Discerning Clinical Responses in Breast Cancer Based On Molecular Signatures

LncRNA AFAP1-AS1 mediates breast cancer cell proliferation and migration through the miR-21/PTEN axis

LncRNAs play various effects, mostly by sponging with miRNAs. Based on public databases integrating bioinformatics analyses and further validation in breast cancer (BC) tissue and cell lines, the effect of lncRNA AFAP1-AS1 on breast cancer cell proliferation and migration was verified. It might work via the miR-21/PTEN axis. The expression of AFAP1-AS1, which was significantly upregulated in BC tissues and cell lines, was correlated with old age and lymph node metastasis of patients with BC. Knockdown of AFAP1-AS1 inhibited the proliferation and migration of BC cells in vitro and in vivo. And downregulated miR-21 expression and upregulated PTEN expression additionally. Mechanistically, the knockdown of lncRNA AFAP1-AS1 upregulated PTEN expression and consequently attenuated miR-21-mediated enhanced BC cell proliferation and migration. LncRNA AFAP1-AS1 is a potential prognostic biomarker for BC patients.

Role of Endorphins in Breast Cancer Pathogenesis and Recovery

Understanding the relationship between stress and breast cancer development is essential to preventing and alleviating the cancer. Recent research has shed light on the cognitive, physiological, cellular, and molecular underpinnings of how the endorphin pathway and stress pathway affect breast cancer. This chapter consists of two parts. Part 1 will discuss the role of endorphins in breast cancer development. This includes a discussion of three topics: (1) the neurophysiological effect of endorphins on breast tumor growth in vivo, along with further experiments that will deepen our knowledge of how β-endorphin affects breast cancer; (2) how both the opioid receptor and somatostatin receptor classes alter intracellular signaling in breast cancer cells; and (3) genetic alleles in the opioid signaling pathway that are correlated with increased breast cancer risk. Part 2 will discuss the role of endorphins in recovery from breast cancer. This includes a discussion of three topics: (1) the relationship between breast cancer diagnosis and depression; (2) the effectiveness of cognitive behavioral therapy in reducing stress in breast cancer patients; and (3) the effect of psychotherapy and exercise on preserving telomere length in breast cancer patients.

N-of-one differential gene expression without control samples using a deep generative model

Differential analysis of bulk RNA-seq data often suffers from lack of good controls. Here, we present a generative model that replaces controls, trained solely on healthy tissues. The unsupervised model learns a low-dimensional representation and can identify the closest normal representation for a given disease sample. This enables control-free, single-sample differential expression analysis. In breast cancer, we demonstrate how our approach selects marker genes and outperforms a state-of-the-art method. Furthermore, significant genes identified by the model are enriched in driver genes across cancers. Our results show that the in silico closest normal provides a more favorable comparison than control samples.

Oral Contraceptive Use and Assessment of Breast Cancer Risk among Premenopausal Women via Molecular Characteristics: Systematic Review with Meta-Analysis

Breast cancer is divided into four molecular subtypes. Each one has distinct clinical features. The aim of this study was to assess individual breast cancer subtype risk in premenopausal women taking oral contraceptives (OCs). Databases (MEDLINE; PubMed, EMBASE, and the Cochrane Library) were searched to January 2022 to identify case-control studies meeting the inclusion criteria. The influence of OCs intake on the risk of ER-positive breast cancer (ER+BC) was revealed to be non-significant with regard to reduction: OR = 0.9134, 95% CI: 0.8128 to 1.0265, p = 0.128. Assessment of ER-negative subtype breast cancer (ER-BC) risk indicated that OCs use significantly increased the risk: OR = 1.3079, 95% CI: 1.0003 to 1.7100, p = 0.050. Analysis for HER2-positive breast cancer (HER2+BC) risk showed that OCs use statistically non-significantly lowered the risk: OR = 0.8810, 95% CI: 0.5977 to 1.2984, p = 0.522. Meta-analysis with regard to Triplet-negative breast cancer (TNBC) risk showed non-statistically significant increased risk: OR = 1.553, 95% CI: 0.99 to 2.43, p = 0.055. The findings of the meta-analysis suggest that breast cancer risk in premenopausal women may vary with respect to molecular subtypes. Extensive scientific work is still necessary in order to understand the impact of OCs use on breast cancer risk in young women.

