC patients and could be an independent risk factor for BC prognosis. Functionally, gain- and loss-of-function experiments in vitro and in vivo showed that circDNAJC11 promoted BC cell proliferation, migration, invasion, and tumor growth. Mechanistically, RNA pull-down, mass spectrum, RNA immunoprecipitation, fluorescence in situ hybridization assays, and rescue experiments were executed. We demonstrated that circDNAJC11 combined with TAF15 to promote BC progression via stabilizing MAPK6 mRNA and activating the MAPK signaling pathway.ConclusionsThe circDNAJC11/TAF15/MAPK6 axis played a crucial role in the progression and development of BC, suggesting that circDNAJC11 might be a novel biomarker and therapeutical target for BC.

Comprehensive analysis of nicotinamide metabolism-related signature for predicting prognosis and immunotherapy response in breast cancer.

Breast cancer (BC) is the most common malignancy among women. Nicotinamide (NAM) metabolism regulates the development of multiple tumors. Herein, we sought to develop a NAM metabolism-related signature (NMRS) to make predictions of survival, tumor microenvironment (TME) and treatment efficacy in BC patients. Transcriptional profiles and clinical data from The Cancer Genome Atlas (TCGA) were analyzed. NAM metabolism-related genes (NMRGs) were retrieved from the Molecular Signatures Database. Consensus clustering was performed on the NMRGs and the differentially expressed genes between different clusters were identified. Univariate Cox, Lasso, and multivariate Cox regression analyses were sequentially conducted to develop the NAM metabolism-related signature (NMRS), which was then validated in the International Cancer Genome Consortium (ICGC) database and Gene Expression Omnibus (GEO) single-cell RNA-seq data. Further studies, such as gene set enrichment analysis (GSEA), ESTIMATE, CIBERSORT, SubMap, and Immunophenoscore (IPS) algorithm, cancer-immunity cycle (CIC), tumor mutation burden (TMB), and drug sensitivity were performed to assess the TME and treatment response. We identified a 6-gene NMRS that was significantly associated with BC prognosis as an independent indicator. We performed risk stratification according to the NMRS and the low-risk group showed preferable clinical outcomes (P < 0.001). A comprehensive nomogram was developed and showed excellent predictive value for prognosis. GSEA demonstrated that the low-risk group was predominantly enriched in immune-associated pathways, whereas the high-risk group was enriched in cancer-related pathways. The ESTIMATE and CIBERSORT algorithms revealed that the low-risk group had a higher abundance of anti-tumor immunocyte infiltration (P < 0.05). Results of Submap, IPS, CIC, TMB, and external immunotherapy cohort (iMvigor210) analyses showed that the low-risk group were indicative of better immunotherapy response (P < 0.05). The novel signature offers a promising way to evaluate the prognosis and treatment efficacy in BC patients, which may facilitate clinical practice and management.

A clinicopathological study and survival analysis of 99 breast cancers with HER2/CEP17 ratio ≥ 2.0 and an average HER2 copy number < 4.0 per cell in China

BackgroundBreast cancer patients of American Society of Clinical Oncology and the College of American Pathologists (ASCO/CAP) Group 2 were all HER2-negative according to the 2018 guideline, not HER2-positive as defined in the 2013 guideline.MethodsWe aims to elucidate the unique clinicopathological features of ASCO/CAP Group 2 patients by comparing with classic HER2-nonamplified cancers, and reveal the efficacy of the former to anti-HER2 therapy. The clinicopathological features, treatment and prognosis information of 99 patients between 2014 and 2018 were collected. HER2 status was re-defined using the updated recommendations.ResultsOf the 99 ASCO/CAP Group 2 tumors, 25.5% (25/99) tumors were immunohistochemical (IHC) 0/1+ and 74.7% (74/99) tumors were IHC 2+. According to the updated 2018 guideline, all of them were HER2 negative. When compared to ASCO/CAP Group 5, patients of ASCO/CAP Group 2 displayed higher ratio of histological grade 3 (P = .03), high Ki67 proliferation index (P = .03) and pN3 (more than 9 lymph nodes metastasis, P = .02), and lower estrogen receptor (ER) positivity (P = .04). There was no statistical difference in the survival of patients received anti-HER2 therapy and patients not received anti-HER2 therapy.ConclusionsPatients of ASCO/CAP Group 2 did not received apparent benefit from anti-HER2 treatment. Although according to the updated guidelines and latest reports, HER2 is negative, but when compared with classic HER2-nonamplified cancers, patients of this group seemed to be more aggressive. We suggest that this group still be regarded as an independent category, in order to accumulate more cases in the future to expand the scope of research.

