The Proliferative and Apoptotic Landscape of Basal-like Breast Cancer

Flurbiprofen axetil is involved in basal-like breast cancer metastasis via suppressing the MEK/ERK signaling pathway

Flurbiprofen axetil is commonly utilized in clinical practice as one of the nonsteroidal anti-inflammatory drugs (NSAIDs) and is included in multimodal analgesia regimens postbreast cancer surgery. Numerous NSAIDs have been studied for their potential to both promote and inhibit cancer. Given the variability in their effects on tumors, further investigation into the specific role of flurbiprofen axetil is warranted. Therefore, the primary objective of this study was to assess the impact of flurbiprofen axetil on basal-like breast cancer (BLBC) metastasis and elucidate the underlying molecular mechanisms involved. The BLBC metastasis mouse model was established by caudal vein injection of tumor cells. The lung metastasis of breast cancer in mice and the effect of flurbiprofen axetil were assessed by in vivo bioluminescence imaging, hematoxylin and eosin staining and immunohistochemistry. In vitro, the results of flurbiprofen axetil on the proliferation, migration, and invasion of MDA-MB-231 human breast cancer cells and BT-549 human breast cancer cells were assessed by colony formation assay and transwell assay. The effects of flurbiprofen axetil on several tumor metastasis-related signaling pathway proteins were examined by western blot, and the reversal extent of the flurbiprofen axetil effect by Ro 67-7476 (ERK phosphorylation agonist) was detected by transwell assay. The results showed that flurbiprofen axetil significantly inhibited BLBC lung metastasis in mice. Flurbiprofen axetil similarly inhibited breast cancer cell migration and invasion in vitro but did not affect their proliferation. Mechanistic investigations have revealed that flurbiprofen axetil exerts a noteworthy inhibitory influence on the MEK/ERK pathway while exhibiting no significant alteration in the expression of other pathway proteins intricately associated with epithelial-mesenchymal transition. In conclusion, the inhibitory effect of flurbiprofen axetil on BLBC metastasis is characterized by its selectivity in targeting the MEK/ERK signaling pathway rather than exerting a broad impact on the global signaling pathway.

POP1 Facilitates Proliferation in Triple-Negative Breast Cancer via m6A-Dependent Degradation of CDKN1A mRNA

Triple-negative breast cancer (TNBC) is currently the worst prognostic subtype of breast cancer, and there is no effective treatment other than chemotherapy. Processing of precursors 1 (POP1) is the most substantially up-regulated RNA-binding protein (RBP) in TNBC. However, the role of POP1 in TNBC remains clarified. A series of molecular biological experiments in vitro and in vivo and clinical correlation analyses were conducted to clarify the biological function and regulatory mechanism of POP1 in TNBC. Here, we identified that POP1 is significantly up-regulated in TNBC and associated with poor prognosis. We further demonstrate that POP1 promotes the cell cycle and proliferation of TNBC in vitro and vivo. Mechanistically, POP1 directly binds to the coding sequence (CDS) region of CDKN1A mRNA and degrades it. The degradation process depends on the N6-methyladenosine (m6A) modification at the 497th site of CDKN1A and the recognition of this modification by YTH N6-methyladenosine RNA binding protein 2 (YTHDF2). Moreover, the m6A inhibitor STM2457 potently impaired the proliferation of POP1-overexpressed TNBC cells and improved the sensitivity to paclitaxel. In summary, our findings reveal the pivotal role of POP1 in promoting TNBC proliferation by degrading the mRNA of CDKN1A and that inhibition of m6A with STM2457 is a promising therapeutic strategy for TNBC.

Breast Cancer Stem Cells and Tumor Heterogeneity: Characteristics and Therapeutic Strategies

Breast cancer is one of the most frequently detected malignancies worldwide. It is responsible for more than 15% of all death cases caused by cancer in women. Breast cancer is a heterogeneous disease representing various histological types, molecular characteristics, and clinical profiles. However, all breast cancers are organized in a hierarchy of heterogeneous cell populations, with a small proportion of cancer stem cells (breast cancer stem cells (BCSCs)) playing a putative role in cancer progression, and they are responsible for therapeutic failure. In different molecular subtypes of breast cancer, they present different characteristics, with specific marker profiles, prognoses, and treatments. Recent efforts have focused on tackling the Wnt, Notch, Hedgehog, PI3K/Akt/mTOR, and HER2 signaling pathways. Developing diagnostics and therapeutic strategies enables more efficient elimination of the tumor mass together with the stem cell population. Thus, the knowledge about appropriate therapeutic methods targeting both "normal" breast cancer cells and breast cancer stem cell subpopulations is crucial for success in cancer elimination.

