Breast Cancer Treatment: A Review

Left-right breast asymmetry and risk of screen-detected and interval cancers in a large population-based screening population

OBJECTIVES

To assess the associations between automated volumetric estimates of mammographic asymmetry and breast cancers detected at the same ("contemporaneous") screen, at subsequent screens, or in between (interval cancers).

METHODS

Automated measurements from mammographic images (N = 79,731) were used to estimate absolute asymmetry in breast volume (BV) and dense volume (DV) in a large ethnically diverse population of attendees of a UK breast screening programme. Logistic regression models were fitted to assess asymmetry associations with the odds of a breast cancer detected at contemporaneous screen (767 cases), adjusted for relevant confounders.Nested case-control investigations were designed to examine associations between asymmetry and the odds of: (a) interval cancer (numbers of cases/age-matched controls: 153/646) and (b) subsequent screen-detected cancer (345/1438), via conditional logistic regression.

RESULTS

DV, but not BV, asymmetry was positively associated with the odds of contemporaneous breast cancer (P-for-linear-trend (Pt) = 0.018). This association was stronger for first (prevalent) screens (Pt = 0.012). Both DV and BV asymmetry were positively associated with the odds of an interval cancer diagnosis (Pt = 0.060 and 0.030, respectively). Neither BV nor DV asymmetry were associated with the odds of having a subsequent screen-detected cancer.

CONCLUSIONS

Increased DV asymmetry was associated with the risk of a breast cancer diagnosis at a contemporaneous screen or as an interval cancer. BV asymmetry was positively associated with the risk of an interval cancer diagnosis.

ADVANCES IN KNOWLEDGE

The findings suggest that DV and BV asymmetry may provide additional signals for detecting contemporaneous cancers and assessing the likelihood of interval cancers in population-based screening programmes.

Two-Stage Strategy for Development of Proteolysis Targeting Chimeras and its Application for Estrogen Receptor Degraders

Proteolysis targeting chimeras (PROTACs) have emerged as useful chemical probes and potential therapeutics by taking advantage of the ubiquitin-proteasome system to degrade intracellular disease-associated proteins. PROTACs are heterobifunctional molecules composed of a target protein ligand, E3 ubiquitin ligase ligand, and a linker between them. The generation of efficient PROTACs requires screening of many parameters, especially the lengths and types of the linkers. We report our proof-of-concept study using a two-stage strategy to facilitate the development of PROTACs against the estrogen receptor (ER). In stage one, a library of close to 100 PROTACs was synthesized by simply mixing a library of ERα ligands containing a hydrazide functional group at different positions with a preassembled library of E3 ligase ligands bearing different types and lengths of linkers with a terminal aldehyde group in a 1:1 ratio. Cell-based screening occurred without further purification, because the formation of the acylhydrazone linkage is highly efficient and produces water as the only byproduct. Compound A3 was the most potent ER degrader in two ER+ cell lines (DC₅₀= ∼ 10 nM, D_max= ≥ 95%). Stage two involved transformation to a more stable amide linker to generate a more drug-like molecule. The new compound, AM-A3, showed comparable biological activity (DC₅₀ = 1.1 nM, D_max = 98%) and induced potent antiproliferation (IC₅₀= 13.2 nM, I_max= 69%) in MCF-7. This proof-of -concept study demonstrates that the two-stage strategy can significantly facilitate the development of PROTACs against ER without the tedious process of making large numbers of PROTACs one by one. It has the potential to be expanded to many other targets.

Monitoring Value of Serum HER2 as a Predictive Biomarker in Patients with Metastatic Breast Cancer

Purpose

The aim of this study was to investigate the monitoring value of serum HER2 in patients with metastatic breast cancer.

Patients and Methods

We firstly evaluated the association of serum HER2 levels with tissue HER2 expression and imaging results in 420 breast cancer patients admitted into Tianjin Medical University Cancer Institute and Hospital between April 2016 and December 2018. Secondly, we analyzed serum HER2 levels in breast cancer patients with different metastatic degrees.

Results

There is a higher correlation between serum HER2 and tissue HER2 in breast cancer patients with stage III (κ=0.670, p<0.001) and stage IV (κ=0.464, p<0.001). Serum HER2 levels were significantly associated with imaging results (κ=0.478, p<0.001). The ROC curve analysis showed that serum HER2 was superior to other serum markers for predicting metastatic breast cancer. Multinomial logistic regression revealed that the patients with higher serum HER2 levels would be more likely to have breast cancer metastasis.

Conclusion

Serum HER2 levels in breast cancer patients can partly reflect tissue HER2 expression and tumor imaging changes, and serum HER2 may be used as a biomarker for evaluating metastatic status in patients with breast cancer.

Macrophage-cancer hybrid membrane-coated nanoparticles for targeting lung metastasis in breast cancer therapy

Cell membrane- covered drug-delivery nanoplatforms have been garnering attention because of their enhanced bio-interfacing capabilities that originate from source cells. In this top-down technique, nanoparticles (NPs) are covered by various membrane coatings, including membranes from specialized cells or hybrid membranes that combine the capacities of different types of cell membranes. Here, hybrid membrane-coated doxorubicin (Dox)-loaded poly(lactic-co-glycolic acid) (PLGA) NPs (DPLGA@[RAW-4T1] NPs) were fabricated by fusing membrane components derived from RAW264.7(RAW) and 4T1 cells (4T1). These NPs were used to treat lung metastases originating from breast cancer. This study indicates that the coupling of NPs with a hybrid membrane derived from macrophage and cancer cells has several advantages, such as the tendency to accumulate at sites of inflammation, ability to target specific metastasis, homogenous tumor targeting abilities in vitro, and markedly enhanced multi-target capability in a lung metastasis model in vivo. The DPLGA@[RAW-4T1] NPs exhibited excellent chemotherapeutic potential with approximately 88.9% anti-metastasis efficacy following treatment of breast cancer-derived lung metastases. These NPs were robust and displayed the multi-targeting abilities of hybrid membranes. This study provides a promising biomimetic nanoplatform for effective treatment of breast cancer metastasis.

RDGN-based predictive model for the prognosis of breast cancer

Background

Breast cancer is the most diagnosed malignancy in females in the United States. The members of retinal determination gene network (RDGN) including DACH, EYA, as well as SIX families participate in the proliferation, apoptosis, and metastasis of multiple tumors including breast cancer. A comprehensive predictive model of RDGN might be helpful to herald the prognosis of breast cancer patients.

Methods

In this study, the Gene Expression Ominibus (GEO) and Gene Set Expression Analysis (GSEA) algorithm were used to investigate the effect of RDGN members on downstream signaling pathways. Besides, based on The Cancer Genome Atlas (TCGA) database, we explored the expression patterns of RDGN members in tumors, normal tissues, and different breast cancer subtypes. Moreover, we estimated the relationship between RDGN members and the outcomes of breast cancer patients. Lastly, we constructed a RDGN-based predictive model by Cox proportional hazard regression and verified the model in two separate GEO datasets.

Results

The results of GSEA showed that the expression of DACH1 was negatively correlated with cell cycle and DNA replication pathways. On the contrary, the levels of EYA2 and SIX1 were significantly positively correlated with DNA replication, mTOR, and Wnt pathways. Further investigation in TCGA database indicated that DACH1 expression was lower in breast cancers especially basal-like subtype. In the meanwhile, SIX1 was remarkably upregulated in breast cancers while EYA2 level was increased in Basal-like and Her-2 enriched subtypes. Survival analyses demonstrated that DACH1 was a favorable factor while EYA2 and SIX1 were risk factors for breast cancer patients. Given the results of Cox proportional hazard regression analysis, two members of RDGN were involved in the present predictive model and patients with high model index had poorer outcomes.

Conclusion

This study showed that aberrant RDGN expression was an unfavorable factor for breast cancer. This RDGN-based comprehensively framework was meaningful for predicting the prognosis of breast cancer patients.

