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Simple Summary: In this study, the researchers aimed to improve the prognostic information provided by the standard One-Step Nucleic Acid Amplification (OSNA) assay used to detect breast cancer (BC) metastasis in sentinel lymph nodes (SLNs). They analysed the expression of an immune gene panel in SLNs from Luminal A early-stage BC (cT1-T2 N0) patients, including those with and without subclinical metastasis. The study identified two distinct immune response profiles—one showing an adaptive anti-tumour immune response, and another with a more undifferentiated response. The researchers also identified seven key immunoregulatory genes that could serve as potential targets for immunotherapy. These findings suggest that analysing immune gene expression in SLNs can provide additional prognostic information beyond the OSNA assay results and may help guide personalised treatment approaches for early-stage BC patients. In the management of early-stage breast cancer (BC), lymph nodes (LNs) are typically characterised using the One-Step Nucleic Acid Amplification (OSNA) assay, a standard procedure for assessing subclinical metastasis in sentinel LNs (SLNs). The pivotal role of LNs in coordinating the immune response against BC is often overlooked. Our aim was to improve prognostic information provided by the OSNA assay and explore immune-related gene signatures in SLNs. The expression of an immune gene panel was analysed in SLNs from 32 patients with Luminal A early-stage BC (cT1-T2 N0). Using an unsupervised approach based on these expression values, this study identified two clusters, regardless of the SLN invasion: one evidencing an adaptive anti-tumoral immune response, characterised by an increase in naive B cells, follicular T helper cells, and activated NK cells; and another with a more undifferentiated response, with an increase in the activated-to-resting dendritic cells (DCs) ratio. Through a protein—protein interaction (PPI) network, we identified seven immunoregulatory hub genes: CD80, CD40, TNF, FCGR3A, CD163, FCGR3B, and CCR2. This study shows that, in Luminal A early-stage BC, SLNs gene expression studies enable the identification of distinct immune profiles that may influence prognosis stratification and highlight key genes that could serve as potential targets for immunotherapy. [ABSTRACT FROM AUTHOR]

Abstract The pandemic of coronavirus disease 19 (COVID-19), caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), had severe repercussions for breast cancer patients. Increasing evidence indicates that SARS-CoV-2 infection may directly impact breast cancer biology, but the effects of SARS-CoV-2 on breast tumor cells are still unknown. Here, we analyzed the molecular events occurring in the MCF7, MDA-MB-231 and HCC1937 breast cancer cell lines, representative of the luminal A, basal B/claudin-low and basal A subtypes, respectively, upon SARS-CoV-2 infection. Viral replication was monitored over time, and gene expression profiling was conducted. We found that MCF7 cells were the most permissive to viral replication. Treatment of MCF7 cells with Tamoxifen reduced the SARS-CoV-2 replication rate, suggesting an involvement of the estrogen receptor in sustaining virus replication in malignant cells. Interestingly, a metagene signature based on genes upregulated by SARS-CoV-2 infection in all three cell lines distinguished a subgroup of premenopausal luminal A breast cancer patients with a poor prognosis. As SARS-CoV-2 still spreads among the population, it is essential to understand the impact of SARS-CoV-2 infection on breast cancer, particularly in premenopausal patients diagnosed with the luminal A subtype, and to assess the long-term impact of COVID-19 on breast cancer outcomes.

The pandemic of coronavirus disease 19 (COVID-19), caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), had severe repercussions for breast cancer patients. Increasing evidence indicates that SARS-CoV-2 infection may directly impact breast cancer biology, but the effects of SARS-CoV-2 on breast tumor cells are still unknown. Here, we analyzed the molecular events occurring in the MCF7, MDA-MB-231 and HCC1937 breast cancer cell lines, representative of the luminal A, basal B/claudin-low and basal A subtypes, respectively, upon SARS-CoV-2 infection. Viral replication was monitored over time, and gene expression profiling was conducted. We found that MCF7 cells were the most permissive to viral replication. Treatment of MCF7 cells with Tamoxifen reduced the SARS-CoV-2 replication rate, suggesting an involvement of the estrogen receptor in sustaining virus replication in malignant cells. Interestingly, a metagene signature based on genes upregulated by SARS-CoV-2 infection in all three cell lines distinguished a subgroup of premenopausal luminal A breast cancer patients with a poor prognosis. As SARS-CoV-2 still spreads among the population, it is essential to understand the impact of SARS-CoV-2 infection on breast cancer, particularly in premenopausal patients diagnosed with the luminal A subtype, and to assess the long-term impact of COVID-19 on breast cancer outcomes. [ABSTRACT FROM AUTHOR]

In the management of early-stage breast cancer (BC), lymph nodes (LNs) are typically characterised using the One-Step Nucleic Acid Amplification (OSNA) assay, a standard procedure for assessing subclinical metastasis in sentinel LNs (SLNs). The pivotal role of LNs in coordinating the immune response against BC is often overlooked. Our aim was to improve prognostic information provided by the OSNA assay and explore immune-related gene signatures in SLNs. The expression of an immune gene panel was analysed in SLNs from 32 patients with Luminal A early-stage BC (cT1-T2 N0). Using an unsupervised approach based on these expression values, this study identified two clusters, regardless of the SLN invasion: one evidencing an adaptive anti-tumoral immune response, characterised by an increase in naive B cells, follicular T helper cells, and activated NK cells; and another with a more undifferentiated response, with an increase in the activated-to-resting dendritic cells (DCs) ratio. Through a protein—protein interaction (PPI) network, we identified seven immunoregulatory hub genes: CD80, CD40, TNF, FCGR3A, CD163, FCGR3B, and CCR2. This study shows that, in Luminal A early-stage BC, SLNs gene expression studies enable the identification of distinct immune profiles that may influence prognosis stratification and highlight key genes that could serve as potential targets for immunotherapy.