Prognostic implications of TOR1B expression across cancer types: a focus on basal-like breast cancer and cellular adaptations to hypoxia

The TOR1B gene is known to play a pivotal role in maintaining cellular homeostasis and responding to endoplasmic reticulum stress. However, its involvement in cancer remains relatively understudied. This study seeks to explore the prognostic implications of TOR1B across various cancers, with a specific focus on Basal-like Breast Cancer (BLBC) and its underlying cellular mechanisms. Through comprehensive analysis of data from TCGA, TARGET, GEO, and GTEx, we investigated TOR1B expression and its correlation with patient outcomes. Furthermore, in vitro experiments conducted on BLBC cell lines examined the impact of TOR1B modulation on cell viability, apoptosis, and metabolic activity under varying oxygen levels. Our statistical analysis encompassed differential expression analysis, survival analysis, and multivariate Cox regression. Our findings indicate that TOR1B is overexpressed in BLBC and other cancers, consistently correlating with poorer prognosis. Elevated TOR1B levels were significantly associated with reduced overall and disease-free survival in BLBC patients. In vitro experiments further revealed that TOR1B knockdown augmented apoptosis and influenced metabolic activity, particularly under hypoxic conditions, highlighting its potential role in cancer cell adaptation to stress. Overall, our study underscores the importance of TOR1B in cancer progression, particularly in BLBC, where it serves as a notable prognostic indicator. The interaction between TOR1B and metabolic pathways, as well as its regulation by HIF-1α, suggests its significance in adapting to hypoxia, thereby positioning TOR1B as a promising therapeutic target for aggressive breast cancer subtypes.

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning

Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate the specific gene expression and tumor staging. However, the knowledge in this regard is still far from complete. Thus, this study aimed to explore these knowledge gaps by analyzing existing gene expression profile data from 3149 breast cancer samples, where each sample was represented by the expression of 19,644 genes and classified into Nottingham histological grade (NHG) classes (Grade 1, 2, and 3). To this end, a machine learning-based framework was designed. First, the profile data were analyzed by using seven feature ranking algorithms to evaluate the importance of features (genes). Seven feature lists were generated, each of which sorted features in accordance with feature importance evaluated from a special aspect. Then, the incremental feature selection method was applied to each list to determine essential features for classification and building efficient classifiers. Consequently, overlapping genes, such as AURKA, CBX2, and MYBL2, were deemed as potentially related to breast cancer malignancy and prognosis, indicating that such genes were identified to be important by multiple feature ranking algorithms. In addition, the study formulated classification rules to reflect special gene expression patterns for three NHG classes. Some genes and rules were analyzed and supported by recent literature, providing new references for studying breast cancer.

Unsupervised Single-Cell Clustering with Asymmetric Within-Sample Transformation and Per-Cluster Supervised Features Selection

This chapter shows applying the Asymmetric Within-Sample Transformation to single-cell RNA-Seq data matched with a previous dropout imputation. The asymmetric transformation is a special winsorization that flattens low-expressed intensities and preserves highly expressed gene levels. Before a standard hierarchical clustering algorithm, an intermediate step removes noninformative genes according to a threshold applied to a per-gene entropy estimate. Following the clustering, a time-intensive algorithm is shown to uncover the molecular features associated with each cluster. This step implements a resampling algorithm to generate a random baseline to measure up/downregulated significant genes. To this aim, we adopt a GLM model as implemented in DESeq2 package. We render the results in graphical mode. While the tools are standard heat maps, we introduce some data scaling to clarify the results' reliability.

Epigenetic Profiles of Triple-Negative Breast Cancers of African American and White Females

Importance

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and appears to have disproportionately higher incidence and worse outcomes among younger African American females.

Objective

To investigate whether epigenetic differences exist in TNBCs of younger African American females that may explain clinical disparities seen in this patient group.