Non-Invasive Assessment of Breast Cancer Molecular Subtypes with Multiparametric Magnetic Resonance Imaging Radiomics

We evaluated the performance of radiomics and artificial intelligence (AI) from multiparametric magnetic resonance imaging (MRI) for the assessment of breast cancer molecular subtypes. Ninety-one breast cancer patients who underwent 3T dynamic contrast-enhanced (DCE) MRI and diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping were included retrospectively. Radiomic features were extracted from manually drawn regions of interest (n = 704 features per lesion) on initial DCE-MRI and ADC maps. The ten best features for subtype separation were selected using probability of error and average correlation coefficients. For pairwise comparisons with >20 patients in each group, a multi-layer perceptron feed-forward artificial neural network (MLP-ANN) was used (70% of cases for training, 30%, for validation, five times each). For all other separations, linear discriminant analysis (LDA) and leave-one-out cross-validation were applied. Histopathology served as the reference standard. MLP-ANN yielded an overall median area under the receiver-operating-characteristic curve (AUC) of 0.86 (0.77–0.92) for the separation of triple negative (TN) from other cancers. The separation of luminal A and TN cancers yielded an overall median AUC of 0.8 (0.75–0.83). Radiomics and AI from multiparametric MRI may aid in the non-invasive differentiation of TN and luminal A breast cancers from other subtypes.

Proliferation-associated long noncoding RNA, TMPO-AS1, is a potential therapeutic target for triple-negative breast cancer

Triple‐negative breast cancer (TNBC) is an aggressive subtype of breast cancer compared with luminal or epidermal growth factor receptor 2 subtypes, thus effective therapeutic options for TNBC are yet to be developed. Nowadays, oncogenic long noncoding RNAs (lncRNAs) are applied to cancer management as a new class of therapeutic targets. We previously showed that thymopoietin antisense transcript 1 (TMPO‐AS1) is a proliferation‐associated lncRNA that contributes to hormone‐dependent breast cancer progression by stabilizing estrogen receptor‐α mRNA. We here showed that TMPO‐AS1 is abundantly expressed in basal‐like breast cancer subtype based on the transcriptomic data in The Cancer Genome Atlas as well as in TNBC cell lines and patient‐derived cells. Small interfering RNA‐based loss‐of‐function analyses showed that TMPO‐AS1 knockdown substantially represses the proliferation and migration of TNBC cells. Expression microarray analysis showed that TMPO‐AS1 alters gene signatures related to transforming growth factor‐β signaling in addition to proliferative E2F signaling pathways. TMPO‐AS1‐targeted siRNA treatment through engineered drug delivery systems using cancer‐targeted polyion complex micelle or nanoball technology significantly impaired the in vivo growth of primary and metastatic TNBC xenograft tumors. Our findings suggest that TMPO‐AS1 plays a key role in TNBC pathophysiology and could be a potential therapeutic target for TNBC.

LyP-1-Modified Oncolytic Adenoviruses Targeting Transforming Growth Factor β Inhibit Tumor Growth and Metastases and Augment Immune Checkpoint Inhibitor Therapy in Breast Cancer Mouse Models

We report here the development of oncolytic adenoviruses (Ads) that have reduced toxicity, enhanced tumor tropism, produce strong antitumor response, and can overcome resistance to immune checkpoint inhibitor therapy in breast cancer. We have shown that LyP-1 receptor (p32) is highly expressed on the surface of breast cancer cells and tumors from cancer patients, and that increased stromal expression of transforming growth factor β-1 (TGFβ-1) is associated with triple-negative breast cancer. Therefore, we constructed oncolytic Ads, AdLyp.sT and mHAdLyp.sT, in which the p32-binding LyP-1 peptide was genetically inserted into the adenoviral fiber protein. Both AdLyp.sT and mHAdLyp.sT express sTGFβRIIFc, a TGFβ decoy that can inhibit TGFβ pathways. mHAdLyp.sT is an Ad5/48 chimeric hexon virus in which hypervariable regions (HVRs 1-7) of Ad5 are replaced with the corresponding Ad48 HVRs. AdLyp.sT and mHAdLyp.sT exhibited better binding, replication, and produced higher sTGFβRIIFc protein levels in breast cancer cell lines compared with Ad.sT or mHAd.sT control viruses without LyP-1 peptide modification. Systemic delivery of mHAdLyp.sT in mice resulted in reduced hepatic/systemic toxicity compared with Ad.sT and AdLyp.sT. Intravenous delivery of AdLyp.sT and mHAdLyp.sT elicited a strong antitumor response in a human MDA-MB-231 bone metastasis model in mice, as indicated by bioluminescence imaging, radiographic tumor burden, serum TRACP 5b and calcium, and body weight analyses. Furthermore, intratumoral delivery of AdLyp.sT in 4T1 model in immunocompetent mice inhibited tumor growth and metastases, and augmented anti-PD-1 and anti-CTLA-4 therapy. Based on these studies, we believe that AdLyp.sT and mHAdLyp.sT can be developed as potential targeted immunotherapy agents for the treatment of breast cancer.

Unraveling the Genomic-Epigenomic Interaction Landscape in Triple Negative and Non-Triple Negative Breast Cancer

Background: The recent surge of next generation sequencing of breast cancer genomes has enabled development of comprehensive catalogues of somatic mutations and expanded the molecular classification of subtypes of breast cancer. However, somatic mutations and gene expression data have not been leveraged and integrated with epigenomic data to unravel the genomic-epigenomic interaction landscape of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC). Methods: We performed integrative data analysis combining somatic mutation, epigenomic and gene expression data from The Cancer Genome Atlas (TCGA) to unravel the possible oncogenic interactions between genomic and epigenomic variation in TNBC and non-TNBC. We hypothesized that within breast cancers, there are differences in somatic mutation, DNA methylation and gene expression signatures between TNBC and non-TNBC. We further hypothesized that genomic and epigenomic alterations affect gene regulatory networks and signaling pathways driving the two types of breast cancer. Results: The investigation revealed somatic mutated, epigenomic and gene expression signatures unique to TNBC and non-TNBC and signatures distinguishing the two types of breast cancer. In addition, the investigation revealed molecular networks and signaling pathways enriched for somatic mutations and epigenomic changes unique to each type of breast cancer. The most significant pathways for TNBC were: retinal biosynthesis, BAG2, LXR/RXR, EIF2 and P2Y purigenic receptor signaling pathways. The most significant pathways for non-TNBC were: UVB-induced MAPK, PCP, Apelin endothelial, Endoplasmatic reticulum stress and mechanisms of viral exit from host signaling Pathways. Conclusion: The investigation revealed integrated genomic, epigenomic and gene expression signatures and signing pathways unique to TNBC and non-TNBC, and a gene signature distinguishing the two types of breast cancer. The study demonstrates that integrative analysis of multi-omics data is a powerful approach for unravelling the genomic-epigenomic interaction landscape in TNBC and non-TNBC.

Computer-Aided Ligand Discovery for Estrogen Receptor Alpha

Breast cancer (BCa) is one of the most predominantly diagnosed cancers in women. Notably, 70% of BCa diagnoses are Estrogen Receptor α positive (ERα+) making it a critical therapeutic target. With that, the two subtypes of ER, ERα and ERβ, have contrasting effects on BCa cells. While ERα promotes cancerous activities, ERβ isoform exhibits inhibitory effects on the same. ER-directed small molecule drug discovery for BCa has provided the FDA approved drugs tamoxifen, toremifene, raloxifene and fulvestrant that all bind to the estrogen binding site of the receptor. These ER-directed inhibitors are non-selective in nature and may eventually induce resistance in BCa cells as well as increase the risk of endometrial cancer development. Thus, there is an urgent need to develop novel drugs with alternative ERα targeting mechanisms that can overcome the limitations of conventional anti-ERα therapies. Several functional sites on ERα, such as Activation Function-2 (AF2), DNA binding domain (DBD), and F-domain, have been recently considered as potential targets in the context of drug research and discovery. In this review, we summarize methods of computer-aided drug design (CADD) that have been employed to analyze and explore potential targetable sites on ERα, discuss recent advancement of ERα inhibitor development, and highlight the potential opportunities and challenges of future ERα-directed drug discovery.