Abstract Background Breast cancer (BC) is the most common malignancy in women and the second leading cause of cancer-related death; chemoresistance is still a clinical challenge mainly because of the different molecular features of this kind of tumour. Doxorubicin (Doxo) is widely used despite its adverse effects and the common onset of resistance. Chaperone-Mediated Autophagy (CMA) has been identified as an important mechanism through which chemotherapeutics can exert their cytotoxic effects and, in this context, LAMP-2A, the key player of CMA, can be a useful biomarker. Methods A cohort of patients and breast cancer cells have been screened for Doxo effect and CMA activation by analysing the LAMP-2A level. Molecular silencing has been used to clarify CMA role in BC responsiveness to treatments. Low Doxo doses were combined with other drugs (TMZ or PX-478, a HIF-1α inhibitor) to evaluate their cytotoxic ability and their role in modulating CMA. Results In this paper, we showed that CMA is an important mechanism mediating the responsiveness of breast cancer cell to different treatments (Doxo and TMZ, as suggested by triple negative cells that are TMZ-resistant and fails to activate CMA). The LAMP-2A expression level was specific for different cell lines and patient-derived tumour subtypes, and was also useful in discriminating patients for their survival rates. Moreover, molecular silencing or pharmacological blockage of HIF-1α activity reverted BC resistance to TMZ. The combination of low-dose Doxo with TMZ or PX-478 showed that the drug associations have synergistic behaviours. Conclusion Here, we demonstrated that CMA activity exerts a fundamental role in the responsiveness to different treatments, and LAMP-2A can be proposed as a reliable prognostic biomarker in breast cancer. In this context, HIF-1α, a potential target of CMA, can also be assessed as a valuable therapeutic target in BC in view of identifying new, more efficient and less toxic therapeutic drug combinations. Moreover, the possibility to combine Doxo with other drugs acting on different but coherent molecular targets could help overcome resistance and open the way to a decrease in the dose of the single drugs.

Background: Breast cancer (BC) is the most common malignancy in women and the second leading cause of cancer-related death; chemoresistance is still a clinical challenge mainly because of the different molecular features of this kind of tumour. Doxorubicin (Doxo) is widely used despite its adverse effects and the common onset of resistance. Chaperone-Mediated Autophagy (CMA) has been identified as an important mechanism through which chemotherapeutics can exert their cytotoxic effects and, in this context, LAMP-2A, the key player of CMA, can be a useful biomarker. Methods: A cohort of patients and breast cancer cells have been screened for Doxo effect and CMA activation by analysing the LAMP-2A level. Molecular silencing has been used to clarify CMA role in BC responsiveness to treatments. Low Doxo doses were combined with other drugs (TMZ or PX-478, a HIF-1α inhibitor) to evaluate their cytotoxic ability and their role in modulating CMA. Results: In this paper, we showed that CMA is an important mechanism mediating the responsiveness of breast cancer cell to different treatments (Doxo and TMZ, as suggested by triple negative cells that are TMZ-resistant and fails to activate CMA). The LAMP-2A expression level was specific for different cell lines and patient-derived tumour subtypes, and was also useful in discriminating patients for their survival rates. Moreover, molecular silencing or pharmacological blockage of HIF-1α activity reverted BC resistance to TMZ. The combination of low-dose Doxo with TMZ or PX-478 showed that the drug associations have synergistic behaviours. Conclusion: Here, we demonstrated that CMA activity exerts a fundamental role in the responsiveness to different treatments, and LAMP-2A can be proposed as a reliable prognostic biomarker in breast cancer. In this context, HIF-1α, a potential target of CMA, can also be assessed as a valuable therapeutic target in BC in view of identifying new, more efficient and less toxic therapeutic drug combinations. Moreover, the possibility to combine Doxo with other drugs acting on different but coherent molecular targets could help overcome resistance and open the way to a decrease in the dose of the single drugs. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is one of the most frequently occurring malignant cancers worldwide. Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two most common histological subtypes of breast cancer. In this study, we aimed to deeply explore molecular characteristics and the relationship between IDC and ILC subtypes in luminal A subgroup of breast cancer using comprehensive proteomics and phosphoproteomics analysis. Methods: Cancer tissues and noncancerous adjacent tissues (NATs) with the luminal A subtype (ER- and PR-positive, HER2-negative) were obtained from paired IDC and ILC patients respectively. Label-free quantitative proteomics and phosphoproteomics methods were used to detect differential proteins and the phosphorylation status between 10 paired breast cancer and NATs. Then, the difference in protein expression and its phosphorylation between IDC and ILC subtypes were explored. Meanwhile, the activation of kinases and their substrates was also revealed by Kinase-Substrate Enrichment Analysis (KSEA). Results: In the luminal A breast cancer, a total of 5,044 high-confidence proteins and 3,808 phosphoproteins were identified from 10 paired tissues. The protein phosphorylation level in ILC tissues was higher than that in IDC tissues. Histone H1.10 was significantly increased in IDC but decreased in ILC, Conversely, complement C4-B and Crk-like protein were significantly decreased in IDC but increased in ILC. Moreover, the increased protein expression of Septin-2, Septin-9, Heterogeneous nuclear ribonucleoprotein A1 and Kinectin but reduce of their phosphorylation could clearly distinguish IDC from ILC. In addition, IDC was primarily related to energy metabolism and MAPK pathway, while ILC was more closely involved in the AMPK and p53/p21 pathways. Furthermore, the kinomes in IDC were primarily significantly activated in the CMGC groups. Conclusions: Our research provides insights into the molecular characterization of IDC and ILC and contributes to discovering novel targets for further drug development and targeted treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: Despite advances in treatment of subtypes of breast cancer, there still lacks reliable biomarkers with precision to predict treatment response at diagnosis. We used machine-learning tools and developed and validated a novel 12-Gene Algorithm as a biomarker for prediction of treatment response for breast cancer patients, especially those suffering triple-negative cancer. The 12-Gene Algorithm based on KRAS-associated gene-mutation profiles showed high accuracy at predicting the response of breast cancer patients including triple-negative subtype to first-line chemotherapy treatment in two independent patient cohorts. Our study suggests that the 12-Gene Algorithm has a potential to be used in clinical practice to improve breast cancer treatment decision-making, especially for triple-negative breast cancer patients. Purpose: There is an urgent need for developing new biomarker tools to accurately predict treatment response of breast cancer, especially the deadly triple-negative breast cancer. We aimed to develop gene-mutation-based machine learning (ML) algorithms as biomarker classifiers to predict treatment response of first-line chemotherapy with high precision. Methods: Random Forest ML was applied to screen the algorithms of various combinations of gene mutation profiles of primary tumors at diagnosis using a TCGA Cohort (n = 399) with up to 150 months follow-up as a training set and validated in a MSK Cohort (n = 807) with up to 220 months follow-up. Subtypes of breast cancer including triple-negative and luminal A (ER+, PR+ and HER2−) were also assessed. The predictive performance of the candidate algorithms as classifiers was further assessed using logistic regression, Kaplan–Meier progression-free survival (PFS) plot, and univariate/multivariate Cox proportional hazard regression analyses. Results: A novel algorithm termed the 12-Gene Algorithm based on mutation profiles of KRAS, PIK3CA, MAP3K1, MAP2K4, PTEN, TP53, CDH1, GATA3, KMT2C, ARID1A, RunX1, and ESR1, was identified. The performance of this algorithm to distinguish non-progressed (responder) vs. progressed (non-responder) to treatment in the TCGA Cohort as determined using AUC was 0.96 (95% CI 0.94–0.98). It predicted progression-free survival (PFS) with hazard ratio (HR) of 21.6 (95% CI 11.3–41.5) (p < 0.0001) in all patients. The algorithm predicted PFS in the triple-negative subgroup with HR of 19.3 (95% CI 3.7–101.3) (n = 42, p = 0.000). The 12-Gene Algorithm was validated in the MSK Cohort with a similar AUC of 0.97 (95% CI 0.96–0.98) to distinguish responder vs. non-responder patients, and had a HR of 18.6 (95% CI 4.4–79.2) to predict PFS in the triple-negative subgroup (n = 75, p < 0.0001). Conclusions: The novel 12-Gene algorithm based on multitude gene-mutation profiles identified through ML has a potential to predict breast cancer treatment response to therapies, especially in triple-negative subgroups patients, which may assist personalized therapies and reduce mortality. [ABSTRACT FROM AUTHOR]