Design, Setting, and Participants

This cross-sectional study used clinical, demographic, DNA methylation (HumanMethylation450; Illumina), and gene expression (RNA sequencing) data for US patient populations from publicly available data repositories (The Cancer Genome Atlas [TCGA], 2006-2012, and Gene Expression Omnibus [GEO], 2004-2013) accessed on April 13, 2021. White and African American females with TNBC identified in TCGA (69 patients) and a validation cohort of 210 African American patients from GEO (GSE142102) were included. Patients without available race or age data were excluded. Data were analyzed from September 2022 through April 2023.

Main Outcomes and Measures

DNA methylation and gene expression profiles of TNBC tumors by race (self-reported) and age were assessed. Age was considered a dichotomous variable using age 50 years as the cutoff (younger [<50 years] vs older [≥50 years]).

Results

A total of 69 female patients (34 African American [49.3%] and 35 White [50.7%]; mean [SD; range] age, 55.7 [11.6; 29-82] years) with TNBC were included in the DNA methylation analysis; these patients and 210 patients in the validation cohort were included in the gene expression analysis (279 patients). There were 1115 differentially methylated sites among younger African American females. The DNA methylation landscape on TNBC tumors in this population had increased odds of enrichment of hormone (odds ratio [OR], 1.82; 95% CI, 1.21 to 2.67; P = .003), muscle (OR, 1.85; 95% CI, 1.44 to 2.36; P < .001), and proliferation (OR, 3.14; 95% CI, 2.71 to 3.64; P < .001) pathways vs other groups (older African American females and all White females). Alterations in regulators of these molecular features in TNBCs of younger African American females were identified involving hormone modulation (downregulation of androgen receptor: fold change [FC] = -2.93; 95% CI, -4.76 to -2.11; P < .001) and upregulation of estrogen-related receptor α (FC = 0.86; 95% CI, 0.34 to 1.38; P = .002), muscle metabolism (upregulation of FOXC1: FC = 1.33; 95% CI, 0.62 to 2.03; P < .001), and proliferation mediators (upregulation of NOTCH1: FC = 0.71; 95% CI, 0.23 to 1.19; P = .004 and MYC (FC = 0.81; 95% CI, 0.18 to 1.45; P = .01).

Conclusions and Relevance

These findings suggest that TNBC of younger African American females may represent a distinct epigenetic entity and offer novel insight into molecular alterations associated with TNBCs of this population. Understanding these epigenetic differences may lead to the development of more effective therapies for younger African American females, who have the highest incidence and worst outcomes from TNBC of any patient group.

Role of RUNX2 in breast cancer development and drug resistance (Review)

Breast cancer is the most common malignancy and ranks second among the causes of tumor-associated death in females. The recurrence and drug resistance of breast cancer are intractable due to the presence of breast cancer stem cells (BCSCs), which are adequate to initiate tumor formation and refractory to conventional remedies. Runt-related transcription factor 2 (RUNX2), a pivotal transcription factor in mammary gland and bone development, has also been related to metastatic cancer and BCSCs. State-of-the-art research has indicated the retention of RUNX2 expression in a more invasive subtype of breast cancer, and in particular, triple-negative breast cancer development and drug resistance are associated with estrogen receptor signaling pathways. The present review mainly focused on the latest updates on RUNX2 in BCSCs and their roles in breast cancer progression and drug resistance, providing insight that may aid the development of RUNX2-based diagnostics and treatments for breast cancer in clinical practice.

Integrating Tumor-Intrinsic and Immunologic Factors to Identify Immunogenic Breast Cancers from a Low-Risk Cohort: Results from the Randomized SweBCG91RT Trial

PURPOSE

The local immune infiltrate's influence on tumor progression may be closely linked to tumor-intrinsic factors. The study aimed to investigate whether integrating immunologic and tumor-intrinsic factors can identify patients from a low-risk cohort who may be candidates for radiotherapy (RT) de-escalation.

EXPERIMENTAL DESIGN

The SweBCG91RT trial included 1,178 patients with stage I to IIA breast cancer, randomized to breast-conserving surgery with or without adjuvant RT, and followed for a median of 15.2 years. We trained two models designed to capture immunologic activity and immunomodulatory tumor-intrinsic qualities, respectively. We then analyzed if combining these two variables could further stratify tumors, allowing for identifying a subgroup where RT de-escalation is feasible, despite clinical indicators of a high risk of ipsilateral breast tumor recurrence (IBTR).