Adoptive cell therapy of triple negative breast cancer with redirected cytokine-induced killer cells

Cytokine-Induced Killer (CIK) cells share several functional and phenotypical properties of both T and natural killer (NK) cells. They represent an attractive approach for cell-based immunotherapy, as they do not require antigen-specific priming for tumor cell recognition, and can be rapidly expanded in vitro. Their relevant expression of FcγRIIIa (CD16a) can be exploited in combination with clinical-grade monoclonal antibodies (mAbs) to redirect their lytic activity in an antigen-specific manner. Here, we report the efficacy of this combined approach against triple negative breast cancer (TNBC), an aggressive tumor that still requires therapeutic options. Different primitive and metastatic TNBC cancer mouse models were established in NSG mice, either by implanting patient-derived TNBC samples or injecting MDA-MB-231 cells orthotopically or intravenously. The combined treatment consisted in the repeated intratumoral or intravenous injection of CIK cells and cetuximab. Tumor growth and metastasis were monitored by bioluminescence or immunohistochemistry, and survival was recorded. CIK cells plus cetuximab significantly restrained primitive tumor growth in mice, either in patient-derived tumor xenografts or MDA-MB-231 cell line models. Moreover, this approach almost completely abolished metastasis spreading and dramatically improved survival. The antigen-specific mAb favored tumor and metastasis tissue infiltration by CIK cells, and led to an enrichment of the CD16a⁺ subset.

Data highlight the potentiality of this novel immunotherapy strategy where a nonspecific cytotoxic cell population can be converted into tumor-specific effectors with clinical-grade antibodies, thus providing not only a therapeutic option for TNBC but also a valid alternative to more complex approaches based on chimeric antigen receptor-engineered cells.

List of abbreviations

ACT, Adoptive Cell Transfer; ADCC, Antibody-Dependent Cell-mediated Cytotoxicity; ADP, Adenosine diphosphate; BLI, Bioluminescence Imaging; CAR, Chimeric Antigen Receptor; CIK, Cytokine Induced Killer cells; CTX, Cetuximab; DMEM, Dulbecco’s Modified Eagle Medium; EGFR, Human Epidermal Growth Factor 1; ER, Estrogen; FBS, Fetal Bovine Serum; FFPE, Formalin-Fixed Paraffin-Embedded; GMP, Good Manufacturing Practices; GVHD, Graft Versus Host Disease; HER2, Human Epidermal Growth Factor 2; HRP, Horseradish Peroxidase; IFN-γ, Interferon-γ; IHC, Immunohistochemistry; IL-2, Interleukin-2; ISO, Irrelevant antibody; i.t., intratumoral; i.v., intravenous, mAbs, Monoclonal Antibodies; mIHC, Multiplex Fluorescence Immunohistochemistry; MHC, Major Histocompatibility Complex; NK, Natural Killer; NKG2D, Natural-Killer group 2 member D; NSG, NOD/SCID common γ chain knockout; PARP, Poly ADP-ribose polymerase; PBMCs, Peripheral Blood Mononuclear Cells; PBS, Phosphate-buffered saline; PDX, Patient-derived xenograft; PR, Progesterone; rhIFN-γ, Recombinant Human Interferon-γ; RPMI, Roswell Park Memorial Institute; STR, Short tandem Repeat; TCR, T Cell Receptor; TNBC, Triple Negative Breast Cancer; TSA, Tyramide Signal Amplification

Clinicopathological factors associated with tumor-infiltrating lymphocyte reactivity in breast cancer

BACKGROUND

The clinical significance of adoptive tumor-infiltrating lymphocyte (TIL) therapy has been demonstrated in many clinical trials. We analyzed the in vitro reactivity of cultured TILs against autologous breast cancer cells.

METHODS

TILs and cancer cells were cultured from 31 breast tumor tissues. Reactivity of TILs against cancer cells was determined by measuring secreted interferon-gamma. Expression levels of epithelial markers, major histocompatibility complex molecules, and programmed death-ligand 1 (PD-L1) in cancer cells, and T cell markers (memory, T cell activation and exhaustion, and regulatory T cell markers) in expanded TILs were analyzed and compared between the reactive and non-reactive groups.

RESULTS

In seven cases, TILs showed reactivity to autologous cancer cells. Six of these cases were associated with triple-negative breast cancer (TNBC). All reactive TNBCs were derived from surgical specimens after neoadjuvant chemotherapy (NAC). Higher expression of Ki67 in tumor tissues and lower expression of PD-L1 in cultured cancer cells were associated with reactivity. Proliferation of reactive TILs was high. High proportions of T cells and PD-1⁺CD4⁺ and PD1⁺CD8⁺ T cells were associated with reactivity in TNBC cases, while other activation or exhaustion markers were not.

CONCLUSION

TILs from approximately half the TNBC cases with NAC showed reactivity against autologous cancer cells. The proportion of PD-1⁺ T cells was higher in the reactive group. Adoptive TIL therapy combined with PD-1 inhibitors might be promising for TNBC patients with residual tumors after NAC.

Exploring the Regulation Mechanism of Xihuang Pill, Olibanum and β-Boswellic Acid on the Biomolecular Network of Triple-Negative Breast Cancer Based on Transcriptomics and Chemical Informatics Methodology

Background

Xihuang Pill (XHP) is mainly used to treat “Ru Yan (breast cancer)”. Evidence-based medical evidence and showed that XHP improves the efficacy of chemotherapy and reduced chemotherapy-induced toxicity in breast cancer patients. However, the mechanism of XHP against breast cancer is not clear.

Methods

The effect of XHP extract on cell half-inhibitory concentration (IC50) and cell viability of MD-MB-231 cells was detected by CCK-8 method. The cell inhibition rate of MDA-MB-453 cells were detected by MTT method. Apoptosis was detected by flow cytometry, cell transfer ability was detected by Transwell method, and cell proliferation ability was detected by colony formation assay. The expression of Notch1, β-catenin and c-myc mRNA in MDA-MB-453 cells were detected by real-time fluorescence quantitative PCR. Then, chemical informatics and transcriptomics methodology was utilized to predict the potential compounds and targets of XHP, and collect triple negative breast cancer (TNBC) genes and the data of Olibanum and β-boswellic acid intervention MD-MB-231 cells (from GSE102891). The cytoscape software was utilized to undergo network construction and network analysis. Finally, the data from the network analysis was imported into the DAVID database for enrichment analysis of signaling pathways and biological processes.

Results

The IC50 was 15.08 g/L (for MD-MB-231 cells). After interfering with MD-MB-231 cells with 15.08 g/L XHP extract for 72 h, compared with the control group, the cell viability, migration and proliferation was significantly decreased, while early apoptosis and late apoptosis were significantly increased (P < 0.01). After interfering with MDA-MB-453 cells with 6 g/L XHP extract for 72 h, compared with the control group, the cell inhibition and apoptosis rate increased, while the expression of Notch1, β-catenin and c-myc mRNA decreased. (P < 0.05). The chemical informatics and transcriptomics analysis showed that four networks were constructed and analyzed: (1) potential compounds-potential targets network of XHP; (2) XHP-TNBC PPI network; (3) DEGs PPI network of Olibanum-treated MD-MB 231 cells; (4) DEGs PPI network of β-boswellic acid -treated MD-MB 231 cells. Several anti-TNBC biological processes, signaling pathways, targets and so on were obtained.