Global Increase in Breast Cancer Incidence: Risk Factors and Preventive Measures

Breast cancer is a global cause for concern owing to its high incidence around the world. The alarming increase in breast cancer cases emphasizes the management of disease at multiple levels. The management should start from the beginning that includes stringent cancer screening or cancer registry to effective diagnostic and treatment strategies. Breast cancer is highly heterogeneous at morphology as well as molecular levels and needs different therapeutic regimens based on the molecular subtype. Breast cancer patients with respective subtype have different clinical outcome prognoses. Breast cancer heterogeneity emphasizes the advanced molecular testing that will help on-time diagnosis and improved survival. Emerging fields such as liquid biopsy and artificial intelligence would help to under the complexity of breast cancer disease and decide the therapeutic regimen that helps in breast cancer management. In this review, we have discussed various risk factors and advanced technology available for breast cancer diagnosis to combat the worst breast cancer status and areas that need to be focused for the better management of breast cancer.

miRNome Profiling Reveals Shared Features in Breast Cancer Subtypes and Highlights miRNAs That Potentially Regulate MYB and EZH2 Expression

Breast cancer (BC) has been extensively studied, as it is one of the more commonly diagnosed cancer types worldwide. The study of miRNAs has increased what is known about the complexity of pathways and signaling and has identified potential biomarkers and therapeutic targets. Thus, miRNome profiling could provide important information regarding the molecular mechanisms involved in BC. On average, more than 430 miRNAs were identified as differentially expressed between BC cell lines and normal breast HMEC cells. From these, 110 miRNAs were common to BC subtypes. The miRNome enrichment analysis and interaction maps highlighted epigenetic-related pathways shared by all BC cell lines and revealed potential miRNA targets. Quantitative evaluation of BC patient samples and GETx/TCGA-BRCA datasets confirmed MYB and EZH2 as potential targets from BC miRNome. Moreover, overall survival was impacted by EZH2 expression. The expression of 15 miRNAs, selected according to aggressiveness of BC subtypes, was confirmed in TCGA-BRCA dataset. Of these miRNAs, miRNA-mRNA interaction prediction revealed 7 novel or underexplored miRNAs in BC: miR-1271-5p, miR-130a-5p, and miR-134 as MYB regulators and miR-138-5p, miR-455-3p, miR-487a, and miR-487b as EZH2 regulators. Herein, we report a novel molecular miRNA signature for BC and identify potential miRNA/mRNAs involved in disease subtypes.

Contrast-Enhanced Spectral Mammography Assessment of Patients Treated with Neoadjuvant Chemotherapy for Breast Cancer

Background: Evaluating the tumor response to neoadjuvant chemotherapy is key to planning further therapy of breast cancer. Our study aimed to evaluate the effectiveness of low-energy and subtraction contrast-enhanced spectral mammography (CESM) images in the detection of complete response (CR) for neoadjuvant chemotherapy (NAC) in breast cancer. Methods: A total of 63 female patients were qualified for our retrospective analysis. Low-energy and subtraction CESM images just before the beginning of NAC and as a follow-up examination 2 weeks before the end of chemotherapy were compared with one another and assessed for compliance with the postoperative histopathological examination (HP). The response to preoperative chemotherapy was evaluated based on the RECIST 1.1 criteria (Response Evaluation Criteria in Solid Tumors). Results: Low-energy images tend to overestimate residual lesions (6.28 mm) and subtraction images tend to underestimate them (2.75 mm). The sensitivity of low-energy images in forecasting CR amounted to 33.33%, while the specificity was 92.86%. In the case of subtraction CESM, the sensitivity amounted to 85.71% and the specificity to 71.42%. Conclusions: CESM is characterized by high sensitivity in the assessment of CR after NAC. The use of only morphological assessment is insufficient. CESM correlates well with the size of residual lesions on histopathological examination but tends to underestimate the dimensions.