Abstract Background The human genome encodes over 14,000 pseudogenes that are evolutionary relics of protein-coding genes and commonly considered as nonfunctional. Emerging evidence suggests that some pseudogenes may exert important functions. However, to what extent human pseudogenes are functionally relevant remains unclear. There has been no large-scale characterization of pseudogene function because of technical challenges, including high sequence similarity between pseudogene and parent genes, and poor annotation of transcription start sites. Results To overcome these technical obstacles, we develop an integrated computational pipeline to design the first genome-wide library of CRISPR interference (CRISPRi) single-guide RNAs (sgRNAs) that target human pseudogene promoter-proximal regions. We perform the first pseudogene-focused CRISPRi screen in luminal A breast cancer cells and reveal approximately 70 pseudogenes that affect breast cancer cell fitness. Among the top hits, we identify a cancer-testis unitary pseudogene, MGAT4EP, that is predominantly localized in the nucleus and interacts with FOXA1, a key regulator in luminal A breast cancer. By enhancing the promoter binding of FOXA1, MGAT4EP upregulates the expression of oncogenic transcription factor FOXM1. Integrative analyses of multi-omic data from the Cancer Genome Atlas (TCGA) reveal many unitary pseudogenes whose expressions are significantly dysregulated and/or associated with overall/relapse-free survival of patients in diverse cancer types. Conclusions Our study represents the first large-scale study characterizing pseudogene function. Our findings suggest the importance of nuclear function of unitary pseudogenes and underscore their underappreciated roles in human diseases. The functional genomic resources developed here will greatly facilitate the study of human pseudogene function.

Purpose: It is well-known that the pathological complete response (pCR) rate in patients with luminal A cancer (LAC) is lower than those of other subtypes of breast cancer. The phenotype of cancer often alters after neoadjuvant chemotherapy (NAC) which may be related to hypoxia, and the latter might induce the drift of the estrogen receptor (ER). The phenotype drift in local advanced LAC after NAC might influence the long-term prognosis. Methods: The oxygen concentration of cancer tissues during NAC was recorded and analyzed (n = 43). The expression of ER and claudin-6 was detected in pre- and post-NAC specimens. Results: NAC might induce the cycling intracanceral hypoxia, and the pattern was related to NAC response. The median follow-up time was 61 months. Most of the patients (67%) with stable or increased ER and claudin-6 expression exhibited perfect prognosis (DFS = 100%, 61 months). About 20% of patients with decreased claudin-6 would undergo the poor prognosis (DFS = 22.2%, 61 months). The contrasting prognosis (100% vs. 22.2%) had nothing to do with the response of NAC in the above patients. Only 13% patients had stable claudin-6 and decreased ER, whose prognosis might relate to the response of NAC. Conclusion: NAC might induce cycling intracanceral hypoxia to promote the phenotype drift in local advanced LAC, and the changes in ER and claudin-6 after NAC would determine the long-term prognosis. [ABSTRACT FROM AUTHOR]

PurposeIt is well-known that the pathological complete response (pCR) rate in patients with luminal A cancer (LAC) is lower than those of other subtypes of breast cancer. The phenotype of cancer often alters after neoadjuvant chemotherapy (NAC) which may be related to hypoxia, and the latter might induce the drift of the estrogen receptor (ER). The phenotype drift in local advanced LAC after NAC might influence the long-term prognosis.MethodsThe oxygen concentration of cancer tissues during NAC was recorded and analyzed (n = 43). The expression of ER and claudin-6 was detected in pre- and post-NAC specimens.ResultsNAC might induce the cycling intracanceral hypoxia, and the pattern was related to NAC response. The median follow-up time was 61 months. Most of the patients (67%) with stable or increased ER and claudin-6 expression exhibited perfect prognosis (DFS = 100%, 61 months). About 20% of patients with decreased claudin-6 would undergo the poor prognosis (DFS = 22.2%, 61 months). The contrasting prognosis (100% vs. 22.2%) had nothing to do with the response of NAC in the above patients. Only 13% patients had stable claudin-6 and decreased ER, whose prognosis might relate to the response of NAC.ConclusionNAC might induce cycling intracanceral hypoxia to promote the phenotype drift in local advanced LAC, and the changes in ER and claudin-6 after NAC would determine the long-term prognosis.