Conclusion

XHP may exert anti-TNBC effects through regulating biological processes, signaling pathways, targets found in this study.

Ibrutinib in Gynecological Malignancies and Breast Cancer: A Systematic Review

Ibrutinib is an orally available, small-molecule tyrosine kinase inhibitor. Its main purpose is to inhibit Bruton's tyrosine kinase (BTK), an enzyme that is crucial in B cell development. It is FDA approved for the treatment of certain hematological malignancies. Several promising off-target drug effects have led to multiple, mostly preclinical investigations regarding its use in solid tumors. Unfortunately, data on its effectiveness in gynecological malignancies are limited, and (systematic) reviews are missing. The objective of this review was to summarize the existing literature and to analyze the evidence of ibrutinib as a treatment option in gynecological malignancies, including breast cancer. Studies were identified in MEDLINE and EMBASE using a defined search strategy, and preclinical or clinical research projects investigating ibrutinib in connection with these malignancies were considered eligible for inclusion. Our findings showed that preclinical studies generally confirm ibrutinib's efficacy in cell lines and animal models of ovarian, breast, and endometrial cancer. Ibrutinib exerts multiple antineoplastic effects, such as on-target BTK inhibition, off-target kinase inhibition, and immunomodulation by interference with myeloid-derived suppressor cells (MDSCs), programmed death-ligand 1 (PD-L1), and T cell response. These mechanisms were elaborated and discussed in the context of the evidence available. Further research is needed in order to transfer the preclinical results to a broader clinical appliance.

Suppression of CCT3 inhibits the proliferation and migration in breast cancer cells

Background

CCT3 is a subunit of chaperonin-containing TCP-1 (CCT), which folds many proteins involved in cancer development and plays an important role in many cancers. However, the role of CCT3 in breast cancer is still unclear.

Methods

CCT3 expression was knocked down by transfecting breast cancer cells with lentiviral shRNA. The proliferation of breast cancer cells (HCC1937 and MDA-MB-231) was detected by Celigo image cytometry and MTT assay, the migration of the cells was measured by Transwell analysis, cell cycle distribution and apoptosis was detected by flow cytometry, and changes in signal transduction proteins were detected by western blot analysis.

Results

The expression of CCT3 was significantly suppressed by transduction with lentiviral shRNA; CCT3 knockdown significantly reduced the proliferation and metastasis ability of breast cancer cells (HCC 1937 and MDA-MB-231), increased the proportion of cells in S phase, and decreased the proportion of cells in G1 phase compared to those in shControl cells. There was no significant change in the number of cells in the G2/M phase. Apoptosis analysis showed that knockdown of CCT3 induced apoptosis in breast cancer cells. Western blot analysis showed that the expression of many signal transduction proteins was changed after suppression of CCT3. A rescue experiment showed that overexpression of NFκB-p65 rescued the cell proliferation and migration affected by CCT3 in breast cancer cells.

Conclusion

CCT3 is closely related to the proliferation and migration of breast cancer and may be a novel therapeutic target.

A Computational Approach with Biological Evaluation: Combinatorial Treatment of Curcumin and Exemestane Synergistically Regulates DDX3 Expression in Cancer Cell Lines

DDX3 belongs to RNA helicase family that demonstrates oncogenic properties and has gained wider attention due to its role in cancer progression, proliferation and transformation. Mounting reports have evidenced the role of DDX3 in cancers making it a promising target to abrogate DDX3 triggered cancers. Dual pharmacophore models were generated and were subsequently validated. They were used as 3D queries to screen the InterBioScreen database, resulting in the selection of curcumin that was escalated to molecular dynamics simulation studies. In vitro anti-cancer analysis was conducted on three cell lines such as MCF-7, MDA-MB-231 and HeLa, which were evaluated along with exemestane. Curcumin was docked into the active site of the protein target (PDB code 2I4I) to estimate the binding affinity. The compound has interacted with two key residues and has displayed stable molecular dynamics simulation results. In vitro analysis has demonstrated that both the candidate compounds have reduced the expression of DDX3 in three cell lines. However, upon combinatorial treatment of curcumin (10 and 20 μM) and exemestane (50 μM) a synergism was exhibited, strikingly downregulating the DDX3 expression and has enhanced apoptosis in three cell lines. The obtained results illuminate the use of curcumin as an alternative DDX3 inhibitor and can serve as a chemical scaffold to design new small molecules.

Clinical association of progesterone receptor isoform A with breast cancer metastasis consistent with its unique mechanistic role in preclinical models

Background

Luminal breast cancer (L-BCa) comprises the majority of incurable, distally metastatic breast cancer cases. Estrogen supports growth of L-BCa cells but suppresses invasiveness. Estrogen also induces the progesterone receptor (PR). Invasiveness and metastasis of L-BCa cells is supported by the short PR isoform (PR-A), in response to the range of pre- and post-menopausal plasma hormone levels, by counteracting the effects of estrogen via micro RNA-mediated cross-talk with the estrogen receptor (ER). PR-B directly supports L-BCa invasion and metastasis and also inhibits tumor growth, both only at high progesterone levels. As public datasets on L-BCa tumors cannot distinguish PR-A, this study was designed to seek clinical evidence for the role of PR-A in metastasis in comparison with PR-B and ER.

Methods

Measurement of tumor PR-A, PR-B and ER mRNA expression in 125 treatment-naive primary L-BCa patients with differential node involvement and analysis using linear mixed effects models. Transcriptional activity assays of PR-A and PR-B.

Results

Lymph node involvement was strongly associated with PR-A expression (median, 3-fold higher vs. node-negative), independent of age, pathologic type, tumor grade, HER2 and PR-B. PR-B and ER correlated weakly with PR-A, but whereas PR-B and the PR-A/PR-B ratio were not significantly associated with node involvement, ER weakly negatively correlated with node positivity. PR-A was hypersensitive to mifepristone compared with PR-B.

Conclusions

Taken together with previous mechanistic studies, the findings provide clinical evidence in support of the role of PR-A in L-BCa metastasis. They also suggest the possibility of developing selective PR-A modulators for future interventions in appropriate clinical situations.

A bioinformatics approach to identify novel long, non-coding RNAs in breast cancer cell lines from an existing RNA-sequencing dataset

Breast cancer research has traditionally centred on genomic alterations, hormone receptor status and changes in cancer-related proteins to provide new avenues for targeted therapies. Due to advances in next generation sequencing technologies, there has been the emergence of long, non-coding RNAs (lncRNAs) as regulators of normal cellular events, with links to various disease states, including breast cancer. Here we describe our bioinformatic analyses of a previously published RNA sequencing (RNA-seq) dataset to identify lncRNAs with altered expression levels in a subset of breast cancer cell lines. Using a previously published RNA-seq dataset of 675 cancer cell lines, a subset of 18 cell lines was selected for our analyses that included 16 breast cancer lines, one ductal carcinoma in situ line and one normal-like breast epithelial cell line. Principal component analysis demonstrated correlation with well-established categorisation methods of breast cancer (i.e. luminal A/B, HER2 enriched and basal-like A/B). Through detailed comparison of differentially expressed lncRNAs in each breast cancer sub-type with normal-like breast epithelial cells, we identified 15 lncRNAs with consistently altered expression, including three uncharacterised lncRNAs. Utilising data from The Cancer Genome Atlas (TCGA) and The Genotype Tissue Expression (GETx) project via Gene Expression Profiling Interactive Analysis (GEPIA2), we assessed clinical relevance of several identified lncRNAs with invasive breast cancer. Lastly, we determined the relative expression level of six lncRNAs across a spectrum of breast cancer cell lines to experimentally confirm the findings of our bioinformatic analyses. Overall, we show that the use of existing RNA-seq datasets, if re-analysed with modern bioinformatic tools, can provide a valuable resource to identify lncRNAs that could have important biological roles in oncogenesis and tumour progression.