CD151 enrichment in exosomes of luminal androgen receptor breast cancer cell line contributes to cell invasion

Breast cancer is the most common and highly heterogeneous disease in women worldwide. Given the challenges in the treatment of advanced metastatic breast cancer, it is necessary to understand the molecular mechanisms related to disease progression. Exosomes play various roles in the progression of tumors, including promoting the invasion and advancing the distant metastasis. To study the molecular mechanisms related to the progression of luminal androgen receptor (LAR) breast cancer, we first isolated exosomes of MDA-MB-453 cells, a representative cell line of LAR. Through quantitative proteomic analysis, we identified 180 proteins specifically enriched in exosomes after comparing with those in cells, microvesicles, and the 150K supernatant. Among these, CD151, a protein involved in the regulation of cell motility was the most enriched one. CD151-knockdown exosomes reduced the invasion ability of the recipient breast cancer cell and lowered the phosphorylation level of tyrosine-protein kinase Lck, indicating that the invasion of LAR breast cancer may be due to CD151-enriched exosomes. Our work reports for the first time that CD151 was highly abundant in the exosomes of MDA-MB-453 cells and expands the understanding of the development process of LAR subtype, suggesting CD151 may be a potential candidate for the treatment of LAR breast cancer.

RNA-seq from archival FFPE breast cancer samples: molecular pathway fidelity and novel discovery

BACKGROUND

Formalin-fixed, paraffin-embedded (FFPE) tissues for RNA-seq have advantages over fresh frozen tissue including abundance and availability, connection to rich clinical data, and association with patient outcomes. However, FFPE-derived RNA is highly degraded and chemically modified, which impacts its utility as a faithful source for biological inquiry.

METHODS

True archival FFPE breast cancer cases (n = 58), stored at room temperature for 2-23 years, were utilized to identify key steps in tissue selection, RNA isolation, and library choice. Gene expression fidelity was evaluated by comparing FFPE data to public data obtained from fresh tissues, and by employing single-gene, gene set and transcription network-based regulon analyses.

RESULTS

We report a single 10 μm section of breast tissue yields sufficient RNA for RNA-seq, and a relationship between RNA quality and block age that was not linear. We find single-gene analysis is limiting with FFPE tissues, while targeted gene set approaches effectively distinguish ER+ from ER- breast cancers. Novel utilization of regulon analysis identified the transcription factor KDM4B to associate with ER+ disease, with KDM4B regulon activity and gene expression having prognostic significance in an independent cohort of ER+ cases.

CONCLUSION

Our results, which outline a robust FFPE-RNA-seq pipeline for broad use, support utilizing FFPE tissues to address key questions in the breast cancer field, including the delineation between indolent and life-threatening disease, biological stratification and molecular mechanisms of treatment resistance.

miRNA in a multiomic context for diagnosis, treatment monitoring and personalized management of metastatic breast cancer

Metastatic breast cancer is characterized by aggressive spreading to distant organs. Despite huge multilevel research, there are still several important challenges that have to be clarified in the management of this disease. Therefore, recent investigations have implemented a modern, multiomic approach with the aim of identifying specific biomarkers for not only early detection but also to predict treatment responses and metastatic spread. Specific attention is paid to short miRNAs, which regulate gene expression at the post-transcriptional level. Aberrant miRNA expression could initiate cancer development, cell proliferation, invasion, migration, metastatic spread or drug resistance. An miRNA signature is, therefore, believed to be a promising biomarker and prediction tool that could be utilized in all phases of carcinogenesis. This article offers comprehensive information about miRNA profiles useful for diagnostic and treatment purposes that may sufficiently advance breast cancer management and improve individual outcomes in the near future.