Breast cancer (BC) is the most prevalent cancer and the one with the highest mortality among women worldwide. Although the molecular classification of BC has been a helpful tool for diagnosing and predicting the treatment of BC, developments are still being made to improve the diagnosis and find new therapeutic targets. Mitochondrial dysfunction is a crucial feature of cancer, which can be associated with cancer aggressiveness. Although the importance of mitochondrial dynamics in cancer is well recognized, its involvement in the mitochondrial function and bioenergetics context in BC molecular subtypes has been scantly explored. In this study, we combined mitochondrial function and bioenergetics experiments in MCF7 and MDA-MB-231 cell lines with statistical and bioinformatics analyses of the mitochondrial proteome of luminal A and basal-like tumors. We demonstrate that basal-like tumors exhibit a vicious cycle between mitochondrial fusion and fission; impaired but not completely inactive mitochondrial function; and the Warburg effect, associated with decreased oxidative phosphorylation (OXPHOS) complexes I and III. Together with the results obtained in the cell lines and the mitochondrial proteome analysis, two mitochondrial signatures were proposed: one signature reflecting alterations in mitochondrial functions and a second signature exclusively of OXPHOS, which allow us to distinguish between luminal A and basal-like tumors. [ABSTRACT FROM AUTHOR]

Abstract Background Breast cancer subtypes are statistically associated with prognosis. The search for markers of breast tumor heterogeneity and the development of precision medicine for patients are the current focuses of the field. Methods We used a bioinformatic approach to identify key disease-causing genes unique to the luminal A and basal-like subtypes of breast cancer. First, we retrieved gene expression data for luminal A breast cancer, basal-like breast cancer, and normal breast tissue samples from The Cancer Genome Atlas database. The differentially expressed genes unique to the 2 breast cancer subtypes were identified and subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. We constructed protein–protein interaction networks of the differentially expressed genes. Finally, we analyzed the key modules of the networks, which we combined with survival data to identify the unique cancer genes associated with each breast cancer subtype. Results We identified 1114 differentially expressed genes in luminal A breast cancer and 1042 differentially expressed genes in basal-like breast cancer, of which the subtypes shared 500. We observed 614 and 542 differentially expressed genes unique to luminal A and basal-like breast cancer, respectively. Through enrichment analyses, protein–protein interaction network analysis, and module mining, we identified 8 key differentially expressed genes unique to each subtype. Analysis of the gene expression data in the context of the survival data revealed that high expression of NMUR1 and NCAM1 in luminal A breast cancer statistically correlated with poor prognosis, whereas the low expression levels of CDC7, KIF18A, STIL, and CKS2 in basal-like breast cancer statistically correlated with poor prognosis. Conclusions NMUR1 and NCAM1 are novel key disease-causing genes for luminal A breast cancer, and STIL is a novel key disease-causing gene for basal-like breast cancer. These genes are potential targets for clinical treatment.

Purpose: There is an urgent need for developing new biomarker tools to accurately predict treatment response of breast cancer, especially the deadly triple-negative breast cancer. We aimed to develop gene-mutation-based machine learning (ML) algorithms as biomarker classifiers to predict treatment response of first-line chemotherapy with high precision. Methods: Random Forest ML was applied to screen the algorithms of various combinations of gene mutation profiles of primary tumors at diagnosis using a TCGA Cohort (n = 399) with up to 150 months follow-up as a training set and validated in a MSK Cohort (n = 807) with up to 220 months follow-up. Subtypes of breast cancer including triple-negative and luminal A (ER+, PR+ and HER2−) were also assessed. The predictive performance of the candidate algorithms as classifiers was further assessed using logistic regression, Kaplan–Meier progression-free survival (PFS) plot, and univariate/multivariate Cox proportional hazard regression analyses. Results: A novel algorithm termed the 12-Gene Algorithm based on mutation profiles of KRAS, PIK3CA, MAP3K1, MAP2K4, PTEN, TP53, CDH1, GATA3, KMT2C, ARID1A, RunX1, and ESR1, was identified. The performance of this algorithm to distinguish non-progressed (responder) vs. progressed (non-responder) to treatment in the TCGA Cohort as determined using AUC was 0.96 (95% CI 0.94–0.98). It predicted progression-free survival (PFS) with hazard ratio (HR) of 21.6 (95% CI 11.3–41.5) (p < 0.0001) in all patients. The algorithm predicted PFS in the triple-negative subgroup with HR of 19.3 (95% CI 3.7–101.3) (n = 42, p = 0.000). The 12-Gene Algorithm was validated in the MSK Cohort with a similar AUC of 0.97 (95% CI 0.96–0.98) to distinguish responder vs. non-responder patients, and had a HR of 18.6 (95% CI 4.4–79.2) to predict PFS in the triple-negative subgroup (n = 75, p < 0.0001). Conclusions: The novel 12-Gene algorithm based on multitude gene-mutation profiles identified through ML has a potential to predict breast cancer treatment response to therapies, especially in triple-negative subgroups patients, which may assist personalized therapies and reduce mortality.

Breast cancer heterogeneity in histology and molecular subtype influences metabolic and proliferative activity and hence the acid load on cancer cells. We hypothesized that acid-base transporters and intracellular pH (pHi) dynamics contribute inter-individual variability in breast cancer aggressiveness and prognosis. We show that Na+,HCO3– cotransport and Na+/H+ exchange dominate cellular net acid extrusion in human breast carcinomas. Na+/H+ exchange elevates pHi preferentially in estrogen receptor-negative breast carcinomas, whereas Na+,HCO3– cotransport raises pHi more in invasive lobular than ductal breast carcinomas and in higher malignancy grade breast cancer. HER2-positive breast carcinomas have elevated protein expression of Na+/H+ exchanger NHE1/SLC9A1 and Na+,HCO3– cotransporter NBCn1/SLC4A7. Increased dependency on Na+,HCO3– cotransport associates with severe breast cancer: enlarged CO2/HCO3–-dependent rises in pHi predict accelerated cell proliferation, whereas enhanced CO2/HCO3–-dependent net acid extrusion, elevated NBCn1 protein expression, and reduced NHE1 protein expression predict lymph node metastasis. Accordingly, we observe reduced survival for patients suffering from luminal A or basal-like/triple-negative breast cancer with high SLC4A7 and/or low SLC9A1 mRNA expression. We conclude that the molecular mechanisms of acid-base regulation depend on clinicopathological characteristics of breast cancer patients. NBCn1 expression and dependency on Na+,HCO3– cotransport for pHi regulation, measured in biopsies of human primary breast carcinomas, independently predict proliferative activity, lymph node metastasis, and patient survival.