RESULTS

The prognostic effect of the immunologic model could be predicted by the tumor-intrinsic model (Pinteraction = 0.01). By integrating measurements of the immunologic- and tumor-intrinsic models, patients who benefited from an active immune infiltrate could be identified. These patients benefited from standard RT (HR, 0.28; 95% CI, 0.09-0.85; P = 0.025) and had a 5.4% 10-year incidence of IBTR after irradiation despite high-risk genomic indicators and a low frequency of systemic therapy. In contrast, high-risk tumors without an immune infiltrate had a high 10-year incidence of IBTR despite RT treatment (19.5%; 95% CI, 12.2-30.3).

CONCLUSIONS

Integrating tumor-intrinsic and immunologic factors may identify immunogenic tumors in early-stage breast cancer populations dominated by ER-positive tumors. Patients who benefit from an activated immune infiltrate may be candidates for RT de-escalation.

Enhanced characterization of breast cancer phenotypes using Raman micro-spectroscopy on stainless steel substrate

Biochemical insights into varying breast cancer (BC) phenotypes can provide a fundamental understanding of BC pathogenesis, while identifying novel therapeutic targets. Raman spectroscopy (RS) can gauge these biochemical differences with high specificity. For routine RS, cells are traditionally seeded onto calcium fluoride (CaF₂) substrates that are costly and fragile, limiting its widespread adoption. Stainless steel has been interrogated previously as a less expensive alternative to CaF₂ substrates, while reporting increased Raman signal intensity than the latter. We sought to further investigate and compare the Raman signal quality measured from stainless steel versus CaF₂ substrates by characterizing different BC phenotypes with altered human epidermal growth factor receptor 2 (HER2) expression. Raman spectra were obtained on stainless steel and CaF₂ substrates for HER2 negative cells - MDA-MB-231, MDA-MB-468 and HER2 overexpressing cells - AU565, SKBr3. Upon analyzing signal-to-noise ratios (SNR), stainless steel provided a stronger Raman signal, improving SNR by 119% at 1450 cm^-1 and 122% at 2925 cm^-1 on average compared to the CaF₂ substrate. Utilizing only 22% of laser power on sample relative to the CaF₂ substrate, stainless steel still yielded improved spectral characterization over CaF₂, achieving 96.0% versus 89.8% accuracy in BC phenotype discrimination and equivalent 100.0% accuracy in HER2 status classification. Spectral analysis further highlighted increased lipogenesis and altered metabolism in HER2 overexpressing cells, which was subsequently visualized with coherent anti-Stokes Raman scattering microscopy. Our findings demonstrate that stainless steel substrates deliver improved Raman signal and enhanced spectral characterization, underscoring its potential as a cost-effective alternative to CaF₂ for non-invasively monitoring cellular biochemical dynamics in translational cancer research.

Identification of prognostic genes for early basal-like breast cancer with weighted gene co-expression network analysis

BACKGROUND

Breast cancer (BC) has become the leading cause of death for women's malignancies and increasingly threatens the health of women worldwide. However, there is a lack of effective targeted drugs for basal-like BC. Therefore, biomarkers related to the prognosis of early BC need to be identified.

METHODS

The RNA-seq data of 87 cases of early basal-like BC and 111 cases of normal breast tissue from The Cancer Genome Atlas were explored by the weighted gene co-expression network analysis method and Limma package. Then, intersected genes were identified, and hub genes were selected by the maximal clique centrality method. The prognostic effect of the hub genes was also evaluated in early basal-like BC.

RESULTS

In total, 601 IGs were identified in this study. An APPI network was constructed, and the top 10 hub genes were selected, namely, cyclin B1, cyclin A2, cyclin-dependent kinase 1, cell division cycle 20, DNA topoisomerase II alpha, BUB1 mitotic checkpoint serine/threonine kinase, aurora kinase B (AURKB), cyclin B2, kinesin family member 11, and assembly factor for spindle microtubules. Only AURKB was found to be significantly associated with the overall prognosis of early basal-like BC. The immune cell infiltration analysis showed that the infiltration numbers of CD4 + T cells and naïve CD8 + T cells were positively correlated with the AURKB expression level, while those of naïve B cells and macrophage M2 cells were negatively correlated with the AURKB expression level in basal-like BC.