Establishment and validation of an aging-related risk signature associated with prognosis and tumor immune microenvironment in breast cancer

BackgroundBreast cancer (BC) is a highly malignant and heterogeneous tumor which is currently the cancer with the highest incidence and seriously endangers the survival and prognosis of patients. Aging, as a research hotspot in recent years, is widely considered to be involved in the occurrence and development of a variety of tumors. However, the relationship between aging-related genes (ARGs) and BC has not yet been fully elucidated.Materials and methodsThe expression profiles and clinicopathological data were acquired in the Cancer Genome Atlas (TCGA) and the gene expression omnibus (GEO) database. Firstly, the differentially expressed ARGs in BC and normal breast tissues were investigated. Based on these differential genes, a risk model was constructed composed of 11 ARGs via univariate and multivariate Cox analysis. Subsequently, survival analysis, independent prognostic analysis, time-dependent receiver operating characteristic (ROC) analysis and nomogram were performed to assess its ability to sensitively and specifically predict the survival and prognosis of patients, which was also verified in the validation set. In addition, functional enrichment analysis and immune infiltration analysis were applied to reveal the relationship between the risk scores and tumor immune microenvironment, immune status and immunotherapy. Finally, multiple datasets and real‐time polymerase chain reaction (RT-PCR) were utilized to verify the expression level of the key genes.ResultsAn 11-gene signature (including FABP7, IGHD, SPIB, CTSW, IGKC, SEZ6, S100B, CXCL1, IGLV6-57, CPLX2 and CCL19) was established to predict the survival of BC patients, which was validated by the GEO cohort. Based on the risk model, the BC patients were divided into high- and low-risk groups, and the high-risk patients showed worse survival. Stepwise ROC analysis and Cox analyses demonstrated the good performance and independence of the model. Moreover, a nomogram combined with the risk score and clinical parameters was built for prognostic prediction. Functional enrichment analysis revealed the robust relationship between the risk model with immune-related functions and pathways. Subsequent immune microenvironment analysis, immunotherapy, etc., indicated that the immune status of patients in the high-risk group decreased, and the anti-tumor immune function was impaired, which was significantly different with those in the low-risk group. Eventually, the expression level of FABP7, IGHD, SPIB, CTSW, IGKC, SEZ6, S100B, CXCL1, IGLV6-57 and CCL19 was identified as down-regulated in tumor cell line, while CPLX2 up-regulated, which was mostly similar with the results in TCGA and Human Protein Atlas (HPA) via RT-PCR.ConclusionsIn summary, our study constructed a risk model composed of ARGs, which could be used as a solid model for predicting the survival and prognosis of BC patients. Moreover, this model also played an important role in tumor immunity, providing a new direction for patient immune status assessment and immunotherapy selection.

Association between the CASC16 rs4784227 polymorphism and breast cancer risk and prognosis in a northeast Chinese Han population.

Breast cancer (BC) poses a serious threat to women worldwide. This research was designed to explore the association between the rs4784227 polymorphism of cancer susceptibility candidate gene 16 (CASC16) and BC susceptibility and prognosis, aiming to provide further information for the early detection of BC and to accelerate comprehensive cancer management. A total of 1,733 subjects were recruited for this case-control study, of which 828 are BC patients and 905 are healthy individuals. The relevance between SNP rs4784227 and BC risk in diverse genetic models was analyzed by using the SNPStats analysis program and was assessed by odds ratios (ORs) and 95% confidence intervals (CIs) using the binary logistic regression model. Pearson's χ 2 test was used to determine the correlation between the polymorphism and clinical characteristics of BC patients. Additionally, univariate survival analysis was performed by the Kaplan-Meier method and log-rank test, and multivariate survival analysis was performed by Cox regression. SNP rs4784227 was significantly associated with susceptibility to BC in the dominant model (CT/TT versus CC, OR = 1.237, 95% CI = 1.012-1.513, P=0.038). The minor allele of SNP rs4784227 was significantly linked to an increased risk of BC (OR = 1.197, 95% CI = 1.022-1.401, P=0.026). In addition, the rs4784227 polymorphism of CASC16 was associated with perineural invasion (P=0.030), menstrual status (P=0.016) and histological grade (P=0.001, P=0.003, P=0.025; respectively) of BC patients. There was no significant association between the genotypes of rs4784227 and disease-free survival (DFS) or overall survival (OS) of breast cancer patients (P>0.05). The rs4784227 polymorphism of CASC16 may affect susceptibility to breast cancer and is associated with perineural invasion, menstrual status and histological grade in BC patients. Additionally, our results could not confirm that this polymorphism was related to breast cancer prognosis.