Luminal A is the most common breast cancer molecular subtype in women worldwide. These tumors have characteristic yet heterogeneous alterations at the genomic and transcriptomic level. Gene co-expression networks (GCNs) have contributed to better characterize the cancerous phenotype. We have previously shown an imbalance in the proportion of intra-chromosomal (cis-) over inter-chromosomal (trans-) interactions when comparing cancer and healthy tissue GCNs. In particular, for breast cancer molecular subtypes (Luminal A included), the majority of high co-expression interactions connect gene-pairs in the same chromosome, a phenomenon that we have called loss of trans- co-expression. Despite this phenomenon has been described, the functional implication of this specific network topology has not been studied yet. To understand the biological role that communities of co-expressed genes may have, we constructed GCNs for healthy and Luminal A phenotypes. Network modules were obtained based on their connectivity patterns and they were classified according to their chromosomal homophily (proportion of cis-/trans- interactions). A functional overrepresentation analysis was performed on communities in both networks to observe the significantly enriched processes for each community. We also investigated possible mechanisms for which the loss of trans- co-expression emerges in cancer GCN. To this end we evaluated transcription factor binding sites, CTCF binding sites, differential gene expression and copy number alterations (CNAs) in the cancer GCN. We found that trans- communities in Luminal A present more significantly enriched categories than cis- ones. Processes, such as angiogenesis, cell proliferation, or cell adhesion were found in trans- modules. The differential expression analysis showed that FOXM1, CENPA, and CIITA transcription factors, exert a major regulatory role on their communities by regulating expression of their target genes in other chromosomes. Finally, identification of CNAs, displayed a high enrichment of deletion peaks in cis- communities. With this approach, we demonstrate that network topology determine, to at certain extent, the function in Luminal A breast cancer network. Furthermore, several mechanisms seem to be acting together to avoid trans- co-expression. Since this phenomenon has been observed in other cancer tissues, a remaining question is whether the loss of long distance co-expression is a novel hallmark of cancer.

Luminal A is the most common breast cancer molecular subtype in women worldwide. These tumors have characteristic yet heterogeneous alterations at the genomic and transcriptomic level. Gene co-expression networks (GCNs) have contributed to better characterize the cancerous phenotype. We have previously shown an imbalance in the proportion of intra-chromosomal (cis-) over inter-chromosomal (trans-) interactions when comparing cancer and healthy tissue GCNs. In particular, for breast cancer molecular subtypes (Luminal A included), the majority of high co-expression interactions connect gene-pairs in the same chromosome, a phenomenon that we have called loss of trans- co-expression. Despite this phenomenon has been described, the functional implication of this specific network topology has not been studied yet. To understand the biological role that communities of co-expressed genes may have, we constructed GCNs for healthy and Luminal A phenotypes. Network modules were obtained based on their connectivity patterns and they were classified according to their chromosomal homophily (proportion of cis-/trans- interactions). A functional overrepresentation analysis was performed on communities in both networks to observe the significantly enriched processes for each community. We also investigated possible mechanisms for which the loss of trans- co-expression emerges in cancer GCN. To this end we evaluated transcription factor binding sites, CTCF binding sites, differential gene expression and copy number alterations (CNAs) in the cancer GCN. We found that trans- communities in Luminal A present more significantly enriched categories than cis- ones. Processes, such as angiogenesis, cell proliferation, or cell adhesion were found in trans- modules. The differential expression analysis showed that FOXM1, CENPA, and CIITA transcription factors, exert a major regulatory role on their communities by regulating expression of their target genes in other chromosomes. Finally, identification of CNAs, displayed a high enrichment of deletion peaks in cis- communities. With this approach, we demonstrate that network topology determine, to at certain extent, the function in Luminal A breast cancer network. Furthermore, several mechanisms seem to be acting together to avoid trans- co-expression. Since this phenomenon has been observed in other cancer tissues, a remaining question is whether the loss of long distance co-expression is a novel hallmark of cancer. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is the most prevalent cancer and the one with the highest mortality among women worldwide. Although the molecular classification of BC has been a helpful tool for diagnosing and predicting the treatment of BC, developments are still being made to improve the diagnosis and find new therapeutic targets. Mitochondrial dysfunction is a crucial feature of cancer, which can be associated with cancer aggressiveness. Although the importance of mitochondrial dynamics in cancer is well recognized, its involvement in the mitochondrial function and bioenergetics context in BC molecular subtypes has been scantly explored. In this study, we combined mitochondrial function and bioenergetics experiments in MCF7 and MDA-MB-231 cell lines with statistical and bioinformatics analyses of the mitochondrial proteome of luminal A and basal-like tumors. We demonstrate that basal-like tumors exhibit a vicious cycle between mitochondrial fusion and fission; impaired but not completely inactive mitochondrial function; and the Warburg effect, associated with decreased oxidative phosphorylation (OXPHOS) complexes I and III. Together with the results obtained in the cell lines and the mitochondrial proteome analysis, two mitochondrial signatures were proposed: one signature reflecting alterations in mitochondrial functions and a second signature exclusively of OXPHOS, which allow us to distinguish between luminal A and basal-like tumors.