Hypomethylating Agent Azacitidine Is Effective in Treating Brain Metastasis Triple-Negative Breast Cancer Through Regulation of DNA Methylation of Keratin 18 Gene

Breast cancer patients presenting with symptomatic brain metastases have poor prognosis, and current chemotherapeutic agents are largely ineffective. In this study, we evaluated the hypomethylating agent azacitidine (AZA) for its potential as a novel therapeutic in preclinical models of brain metastasis of breast cancer. We used the parental triple-negative breast cancer MDA-MB-231 (231) cells and their brain colonizing counterpart (231Br) to ascertain phenotypic differences in response to AZA. We observed that 231Br cells have higher metastatic potential compared to 231 cells. With regard to therapeutic value, the AZA IC50 value in 231Br cells is significantly lower than that in parental cells (P < .01). AZA treatment increased apoptosis and inhibited the Wnt signaling transduction pathway, angiogenesis, and cell metastatic capacity to a significantly higher extent in the 231Br line. AZA treatment in mice with experimental brain metastases significantly reduced tumor burden (P = .0112) and increased survival (P = .0026) compared to vehicle. Lastly, we observed a decreased expression of keratin 18 (an epithelial maker) in 231Br cells due to hypermethylation, elucidating a potential mechanism of action of AZA in treating brain metastases from breast cancer.

Identification of key differentially expressed genes between ER-positive/HER2-negative breast cancer and ER-negative/HER2-negative breast cancer using integrated bioinformatics analysis

Background

Treatment strategies for various subtypes of breast cancer (BC) are different based on their distinct molecular characteristics. Therefore, it is very important to identify key differentially expressed genes (DEGs) between ER-positive/HER2-negative BC and ER-negative/HER2-negative BC.

Methods

Gene expression profiles of GSE22093 and GSE23988 were obtained from the Gene Expression Omnibus database. There were 74 ER-positive/HER2-negative BC tissues and 85 ER-negative/HER2-negative BC tissues in the two profile datasets. DEGs between ER-positive/HER2-negative tissues and ER-negative/HER2-negative BC tissues were identified by the GEO2R tool. The common DEGs among the two datasets were detected with Venn software online. Next, we made use of the Database for Annotation, Visualization and Integrated Discovery to analyze enriched Kyoto Encyclopedia of Gene and Genome (KEGG) pathways and gene ontology terms. Then, the protein-protein interactions (PPIs) of these DEGs were visualized by Cytoscape with the Search Tool for the Retrieval of Interacting Genes. Of the proteins in the PPI network, Molecular Complex Detection plug-in analysis identified nine core upregulated genes and one core downregulated gene. UALCAN and Gene Expression Profiling Interactive Analysis were applied to determine the expression of these 10 genes in BC. Furthermore, for the analysis of overall survival among those genes, the Kaplan-Meier method was implemented.

Results

Ninety-three common DEGs (63 upregulated and 30 downregulated) were identified. KEGG pathway enrichment analysis showed that upregulated DEGs were particularly enriched in the progesterone-mediated oocyte maturation pathway. In addition, PGR might be a prognostic biomarker for ER-positive/HER2-negative BC. CCND1 is a poor prognostic biomarker for ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. Moreover, TFF1, AGR2 and EGFR might be predictive biomarkers of node metastasis in ER-positive/HER2-negative BC and ER-negative/HER2-negative BC.

Conclusions

CCND1, AGR2, PGR, TFF1 and EGFR are the key DEGs between ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. Further studies are required to confirm the functions of the identified genes.

Breast cancer: insights in disease and influence of drug methotrexate

According to the World Health Organization, cancer is one of the leading causes of morbidity and mortality worldwide. The previously estimated 14 million new cases in the year of 2012 are expected to rise, yearly, over the following 2 decades. Among women, breast cancer is the most common one. In 2012, almost 1.7 million people were diagnosed worldwide and half a million died from the disease. Despite having several treatments available, from surgery to chemotherapy, most of these treatments have severe adverse effects. Chemotherapy has a narrow therapeutic window and requires high dosage treatment in patients with advanced-stage cancers and further need innovative treatment strategies. Although methotrexate (MTX) is not a first line drug used against breast cancer, however, it might be valuable to fight the disease. MTX is an effective and cheap drug that might impair malignant growth without irreversible damage to normal tissues. Nevertheless, while MTX does present some disadvantages including poor solubility and low permeability, several strategies are being used to discover and provide novel and effective targeted treatment against breast cancer. In this review, we analyze the chemotherapy of breast cancer and its relationship with drug MTX.

T-cell-based breast cancer immunotherapy

Cancer immunotherapy has witnessed a new renaissance with the advent of immune checkpoint inhibitors, which reactivate T cells and foster endogenous anti-tumor responses. The excellent results of immunotherapy in the field of melanoma, renal cancer, lung cancer, and other cancer types that have traditionally been known to be immunogenic, rekindled the interest of the oncology community in extending the benefits to all cancers including breast cancer (BC). In this review, we highlight the current state of using T cells as both markers for clinical practice and therapeutic options for BC.

The role of autophagy in resistance to targeted therapies

Autophagy is a self-degradative cellular process, involved in stress response such as starvation, hypoxia, and oxidative stress. This mechanism balances macro-molecule recycling to regulate cell homeostasis. In cancer, autophagy play a role in the development and progression, while several studies describe it as one of the key processes in drug resistance. In the last years, in addition to standard anti-cancer treatments such as chemotherapies and irradiation, targeted therapy became one of the most adopted strategies in clinical practices, mainly due to high specificity and reduced side effects. However, similar to standard treatments, drug resistance is the main challenge in most patients. Here, we summarize recent studies that investigated the role of autophagy in drug resistance after targeted therapy in different types of cancers. We highlight positive results and limitations of pre-clinical and clinical studies in which autophagy inhibitors are used in combination with targeted therapies.

Antibody-drug conjugates targeting RON receptor tyrosine kinase as a novel strategy for treatment of triple-negative breast cancer

Treatment of triple-negative breast cancer (TNBC) is a challenge to oncologists. Currently, the lack of effective therapy has fostered a major effort to discover new targets and therapeutics to combat this disease. The recepteur d'origine nantais (RON) receptor has been implicated in the pathogenesis of TNBC. Clinical studies have revealed that aberrant RON expression is crucial in regulating TNBC malignant phenotypes. Increased RON expression also has prognostic value for breast cancer progress. These features provide the rationale to target RON for TNBC treatment. In this review, we discuss the importance of RON in TNBC tumorigenesis and the development of anti-RON antibody-drug conjugates (ADCs) for clinical application. The findings from preclinical studies lay the foundation for clinical trials of this novel biotherapeutic for TNBC therapy.

Nanotherapeutics for Antimetastatic Treatment

Tumor metastases, that is, the development of secondary tumors in organs distant from the primary tumor, and their treatment remain a serious problem in cancer therapy. The unique challenges for tracking and treating tumor metastases lie in the small size, high heterogeneity, and wide dispersion to distant organs of metastases. Recently, nanomedicines, with the capacity to precisely deliver therapeutic agents to both primary and secondary tumors, have demonstrated many potential benefits for metastatic cancer theranostics. Given the remarkable progression in emerging nanotherapeutics for antimetastatic treatment, it is timely to summarize the latest advances in this field. This review highlights the rationale, advantages, and challenges for integrating biomedical nanotechnology with cancer biology to develop antimetastatic nanotherapeutics.

