Progesterone receptor modulates ERα action in breast cancer

Breast cancer diagnosis and prognosis using a high b-value non-Gaussian continuous-time random-walk model

AIM

To compare the diagnostic performance of mono-exponential model-derived apparent diffusion coefficient (ADC), continuous-time random-walk (CTRW) model-derived D_m, α, β and their combinations in discriminating malignancy of breast lesions, and investigate the association between model-derived parameters and prognosis-related immunohistochemical indices.

MATERIALS AND METHODS

A total of 85 patients with breast lesions (51 malignant, 34 benign) were analysed in this retrospective study. Clinical characteristics include oestrogen receptor (ER), progesterone receptor (PR), human epidermal receptor 2 (HER2), and Ki-67. The ADC was fitted using a mono-exponential model (b-values = 0, 800 s/mm²), while D_m, α, and β were fitted using a CTRW model. Independent Student's t-test and the Mann-Whitney U-test were used for the comparison of parameters. Discrimination performance was accomplished by receiver operating characteristic (ROC) analysis, and Spearman's correlation analysis was used to explore the association between immunohistochemical indices and diffusion parameters, the statistical significance level was p<0.05.

RESULTS

D_m and ADC demonstrated similar performance in differentiating malignant and benign lesions (AUC = 0.928 versus 0.930), while the combination of D_m, α, and β could improve the AUC to 0.969. The combined parameter generated by ADC, D_m, α, and β was effective in identifying the ER+/ER- and PR+/PR- patients. Temporal heterogeneity parameter α correlated significantly with the expression of PR.

CONCLUSION

Diffusion parameters derived from the CTRW model could effectively discriminate the malignancy of breast lesions. Meanwhile, the hormone receptor expression could be distinguished by combined diffusion parameters, and have the potential to reflect the prognosis.

Making In Vitro Tumor Models Whole Again

As a reductionist approach, patient-derived in vitro tumor models are inherently still too simplistic for personalized drug testing as they do not capture many characteristics of the tumor microenvironment (TME), such as tumor architecture and stromal heterogeneity. This is especially problematic for assessing stromal-targeting drugs such as immunotherapies in which the density and distribution of immune and other stromal cells determine drug efficacy. On the other end, in vivo models are typically costly, low-throughput, and time-consuming to establish. Ex vivo patient-derived tumor explant (PDE) cultures involve the culture of resected tumor fragments that potentially retain the intact  TME of the original tumor. Although developed decades ago, PDE cultures have not been widely adopted likely because of their low-throughput and poor long-term viability. However, with growing recognition of the importance of patient-specific TME in mediating drug response, especially in the field of immune-oncology, there is an urgent need to resurrect these holistic cultures. In this Review, the key limitations of patient-derived tumor explant cultures are outlined and technologies that have been developed or could be employed to address these limitations are discussed. Engineered holistic tumor explant cultures may truly realize the concept of personalized medicine for cancer patients.

Anticancer genes (NOXA, PAR-4, TRAIL) are de-regulated in breast cancer patients and can be targeted by using a ribosomal inactivating plant protein (riproximin)

BACKGROUND

Anticancer genes are an endogenous defense against transformed cells as they impose antineoplastic effects upon ectopic expression. Profiling the expression of these genes is fundamental for exploring their prognostic and therapeutic relevance in cancers. Natural compounds can upregulate anticancer genes in malignant cells and thus be useful for therapeutic purposes. In this study, we identified the expression levels of anticancer genes in breast cancer clinical isolates. In addition, the purified and sequenced plant protein (riproximin) was evaluated for its potential to induce anticancer genes in two breast cancer cell lines.

METHODOLOGY

Expression profiles of three anticancer genes (NOXA, PAR-4, TRAIL) were identified by immunohistochemistry in 45 breast cancer clinical isolates. Breast cancer cells were exposed to riproximin and expression of the anticancer genes was determined by microarray, real-time PCR and western blot methodologies. Lastly, a bioinformatic approach was adopted to highlight the molecular/functional significance of the anticancer genes.

RESULTS

NOXA expression was evenly de-regulated among the clinical isolates, while PAR-4 was significantly down-regulated in majority of the breast cancer tissues. In contrast, TRAIL expression was increased in most of the clinical samples. Expression levels of the anticancer genes followed a distinct trend in accordance with the disease severity. Riproximin showed a substantial potential of inducing expression of the anticancer genes in breast cancer cells at transcriptomic and protein levels. The bioinformatic approach revealed involvement of anticancer genes in multiple cellular functions and signaling cascades.

CONCLUSION

Anticancer genes were de-regulated and showed discrete expression patterns in breast cancer patient samples. Riproximin effectively induced the expression of selected anticancer genes in breast cancer cells.

A Review of Endocrine Therapy in Early-stage Breast Cancer: The Journey From Crudeness to Precision

Endocrine therapy (ET) is the standard of care for hormone receptor-positive early-stage breast cancer in the adjuvant setting. However, response to ET can vary across patient subgroups. Historically, hormone receptor expression and clinical stage are the main predictors of the benefit of ET. A "window of opportunity" trials has raised significant interest in recent years as a means of assessing the sensitivity of a patient's cancer to short-term neoadjuvant ET, which provides important prognostic information, and helps in decision-making regarding treatment options in a time-efficient and cost-efficient manner. In the era of genomics, molecular profiling has led to the discovery and evaluation of the prognostic and predictive abilities of new molecular profiles. To realize the goal of personalized medicine, we are in urgent need to explore reliable biomarkers or genomic signatures to accurately predict the clinical response and long-term outcomes associated with ET. Validation of these biomarkers as reliable surrogate endpoints can also lead to a revolution in the clinical trial designs, and potentially avoid the need for repeated tissue biopsies in the surveillance of disease response. The clinical potential of tumor genomic profiling marks the beginning of a new era of precision medicine in breast cancer treatment.

The correlation of ESR1 genetic aberrations with estrogen receptor and progesterone receptor status in metastatic and primary estrogen receptor-positive breast carcinomas

INTRODUCTION

Genetic aberrations in the Estrogen Receptor 1 (ESR1) gene have been identified as an important mechanism of resistance to endocrine therapy in metastatic breast carcinoma. In this study, we aimed to correlate ESR1 genetic aberrations with the ER and PR status in paired metastatic and primary breast carcinomas.

METHODS

Patients with ER-positive breast cancer were divided into two groups: ESR1 genetic aberration (n=26) and wild-type control (n=29) based on genetic profiling of their metastatic tumors. Clinicopathological features and ER/PR status were analyzed in paired primary and metastatic tumors.

RESULTS

Although there was no significant difference in ER expression between the ESR1 aberration and control groups in primary tumors, ER positivity rate in metastatic tumors was significantly higher in the ESR1 aberration group than in the control group (100% vs. 86%, p<0.05). ESR1 aberrated cases were associated with more liver metastases than control tumors (46% vs. 10%, p<0.01). The ER percentage and intensity slightly increased from primary to metastatic tumors in the ESR1 aberration group compared to a decrease in both in the wild-type group (percentage increase 2% vs. decrease 19%, p=0.0594; intensity increase 0.04 vs. decrease 0.8, p<0.05). Patients with ESR1 aberrated metastases were more likely than those with wild-type ESR1 metastases to have the following characteristics: 1) ER percentage ≥ 90% and intensity >2, as well as PR percentage ≥ 30% and intensity >1 in metastatic tumors; 2) ER percentage ≥ 90% and PR percentage ≥ 70% in primary tumors; and 3) slightly increase in ER percentage and intensity from primary to metastatic tumors.

CONCLUSION

Based on the ER/PR parameters of paired primary and metastatic breast cancer, ESR1 aberration in metastasis may be predicted.

Organoids as an Enabler of Precision Immuno-Oncology

Since the dawn of the past century, landmark discoveries in cell-mediated immunity have led to a greater understanding of the innate and adaptive immune systems and revolutionised the treatment of countless diseases, including cancer. Today, precision immuno-oncology (I/O) involves not only targeting immune checkpoints that inhibit T-cell immunity but also harnessing immune cell therapies. The limited efficacy in some cancers results mainly from a complex tumour microenvironment (TME) that, in addition to adaptive immune cells, comprises innate myeloid and lymphoid cells, cancer-associated fibroblasts, and the tumour vasculature that contribute towards immune evasion. As the complexity of TME has called for more sophisticated human-based tumour models, organoids have allowed the dynamic study of spatiotemporal interactions between tumour cells and individual TME cell types. Here, we discuss how organoids can study the TME across cancers and how these features may improve precision I/O. We outline the approaches to preserve or recapitulate the TME in tumour organoids and discuss their potential, advantages, and limitations. We will discuss future directions of organoid research in understanding cancer immunology in-depth and identifying novel I/O targets and treatment strategies.