CONCLUSION

AURKB might be a potential prognostic indicator in early basal-like BC.

c-Kit Induces Migration of Triple-Negative Breast Cancer Cells and Is a Promising Target for Tyrosine Kinase Inhibitor Treatment

Triple-negative breast cancer (TNBC) is associated with a poor prognosis and the absence of targeted therapy. c-Kit, a receptor tyrosine kinase (RTK), is considered a molecular target for anticancer drugs. Tyrosine kinase inhibitors (TKIs) recognizing c-Kit are used for the treatment of c-Kit-expressing tumors. However, the expression, function, and therapeutic potential of c-Kit have been little explored in TNBC. Here, we studied the expression and effects of c-Kit in TNBC through in vitro and in silico analysis, and evaluated the response to TKIs targeting c-Kit. Analysis of TNBC cells showed the expression of functional c-Kit at the cell membrane. The stimulation of c-Kit with its ligand induced the activation of STAT3, Akt, and ERK1/2, increasing cell migration, but had no effect on cell proliferation or response to Doxorubicin. Analysis of public datasets showed that the expression of c-Kit in tumors was not associated with patient survival. Finally, TNBC cells were susceptible to TKIs, in particular the effect of Nilotinib was stronger than Doxorubicin in all cell lines. In conclusion, TNBC cells express functional c-Kit, which is a targetable molecule, and show a strong response to Nilotinib that may be considered a candidate drug for the treatment of TNBC.

High cyclin E1 protein, but not gene amplification, is prognostic for basal-like breast cancer

Basal-like breast cancer (BLBC) has a greater overlap in molecular features with high-grade serous ovarian cancer (HGSOC) than with other breast cancer subtypes. Similarities include BRCA1 mutation, high frequency of TP53 mutation, and amplification of CCNE1 (encoding the cyclin E1 protein) in 6-34% of cases, and these features can be used to group patients for targeted therapies in clinical trials. In HGSOC, we previously reported two subsets with high levels of cyclin E1: those in which CCNE1 is amplified, have intact homologous recombination (HR), and very poor prognosis; and a CCNE1 non-amplified subset, with more prevalent HR defects. Here, we investigate whether similar subsets are identifiable in BLBC that may allow alignment of patient grouping in clinical trials of agents targeting cyclin E1 overexpression. We examined cyclin E1 protein and CCNE1 amplification in a cohort of 76 BLBCs and validated the findings in additional breast cancer datasets. Compared to HGSOC, CCNE1 amplified BLBC had a lower level of amplification (3.5 versus 5.2 copies) and lower relative cyclin E1 protein, a lack of correlation of amplification with expression, and no association with polyploidy. BLBC with elevated cyclin E1 protein also had prevalent HR defects, and high-level expression of the cyclin E1 deubiquitinase ubiquitin-specific protease 28 (USP28). Using a meta-analysis across multiple studies, we determined that cyclin E1 protein overexpression but not amplification is prognostic in BLBC, while both cyclin E1 overexpression and amplification are prognostic in HGSOC. Overall CCNE1 gene amplification is not equivalent between BLBC and HGSOC. However, high cyclin E1 protein expression can co-occur with HR defects in both BLBC and HGSOC, and is associated with poor prognosis in BLBC.

Increased FOXA1 levels induce apoptosis and inhibit proliferation in FOXA1-low expressing basal breast cancer cells

The transcription factor FOXA1, which is a member of the forkhead class of DNA-binding proteins, interacts with Estrogen Receptor (ER) to mediate breast cancer progression. However, its role in basal breast cancer cells remains unclear. Although the overall levels of FOXA1 are decreased in the basal subtype of clinical TCGA breast cancer samples, the high levels of FOXA1 improve the survival of the patients from this subtype. This clinical phenomenon is consistent with that of FOXA1 stimulating apoptosis in FOXA1-low expressing basal breast cancer cells, such as MDA-MB-231, and MDA-MB-468 cells. In this study, we have constructed an inducible expression system of FOXA1 and demonstrated the induced expression of FOXA1 resulting in apoptosis and cell cycle arrest in MDA-MB-231 cells, as confirmed by transcriptomic analysis and in vivo tumor-grafted models. Furthermore, the low levels of Estrogen Receptor-1 (ESR1) are critical for FOXA1 in terms of its repressive roles in the cells, as evidenced by clinical data analysis indicating that the high levels of FOXA1 improve the survival of ESR1^Low patients, but worsen the survival of ESR1^High patients of breast cancer. When introduced into MDA-MB-231 cells, ESR1 counteracts the tumor suppressor roles of FOXA1 by altering the FOXA1-regulated gene transcription and the two proteins together maintain the tumor progression in vivo. Our cumulative results suggest that FOXA1 suppresses the basal breast cancer cells with FOXA1-low expressing status independent of ESR1 by inducing apoptosis and inhibiting cell proliferation, thereby implicating its potential therapeutic role in this group of breast cancer.