Effects of a Plant-Based High-Protein Diet on Fatigue in Breast Cancer Patients Undergoing Adjuvant Chemotherapy – a Randomized Controlled Trial

Background Breast cancer patients undergoing chemotherapy (CT) experience fatigue and other side-effects. Studies exploring interventions with a plant-based, high-protein diet on fatigue and body composition are lacking. The effects of these interventions on fatigue, body mass index (BMI), and body composition were evaluated. Method Newly diagnosed breast cancer patients who were scheduled for adjuvant CT (n = 103) were randomly assigned to the intervention or control group. Study outcomes included fatigue using fatigue symptom inventory and body composition using bioelectric impedance analyzer done at the start of CT, 3rd CT, and 3 weeks after CT. Linear mixed models were used to compare groups over time. Results Fatigue decreased from 57% to 28% in the intervention group and increased from 65% to 78% in the control group (p < 0.001). BMI decreased by 0.7 ± 0.8 kg/m2 in the intervention group, while the decrease was 0.4 ± 1.3 kg/m2 in the control group (p = 0.015). Fat mass decreased in the intervention group (p < 0.001) and muscle mass improved in the intervention group and decreased in the control group (p < 0.05). Conclusions A plant-based, high-protein diet during CT resulted in positive changes in fatigue, BMI and body composition.

THOR is a targetable epigenetic biomarker with clinical implications in breast cancer

BackgroundBreast cancer (BC) is the most frequently diagnosed cancer and a leading cause of death among women worldwide. Early BC is potentially curable, but the mortality rates still observed among BC patients demonstrate the urgent need of novel and more effective diagnostic and therapeutic options. Limitless self-renewal is a hallmark of cancer, governed by telomere maintenance. In around 95% of BC cases, this process is achieved by telomerase reactivation through upregulation of the human telomerase reverse transcriptase (hTERT). The hypermethylation of a specific region within the hTERT promoter, termed TERT hypermethylated oncological region (THOR) has been associated with increased hTERT expression in cancer. However, its biological role and clinical potential in BC have never been studied to the best of our knowledge. Therefore, we aimed to investigate the role of THOR as a biomarker and explore the functional impact of THOR methylation status in hTERT upregulation in BC.ResultsTHOR methylation status in BC was assessed by pyrosequencing on discovery and validation cohorts. We found that THOR is significantly hypermethylated in malignant breast tissue when compared to benign tissue (40.23% vs. 12.81%, P < 0.0001), differentiating malignant tumor from normal tissue from the earliest stage of disease. Using a reporter assay, the addition of unmethylated THOR significantly reduced luciferase activity by an average 1.8-fold when compared to the hTERT core promoter alone (P < 0.01). To further investigate its biological impact on hTERT transcription, targeted THOR demethylation was performed using novel technology based on CRISPR-dCas9 system and significant THOR demethylation was achieved. Cells previously demethylated on THOR region did not develop a histologic cancer phenotype in in vivo assays. Additional studies are required to validate these observations and to unravel the causality between THOR hypermethylation and hTERT upregulation in BC.ConclusionsTHOR hypermethylation is an important epigenetic mark in breast tumorigenesis, representing a promising biomarker and therapeutic target in BC. We revealed that THOR acts as a repressive regulatory element of hTERT and that its hypermethylation is a relevant mechanism for hTERT upregulation in BC.