Vascular Endothelial Growth Factor Ligands and Receptors in Breast Cancer

Breast cancer (BC) is the most common malignancy responsible for the largest number of deaths in women worldwide. The risk of developing BC is predisposed by many factors such as age, presence of genetic mutations or body weight. The diagnosis is mostly made relatively late, which is why patients are exposed to radical surgical treatments, long-term chemotherapy and lower survival rates. There are no sufficiently sensitive and specific screening tests; therefore, researchers are still looking for new diagnostic biomarkers that would indicate the appearance of neoplastic changes in the initial stage of neoplasm. The VEGF family of proteins (VEGF-A, VEGF-B, VEGF-C, VEGF-D, EG-VEGF, PlGF) and their receptors are significant factors in the pathogenesis of BC. They play a significant role in the process of angiogenesis and lymphangiogenesis in both physiological and pathological conditions. The usefulness of these proteins as potential diagnostic biomarkers has been initially proven. Moreover, the blockage of VEGF-related pathways seems to be a valid therapeutic target. Recent studies have tried to describe novel strategies, including targeting pericytes, use of miRNAs and extracellular tumor-associated vesicles, immunotherapeutic drugs and nanotechnology. This indicates their possible contribution to the formation of breast cancer and their usefulness as potential biomarkers and therapeutic targets.

Deciphering breast cancer: from biology to the clinic

Breast cancer remains a leading cause of cancer-related mortality in women, reflecting profound disease heterogeneity, metastasis, and therapeutic resistance. Over the last decade, genomic and transcriptomic data have been integrated on an unprecedented scale and revealed distinct cancer subtypes, critical molecular drivers, clonal evolutionary trajectories, and prognostic signatures. Furthermore, multi-dimensional integration of high-resolution single-cell and spatial technologies has highlighted the importance of the entire breast cancer ecosystem and the presence of distinct cellular "neighborhoods." Clinically, a plethora of new targeted therapies has emerged, now being rapidly incorporated into routine care. Resistance to therapy, however, remains a crucial challenge for the field.

Sex steroid hormones and DNA repair regulation: Implications on cancer treatment responses

The role of sex steroid hormones (SSHs) has been shown to modulate cancer cytotoxic treatment sensitivity. Dysregulation of DNA repair associated with genomic instability, abnormal cell survival and not only promotes cancer progression but also resistance to cancer treatment. The three major SSHs, androgen, estrogen, and progesterone, have been shown to interact with several essential DNA repair components. The presence of androgens directly regulates key molecules in DNA double-strand break (DSB) repair. Estrogen can promote cell proliferation and DNA repair, allowing cancer cells to tolerate chemotherapy and radiotherapy. Information on the role of progesterone in DNA repair is limited: progesterone interaction with some DNA repair components has been identified, but the biological significance is still unknown. Here, we review the roles of how each SSH affects DNA repair regulation and modulates response to genotoxic therapies and discuss future research that can be beneficial when combining SSHs with cancer therapy. We also provide preliminary analysis from publicly available databases defining the link between progesterone/PR and DDRs & DNA repair regulation that plausibly contribute to chemotherapy response and breast cancer patient survival.

Regulation of progesterone receptor expression in endometriosis, endometrial cancer, and breast cancer by estrogen, polymorphisms, transcription factors, epigenetic alterations, and ubiquitin-proteasome system

The uterus and breasts are hormone-responsive tissues. Progesterone and estradiol regulate gonadotropin secretion, prepare the endometrium for implantation, maintain pregnancy, and regulate the differentiation of breast tissue. Dysregulation of these hormones causes endometriosis, endometrial cancer, and breast cancer, damaging the physical and mental health of women. Emerging evidence has shown that progesterone resistance or elevated progesterone activity is the primary hormonal substrate of these diseases. Since progesterone acts through its specific nuclear receptor, the abnormal expression of the progesterone receptor (PR) dysregulates progesterone function. This review discusses the regulatory mechanisms of PR expression in patients with endometriosis, and endometrial or breast cancer, including estrogen, polymorphisms, transcription factors, epigenetics, and the ubiquitin-proteasome system. (1) Estrogen promotes the expression of PRA (a PR isoform) mRNA and protein through the interaction of estrogen receptors (ERs) and Sp1 with half-ERE/Sp1 binding sites. ERs also affect the binding of Sp1 and Sp1 sites to promote the expression of PRB (another PR isoform)(2) PR polymorphisms, mainly PROGINS and + 331 G/A polymorphism, regulate PR expression by affecting DNA methylation and transcription factor binding. (3) The influence of epigenetic alterations on PR expression occurs through DNA methylation, histone modification, and microRNA. (4) As one of the main protein degradation pathways in vivo, the ubiquitin-proteasome system (UPS) regulates PR expression by participating in protein degradation. These mechanisms may provide new molecular targets for diagnosing and treating endometriosis, endometrial, and breast cancer.

Unraveling the Role of Scutellaria baicalensis for the Treatment of Breast Cancer Using Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

Scutellaria baicalensis is often used to treat breast cancer, but the molecular mechanism behind the action is unclear. In this study, network pharmacology, molecular docking, and molecular dynamics simulation are combined to reveal the most active compound in Scutellaria baicalensis and to explore the interaction between the compound molecule and the target protein in the treatment of breast cancer. In total, 25 active compounds and 91 targets were screened out, mainly enriched in lipids in atherosclerosis, the AGE-RAGE signal pathway of diabetes complications, human cytomegalovirus infection, Kaposi-sarcoma-associated herpesvirus infection, the IL-17 signaling pathway, small-cell lung cancer, measles, proteoglycans in cancer, human immunodeficiency virus 1 infection, and hepatitis B. Molecular docking shows that the two most active compounds, i.e., stigmasterol and coptisine, could bind well to the target AKT1. According to the MD simulations, the coptisine-AKT1 complex shows higher conformational stability and lower interaction energy than the stigmasterol-AKT1 complex. On the one hand, our study demonstrates that Scutellaria baicalensis has the characteristics of multicomponent and multitarget synergistic effects in the treatment of breast cancer. On the other hand, we suggest that the best effective compound is coptisine targeting AKT1, which can provide a theoretical basis for the further study of the drug-like active compounds and offer molecular mechanisms behind their roles in the treatment of breast cancer.

Identification and characterization of a proliferative cell population in estrogen receptor-positive metastatic breast cancer through spatial and single-cell transcriptomics

Background

Intratumor heterogeneity is a hallmark of most solid tumors, including breast cancers. We applied spatial transcriptomics and single-cell RNA-sequencing technologies to profile spatially resolved cell populations within estrogen receptor-positive (ER ⁺ ) metastatic breast cancers and elucidate their importance in estrogen-dependent tumor growth.

Methods

Spatial transcriptomics and single-cell RNA-sequencing were performed on two patient-derived xenografts (PDXs) of "ER-high" metastatic breast cancers with opposite estrogen-mediated growth responses: estrogen-suppressed GS3 (80-100% ER) and estrogen-stimulated SC31 (30-75% ER) models. The analyses included samples treated with and without 17β-estradiol. The findings were validated via scRNA-seq analyses on "ER-low" estrogen-accelerating PDX, GS1 (5% ER). The results from our spatial and single-cell analyses were further supported by the analysis of a publicly available single cell dataset and a protein-based dual immunohistochemical (IHC) evaluation using three important clinical markers [i.e., ER, progesterone receptor (PR), and Ki67]. The translational implication of these results was assessed by clinical outcome analyses on public breast cancer cohorts.

Results

Our novel space-gene-function study revealed a "proliferative" cell population in addition to three major spatially distinct compartments within ER ⁺ metastatic breast cancers. These compartments showed functional diversity (i.e., estrogen-responsive, proliferative, hypoxia-induced, and inflammation-related). The "proliferative ( MKI67 ⁺ )" population, not "estrogen-responsive" compartment, was crucial for estrogen-dependent tumor growth, leading to the acquisition of luminal B features. The cells with induction of typical estrogen-responsive genes such as PGR were not directly linked to estrogen-dependent proliferation. Additionally, the dual IHC analyses demonstrated the distinct contribution of the Ki67 ⁺ proliferative cells toward estrogen-mediated growth and their response to palbociclib, a CDK4/6 inhibitor. The gene signatures developed from the proliferative, hypoxia-induced, and inflammation-related compartments were significantly correlated with worse clinical outcomes, while patients with the high estrogen-responsive scores showed better prognosis, confirming that the estrogen-responsive compartment would not be directly associated with estrogen-dependent tumor progression.