Synergistic targeting of BRCA1 mutated breast cancers with PARP and CDK2 inhibition

Basal-like breast cancers (BLBC) are aggressive breast cancers that respond poorly to targeted therapies and chemotherapies. In order to define therapeutically targetable subsets of BLBC we examined two markers: cyclin E1 and BRCA1 loss. In high grade serous ovarian cancer (HGSOC) these markers are mutually exclusive, and define therapeutic subsets. We tested the same hypothesis for BLBC. Using a BLBC cohort enriched for BRCA1 loss, we identified convergence between BRCA1 loss and high cyclin E1 protein expression, in contrast to HGSOC in which CCNE1 amplification drives increased cyclin E1. In cell lines, BRCA1 loss was associated with stabilized cyclin E1 during the cell cycle, and BRCA1 siRNA led to increased cyclin E1 in association with reduced phospho-cyclin E1 T62. Mutation of cyclin E1 T62 to alanine increased cyclin E1 stability. We showed that tumors with high cyclin E1/BRCA1 mutation in the BLBC cohort also had decreased phospho-T62, supporting this hypothesis. Since cyclin E1/CDK2 protects cells from DNA damage and cyclin E1 is elevated in BRCA1 mutant cancers, we hypothesized that CDK2 inhibition would sensitize these cancers to PARP inhibition. CDK2 inhibition induced DNA damage and synergized with PARP inhibitors to reduce cell viability in cell lines with homologous recombination deficiency, including BRCA1 mutated cell lines. Treatment of BRCA1 mutant BLBC patient-derived xenograft models with combination PARP and CDK2 inhibition led to tumor regression and increased survival. We conclude that BRCA1 status and high cyclin E1 have potential as predictive biomarkers to dictate the therapeutic use of combination CDK inhibitors/PARP inhibitors in BLBC.

Preoperative Rim Enhancement on Magnetic Resonance Imaging Indicates Larger Tumor Size and Poor Prognosis in Chinese Basal-Like Breast Cancer Patients

Background: This study was to investigate the prevalence of preoperative rim enhancement, and its association with clinicopathological features, relapse, and survival profiles in Chinese basal-like breast cancer (BC) patients. Materials and Methods: The preoperative breast magnetic resonance imaging images of 145 basal-like BC patients who underwent surgical excision were obtained to determine rim enhancement. Besides, based on disease status and survival status during follow-up, the 1-year relapse rate/mortality, 3-year relapse rate/mortality, 5-year relapse rate/mortality were calculated; disease-free survival (DFS) and overall survival (OS) were determined. Results: There were 51 (35.2%) patients with rim enhancement and 94 (64.8%) patients without rim enhancement. Furthermore, rim enhancement was associated with larger tumor size and advanced T stage, whereas it did not associate with age, pathological differentiation, N stage, or TNM stage. In addition, rim enhancement was associated with higher 1-, 3-, and 5-year relapse rate and shorter DFS; meanwhile, rim enhancement was associated with increased 1-, 3-, and 5-year mortality rate and decreased OS. By multivariate Cox's regression analyses, rim enhancement, pathological differentiation, and N stage independently predicted reduced DFS; T stage independently predicted declined OS. Conclusion: Preoperative rim enhancement on MRI might be a possible noninvasive indicator for guiding personalized treatment strategies and improving prognosis in Chinese basal-like BC patients.

AGR2 and AGR3 play an important role in the clinical characterization and prognosis of basal like breast cancer

INTRODUCTION

Basal-like Breast Cancer (BLBC) represents an important molecular subtype of breast cancer characterized by an aggressive behavior, molecular pathology poorly understood and a limited treatment.