COVID-19 Incidence and Mortality in Patients Operated on for Breast Cancer. Comparison with the General Population

BackgroundBreast Cancer (BC) remains the most diagnosed malignancy and the most common cause of cancer-related mortality in women worldwide. Covid-19 mortality in BC patients has been linked to comorbid conditions rather than to cancer treatment itself, although this was not confirmed by a meta-analysis. Also, during Covid-19 outbreaks, a great deal of health care resources is reassigned to critical Covid-19 patients. Patients and MethodsDuring 5 consecutive trimesters (from 1/12/2020 to 31/3/2021) 2511 BC patients older than 20 years from our institution were surveyed. 1043 of them had received a Covid test and these made our study group, which was conveniently compared with the Covid-19 tested background feminine Catalan population. Results13.1% of our patients presented with a positive Covid-19 test, whereas confirmed COVID-19 infection amounted to 7.1% of the feminine Catalan tested population. The COVID-19-specific mortality rate was 11.7% (16/137) in the study group, which compares with a 4.7% rate for the overall population. Most deaths occurred in patients over 70. ConclusionThree clinical factors were significantly associated with Covid-19 mortality in BC, namely lack of hormone therapy, distant metastases, and BC dwelling in nursing homes. BC patients are at a higher risk of Covid-19 infection and mortality in comparison with the reference group without BC.

Using machine learning to identify gene interaction networks associated with breast cancer

BackgroundBreast cancer (BC) is one of the most prevalent cancers worldwide but its etiology remains unclear. Obesity is recognized as a risk factor for BC, and many obesity-related genes may be involved in its occurrence and development. Research assessing the complex genetic mechanisms of BC should not only consider the effect of a single gene on the disease, but also focus on the interaction between genes. This study sought to construct a gene interaction network to identify potential pathogenic BC genes.MethodsThe study included 953 BC patients and 963 control individuals. Chi-square analysis was used to assess the correlation between demographic characteristics and BC. The joint density-based non-parametric differential interaction network analysis and classification (JDINAC) was used to build a BC gene interaction network using single nucleotide polymorphisms (SNP). The odds ratio (OR) and 95% confidence interval (95% CI) of hub gene SNPs were evaluated using a logistic regression model. To assess reliability, the hub genes were quantified by edgeR program using BC RNA-seq data from The Cancer Genome Atlas (TCGA) and identical edges were verified by logistic regression using UK Biobank datasets. Go and KEGG enrichment analysis were used to explore the biological functions of interactive genes.ResultsBody mass index (BMI) and menopause are important risk factors for BC. After adjusting for potential confounding factors, the BC gene interaction network was identified using JDINAC. LEP, LEPR, XRCC6, and RETN were identified as hub genes and both hub genes and edges were verified. LEPR genetic polymorphisms (rs1137101 and rs4655555) were also significantly associated with BC. Enrichment analysis showed that the identified genes were mainly involved in energy regulation and fat-related signaling pathways.ConclusionWe explored the interaction network of genes derived from SNP data in BC progression. Gene interaction networks provide new insight into the underlying mechanisms of BC.

A randomized controlled trial of a coping-focused family resilience intervention program for breast cancer patients: Study protocol.

BackgroundBreast cancer patients and their families are under various pressures in the process of disease diagnosis and treatment, which seriously threaten their physical and mental health. Findings from existing research suggest that good family resilience can help breast cancer families better adapt and cope with adversity and challenges. However, there are only a few intervention studies on family resilience and no intervention studies on resilience among the families of breast cancer patients. Therefore, this study aims to explore appropriate measures to improve the resilience level of breast cancer families and help them better cope with the disease.ObjectiveThe purpose of this study protocol is to demonstrate a coping-focused family resilience intervention to increase the level of resilience in the families of breast cancer patients and help them better cope with adversity.MethodsThe trial will recruit 80 breast cancer families and randomly assign them to experimental and control groups in a 1:1 ratio. The control group will receive routine care, and the intervention group will receive a 6-week one-on-one online family resilience intervention based on the control group. Two groups of subjects will be assessed at baseline and at 1 week, 1 month, and 3 months after the intervention. The primary outcome is family resilience, and the secondary outcomes are coping style, social support, family disease burden, and levels of anxiety and depression.Expected resultsWe hypothesized that after the intervention, the intervention group would have significantly higher levels of family resilience than the preintervention and control groups. In the intervention group, other aspects related to family resilience, such as family disease burden and anxiety and depression levels of patients and their families, were significantly alleviated, and disease coping and social support levels were improved accordingly.DiscussionIf the program works, it can help breast cancer families identify family strengths and resources to proactively address challenges so that families can successfully navigate the crisis and patient and family recovery can be facilitated. It can also provide a practical path for clinical workers to help breast cancer families adjust rationally.Clinical Trial RegistrationThis study has been registered in the Chinese Clinical Trials Registry (Registration Number: http://www.chictr.org.cn/ChiCTR2100052108).