Conclusions

For the first time, our study elucidated a "proliferative" cell population distinctly distributed in ER ⁺ metastatic breast cancers. They contribute differently toward progression of these cancers, and the gene signature in the "proliferative" compartment is an important determinant of luminal cancer subtypes.

Proteogenomics decodes the evolution of human ipsilateral breast cancer

Ipsilateral breast tumor recurrence (IBTR) is a clinically important event, where an isolated in-breast recurrence is a potentially curable event but associated with an increased risk of distant metastasis and breast cancer death. It remains unclear if IBTRs are associated with molecular changes that can be explored as a resource for precision medicine strategies. Here, we employed proteogenomics to analyze a cohort of 27 primary breast cancers and their matched IBTRs to define proteogenomic determinants of molecular tumor evolution. Our analyses revealed a relationship between hormonal receptors status and proliferation levels resulting in the gain of somatic mutations and copy number. This in turn re-programmed the transcriptome and proteome towards a highly replicating and genomically unstable IBTRs, possibly enhanced by APOBEC3B. In order to investigate the origins of IBTRs, a second analysis that included primaries with no recurrence pinpointed proliferation and immune infiltration as predictive of IBTR. In conclusion, our study shows that breast tumors evolve into different IBTRs depending on hormonal status and proliferation and that immune cell infiltration and Ki-67 are significantly elevated in primary tumors that develop IBTR. These results can serve as a starting point to explore markers to predict IBTR formation and stratify patients for adjuvant therapy.

A review of prognostic and predictive biomarkers in breast cancer

Breast cancer (BC) is a common cancer all over the world that affects women. BC is one of the leading causes of cancer mortality in women, which today has decreased with the advancement of technology and new diagnostic and therapeutic methods. BCs are histologically divided into in situ and invasive carcinoma, and both of them can be divided into ductal and lobular. The main function after the diagnosis of invasive breast cancer is which patient should use chemotherapy, which patient should receive adjuvant therapy, and which should not. If the decision is for adjuvant therapy, the next challenge is to identify the most appropriate treatment or combination of treatments for a particular patient. Addressing the first challenge can be helped by prognostic biomarkers, while addressing the second challenge can be done by predictive biomarkers. Among the molecular markers related to BC, ER, PR, HER2, and the Mib1/Ki-67 proliferation index are the most significant ones and are tightly confirmed in the standard care of all primary, recurrent, and metastatic BC patients. CEA and CA-15-3 antigens are the most valuable markers of serum tumors in BC patients. Determining the series of these markers helps monitor response to the treatment and early detection of recurrence or metastasis. miRNAs have been demonstrated to be intricate in mammary gland growth, proliferation, and formation of BC known to be incriminated in BC biology. By combining established prognostic factors with valid prognostic/predicted biomarkers, we can start the journey to personalized treatment for every recently diagnosed BC patient.

ATM suppresses c-Myc overexpression in the mammary epithelium in response to estrogen

ATM gene mutation carriers are predisposed to estrogen-receptor-positive breast cancer (BC). ATM prevents BC oncogenesis by activating p53 in every cell; however, much remains unknown about tissue-specific oncogenesis after ATM loss. Here, we report that ATM controls the early transcriptional response to estrogens. This response depends on topoisomerase II (TOP2), which generates TOP2-DNA double-strand break (DSB) complexes and rejoins the breaks. When TOP2-mediated ligation fails, ATM facilitates DSB repair. After estrogen exposure, TOP2-dependent DSBs arise at the c-MYC enhancer in human BC cells, and their defective repair changes the activation profile of enhancers and induces the overexpression of many genes, including the c-MYC oncogene. CRISPR/Cas9 cleavage at the enhancer also causes c-MYC overexpression, indicating that this DSB causes c-MYC overexpression. Estrogen treatment induced c-Myc protein overexpression in mammary epithelial cells of ATM-deficient mice. In conclusion, ATM suppresses the c-Myc-driven proliferative effects of estrogens, possibly explaining such tissue-specific oncogenesis.

Nuclear Receptor Imaging In Vivo-Clinical and Research Advances

Nuclear receptors are transcription factors that function in normal physiology and play important roles in diseases such as cancer, inflammation, and diabetes. Noninvasive imaging of nuclear receptors can be achieved using radiolabeled ligands and positron emission tomography (PET). This quantitative imaging approach can be viewed as an in vivo equivalent of the classic radioligand binding assay. A main clinical application of nuclear receptor imaging in oncology is to identify metastatic sites expressing nuclear receptors that are targets for approved drug therapies and are capable of binding ligands to improve treatment decision-making. Research applications of nuclear receptor imaging include novel synthetic ligand and drug development by quantifying target drug engagement with the receptor for optimal therapeutic drug dosing and for fundamental research into nuclear receptor function in cells and animal models. This mini-review provides an overview of PET imaging of nuclear receptors with a focus on radioligands for estrogen receptor, progesterone receptor, and androgen receptor and their use in breast and prostate cancer.

Progesterone modulates the DSCAM-AS1/miR-130a/ESR1 axis to suppress cell invasion and migration in breast cancer

BACKGROUND

A preoperative-progesterone intervention increases disease-free survival in patients with breast cancer, with an unknown underlying mechanism. We elucidated the role of non-coding RNAs in response to progesterone in human breast cancer.

METHODS

Whole transcriptome sequencing dataset of 30 breast primary tumors (10 tumors exposed to hydroxyprogesterone and 20 tumors as control) were re-analyzed to identify differentially expressed non-coding RNAs followed by real-time PCR analyses to validate the expression of candidates. Functional analyses were performed by genetic knockdown, biochemical, and cell-based assays.

RESULTS

We identified a significant downregulation in the expression of a long non-coding RNA, Down syndrome cell adhesion molecule antisense DSCAM-AS1, in response to progesterone treatment in breast cancer. The progesterone-induced expression of DSCAM-AS1 could be effectively blocked by the knockdown of progesterone receptor (PR) or treatment of cells with mifepristone (PR-antagonist). We further show that knockdown of DSCAM-AS1 mimics the effect of progesterone in impeding cell migration and invasion in PR-positive breast cancer cells, while its overexpression shows an opposite effect. Additionally, DSCAM-AS1 sponges the activity of miR-130a that regulates the expression of ESR1 by binding to its 3'-UTR to mediate the effect of progesterone in breast cancer cells. Consistent with our findings, TCGA analysis suggests that high levels of miR-130a correlate with a tendency toward better overall survival in patients with breast cancer.

CONCLUSION

This study presents a mechanism involving the DSCAM-AS1/miR-130a/ESR1 genomic axis through which progesterone impedes breast cancer cell invasion and migration. The findings highlight the utility of progesterone treatment in impeding metastasis and improving survival outcomes in patients with breast cancer.

Progesterone Receptor-Mediated Regulation of Cellular Glucose and 18F-Fluorodeoxyglucose Uptake in Breast Cancer

Context

Positron emission tomography imaging with 2-deoxy-2-[¹⁸F]-fluoro-D-glucose (FDG) is used clinically for initial staging, restaging, and assessing therapy response in breast cancer. Tumor FDG uptake in steroid hormone receptor-positive breast cancer and physiologic FDG uptake in normal breast tissue can be affected by hormonal factors such as menstrual cycle phase, menopausal status, and hormone replacement therapy.

Objective

The purpose of this study was to determine the role of the progesterone receptor (PR) in regulating glucose and FDG uptake in breast cancer cells.

Methods and Results

PR-positive T47D breast cancer cells treated with PR agonists had increased FDG uptake compared with ethanol control. There was no significant change in FDG uptake in response to PR agonists in PR-negative MDA-MB-231 cells, MDA-MB-468 cells, or T47D PR knockout cells. Treatment of T47D cells with PR antagonists inhibited the effect of R5020 on FDG uptake. Using T47D cell lines that only express either the PR-A or the PR-B isoform, PR agonists increased FDG uptake in both cell types. Experiments using actinomycin D and cycloheximide demonstrated the requirement for both transcription and translation in PR regulation of FDG uptake. GLUT1 and PFKFB3 mRNA expression and the enzymatic activity of glucose-6-phosphate dehydrogenase and 6-phosphogluconate dehydrogenase were increased after progestin treatment of T47D cells.