Background: Epirubicin combined with docetaxel is the cornerstone of neoadjuvant chemotherapy (NAC) for breast cancer. The efficacy of NAC for luminal A breast cancer patients is very limited, and single nucleotide polymorphism is one of the most important factors that influences the efficacy. Our study is aimed to explore genetic markers for the efficacy of epirubicin combined with docetaxel for NAC in patients with luminal A breast cancer.Methods: A total of 421 patients with two stages of luminal A breast cancer were enrolled in this study from 2 centers. Among them 231 patients were included in the discovery cohort and 190 patients are in the replication cohort. All patients received epirubicin 75 mg/m2 and docetaxel 75 mg/m2 on day 1, in a 21-day cycle, a cycle for 2–6 cycles. Before treatment, 2 ml of peripheral blood was collected from each patient to isolate genomic DNA. Fourteen functional variants potentially regulating epirubicin/docetaxel response genes were prioritized by CellMiner and bioinformatics approaches. Moreover, biological assays were performed to determine the effect of genetic variations on response to chemotherapy.Results: The patients carrying rs6484711 variant A allele suffered a poor response to epirubicin and docetaxel for NAC (OR = 0.37, 95% CI: 0.18–0.74, P = 0.005) in combined stage. Moreover, expression quantitative trait loci (eQTL) analyses and luciferase reporter assays revealed that rs6484711 A allele significantly increased the expression of ABTB2. Subsequent biological assays illustrated that upregulation of ABTB2 significantly reduced the apoptosis rate of breast cancer cells and enhanced the chemo-resistance to epirubicin.Conclusions: Our study demonstrated rs6484711 polymorphism regulating ABTB2 expression might predict efficacy to epirubicin based NAC in luminal A breast cancer patients. These results provided valuable information about potential role of genetic variations in individualized chemotherapy.

Background: Epirubicin combined with docetaxel is the cornerstone of neoadjuvant chemotherapy (NAC) for breast cancer. The efficacy of NAC for luminal A breast cancer patients is very limited, and single nucleotide polymorphism is one of the most important factors that influences the efficacy. Our study is aimed to explore genetic markers for the efficacy of epirubicin combined with docetaxel for NAC in patients with luminal A breast cancer. Methods: A total of 421 patients with two stages of luminal A breast cancer were enrolled in this study from 2 centers. Among them 231 patients were included in the discovery cohort and 190 patients are in the replication cohort. All patients received epirubicin 75 mg/m2 and docetaxel 75 mg/m2 on day 1, in a 21-day cycle, a cycle for 2–6 cycles. Before treatment, 2 ml of peripheral blood was collected from each patient to isolate genomic DNA. Fourteen functional variants potentially regulating epirubicin/docetaxel response genes were prioritized by CellMiner and bioinformatics approaches. Moreover, biological assays were performed to determine the effect of genetic variations on response to chemotherapy. Results: The patients carrying rs6484711 variant A allele suffered a poor response to epirubicin and docetaxel for NAC (OR = 0.37, 95% CI: 0.18–0.74, P = 0.005) in combined stage. Moreover, expression quantitative trait loci (eQTL) analyses and luciferase reporter assays revealed that rs6484711 A allele significantly increased the expression of ABTB2. Subsequent biological assays illustrated that upregulation of ABTB2 significantly reduced the apoptosis rate of breast cancer cells and enhanced the chemo-resistance to epirubicin. Conclusions: Our study demonstrated rs6484711 polymorphism regulating ABTB2 expression might predict efficacy to epirubicin based NAC in luminal A breast cancer patients. These results provided valuable information about potential role of genetic variations in individualized chemotherapy. [ABSTRACT FROM AUTHOR]

The prognosis of hormone receptor-positive and HER2-negative breast cancer is better than that of other subtypes. Current guidelines recommend chemotherapy for N1 breast cancer patients. However, this has the possibility to be over-treatment. This was a retrospective study of 18,549 patients who were surgically treated for invasive breast cancer, at a single center in South Korea, between January 1993 and December 2012. N1 stage breast cancer patients who were hormone receptor-positive and HER2-negative were enrolled, and propensity score matching was performed to compare patients treated with anti-hormonal therapy alone (N = 83) and those treated with chemotherapy followed by anti-hormonal therapy (N = 85). In survival analysis, the survival parameters of the endocrine therapy-only group and the chemotherapy with endocrine therapy group were respectively 96.1% and 94.0% for 5-year recurrence free survival (RFS), 89.6% and 94.0% for 10-year RFS, 97.4% and 94.0% for 5-year distant metastasis-free survival (DMFS), 93.2% and 94.0% for 10-year DMFS, 98.7% and 98.8% for 10-year breast cancer-specific survival (BCSS), and 98.7% and 98.8% for 10-year overall survival (OS). There were no significant differences in RFS (p = 0.871), DMFS (p = 0.491), BCSS (p = 0.569) and OS (p = 0.731) between the two groups. Several patients with clinicopathologic features like hormone receptor positivity and HER2 negativity can avoid chemotherapy even with lymph node metastasis. Future studies with a long-term follow-up and a larger number of patients are required for validating our results. [ABSTRACT FROM AUTHOR]

Breast cancer is a highly concerning and prevalent disease that impacts a significant proportion of women worldwide, whose repeated exposure to therapies leads to resistance for drugs; making it alarming to identify novel chemotherapeutic agents. Sinapic acid is a phenolic acid that occurs naturally and is known to exhibit cytotoxic action in a variety of cancer cell types. In the present study, we utilized cell cytotoxicity assays to assess the cytotoxic potential of sinapic acid on various breast cancer subtypes. In addition, we assessed the cell migration rate, cell apoptosis, and cell cycle phases. Moreover, we utilized multiple system biology tools to predict the potential targets, and molecular docking was performed on the hub targets followed by molecular dynamic (MD) simulations. Cytotoxicity assay was performed on cell lines MCF7, T47D, MDA-MB-468, and SKBR3 at different time exposures of 24, 48, and 96 h. Our results revealed sinapic acid to be potent on MCF7 and T47D cell lines. The cell cycle analysis and cell apoptotic assays revealed sinapic acid to cause cell death by apoptosis majorly in the G0/G1 phase. Computational biology revealed KIF18B and VKORC1 to possess the highest binding affinity of -6.5 and -7.5 kcal/mol; displayed stable trajectories on MD run. The cytotoxicity of sinapic acid on luminal A cell lines may be due to the modulation of VKORC1 and KIF18B with major cell death in the G0/G1 phase. However, the mechanism has been proposed via in silico tools, which need further validation using wet lab protocols.Communicated by Ramaswamy H. Sarma.