Trimodal distribution of arylamine N-acetyltransferase 1 mRNA in breast cancer tumors: association with overall survival and drug resistance

BACKGROUND

Arylamine N-acetyltransferase 1 (NAT1) is a drug metabolizing enzyme that has been associated with cancer cell proliferation in vitro and with survival in vivo. NAT1 expression has been associated with the estrogen receptor and it has been proposed as a prognostic marker for estrogen receptor positive cancers. However, little is known about the distribution of NAT1 mRNA across an entire patient population or its effects on outcomes. To address this, gene expression data from breast cancer patient cohorts were investigated to identify sub-populations based on the level of NAT1 expression. Patient survival and drug response was examined to determine whether NAT1 mRNA levels influenced any of these parameters.

RESULTS

NAT1 expression showed a trimodal distribution in breast cancer samples (n = 1980) but not in tumor tissue from ovarian, prostate, cervical or colorectal cancers. In breast cancer, NAT1 mRNA in each sub-population correlated with a separate set of genes suggesting different mechanisms of NAT1 gene regulation. Kaplan-Meier plots showed significantly better survival in patients with highest NAT1 mRNA compared to those with intermediate or low expression. While NAT1 expression was elevated in estrogen receptor-positive patients, it did not appear to be dependent on estrogen receptor expression. Overall survival was analyzed in patients receiving no treatment, hormone therapy or chemotherapy. NAT1 expression correlated strongly with survival in the first 5 years in those patients receiving chemotherapy but did not influence survival in the other two groups. This suggests that low NAT1 expression is associated with chemo-resistance. The sensitivity of NAT1 mRNA levels as a single parameter to identify non-responders to chemotherapy was 0.58 at a log(2) < 6.5.

CONCLUSIONS

NAT1 mRNA can be used to segregate breast cancer patients into sub-populations that demonstrate different overall survival. Moreover, low NAT1 expression shows a distinct poor response to chemotherapy. Analysis of NAT1 expression may be useful for identifying specific individuals who would benefit from alternative therapy or drug combinations. However, additional information is required to increase the sensitivity of identifying non-responders.

Orchestrating a biomarker panel with lncRNAs and mRNAs for predicting survival in pancreatic ductal adenocarcinoma

The low survival of patients with pancreatic ductal adenocarcinoma (PDAC) makes the treatment of this disease one of the most challenging task in modern medicine. Here, by mining a large-scale cancer genome atlas data set of pancreatic cancer tissues, we identified 21 long noncoding RNAs (lncRNAs) that significantly associated with overall survival in patients with PDAC (P < .01). Further analysis revealed that 8 lncRNAs turned out to be independently correlated with patients' overall survival, and the risk score could be calculated based on their expression. To obtain a better predicting power, we integrated lncRNA data with a total of 410 differently expressed messenger RNAs (mRNAs) screened from PDAC and normal tissues in gene expression omnibus (GEO) database. The integration resulted in a much better panel including 8 lncRNAs (RP3.470B24.5, CTA.941F9.9, RP11.557H15.3, LINC00960, AP000479.1, LINC00635, LINC00636, and AC073133.1) and 8 mRNAs (DHRS9, ONECUT1, OR8D4, MT1M, TCN1, MMP9, DPYSL3, and TTN) to predict prognosis. A functional evaluation showed that these lncRNAs might play roles in pancreatic secretion, cell adhesion, and proteolysis. Using normal and pancreatic cancer cell lines, we confirmed that a majority of identified lncRNAs and mRNAs showed altered expressions in pancreatic cancer cells. Especially, LINC01589, LINC00960, TCN1, and MT1M showed a profoundly increased expression in pancreatic cancer cells, which suggests their potentially important role in pancreatic cancer. The results of our work indicate that lncRNAs have vital roles in PADC and provide new insights to integrate multiple kinds of markers in clinical practices.

Gene expression data and FTIR spectra provide a similar phenotypic description of breast cancer cell lines in 2D and 3D cultures

Gene expression patterns and FTIR spectral data are strongly correlated. Both identified the genotypes and phenotypes of breast cancer cell lines.

Next-Generation Breast Cancer Omics

This Editorial highlights the reviews in the Breast Cancer Theme Issue that features topics related to next-generation breast cancer omics.