Conclusion

Thus, progesterone and progestins increase FDG uptake in T47D breast cancer cells through the classical action of PR as a ligand-activated transcription factor. Ligand-activated PR ultimately increases expression and activity of proteins involved in glucose uptake, glycolysis, and the pentose phosphate pathway.

Significance and possible causes of hormone receptor expression loss in metastatic breast cancer. Phenotypic evolution of luminal <i>BRCA1</i>-associated breast cancer to triple negative subtype in lung metastasis and PARP inhibition strategy in early-line therapy

Current clinical recommendations indicate the need for a biopsy of a metastatic focus in metastatic breast cancer (BC), but the optimal frequency of additional molecular analysis remains unclear. The discordance of hormonal receptors (HR) between the primary tumor and metastatic foci has prognostic significance, while the transition from HR-positive BC to a triple negative phenotype is associated with a worse clinical prognosis. Acquisition of HR expression in primary triple negative BC is more favorable due to the wide range of options for HR-positive BC treatment. Over the past few years, PARP inhibitors have become an important therapeutic option for the treatment of various tumor types, including BC and luminal surrogate subtypes. However, some questions still remain unresolved, the most important of which are: what is the optimal sequence of the use of CDK4 / 6 inhibitors as part of combined hormone therapy and PARP inhibitors in luminal types of BRCA-associated BC and how effective is the strategy of PARP inhibition after the use of combined hormone therapy with CDK4 / 6 inhibitors? It is obvious that the answers to the questions can be partially obtained by performing a biopsy of the most clinically significant metastatic focus and selecting therapy according to the phenotypic surrogate subtype. A clinical case of the phenotypic evolution of HR-positive BRCA1-associated BC into a triple negative phenotype during metastasis to the lungs and the luminal phenotype of tumor metastasis in soft tissues is presented. Biopsy of the most clinically significant metastatic lesion in the lungs in this case changed the strategy of early-line therapy for estrogen-receptor-positive disease, when in the absence of a biopsy, a combined hormone therapy regimen with CDK4 / 6 inhibitors could be applied. At the same time, the strategy of using PARP inhibitor talazoparib, which has shown efficacy in all surrogate subtypes, should certainly be prescribed in the early line of therapy for BRCA-associated disease with loss of estrogen receptor expression. Despite the luminal phenotype of metastasis in the soft tissues of the back and the unknown status of bone metastases, the drug demonstrates efficacy in these cases as well. It should be noted that partial response according on RECIST 1.1 months with an improvement in the quality of life and the disappearance of pain syndrome was evaluated after 10 weeks of treatment. The response duration was an unprecedented 10 months.

Classification of breast cancer subtypes based on RNA profiling and immunohistochemical methods: clinical and biological aspects: A review

Transcriptome analysis provided a tool to identify expression subtypes of breast cancer (BC). A significant part of BCs are carcinomas that differ in the expression of luminal mammary ductal epithelium markers and estrogen signaling cascade genes (luminal subtypes A and B). Another group of BCs is characterized by the expression of ductal basal lining genes. Another subtype of BC has genes typically expressed in HER2-induced tumors. Immunohistochemical (IHC) examination is reliable in identifying the tumor subtype. Tumors with high IHC-expression of estrogen (ER) and progesterone (PR) receptors with no signs of HER2 gene activation and low proliferative activity should be referred to as luminal type A. The absence of ER, PR, and HER2 expression should be considered a sign of basal tumor subtype. However, the IHC classification cannot reliably distinguish HER2-positive tumors and HER2-enriched subtypes, which do not reflect the biological features of some BCs. For instance, a significant number of ER-positive breast cancer patients included in the MONALEESA ribociclib clinical study had HER2-subtype transcriptional signatures in the absence of HER2 receptor expression, and these were the ones who demonstrated a pronounced response to treatment.

Estrogen regulates divergent transcriptional and epigenetic cell states in breast cancer

Breast cancers are known to be driven by the transcription factor estrogen receptor and its ligand estrogen. While the receptor's cis-binding elements are known to vary between tumors, heterogeneity of hormone signaling at a single-cell level is unknown. In this study, we systematically tracked estrogen response across time at a single-cell level in multiple cell line and organoid models. To accurately model these changes, we developed a computational tool (TITAN) that quantifies signaling gradients in single-cell datasets. Using this approach, we found that gene expression response to estrogen is non-uniform, with distinct cell groups expressing divergent transcriptional networks. Pathway analysis suggested the two most distinct signatures are driven separately by ER and FOXM1. We observed that FOXM1 was indeed activated by phosphorylation upon estrogen stimulation and silencing of FOXM1 attenuated the relevant gene signature. Analysis of scRNA-seq data from patient samples confirmed the existence of these divergent cell groups, with the FOXM1 signature predominantly found in ER negative cells. Further, multi-omic single-cell experiments indicated that the different cell groups have distinct chromatin accessibility states. Our results provide a comprehensive insight into ER biology at the single-cell level and potential therapeutic strategies to mitigate resistance to therapy.

17β-estradiol Enhances 5-Fluorouracil Anti-Cancer Activities in Colon Cancer Cell Lines

BACKGROUND

5-Fluorouracil (5-FU) represents one of the major constituents of chemotherapy combination regimens in colon cancer (CRC) treatments; however, this regimen is linked with severe adverse effects and chemoresistance. Thus, developing more efficient approaches for CRC is urgently needed to overcome these problems and improve the patient survival rate. Currently, 17β-estradiol (E2) has gained greater attention in colon carcinogenesis, significantly lowering the incidence of CRC in females at reproductive age compared with age-matched males.

AIMS

This study measured the effects of E2 and/or 5-FU single/dual therapies on cell cycle progression and apoptosis against human HT-29 female and SW480 male primary CRC cells versus their impact on SW620 male metastatic CRC cells.

METHODS

The HT-29, SW480, and SW620 cells were treated with IC₅₀ of E2 (10 nM) and 5-FU (50 μM), alone or combined (E+F), for 48 h before cell cycle and apoptosis analyses using flow cytometry.

RESULTS

The data here showed that E2 monotherapy has great potential to arrest the cell cycle and induce apoptosis in all the investigated colon cancer cells, with the most remarkable effects on metastatic cells (SW620). Most importantly, the dual therapy (E+F) has exerted anti-cancer activities in female (HT-29) and male (SW480) primary CRC cells by inducing apoptosis, which was preferentially provoked in the sub-G₁ phase. However, the dual treatment showed the smallest effect in SW620 metastatic cells.

CONCLUSION

this is the first study that demonstrated that the anti-cancer actions of 17β-estradiol and 5-Fluorouracil dual therapy were superior to the monotherapies in female and male primary CRC cells; it is proposed that this treatment strategy could be promising for the early stages of CRC. At the same time, 17β-estradiol monotherapy could be a better approach for treating the metastatic forms of the disease. Nevertheless, additional investigations are still required to determine their precise therapeutic values in CRC.

Molecular Mechanisms of Anti-Estrogen Therapy Resistance and Novel Targeted Therapies

Breast cancer (BC) is the most commonly diagnosed cancer in women, constituting one-third of all cancers in women, and it is the second leading cause of cancer-related deaths in the United States. Anti-estrogen therapies, such as selective estrogen receptor modulators, significantly improve survival in estrogen receptor-positive (ER+) BC patients, which represents about 70% of cases. However, about 60% of patients inevitably experience intrinsic or acquired resistance to anti-estrogen therapies, representing a major clinical problem that leads to relapse, metastasis, and patient deaths. The resistance mechanisms involve mutations of the direct targets of anti-estrogen therapies, compensatory survival pathways, as well as alterations in the expression of non-coding RNAs (e.g., microRNA) that regulate the activity of survival and signaling pathways. Although cyclin-dependent kinase 4/6 and phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) inhibitors have significantly improved survival, the efficacy of these therapies alone and in combination with anti-estrogen therapy for advanced ER+ BC, are not curative in advanced and metastatic disease. Therefore, understanding the molecular mechanisms causing treatment resistance is critical for developing highly effective therapies and improving patient survival. This review focuses on the key mechanisms that contribute to anti-estrogen therapy resistance and potential new treatment strategies alone and in combination with anti-estrogen drugs to improve the survival of BC patients.