Clinical Benefit in the Treatment of Patients with Early Breast Cancer

Adjuvant treatment for early breast cancer involves multiple modalities with distinct toxicities and varying relative contributions to the improvement of long-term outcomes. In many situations the expected benefits of treatment may be modest and thus debated, and even in higher risk scenarios, when treatment is clearly indicated, several options are available with varying schedules and toxicities. Regulatory and professional society guidelines defining clinical benefit are available to guide decision-making, but do not capture clinical meaningfulness. There is wide variation among patients regarding the expected improvement in outcomes sufficient to make adjuvant chemotherapy or endocrine therapy worthwhile. While many consider small improvements in outcomes meaningful, some need greater benefit, and a small minority prefer to avoid adjuvant therapies at any rate. Shared decision making has a central role in bridging between clinical evidence, multiple treatment alternatives and patient preferences in the adjuvant treatment of early breast cancer. It is associated with increased patient involvement and responsibility, satisfaction, quality of life and in some instances increase the likelihood of accepting adjuvant treatment. A current understanding of evidence and clinical guidelines, combined with the skills to elicit and appreciate individual patient preferences, is necessary to determine an optimal treatment approach for every individual with breast cancer.

Predicting novel CircRNA-disease associations based on random walk and logistic regression model

Circular RNAs (circRNAs), a large group of small endogenous noncoding RNA molecules, have been proved to modulate protein-coding genes in the human genome. In recent years, many experimental studies have demonstrated that circRNAs are dysregulated in a number of diseases, and they can serve as biomarkers for disease diagnosis and prognosis. However, it is expensive and time-consuming to identify circRNA-disease associations by biological experiments and few computational models have been proposed for novel circRNA-disease association prediction. In this study, we develop a computational model based on the random walk and the logistic regression (RWLR) to predict circRNA-disease associations. Firstly, a circRNA-circRNA similarity network is constructed by calculating their functional similarity of circRNA based on circRNA-related gene ontology. Then, a random walk with restart is implemented on the circRNA similarity network, and the features of each pair of circRNA-disease are extracted based on the results of the random walk and the circRNA-disease association matrix. Finally, a logistic regression model is used to predict novel circRNA-disease associations. Leave one out validation (LOOCV), five-fold cross validation (5CV) and ten-fold cross validation (10CV) are adopted to evaluate the prediction performance of RWLR, by comparing with the latest two methods PWCDA and DWNN-RLS. The experiment results show that our RWLR has higher AUC values of LOOCV, 5CV and 10CV than the other two latest methods, which demonstrates that RWLR has a better performance than other computational methods. What's more, case studies also illustrate the reliability and effectiveness of RWLR for circRNA-disease association prediction.

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Preclinical models that faithfully recapitulate tumor heterogeneity and therapeutic response are critical for translational breast cancer research. Immortalized cell lines are easy to grow and genetically modify to study molecular mechanisms, yet the selective pressure from cell culture often leads to genetic and epigenetic alterations over time. Patient-derived xenograft (PDX) models faithfully recapitulate the heterogeneity and drug response of human breast tumors. PDX models exhibit a relatively short latency after orthotopic transplantation that facilitates the investigation of breast tumor biology and drug response. The transplantable genetically engineered mouse models allow the study of breast tumor immunity. The current protocol describes the method to orthotopically transplant breast tumor fragments into the mammary fat pad followed by drug treatments. These preclinical models provide valuable approaches to investigate breast tumor biology, drug response, biomarker discovery and mechanisms of drug resistance.

Breast Cancer Derived Extracellular Vesicles in Bone Metastasis Induction and Their Clinical Implications as Biomarkers

Cancer incidence and mortality are rapidly growing worldwide. The main risk factors for cancer can be associated with aging as well as the growth of the population and socioeconomic condition. Breast cancer, a crucial public health problem, is the second cause of death among women. About 70% of patients with advanced breast cancer have bone metastases. In bone metastasis, cancer cells and osteoclasts form a vicious cycle: cancer cells promote osteoclast differentiation and activation that, in turn, induce cancer cell seeding and proliferation in the bone. Growing evidence shows that extracellular vesicles (EVs) play a key role in carcinogenesis, proliferation, pre-metastatic niche formation, angiogenesis, metastasis, and chemoresistance in several tumors, such as breast, lung, prostate, and liver cancer. Here, we discuss the role of EVs released by breast cancer cells, focusing on bone metastasis induction and their clinical implications as biomarkers.

Proapoptotic and Antiangiogenic Activities of Arctium Lappa L. on Breast Cancer Cell Lines

In this study, the bioactivity-guided fractionation was conducted on the aerial parts of Arctium lappa L. and then the extracts were tested in vitro on breast cancer (MCF-7), colorectal cancer (HCT-116), and normal cells (EA.hy926). The n-hexane fraction (EHX) of the ethanolic extract showed strong activity against both MCF-7 and EA.hy926 cell lines (IC₅₀ values: 14.08 ± 3.64 and 27.25 ± 3.45 μg/mL, respectively). The proapoptotic activity of EHX was assessed using MCF-7. Morphological alterations were visualized using Hoechst staining and a transmission electron microscope. Cancer cell signal transduction pathways were investigated, and EHX significantly upregulated p53, TGF-β, and NF-κB. Furthermore, EHX was found to disrupt the metastatic cascade of breast cancer cells by the inhibition of cell proliferation, migration, invasion, and colonization. The antiangiogenic activity of EHX fraction showed potent inhibition of rat aorta microvessels with IC₅₀ value: 4.34 ± 1.64 μg/mL. This result was supported by the downregulation of VEGF-A expression up to 54%. Over 20 compounds were identified in EHX using GC-MS, of which stigmasterol, ß-sitosterol, and 3-O-acetyllupeol are the major active compounds. Phytochemical analysis of EHX showed higher phenolic and flavonoid contents with a substantial antioxidant activity. In conclusion, this work demonstrated that A. lappa has valuable anticancer activity and antiangiogenic properties that might be useful in breast cancer therapy.

Effect of COL4A1 Expression on the Survival of Neoadjuvant Chemotherapy Breast Cancer Patients

Optimal therapy for each patient depends on their subtype, anatomic cancer stage, gene status, and preferences. Neoadjuvant chemotherapy-treated tumors have shown attenuated tumor growth, but the therapy cannot completely reduce tumor cell dissemination to blood stream and distant metastasis. Though it has been indicated that the protein of the collagen type IV alpha 1 (COL4A1) gene is induced by p53 to inhibit angiogenesis and tumorigenic activity in cancer cells, its prognostic significance in breast cancer (BC) patients has not yet been fully elucidated. We analysed 206 BC and fresh paired-match adjacent normal breast tissue from tissue microarrays (TMAs) and COL4A1-stained TMAs using immunohistochemistry. These were used to evaluate COL4A1 expression in BC and to analyse the relationship between this expression and clinicopathological factors and prognosis. The expression of the COL4A1 protein was significantly higher in normal adjacent tissue than in the tumor tissues of BC (P < 0.0001). The low COL4A1 expression of the BC patients had decreased metastasis incidence ratio than those exhibiting high COL4A1 expression (P=0.034). Low COL4A1 expression in the tumor cells of BC patients was found to significantly reduce the overall survival (OS) and relapse-free survival (RFS) rates of neoadjuvant chemotherapy patients (P=0.047 and P=0.025, respectively). We also validated the results to ensure their consistency with a web server program for survival analysis from the Cancer Genome Atlas (TCGA) database (P=0.057). Additionally, COL4A1 expression was positively correlated with p53 expression (P=0.00076). Thus, we present clinical evidence that COL4A1 expression can be used as a biomarker of better prognosis of BC patients receiving neoadjuvant chemotherapy.

Cyclodextrin as a magic switch in covalent and non-covalent anticancer drug release systems

Cancer has been a threat to human health, so its treatment is a huge challenge to the present medical field. One of commonly used methods is the controlled release of anticancer drug to reduce the dose for patients, increase the stability of drug treatment and minimize side effects. Cyclodextrin is a kind of cyclic oligosaccharide produced by amylase hydrolysis. Because cyclodextrin contains a cavity structure and active hydroxyl groups, it has a positive effect on the study of the controlled release of anticancer drugs. This article reviews the controlled release of current anticancer drugs based on cyclodextrins as a "flexible switch", and discusses the classification of different types of release systems, highlighting their role in cancer treatment. Moreover, the opportunities and challenges of cyclodextrin as a magic switch in the controlled release of anticancer drugs are discussed.