Endocrine therapy and radiotherapy are the main treatments for luminal A breast cancer. However, drug and radiotherapy resistance could occur during long‐term treatment, leading to local recurrence and distant metastasis. Some studies have found that drug resistance might be related to human epidermal growth factor receptor‐3 (HER3) overexpression. However, whether HER3 plays a role in radiotherapy resistance is unknown. The purpose of this study is to elucidate the effect of HER3 in radiotherapy and to assess whether HER3 could be a potential target for radiosensitivity. We used retroviruses to construct stable low expression of HER3 in MCF‐7 and ZR75‐1cells. The CCK‐8 assay was used to observe proliferation. Colony‐forming assay was used to detect radiosensitivity. Flow cytometry was used to observe the cell cycle and apoptosis. Immunofluorescence assay was used to detect the number of γH2AX foci in the nucleus with or without ionizing radiation (IR). Western blot analysis was used to verify the change of relative proteins. Nude mice were used to observe tumor growth in vivo. In our study, silencing HER3 reduced cell proliferation and clone formation ability after IR, so silencing HER3 increased the sensitivity of luminal A breast cancer cells to radiotherapy. In terms of radiosensitivity mechanisms, it is suggested that the silencing of HER3 enhanced IR‐induced DNA damage, reduced DNA repair, and increased apoptosis and G2/M arrest. In addition, silencing HER3 combined with IR clearly inhibited the transplanted tumor growth in vivo. Therefore, we concluded that HER3 played a role in radiotherapy resistance. Silencing HER3 increased the radiosensitivity of luminal A breast cancer cells and HER3 could be a potential target for radiosensitivity. The purpose of this study is to elucidate the effect of human epidermal growth factor receptor‐3 (HER3) in radiotherapy resistance and further assess whether HER3 could be a potential target for radiosensitivity. We concluded that silencing HER3 could significantly increase the radiosensitivity of luminal A breast cancer cells and HER3 could be a potential target for radiotherapy. [ABSTRACT FROM AUTHOR]

The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is one of the most frequently occurring malignant cancers worldwide. Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two most common histological subtypes of breast cancer. In this study, we aimed to deeply explore molecular characteristics and the relationship between IDC and ILC subtypes in luminal A subgroup of breast cancer using comprehensive proteomics and phosphoproteomics analysis., Methods: Cancer tissues and noncancerous adjacent tissues (NATs) with the luminal A subtype (ER- and PR-positive, HER2-negative) were obtained from paired IDC and ILC patients respectively. Label-free quantitative proteomics and phosphoproteomics methods were used to detect differential proteins and the phosphorylation status between 10 paired breast cancer and NATs. Then, the difference in protein expression and its phosphorylation between IDC and ILC subtypes were explored. Meanwhile, the activation of kinases and their substrates was also revealed by Kinase-Substrate Enrichment Analysis (KSEA)., Results: In the luminal A breast cancer, a total of 5,044 high-confidence proteins and 3,808 phosphoproteins were identified from 10 paired tissues. The protein phosphorylation level in ILC tissues was higher than that in IDC tissues. Histone H1.10 was significantly increased in IDC but decreased in ILC, Conversely, complement C4-B and Crk-like protein were significantly decreased in IDC but increased in ILC. Moreover, the increased protein expression of Septin-2, Septin-9, Heterogeneous nuclear ribonucleoprotein A1 and Kinectin but reduce of their phosphorylation could clearly distinguish IDC from ILC. In addition, IDC was primarily related to energy metabolism and MAPK pathway, while ILC was more closely involved in the AMPK and p53/p21 pathways. Furthermore, the kinomes in IDC were primarily significantly activated in the CMGC groups., Conclusions: Our research provides insights into the molecular characterization of IDC and ILC and contributes to discovering novel targets for further drug development and targeted treatment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yang, Zuo, Lin, Zhou, Wen, Zhang, Xiao, Jiang, Fujita, Gao and Fu.)

Though combination chemotherapy or antitumor nanomedicine is extensively investigated, their combining remains in infancy. Additionally, enhanced delivery of estrogen or its analogs to tumor with highly-expressed estrogen-receptor (ER) is seldom considered, despite its necessity for ER-positive breast cancer treatment. Here, nanomedicine based combination therapy using QLPVM conjugated liposomal tamoxifen (TAM) and doxorubicin (DOX) was designed and testified, where the penta-peptide was derived from Ku70 Bax-binding domain. Quantitative, semi-quantitative and qualitative approaches demonstrated the enhanced endocytosis and cytotoxicity of QLPVM conjugated sterically stabilized liposomes (QLPVM-SSLs) in vitro and in vivo . Mechanism studies of QLPVM excluded the possible electrostatic, hydrophobic or receptor–ligand interactions. However, as a weak cell-penetrating peptide, QLPVM significantly induced drug release from QLPVM-SSLs during their interaction with cells, which was favorable for drug internalization. These findings suggested that the nanomedicine based combination therapy using QLPVM-SSL-TAM and QLPVM-SSL-DOX might provide a rational strategy for Luminal A breast cancer. From the Clinical Editor Breast cancer remains a leading cause of mortality in women worldwide. Although combined therapy using hormonal antagonist and chemotherapy is the norm nowadays, the use of these agents together in a single delivery system has not been tested. Here, the authors investigated this approach using QLPVM conjugated liposomes in in-vitro and in-vivo models. The positive findings may provide a novel direction for breast cancer treatment in the near future. [ABSTRACT FROM AUTHOR]