Prognostic Factors for Bone Survival and Functional Outcomes in Patients With Breast Cancer Spine Metastases

According to the Global Cancer Statistics 2020 report, breast cancer is the most commonly diagnosed cancer worldwide. Patients with mammary cancer live longer due to the continuous optimization of chemotherapy, targeted drugs, and hormone therapy, which will inevitably lead to an increase in the prevalence of metastatic bone tumors. Bone metastasis affects approximately 8% of patients with mammary cancer, with the spine being the most common site. Metastatic neoplasms can invade the centrum and its attachments, leading to local pain, spinal instability, vertebral pathological fractures, spinal cord compression, impaired neurological function, and paralysis, ultimately reducing the quality of life. Multidisciplinary and personalized management using analgesic drugs, endocrine therapy, corticosteroid therapy, chemotherapy, bisphosphonates, immunotherapy, targeted drugs, radiotherapy, and surgery has been advocated for the treatment of spinal metastases. Multiple paradigms and systems have been proposed to determine suitable treatments. In the early stages, the occurrence of metastasis indicates a terminal stage of the tumor process in patients with malignant tumors, implying that their lifespan is limited. As a result, the choice of treatment is heavily influenced by longevity. However, with the development of treatment methods, the lifespan of patients with tumors has considerably increased in recent years. This leads to the choice of patient's treatment, which depends not only on the patient's survival, but also on the radiotherapy or postoperative functional outcomes. Nevertheless, they fall short of determining the variables that affect survival and functional outcomes in histology-specific subgroups of breast cancer. To accurately predict the bone survival and functional outcomes of patients with breast cancer spine metastases a review of prognostic factors was performed.

Genome engineering for estrogen receptor mutations reveals differential responses to anti-estrogens and new prognostic gene signatures for breast cancer

Mutations in the estrogen receptor (ESR1) gene are common in ER-positive breast cancer patients who progress on endocrine therapies. Most mutations localise to just three residues at, or near, the C-terminal helix 12 of the hormone binding domain, at leucine-536, tyrosine-537 and aspartate-538. To investigate these mutations, we have used CRISPR-Cas9 mediated genome engineering to generate a comprehensive set of isogenic mutant breast cancer cell lines. Our results confirm that L536R, Y537C, Y537N, Y537S and D538G mutations confer estrogen-independent growth in breast cancer cells. Growth assays show mutation-specific reductions in sensitivities to drugs representing three classes of clinical anti-estrogens. These differential mutation- and drug-selectivity profiles have implications for treatment choices following clinical emergence of ER mutations. Our results further suggest that mutant expression levels may be determinants of the degree of resistance to some anti-estrogens. Differential gene expression analysis demonstrates up-regulation of estrogen-responsive genes, as expected, but also reveals that enrichment for interferon-regulated gene expression is a common feature of all mutations. Finally, a new gene signature developed from the gene expression profiles in ER mutant cells predicts clinical response in breast cancer patients with ER mutations.

StackPR is a new computational approach for large-scale identification of progesterone receptor antagonists using the stacking strategy

Progesterone receptors (PRs) are implicated in various cancers since their presence/absence can determine clinical outcomes. The overstimulation of progesterone can facilitate oncogenesis and thus, its modulation through PR inhibition is urgently needed. To address this issue, a novel stacked ensemble learning approach (termed StackPR) is presented for fast, accurate, and large-scale identification of PR antagonists using only SMILES notation without the need for 3D structural information. We employed six popular machine learning (ML) algorithms (i.e., logistic regression, partial least squares, k-nearest neighbor, support vector machine, extremely randomized trees, and random forest) coupled with twelve conventional molecular descriptors to create 72 baseline models. Then, a genetic algorithm in conjunction with the self-assessment-report approach was utilized to determine m out of the 72 baseline models as means of developing the final meta-predictor using the stacking strategy and tenfold cross-validation test. Experimental results on the independent test dataset show that StackPR achieved impressive predictive performance with an accuracy of 0.966 and Matthew’s coefficient correlation of 0.925. In addition, analysis based on the SHapley Additive exPlanation algorithm and molecular docking indicates that aliphatic hydrocarbons and nitrogen-containing substructures were the most important features for having PR antagonist activity. Finally, we implemented an online webserver using StackPR, which is freely accessible at http://pmlabstack.pythonanywhere.com/StackPR. StackPR is anticipated to be a powerful computational tool for the large-scale identification of unknown PR antagonist candidates for follow-up experimental validation.

Giredestrant reverses progesterone hypersensitivity driven by estrogen receptor mutations in breast cancer

ESR1 (estrogen receptor 1) hotspot mutations are major contributors to therapeutic resistance in estrogen receptor-positive (ER⁺) breast cancer. Such mutations confer estrogen independence to ERα, providing a selective advantage in the presence of estrogen-depleting aromatase inhibitors. In addition, ESR1 mutations reduce the potency of tamoxifen and fulvestrant, therapies that bind ERα directly. These limitations, together with additional liabilities, inspired the development of the next generation of ERα-targeted therapeutics, of which giredestrant is a high-potential candidate. Here, we generated Esr1 mutant-expressing mammary gland models and leveraged patient-derived xenografts (PDXs) to investigate the biological properties of the ESR1 mutations and their sensitivity to giredestrant in vivo. In the mouse mammary gland, Esr1 mutations promote hypersensitivity to progesterone, triggering pregnancy-like tissue remodeling and profoundly elevated proliferation. These effects were driven by an altered progesterone transcriptional response and underpinned by gained sites of ERα-PR (progesterone receptor) cobinding at the promoter regions of pro-proliferation genes. PDX experiments showed that the mutant ERα-PR proliferative program is also relevant in human cancer cells. Giredestrant suppressed the mutant ERα-PR proliferation in the mammary gland more so than the standard-of-care agents, tamoxifen and fulvestrant. Giredestrant was also efficacious against the progesterone-stimulated growth of ESR1 mutant PDX models. In addition, giredestrant demonstrated activity against a molecularly characterized ESR1 mutant tumor from a patient enrolled in a phase 1 clinical trial. Together, these data suggest that mutant ERα can collaborate with PR to drive protumorigenic proliferation but remain sensitive to inhibition by giredestrant.

Upregulation of an estrogen receptor-regulated gene by first generation progestins requires both the progesterone receptor and estrogen receptor alpha

Progestins, synthetic compounds designed to mimic the activity of natural progesterone (P4), are used globally in menopausal hormone therapy. Although the older progestins medroxyprogesterone acetate (MPA) and norethisterone (NET) have been implicated in increased breast cancer risk, little is known regarding newer progestins, and no significant risk has been associated with P4. Considering that breast cancer is the leading cause of mortality in women, establishing which progestins increase breast cancer incidence and elucidating the underlying mechanisms is a global priority. We showed for the first time that the newer-generation progestin drospirenone (DRSP) is the least potent progestin in terms of proliferation of the estrogen-responsive MCF-7 BUS breast cancer cell line, while NET and P4 have similar potencies to estradiol (E2), the known driver of breast cancer cell proliferation. Notably, MPA, the progestin most frequently associated with increased breast cancer risk, was significantly more potent than E2. While all the progestogens enhanced the anchorage-independent growth of the MCF-7 BUS cell line, MPA promoted a greater number of colonies than P4, NET or DRSP. None of the progestogens inhibited E2-induced proliferation and anchorage-independent growth. We also showed that under non-estrogenic conditions, MPA and NET, unlike P4 and DRSP, increased the expression of the estrogen receptor (ER) target gene, cathepsin D, via a mechanism requiring the co-recruitment of ERα and the progesterone receptor (PR) to the promoter region. In contrast, all progestogens promoted the association of the PR and ERα on the promoter of the PR target gene, MYC, thereby increasing its expression under non-estrogenic and estrogenic conditions. These results suggest that progestins differentially regulate the way the PR and ER converge to modulate the expression of PR and ER-regulated genes. Our novel findings indicating similarities and differences between P4 and the progestins, emphasize the importance of comparatively investigating effects of individual progestins rather than grouping them as a class. Further studies are required to underpin the clinical relevance of PR/ERα crosstalk in response to different progestins in both normal and malignant breast tissue, to either confirm or refute their suitability in combination therapy for ER-positive breast cancer.

Prediction of lymph node metastasis in patients with breast invasive micropapillary carcinoma based on machine learning and SHapley Additive exPlanations framework

Abstract

Background and purpose: Machine learning (ML) is applied for outcome prediction and treatment support. This study aims to develop different ML models to predict risk of axillary lymph node metastasis (LNM) in breast invasive micropapillary carcinoma (IMPC) and to explore the risk factors of LNM.

Methods

From the Surveillance, Epidemiology, and End Results (SEER) database and the records of our hospital, a total of 1547 patients diagnosed with breast IMPC were incorporated in this study. The ML model is built and the external validation is carried out. SHapley Additive exPlanations (SHAP) framework was applied to explain the optimal model; multivariable analysis was performed with logistic regression (LR); and nomograms were constructed according to the results of LR analysis.