FHITlow /pHER2high signature in non-small cell lung cancer is predictive of anti-HER2 molecule efficacy

Despite its efficacy in solid tumours, in particular HER2⁺ breast cancer, HER2-targeted therapy has given rise to disappointing results in non-small cell lung cancer (NSCLC). With the aim of refining the target population for anti-HER2 therapies in NSCLC, we investigated the relationships between HER2 and the tumour suppressor fragile histidine triad (FHIT) in lung tumour cells. First, we observed a negative correlation between FHIT expression and the activated form of HER2 (pHER2) in NSCLC samples and in lung tumour cell lines. Moreover, the silencing or overexpression of FHIT in lung cell lines led to an increase or decrease of HER2 activity, respectively. We also demonstrated that two anti-HER2 drugs, irbinitinib and trastuzumab, restore a more epithelial phenotype and counteract cell invasiveness and growth of FHIT-silenced tumour cell lines. Finally, we showed that the FHIT^low /pHER2^high phenotype predicts sensitivity to an anti-HER2 therapy in primary tumour cells from NSCLC patients. Our results show that FHIT regulates the activity of HER2 in lung tumour cells and that FHIT-inactivated tumour cells are sensitive to HER2 inhibitors. A new subclass of patients with NSCLC may be eligible for an anti-HER2 therapy. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The Burden and Trends of Breast Cancer From 1990 to 2017 at the Global, Regional, and National Levels: Results From the Global Burden of Disease Study 2017

Background: Data on burden and changing trends of breast cancer are of value for policymaking. We aimed to determine the pattern of breast cancer incidence, mortality, and disability-adjusted life-years (DALYs), as well as temporal trends, from 1990 to 2017.

Methods: We collected detailed information on breast cancer between 1990 and 2017 using the results of the Global Burden of Disease study. The number of incident cases, deaths, and DALYs attributable to breast cancer are reported as well as age-standardized rates. Estimated annual percentage changes (EAPCs) in age-standardized rates were calculated to quantify the temporal trends. Moreover, the attributable burden to breast cancer risk factors was also estimated.

Results: There were 1,960,682 incident cases and 611,625 deaths of breast cancer globally in 2017, contributing to 17,708,600 DALYs. The age-standardized incidence rates (ASIRs) increased between 1990 and 2017, while the age-standardized mortality rates and DALY rates decreased. The corresponding EAPCs were 0.41, −0.62, and −0.56, respectively. These trends were heterogeneous across regions and countries. The increase in the ASIRs was more prominent in countries with a low sociodemographic index. The percentages of breast cancer deaths due to alcohol use and tobacco were decreasing, while deaths due to high body mass index and high fasting plasma glucose were increasing.

Conclusion: Breast cancer remained a major public health concern globally. The trends of incidence, mortality, and DALYs were heterogeneous across regions and countries, suggesting that the allocation of appropriate health care resources for breast cancer should be considered at the national scale and even at the subnational scale.

Novel antibody-drug conjugates for triple negative breast cancer

Triple negative breast cancer (TNBC) is a heterogenous subtype of breast cancer often associated with an aggressive phenotype and poor prognosis. Antibody–drug conjugate (ADC), comprising of a monoclonal antibody linked to a cytotoxic payload by a linker, is gaining increasing traction as an anti-cancer therapeutic. Emerging ADC drugs such as sacituzumab govitecan (IMMU-132) and trastuzumab deruxtecan (DS-8201a) are in late stages of clinical development for patients with metastatic breast cancer, including TNBC. In this article, we review and discuss the development and clinical application of ADCs in patients with advanced TNBC.

Long Non-Coding RNA HOTAIR in Breast Cancer Therapy

Breast cancer (BC) is the most common cancer type among women, and morbidity and mortality rates are still very high. Despite new innovative therapeutic approaches for all BC molecular subtypes, the discovery of new molecular biomarkers involved in tumor progression has been fundamental for the implementation of personalized treatment strategies and improvement of patient management. Many experimental studies indicate that long non-coding RNAs (lncRNAs) are strongly involved in BC initiation, metastatic progression, and drug resistance. In particular, aberrant expression of HOX transcript antisense intergenic RNA (HOTAIR) lncRNA plays an important role in BC contributing to its progression and represents a predictor of BC metastasis. For its proven prognostic value, HOTAIR could represent a potential therapeutic target in BC. In the present review, we summarize the role of HOTAIR in cancer progression and drug resistance, in particular in BC, and we illustrate the main approaches for silencing it.

Inhibition of the polyamine synthesis enzyme ornithine decarboxylase sensitizes triple-negative breast cancer cells to cytotoxic chemotherapy

Treatment of patients with triple-negative breast cancer (TNBC) is limited by a lack of effective molecular therapies targeting this disease. Recent studies have identified metabolic alterations in cancer cells that can be targeted to improve responses to standard-of-care chemotherapy regimens. Using MDA-MB-468 and SUM-159PT TNBC cells, along with LC-MS/MS and HPLC metabolomics profiling, we found here that exposure of TNBC cells to the cytotoxic chemotherapy drugs cisplatin and doxorubicin alter arginine and polyamine metabolites. This alteration was because of a reduction in the levels and activity of a rate-limiting polyamine biosynthetic enzyme, ornithine decarboxylase (ODC). Using gene silencing and inhibitor treatments, we determined that the reduction in ODC was mediated by its negative regulator antizyme, targeting ODC to the proteasome for degradation. Treatment with the ODC inhibitor difluoromethylornithine (DFMO) sensitized TNBC cells to chemotherapy, but this was not observed in receptor-positive breast cancer cells. Moreover, TNBC cell lines had greater sensitivity to single-agent DFMO, and ODC levels were elevated in TNBC patient samples. The alterations in polyamine metabolism in response to chemotherapy, as well as DFMO-induced preferential sensitization of TNBC cells to chemotherapy, reported here suggest that ODC may be a targetable metabolic vulnerability in TNBC.

Identification of ALDH1A3 as a Viable Therapeutic Target in Breast Cancer Metastasis-Initiating Cells

The development of efficacious therapies targeting metastatic spread of breast cancer to the brain represents an unmet clinical need. Accordingly, an improved understanding of the molecular underpinnings of central nervous system spread and progression of breast cancer brain metastases (BCBM) is required. In this study, the clinical burden of disease in BCBM was investigated, as well as the role of aldehyde dehydrogenase 1A3 (ALDH1A3) in the metastatic cascade leading to BCBM development. Initial analysis of clinical survival trends for breast cancer and BCBM determined improvement of breast cancer survival rates; however, this has failed to positively affect the prognostic milestones of triple-negative breast cancer (TNBC) brain metastases (BM). ALDH1A3 and a representative epithelial-mesenchymal transition (EMT) gene signature (mesenchymal markers, CD44 or Vimentin) were compared in tumors derived from BM, lung metastases (LM), or bone metastases (BoM) of patients as well as mice after injection of TNBC cells. Selective elevation of the EMT signature and ALDH1A3 were observed in BM, unlike LM and BoM, especially in the tumor edge. Furthermore, ALDH1A3 was determined to play a role in BCBM establishment via regulation of circulating tumor cell adhesion and migration phases in the BCBM cascade. Validation through genetic and pharmacologic inhibition of ALDH1A3 via lentiviral shRNA knockdown and a novel small-molecule inhibitor demonstrated selective inhibition of BCBM formation with prolonged survival of tumor-bearing mice. Given the survival benefits via targeting ALDH1A3, it may prove an effective therapeutic strategy for BCBM prevention and/or treatment.