In process of infiltrating growth in solid tumor, the tumor cells undergo a periodic hypoxia/reoxygenation (circulating hypoxia) microenvironment, which might be one of principle reasons to promote formation of tumor heterogeneity and treatment failure. Therefore, it is very important to study how the microenvironment of circulating hypoxia induces the heterogeneous subclones in tumors. The maximum cross-section of luminal A tumor (LAT) was selected for the expression of hypoxia inducible factor-1 alpha (HIF-1 alpha) and estrogen receptor-alpha (ER-alpha), and the correlation between it and tumor diameter was observed. The distribution of intratumoral micro-vessels were analyzed by 3D reconstruction and CD34 staining. A circulating hypoxia model of MCF-7 was established to detect the HIF-1alpha and ER-alpha. There was a negative correlation between the expressions of ER-alpha and HIF-1alpha (c=−2.40; p = 0.044) in the LAT. As shown by 3D ultrasound image, there were less functional micro-vessels in the center than the periphery of tumor(P < 0.05). ER-alpha expression gradually decreased with the time course of cycling hypoxia, which is inversely related to the expression of HIF-1alpha. LAT is composed of heterogeneous subclone cells which can be distinguished by ER-alpha and HIF-1alpha, which was closely related with cycling hypoxia microenvironment. • The tumor cells undergo circulating hypoxia might promote formation of tumor heterogeneity and treatment failure. • It is very important to study how the microenvironment of circulating hypoxia induces the heterogeneous subclones in tumors. • Estrogen receptor-alpha and hypoxia inducible factor-1alpha were closely related with cycling hypoxia microenvironment. • Our study suggested that luminal A tumor was composed of heterogeneous subclone cells, which could be distinguished by HIF-1alpha and ER-alpha. • The heterogeneity between edge and center of the tumor aggravated along with the primary tumor growth. [ABSTRACT FROM AUTHOR]

Convincing epidemiologic evidence indicates that physical activity is inversely associated with breast cancer risk. Whether this association varies by the tumor protein expression status of the estrogen receptor ( ER), progesterone receptor ( PR), human epidermal growth factor receptor 2 ( HER2), or p53 is unclear. We evaluated the effects of recreational physical activity on risk of invasive breast cancer classified by the four biomarkers, fitting multivariable unconditional logistic regression models to data from 1195 case and 2012 control participants in the population-based Women's Contraceptive and Reproductive Experiences Study. Self-reported recreational physical activity at different life periods was measured as average annual metabolic equivalents of energy expenditure [ MET]-hours per week. Our biomarker-specific analyses showed that lifetime recreational physical activity was negatively associated with the risks of ER-positive ( ER+) and of HER2-negative ( HER2−) subtypes (both Ptrend ≤ 0.04), but not with other subtypes (all Ptrend > 0.10). Analyses using combinations of biomarkers indicated that risk of invasive breast cancer varied only by HER2 status. Risk of HER2-breast cancer decreased with increasing number of MET-hours of recreational physical activity in each specific life period examined, although some trend tests were only marginally statistically significant (all Ptrend ≤ 0.06). The test for homogeneity of trends ( HER2- vs. HER2+ ) reached statistical significance only when evaluating physical activity during the first 10 years after menarche ( Phomogeneity = 0.03). Our data suggest that physical activity reduces risk of invasive breast cancers that lack HER2 overexpression, increasing our understanding of the biological mechanisms by which physical activity acts. [ABSTRACT FROM AUTHOR]

As one of the most common breast cancer subtypes, luminal A breast cancer is sensitive to endocrine-based therapy and insensitive to chemotherapy. Patients with luminal A subtype of breast cancer have a relatively good prognosis compared with that of patients with other subtypes of breast cancer. However, with the increased incidence in endocrine resistance and severe side effects, simple endocrine therapy has become unsuitable for the treatment of luminal A breast cancer. Therefore, identifying novel therapeutic targets for luminal A breast cancer may accelerate the development of an effective therapeutic strategy. The bioinformatical analysis of the current study, which included KEGG and GO analyses of the GSE20437 dataset containing 24 healthy and 18 breast cancer tissue samples, identified key target genes associated with breast cancer. Moreover, survival analysis results revealed that a low expression of BTG2 was significantly associated with the low survival rate of patients with breast cancer, indicated that B-cell translocation gene 2 (BTG2) may be a potential target in breast cancer. However, BTG2 may be cancer type-dependent, as overexpression of BTG2 has been demonstrated to suppress the proliferation of pancreatic and lung cancer cells, but promote the proliferation of bladder cancer cells. Since the association between BTG2 and luminal A-subtype breast cancer remains unclear, it is important to understand the biological function of BTG2 in luminal A breast cancer. Based on the expression levels of estrogen receptor, progesterone receptor and human epidermal growth factor receptor, MCF-7 cells were selected in the present study as a luminal A breast cancer cell type. MTT, Transwell invasion and wound healing assays revealed that overexpression of BTG2 suppressed the levels of MCF-7 cell proliferation, migration and invasion. In addition, the downregulation of BTG2 at the mRNA and protein level was also confirmed in luminal A breast tumor tissue, which was consistent with the results in vitro. These results indicated that BTG2 may act as an effective target for the treatment of luminal A breast cancer. [ABSTRACT FROM AUTHOR]

Breast cancer is a collection of diseases with distinct molecular traits, prognosis, and therapeutic options. Luminal A breast cancer is the most heterogeneous, both molecularly and clinically. Using genomic data from over 1,000 Luminal A tumors from multiple studies, we analyzed the copy number and mutational landscape of this tumor subtype. This integrated analysis revealed four major subtypes defined by distinct copy-number and mutation profiles. We identified an atypical Luminal A subtype characterized by high genomic instability, TP53 mutations, and increased Aurora kinase signaling; these genomic alterations lead to a worse clinical prognosis. Aberrations of chromosomes 1, 8, and 16, together with PIK3CA, GATA3, AKT1, and MAP3K1 mutations drive the other subtypes. Finally, an unbiased pathway analysis revealed multiple rare, but mutually exclusive, alterations linked to loss of activity of co-repressor complexes N-Cor and SMRT. These rare alterations were the most prevalent in Luminal A tumors and may predict resistance to endocrine therapy. Our work provides for a further molecular stratification of Luminal A breast tumors, with potential direct clinical implications. [ABSTRACT FROM AUTHOR]