Results

Age and tumor size were correlated with LNM in both cohorts. The luminal subtype is the most common in patients, with the tumor size <=20mm. Compared to other models, Xgboost was the best ML model with the biggest AUC of 0.813 (95% CI: 0.7994 - 0.8262) and the smallest Brier score of 0.186 (95% CI: 0.799-0.826). SHAP plots demonstrated that tumor size was the most vital risk factor for LNM. In both training and test sets, Xgboost had better AUC (0.761 vs 0.745; 0.813 vs 0.775; respectively), and it also achieved a smaller Brier score (0.202 vs 0.204; 0.186 vs 0.191; 0.220 vs 0.221; respectively) than the nomogram model based on LR in those three different sets. After adjusting for five most influential variables (tumor size, age, ER, HER-2, and PR), prediction score based on the Xgboost model was still correlated with LNM (adjusted OR:2.73, 95% CI: 1.30-5.71, P=0.008).

Conclusions

The Xgboost model outperforms the traditional LR-based nomogram model in predicting the LNM of IMPC patients. Combined with SHAP, it can more intuitively reflect the influence of different variables on the LNM. The tumor size was the most important risk factor of LNM for breast IMPC patients. The prediction score obtained by the Xgboost model could be a good indicator for LNM.

Ectopic JAK–STAT activation enables the transition to a stem-like and multilineage state conferring AR-targeted therapy resistance

Emerging evidence indicates that various cancers can gain resistance to targeted therapies by acquiring lineage plasticity. Although various genomic and transcriptomic aberrations correlate with lineage plasticity, the molecular mechanisms enabling the acquisition of lineage plasticity have not been fully elucidated. We reveal that Janus kinase (JAK)–signal transducer and activator of transcription (STAT) signaling is a crucial executor in promoting lineage plasticity-driven androgen receptor (AR)-targeted therapy resistance in prostate cancer. Importantly, ectopic JAK–STAT activation is specifically required for the resistance of stem-like subclones expressing multilineage transcriptional programs but not subclones exclusively expressing the neuroendocrine-like lineage program. Both genetic and pharmaceutical inhibition of JAK–STAT signaling resensitizes resistant tumors to AR-targeted therapy. Together, these results suggest that JAK–STAT are compelling therapeutic targets for overcoming lineage plasticity-driven AR-targeted therapy resistance.

High Levels of Progesterone Receptor B in MCF-7 Cells Enable Radical Anti-Tumoral and Anti-Estrogenic Effect of Progestin

The widely reported conflicting effects of progestin on breast cancer suggest that the progesterone receptor (PR) has dual functions depending on the cellular context. Cell models that enable PR to fully express anti-tumoral properties are valuable for the understanding of molecular determinant(s) of the anti-tumoral property. This study evaluated whether the expression of high levels of PR in MCF-7 cells enabled a strong anti-tumoral response to progestin. MCF-7 cells were engineered to overexpress PRB by stable transfection. A single dose of Promegestone (R5020) induced an irreversible cell growth arrest and senescence-associated secretory phenotype in MCF-7 cells with PRB overexpression (MCF-7PRB cells) but had no effect on MCF-7 cells with PRA overexpression. The growth-arresting effect was associated with downregulations of cyclin A2 and B1, CDK2, and CDK4 despite an initial upregulation of cyclin A2 and B1. R5020 also induced an evident activation of Nuclear Factor κB (NF-κB) and upregulation of interleukins IL-1α, IL-1β, and IL-8. Although R5020 caused a significant increase of CD24+CD44+ cell population, R5020-treated MCF-7PRB cells were unable to form tumorspheres and underwent massive apoptosis, which is paradoxically associated with marked downregulations of the pro-apoptotic proteins BID, BAX, PARP, and Caspases 7 and 8, as well as diminution of anti-apoptotic protein BCL-2. Importantly, R5020-activated PRB abolished the effect of estrogen. This intense anti-estrogenic effect was mediated by marked downregulation of ERα and pioneer factor FOXA1, leading to diminished chromatin-associated ERα and FOXA1 and estrogen-induced target gene expression. In conclusion, high levels of agonist-activated PRB in breast cancer cells can be strongly anti-tumoral and anti-estrogenic despite the initial unproductive cell cycle acceleration. Repression of ERα and FOXA1 expression is a major mechanism for the strong anti-estrogenic effect.

Novel Signatures Based on the Lymphocyte-to-C-Reactive Protein Ratio Predict the Prognosis of Patients with Early Breast Cancer: A Retrospective Study

Background

The value of the lymphocyte-to-C-reactive protein (CRP) ratio (LCR) in early breast cancer (BC) is unclear. We explored the correlation between the LCR and survival of patients with early BC and established effective LCR-based prognostic signatures for predicting prognosis.

Methods

In this retrospective study, we randomized 623 patients with early-stage BC diagnosed in December 2010 to October 2012 at the Sun Yat-sen University Cancer Center to training and verification datasets. The median follow-up of all patients was 109 months. The survival differences were calculated by Kaplan–Meier method using the Log rank test. For overall survival (OS) and disease-free survival (DFS), the independent factors in the training dataset were identified using univariate and multivariate Cox analyses, in which two-tailed P-values < 0.05 were considered statistically significant. Based on this, we respectively constructed novel signatures for survival prediction and validated the efficiency of signatures through the concordance index (C-index), calibration and receiver operating characteristic (ROC) curves in both datasets.

Results

The LCR, lymphatic vessel invasion (LVI), progesterone receptor (PR) status, and Ki67 index were independent prognostic factors of OS. And the LCR and LVI are associated to DFS too. High LCR was associated with better OS and DFS. We constructed the prediction signatures based on those independent prognostic factors and calculated the risk scores. Patients in the training dataset with higher risk scores had significantly worse prognosis (P < 0.001). The signature had excellent discrimination capacity, with an OS C-index of 0.785 [95% confidence interval (CI): 0.713–0.857] and 0.750 (95% CI: 0.669–0.832) in the training and verification datasets, respectively. The time–ROC curves also suggest accurate prediction by the signature.

Conclusion

The LCR was a significant prognostic predictor of OS and DFS in early BC. The LCR-based prognostic signatures could be a useful tool for individualized therapeutic guidance.

Membrane-Initiated Estrogen, Androgen, and Progesterone Receptor Signaling in Health and Disease

Rapid effects of steroid hormones were discovered in the early 1950s, but the subject was dominated in the 1970s by discoveries of estradiol and progesterone stimulating protein synthesis. This led to the paradigm that steroid hormones regulate growth, differentiation, and metabolism via binding a receptor in the nucleus. It took 30 years to appreciate not only that some cellular functions arise solely from membrane-localized steroid receptor (SR) actions, but that rapid sex steroid signaling from membrane-localized SRs is a prerequisite for the phosphorylation, nuclear import, and potentiation of the transcriptional activity of nuclear SR counterparts. Here, we provide a review and update on the current state of knowledge of membrane-initiated estrogen (ER), androgen (AR) and progesterone (PR) receptor signaling, the mechanisms of membrane-associated SR potentiation of their nuclear SR homologues, and the importance of this membrane-nuclear SR collaboration in physiology and disease. We also highlight potential clinical implications of pathway-selective modulation of membrane-associated SR.

Sex-biased adaptive immune regulation in cancer development and therapy

The cancer research field is finally starting to unravel the mystery behind why males have a higher incidence and mortality rate than females for nearly all cancer types of the non-reproductive systems. Here, we explain how sex - specifically sex chromosomes and sex hormones - drives differential adaptive immunity across immune-related disease states including cancer, and why males are consequently more predisposed to tumor development. We highlight emerging data on the roles of cell-intrinsic androgen receptors in driving CD8⁺ T cell dysfunction or exhaustion in the tumor microenvironment and summarize ongoing clinical efforts to determine the impact of androgen blockade on cancer immunotherapy. Finally, we outline a framework for future research in cancer biology and immuno-oncology, underscoring the importance of a holistic research approach to understanding the mechanisms of sex dimorphisms in cancer, so sex will be considered as an imperative factor for guiding treatment decisions in the future.