OBJECTIVE

We aim to search for molecular differences between non-BLBC and BLBC tumors in order to propose possible diagnostic and prognostic biomarkers using databases. Metodology: Microarray processed data were downloaded from GEO database considering non-BLBC and BLBC. Enrichment analysis was evaluated using GO consortium and Ingenuity, protein-protein interaction, gene Ontology and co-expression analysis using STRING. Gene expression data was extracted using TCGA, METABRIC and Breast Cancer Gene-Expression Miner v4.2 databases. The Survival was evaluated using The Kaplan-Meier plotter.

RESULTS

Were identified 58 upregulated and 58 downregulated genes enriched in signaling pathways like PDGF, Angiogenesis, Integrin and WNT. AGR2 and AGR3 expression were reduced in BLBC in relation to non-BLBC tumors, patients aged ≤51 years, and with negativity of ER, PR and HER-2 and nodal status. Low expression of AGR2 and AGR3 were associated with worse OS and RFS for all breast cancer cases. But according to the molecular stratification, low AGR2 conferred worst OS in luminal A, worst RFS in BLBC and good OS and RFS in luminal B. High AGR3 conferred worse OS and RFS in BLBC, but low AGR3 attributed worse OS in luminal A.

CONCLUSION

AGR2 and AGR3 expression were able to differentiate non-BLBC from BLBC. Downregulation of AGR2 and AGR3 was associated with BLBC clinical phenotype. Furthermore, both genes behave different when considering prognosis and molecular stratification.

Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer

Background

Contemporary deep learning approaches show cutting-edge performance in a variety of complex prediction tasks. Nonetheless, the application of deep learning in healthcare remains limited since deep learning methods are often considered as non-interpretable black-box models. However, the machine learning community made recent elaborations on interpretability methods explaining data point-specific decisions of deep learning techniques. We believe that such explanations can assist the need in personalized precision medicine decisions via explaining patient-specific predictions.

Methods

Layer-wise Relevance Propagation (LRP) is a technique to explain decisions of deep learning methods. It is widely used to interpret Convolutional Neural Networks (CNNs) applied on image data. Recently, CNNs started to extend towards non-Euclidean domains like graphs. Molecular networks are commonly represented as graphs detailing interactions between molecules. Gene expression data can be assigned to the vertices of these graphs. In other words, gene expression data can be structured by utilizing molecular network information as prior knowledge. Graph-CNNs can be applied to structured gene expression data, for example, to predict metastatic events in breast cancer. Therefore, there is a need for explanations showing which part of a molecular network is relevant for predicting an event, e.g., distant metastasis in cancer, for each individual patient.

Results

We extended the procedure of LRP to make it available for Graph-CNN and tested its applicability on a large breast cancer dataset. We present Graph Layer-wise Relevance Propagation (GLRP) as a new method to explain the decisions made by Graph-CNNs. We demonstrate a sanity check of the developed GLRP on a hand-written digits dataset and then apply the method on gene expression data. We show that GLRP provides patient-specific molecular subnetworks that largely agree with clinical knowledge and identify common as well as novel, and potentially druggable, drivers of tumor progression.

Conclusions

The developed method could be potentially highly useful on interpreting classification results in the context of different omics data and prior knowledge molecular networks on the individual patient level, as for example in precision medicine approaches or a molecular tumor board.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13073-021-00845-7).

N-glycosylated SGK196 suppresses the metastasis of basal-like breast cancer cells

SGK196 is a protein O-mannose kinase involved in an indispensable phosphorylation step during laminin-binding glycan synthesis on alpha-dystroglycan (α-DG). However, the function of SGK196 in cancer diseases remains elusive. In the current study, we demonstrated that SGK196 is primarily modified by N-glycosylation in breast cancer (BC) cells. Furthermore, gain and loss-of-function studies showed that N-glycosylated SGK196 suppresses cell migration, invasion, and metastasis in BC, particularly in the basal-like breast cancer (BLBC) type. In addition, we found that SGK196 N-glycosylation performs the regulatory function through the PI3K/AKT/GSK3β signaling pathway. Collectively, our results show that N-glycosylated SGK196 plays suppression roles in BLBC metastases, therefore providing new insights into SGK196 function in BC.