Large-Scale Differential Gene Expression Transcriptomic Analysis Identifies a Metabolic Signature Shared by All Cancer Cells

Cancer-dependent metabolic rewiring is often manifested by selective expression of enzymes essential for the transformed cells’ viability. However, the metabolic variations between normal and transformed cells are not fully characterized, and therefore, a systematic analysis will result in the identification of unknown cellular mechanisms crucial for tumorigenesis. Here, we applied differential gene expression transcriptome analysis to examine the changes in metabolic gene profiles between a wide range of normal tissues and cancer samples. We found that, in contrast to normal tissues which exhibit a tissue-specific expression profile, cancer samples are more homogenous despite their diverse origins. This similarity is due to a “proliferation metabolic signature” (PMS), composed of 158 genes (87 upregulated and 71 downregulated gene sets), where 143 are common to all proliferative cells but 15 are cancer specific. Intriguingly, the PMS gene set is enriched for genes encoding rate-limiting enzymes, and its upregulated set with genes associated with poor patient outcome and essential genes. Among these essential genes is ribulose-5-phosphate-3-epimerase (RPE), which encodes a pentose phosphate pathway enzyme and whose role in cancer is still unclear. Collectively, we identified a set of metabolic genes that can serve as novel cancer biomarkers and potential targets for drug development.

A Randomized Parallel Controlled Phase II Trial of Recombinant Human Endostatin Added to Neoadjuvant Chemotherapy for Stage III Breast Cancer

BACKGROUND

To explore the potential advantage of preoperative anti-angiogenosis therapy, we implemented a study to evaluate the efficacy of recombinant human endostatin (EN) in combination with neoadjuvant chemotherapy in the treatment of stage III breast cancer.

PATIENTS AND METHODS

Eighty-seven patients were randomized to neoadjuvant TEC (docetaxel, epirubicin, and cyclophosphamide) or to EN+TEC, followed by surgery. The primary endpoint was the objective response rate (ORR). Secondary endpoints included pathologic complete response (pCR), relapse-free survival (RFS), overall survival (OS), and safety.

RESULTS

Patients receiving EN+TEC achieved significantly higher ORR (81.82%; 36/44) compared with those receiving TEC (58.14%; 25/43; P=0.016). There was a non-significant trend of increased pCR with EN treatment (15.91% vs. 6.98%). The median follow-up was 54 months and revealed a significantly higher RFS with EN+TEC (median, 67.3 months; 95% confidence interval [CI], 61.0-73.7 months), compared with TEC (median, 55.0 months; 95% CI, 48.3-61.7 months; P =0.014). EN+TEC also significantly improved OS (74.2 months; 95% CI, 68.9-79.6 months), compared with TEC (59.1 months; 95% CI, 52.0-66.1 months; P =0 .006). The 3- and 5-year OS rates are estimated to be 88.5% and 82.8% with EN+TEC and 76.7% and 54.4% with TEC, respectively. Cox proportional regression analyses showed that EN+TEC was associated with improved OS (hazard ratio, 0.377; 95% CI, 0.418-0.959; P =0 .041). There was no significant difference in adverse events between EN+TEC and TEC.

CONCLUSION

The combination of EN+TEC neoadjuvant chemotherapy significantly improved the ORR and OS, suggesting a benefit of adding anti-angiogenesis to standard chemotherapy in the treatment of locally advanced breast cancer.

Application of a Biphasic Mathematical Model of Cancer Cell Drug Response for Formulating Potent and Synergistic Targeted Drug Combinations to Triple Negative Breast Cancer Cells

Triple negative breast cancer is a collection of heterogeneous breast cancers that are immunohistochemically negative for estrogen receptor, progesterone receptor, and ErbB2 (due to deletion or lack of amplification). No dominant proliferative driver has been identified for this type of cancer, and effective targeted therapy is lacking. In this study, we hypothesized that triple negative breast cancer cells are multi-driver cancer cells, and evaluated a biphasic mathematical model for identifying potent and synergistic drug combinations for multi-driver cancer cells. The responses of two triple negative breast cancer cell lines, MDA-MB-231 and MDA-MB-468, to a panel of targeted therapy drugs were determined over a broad range of concentrations. The analyses of the drug responses by the biphasic mathematical model revealed that both cell lines were indeed dependent on multiple drivers, and inhibitors of individual drivers caused a biphasic response: a target-specific partial inhibition at low nM concentrations, and an off-target toxicity at μM concentrations. We further demonstrated that combinations of drugs, targeting each driver, cause potent, synergistic, and cell-specific cell killing. Immunoblotting analysis of the effects of the individual drugs and drug combinations on the signaling pathways supports the above conclusion. These results support a multi-driver proliferation hypothesis for these triple negative breast cancer cells, and demonstrate the applicability of the biphasic mathematical model for identifying effective and synergistic targeted drug combinations for triple negative breast cancer cells.

Drug utilization and expenditure of anticancer drugs for breast cancer

Purpose

Drug utilization studies have proven to be an effective tool in the evaluation of rational drug use in different health care systems, including oncology. The drug utilization studies were used in many institutes to ensure the safe, effective and appropriate use of drugs being prescribed. The main aim of this study was to assess the utilization pattern of anticancer drugs in breast cancer patients.

Method

A retrospective cross-sectional observational study was carried out at King Saud University Medical City (KSUMC) for 1 year from January 2016 to December 2016. All female patients diagnosed with breast cancer during this year were included in the study.

Results

A total of 101 patients were included in this study. Most patients received an average of three anticancer drugs. The most commonly prescribed medication was fluorouracil, epirubicin, and cyclophosphamide (FEC) regimen, which was used in 81% of patients. Combinations of FEC + docetaxel and FEC + docetaxel + trastuzumab were received by43% and 23% of patients, respectively. Docetaxel was the most commonly used drug in neoadjuvant setting, whereas letrozole and trastuzumab were prescribed more frequently in hormonal and targeted therapies, respectively. The total drug expenditure on anticancer therapy was approximately 3.8 million Saudi Riyals (S.R), with adjuvant therapy constituting over half of the total spending. In neoadjuvant settings, the spending cost for hormonal therapy was the highest. The condition of most breast cancer patients was improved during the study period, whereas only 29% of the included patients progressed.

Conclusion

FEC was the most common regimen used in this study, consistent with the National Comprehensive Cancer Network (NCCN) guideline recommendation. Our results indicated that adherence to a clinical guideline and recommended medication regimens improved patient outcomes. Our finding indicate how analyzing drug utilization pattern could benefit institutions in managing inventory and efficiently using health care resources.

Cellular Plasticity in Breast Cancer Progression and Therapy

With the exception of non-melanoma skin cancer, breast cancer is the most frequently diagnosed malignant disease among women, with the majority of mortality being attributable to metastatic disease. Thus, even with improved early screening and more targeted treatments which may enable better detection and control of early disease progression, metastatic disease remains a significant problem. While targeted therapies exist for breast cancer patients with particular subtypes of the disease (Her2+ and ER/PR+), even in these subtypes the therapies are often not efficacious once the patient's tumor metastasizes. Increases in stemness or epithelial-to-mesenchymal transition (EMT) in primary breast cancer cells lead to enhanced plasticity, enabling tumor progression, therapeutic resistance, and distant metastatic spread. Numerous signaling pathways, including MAPK, PI3K, STAT3, Wnt, Hedgehog, and Notch, amongst others, play a critical role in maintaining cell plasticity in breast cancer. Understanding the cellular and molecular mechanisms that regulate breast cancer cell plasticity is essential for understanding the biology of breast cancer progression and for developing novel and more effective therapeutic strategies for targeting metastatic disease. In this review we summarize relevant literature on mechanisms associated with breast cancer plasticity, tumor progression, and drug resistance.