Targeting LIPA independent of its lipase activity is a therapeutic strategy in solid tumors via induction of endoplasmic reticulum stress

Triple-negative breast cancer (TNBC) has a poor clinical outcome, due to a lack of actionable therapeutic targets. Herein we define lysosomal acid lipase A (LIPA) as a viable molecular target in TNBC and identify a stereospecific small molecule (ERX-41) that binds LIPA. ERX-41 induces endoplasmic reticulum (ER) stress resulting in cell death, and this effect is on target as evidenced by specific LIPA mutations providing resistance. Importantly, we demonstrate that ERX-41 activity is independent of LIPA lipase function but dependent on its ER localization. Mechanistically, ERX-41 binding of LIPA decreases expression of multiple ER-resident proteins involved in protein folding. This targeted vulnerability has a large therapeutic window, with no adverse effects either on normal mammary epithelial cells or in mice. Our study implicates a targeted strategy for solid tumors, including breast, brain, pancreatic and ovarian, whereby small, orally bioavailable molecules targeting LIPA block protein folding, induce ER stress and result in tumor cell death.

FGF7/FGFR2-JunB signalling counteracts the effect of progesterone in luminal breast cancer

We have recently demonstrated that fibroblast growth factor receptor 2 (FGFR2)‐mediated signalling alters progesterone receptor (PR) activity and response of oestrogen receptor α (ER)‐positive (ER+) breast cancer (BCa) cell lines to anti‐ER agents. Little is known about whether the crosstalk between ER and PR, shown to be modulated by the hormonal background, might also be affected by FGFR2. Here, PR‐dependent behaviour of ER+ BCa cells was studied in the presence of oestrogen (E2) and progesterone (P4) and/or FGF7. In vitro analyses showed that FGF7/FGFR2 signalling: (a) abolished the effect of P4 on E2‐promoted 3D cell growth and response to tamoxifen; (b) regulated ER and PR expression and activity; (c) increased formation of ER–PR complexes; and (d) reversed P4‐triggered deregulation of ER‐dependent genes. Analysis of clinical data demonstrated that the prognostic value of FGFR2 varied between patients with different menopausal status; that is, high expression of FGFR2 was significantly associated with longer progression‐free survival (PFS) in postmenopausal patients, whereas there was no significant association in premenopausal patients. FGFR2 was found to positively correlate with the expression of JunB proto‐oncogene, AP‐1 transcription factor subunit (JUNB), an ER‐dependent gene, only in premenopausal patients. Molecular analyses revealed that the presence of JunB was a prerequisite for FGFR2‐mediated abrogation of P4‐induced inhibition of cell growth. Our results demonstrate for the first time that the FGF7/FGFR2–JunB axis abolishes the modulatory effects of PR on ER‐associated biological functions in premenopausal ER+ BCa. This may provide foundations for a better selection of patients for FGFR‐targeting therapeutic strategies.

Epigenetic Mechanisms Influencing Therapeutic Response in Breast Cancer

The majority of breast cancers are estrogen receptor (ER)+ and agents targeting the ER signaling pathway have markedly increased survival for women with breast cancer for decades. However, therapeutic resistance eventually emerges, especially in the metastatic setting. In the past decade disrupted epigenetic regulatory processes have emerged as major contributors to carcinogenesis in many cancer types. Aberrations in chromatin modifiers and transcription factors have also been recognized as mediators of breast cancer development and therapeutic outcome, and new epigenetic-based therapies in combination with targeted therapies have been proposed. Here we will discuss recent progress in our understanding of the chromatin-based mechanisms of breast tumorigenesis, how these mechanisms affect therapeutic response to standard of care treatment, and discuss new strategies towards therapeutic intervention to overcome resistance.

Estrogen receptor positive breast cancers have patient specific hormone sensitivities and rely on progesterone receptor

Estrogen and progesterone receptor (ER, PR) signaling control breast development and impinge on breast carcinogenesis. ER is an established driver of ER + disease but the role of the PR, itself an ER target gene, is debated. We assess the issue in clinically relevant settings by a genetic approach and inject ER + breast cancer cell lines and patient-derived tumor cells to the milk ducts of immunocompromised mice. Such ER + xenografts were exposed to physiologically relevant levels of 17-β-estradiol (E2) and progesterone (P4). We find that independently both premenopausal E2 and P4 levels increase tumor growth and combined treatment enhances metastatic spread. The proliferative responses are patient-specific with MYC and androgen receptor (AR) signatures determining P4 response. PR is required for tumor growth in patient samples and sufficient to drive tumor growth and metastasis in ER signaling ablated tumor cells. Our findings suggest that endocrine therapy may need to be personalized, and that abrogating PR expression can be a therapeutic option.

Germline and somatic genetic variability of oxysterol-related genes in breast cancer patients with early disease of the luminal subtype

Oxysterols, oxidized derivatives of cholesterol, have been implicated in multiple pathologies, including cancer. In breast cancer, the link is especially strong due to interactions between oxysterols and estrogen receptor activity. Here, we provide the first dedicated study of 113 oxysterol-related genes in breast cancer patients of the luminal subtype, in terms of both their somatic and germline variability, using targeted high-throughput DNA sequencing of 100 normal-tumor pairs with very high coverage. In the full cohort, or subsets of patients stratified by therapy, we found 12 germline variants in ABCA1, ABCA8, ABCC1, GPR183, LDLR, MBTPS1, NR1I2, OSBPL2, OSBPL3, and OSBPL5 to associate with poor survival of patients and variants in ABCA8, ABCG2, and HSD3B7 (three in total) associated with better survival. However, no associations remained significant after correction for multiple tests. Analysis of somatic variants revealed significantly (after FDR correction) poorer survival in patients mutated in CYP46A1 and 9 interacting (according to STRING analysis) genes, as well as in OSBPL3 and a set of 20 genes that collectively associated with the progesterone receptor status of patients. We propose further exploration of these genes in an integrative manner together with gene expression and epigenomic data.

Polarity protein SCRIB interacts with SLC3A2 to regulate proliferation and tamoxifen resistance in ER+ breast cancer

Estrogen receptor (ER) positive breast cancer represents 75% of all breast cancers in women. Although patients with ER+ cancers receive endocrine therapies, more than 30% develop resistance and succumb to the disease, highlighting the need to understand endocrine resistance. Here we show an unexpected role for the cell polarity protein SCRIB as a tumor-promoter and a regulator of endocrine resistance in ER-positive breast cancer cells. SCRIB expression is induced by estrogen signaling in a MYC-dependent manner. SCRIB interacts with SLC3A2, a heteromeric component of leucine amino acid transporter SLC7A5. SLC3A2 binds to the N-terminus of SCRIB to facilitate the formation of SCRIB/SLC3A2/LLGL2/SLC7A5 quaternary complex required for membrane localization of the amino acid transporter complex. Both SCRIB and SLC3A2 are required for cell proliferation and tamoxifen resistance in ER+ cells identifying a new role for the SCRIB/SLC3A2 complex in ER+ breast cancer.

The Divergent Effects of Ovarian Steroid Hormones in the MCF-7 Model for Luminal A Breast Cancer: Mechanistic Leads for Therapy

The growth modulating effects of the ovarian steroid hormones 17β-estradiol (E₂) and progesterone (PRG) on endocrine-responsive target tissues are well established. In hormone-receptor-positive breast cancer, E₂ functions as a potent growth promoter, while the function of PRG is less defined. In the hormone-receptor-positive Luminal A and Luminal B molecular subtypes of clinical breast cancer, conventional endocrine therapy predominantly targets estrogen receptor function and estrogen biosynthesis and/or growth factor receptors. These therapeutic options are associated with systemic toxicity, acquired tumor resistance, and the emergence of drug-resistant cancer stem cells, facilitating the progression of therapy-resistant disease. The limitations of targeted endocrine therapy emphasize the identification of nontoxic testable alternatives. In the human breast, carcinoma-derived hormone-receptor-positive MCF-7 model treatment with E₂ within the physiological concentration range of 1 nM to 20 nM induces progressive growth, upregulated cell cycle progression, and downregulated cellular apoptosis. In contrast, treatment with PRG at the equimolar concentration range exhibits dose-dependent growth inhibition, downregulated cell-cycle progression, and upregulated cellular apoptosis. Nontoxic nutritional herbs at their respective maximum cytostatic concentrations (IC₉₀) effectively increase the E₂ metabolite ratio in favor of the anti-proliferative metabolite. The long-term exposure to the selective estrogen-receptor modulator tamoxifen selects a drug-resistant phenotype, exhibiting increased expressions of stem cell markers. The present review discusses the published evidence relevant to hormone metabolism, growth modulation by hormone metabolites, drug-resistant stem cells, and growth-inhibitory efficacy of nutritional herbs. Collectively, this evidence provides proof of the concept for future research directions that are focused on novel therapeutic options for endocrine therapy-resistant breast cancer that may operate via E₂- and/or PRG-mediated growth regulation.

Pyrotinib-Containing Neoadjuvant Therapy in Patients With HER2-Positive Breast Cancer: A Multicenter Retrospective Analysis

Background

Pyrotinib, a small-molecule tyrosine kinase inhibitor, has been investigated as a component of neoadjuvant therapy in phase 2 trials of human epidermal growth factor receptor 2 (HER2)-positive breast cancer. This study aimed to evaluate the effectiveness and safety of pyrotinib-containing neoadjuvant therapy for patients with HER2-positive early or locally advanced breast cancer in the real-world setting.

Methods

Data of 97 patients with HER2-positive breast cancer from 21 centers across China treated with pyrotinib-containing neoadjuvant therapy were reviewed. Neoadjuvant therapy consisted of taxane/carboplatin/trastuzumab plus pyrotinib (TCbH+Py, 30 [30.9%]), anthracycline/cyclophosphamide followed by taxane/trastuzumab plus pyrotinib (AC-TH+Py) or taxane followed by anthracycline/cyclophosphamide/trastuzumab plus pyrotinib (T-ACH+Py, 29 [29.9%]), taxane/trastuzumab plus pyrotinib (TH+Py, 23 [23.7%]), and other pyrotinib-containing neoadjuvant treatment (15 [15.5%]). The primary outcome was breast pathological complete response (bpCR, ypT0/is) rate. Secondary outcomes included total pathological complete response (tpCR, ypT0/is ypN0) rate, objective response rate (ORR), and the incidence of preoperative adverse events.

Results

The ORR of pyrotinib-containing neoadjuvant therapy was 87.6% (85/97). The bpCR and tpCR rates were 54.6% (95% confidence interval [CI], 44.2%-64.7%) and 48.5% [95% CI, 38.2%-58.8%], respectively. The most common grade 3 or 4 treatment-related adverse events included diarrhea (15 [15.5%]), decreased hemoglobin (nine [9.3%]), and decreased neutrophil count (eight [8.2%]). No treatment-related deaths occurred.

Conclusion

Pyrotinib-containing neoadjuvant therapy for patients with HER2-positive early or locally advanced breast cancer shows favorable effectiveness with manageable toxicity in the real-world setting. Trastuzumab plus pyrotinib may be a novel option of dual HER2-targeted blockade.

Ligand-mediated nanomedicines against breast cancer: a review

Ligand-mediated targeting represents the cutting edge in precision-guided therapy for several diseases. Surface engineering of nanomedicines with ligands exhibiting selective or tailored affinity for overexpressed biomolecules of a specific disease may increase therapeutic efficiency and reduce side effects and recurrence. This review focuses on newly developed approaches and strategies to improve treatment and overcome the mechanisms associated with breast cancer resistance.

ESR1 mutant breast cancers show elevated basal cytokeratins and immune activation

Estrogen receptor alpha (ER/ESR1) is frequently mutated in endocrine resistant ER-positive (ER+) breast cancer and linked to ligand-independent growth and metastasis. Despite the distinct clinical features of ESR1 mutations, their role in intrinsic subtype switching remains largely unknown. Here we find that ESR1 mutant cells and clinical samples show a significant enrichment of basal subtype markers, and six basal cytokeratins (BCKs) are the most enriched genes. Induction of BCKs is independent of ER binding and instead associated with chromatin reprogramming centered around a progesterone receptor-orchestrated insulated neighborhood. BCK-high ER+ primary breast tumors exhibit a number of enriched immune pathways, shared with ESR1 mutant tumors. S100A8 and S100A9 are among the most induced immune mediators and involve in tumor-stroma paracrine crosstalk inferred by single-cell RNA-seq from metastatic tumors. Collectively, these observations demonstrate that ESR1 mutant tumors gain basal features associated with increased immune activation, encouraging additional studies of immune therapeutic vulnerabilities.

Therapeutic Strategies and Potential Actions of Female Sex Steroid Hormones and Their Receptors in Colon Cancer Based on Preclinical Studies

Several epidemiological studies have reported that the use of female sex steroid hormones could reduce the risk of colon cancer (CRC). This review summarizes the available data related to estradiol (E2) and progesterone (P4) single and dual treatments in CRC male and female in vitro and in vivo models, mainly from preclinical studies, alongside their potential molecular mechanisms. Most of the studies showed that E2 exogenous treatment and/or reactivation of its beta receptor (ERβ) significantly inhibited cell proliferation, induced cell cycle arrest, and promoted apoptosis by modulating several molecular pathways. Likewise, the inhibition of ERα receptors produced similar antitumorigenic actions, both in vivo and in vitro, suggesting that E2 could have dual opposing roles in CRC that are dependent on the expression profile of its nuclear receptors. The available studies on P4 are scarce, and the results revealed that in vitro and in vivo treatments with natural and synthetic progesterone were also associated with promising tumoricidal actions. Nevertheless, the combination of E2 with P4 showed enhanced anticancer activities compared with their monotherapy protocols in male–female cell lines and animals. Collectively, the studies suggested that the female sex steroid hormones could provide a novel and effective therapeutic strategy against CRC.

Prognostic Relevance of Progesterone Receptor Levels in Early Luminal-Like HER2 Negative Breast Cancer Subtypes: A Retrospective Analysis

Introduction

In luminal-like early breast cancer (BC), the lack of Progesterone Receptor (PR) expression generally correlates with more aggressive behavior but the clinical validity of low PR levels remains a debated issue.

Methods

The main aim of this retrospective analysis was to assess the survival outcome (Breast cancer specific survival, BCSS) in a cohort of 687 luminal-like HER2 negative early BC patients treated at our Institutions from January 2000 to December 2018, using a sub-classification of tumors in subgroup 1 (PR high/Ki67 low), subgroup 2 (PR high/Ki67 high), subgroup 3 (PR low/Ki67 low), subgroup 4 (PR low/Ki67 high) according to PR and Ki67 values.

Results

At a median follow-up of 7 years, BCSS rates were 96.3%, 89%, 86.8% and 85% in the subgroup 1, 2, 3, 4 respectively. Overall, a statistically significant difference in BCSS rates was observed among the 4 subgroups (p=0.0036). On univariate analysis, post-menopause, older age (≥ 50 years), low PR and high Ki67 expression, poorly differentiated grade and size ≥ 2 cm as well as luminal B-like tumors (subgroups 2, 3, 4) were significantly associated with a worse BCSS. Multivariate analysis identified grade, size and subgroup classification of BC as independent prognostic markers of poorer outcome. In particular, subgroups 4, 3 and 2 displayed a significantly higher risk of BC-related death (HR=4.11; p=0.008; HR=3.43; p=0-007; HR=2.57; p=0.020, respectively) when compared to subgroup 1.

Conclusions

Our results support the usefulness of PR and Ki67 levels as prognostic markers, corroborating their crucial role in the decision-making process of patients with luminal-like HER2 negative early BC. Clinical application of these parameters should be assessed prospectively.

Supervised Graph Clustering for Cancer Subtyping Based on Survival Analysis and Integration of Multi-Omic Tumor Data

Identifying cancer subtypes by integration of multi-omic data is beneficial to improve the understanding of disease progression, and provides more precise treatment for patients. Cancer subtypes identification is usually accomplished by clustering patients with unsupervised learning approaches. Thus, most existing integrative cancer subtyping methods are performed in an entirely unsupervised way. An integrative cancer subtyping approach can be improved to discover clinically more relevant cancer subtypes when considering the clinical survival response variables. In this study, we propose a Survival Supervised Graph Clustering (S2GC)for cancer subtyping by taking into consideration survival information. Specifically, we use a graph to represent similarity of patients, and develop a multi-omic survival analysis embedding with patient-to-patient similarity graph learning for cancer subtype identification. The multi-view (omic)survival analysis model and graph of patients are jointly learned in a unified way. The learned optimal graph can be unitized to cluster cancer subtypes directly. In the proposed model, the survival analysis model and adaptive graph learning could positively reinforce each other. Consequently, the survival time can be considered as supervised information to improve the quality of the similarity graph and explore clinically more relevant subgroups of patients. Experiments on several representative multi-omic cancer datasets demonstrate that the proposed method achieves better results than a number of state-of-the-art methods. The results also suggest that our method is able to identify biologically meaningful subgroups for different cancer types. (Our Matlab source code is available online at github: https://github.com/CLiu272/S2GC).