Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies

Suppressing Wnt signaling of the blood‒tumor barrier to intensify drug delivery and inhibit lipogenesis of brain metastases

Lipogenesis is often highly upregulated in breast cancer brain metastases to adapt to intracranial low lipid microenvironments. Lipase inhibitors hold therapeutic potential but their intra-tumoral distribution is often blocked by the blood‒tumor barrier (BTB). BTB activates its Wnt signaling to maintain barrier properties, e.g., Mfsd2a-mediated BTB low transcytosis. Here, we reported VCAM-1-targeting nano-wogonin (W@V-NPs) as an adjuvant of nano-orlistat (O@V-NPs) to intensify drug delivery and inhibit lipogenesis of brain metastases. W@V-NPs were proven to be able to inactivate BTB Wnt signaling, downregulate BTB Mfsd2a, accelerate BTB vesicular transport, and enhance tumor accumulation of O@V-NPs. With the ability to specifically kill cancer cells in a lipid-deprived environment with IC50 at 48 ng/mL, W@V-NPs plus O@V-NPs inhibited the progression of brain metastases with prolonged survival of model mice. The combination did not induce brain edema, cognitive impairment, and systemic toxicity in healthy mice. Targeting Wnt signaling could safely modulate the BTB to improve drug delivery and metabolic therapy against brain metastases.

Patient Characteristics Associated with Growth of Patient-Derived Tumor Implants in Mice (Patient-Derived Xenografts)

Background: patient-derived xenografts (PDXs) have defined the field of translational cancer research in recent years, becoming one of the most-used tools in early drug development. The process of establishing cancer models in mice has turned out to be challenging, since little research focuses on evaluating which factors impact engraftment success. We sought to determine the clinical, pathological, or molecular factors which may predict better engraftment rates in PDXs. Methods: between March 2017 and January 2021, tumor samples obtained from patients with primary or metastatic cancer were implanted into athymic nude mice. A full comprehensive evaluation of baseline factors associated with the patients and patients' tumors was performed, with the goal of potentially identifying predictive markers of engraftment. We focused on clinical (patient factors) pathological (patients' tumor samples) and molecular (patients' tumor samples) characteristics, analyzed either by immunohistochemistry (IHC) or next-generation sequencing (NGS), which were associated with the likelihood of final engraftment, as well as with tumor growth rates in xenografts. Results: a total of 585 tumor samples were collected and implanted. Twenty-one failed to engraft, due to lack of malignant cells. Of 564 tumor-positive samples, 187 (33.2%) grew at time of analysis. The study was able to find correlation and predictive value for engraftment for the following: the use of systemic antibiotics by the patient within 2 weeks of sampling (38.1% (72/189) antibiotics- group vs. 30.7% (115/375) no-antibiotics) (p = 0.048), and the administration of systemic steroids to the patients within 2 weeks of sampling (41.5% (34/48) steroids vs. 31.7% (153/329), no-steroids) (p = 0.049). Regarding patient's baseline tests, we found certain markers could help predict final engraftment success: for lactate dehydrogenase (LDH) levels, 34.1% (140/411) of tumors derived from patients with baseline blood LDH levels above the upper limit of normality (ULN) achieved growth, against 30.7% (47/153) with normal LDH (p = 0.047). Histological tumor characteristics, such as grade of differentiation, were also correlated. Grade 1: 25.4% (47/187), grade 2: 34.8% (65/187) and grade 3: 40.1% (75/187) tumors achieved successful growth (p = 0.043), suggesting the higher the grade, the higher the likelihood of success. Similarly, higher ki67 levels were also correlated with better engraftment rates: low (Ki67 < 15%): 8.9% (9/45) achieved growth vs. high (Ki67 ≥ 15%): 31% (35/113) (p: 0.002). Other markers of aggressiveness such as the presence of lymphovascular invasion in tumor sample of origin was also predictive: 42.2% (97/230) with lymphovascular vs. 26.9% (90/334) of samples with no invasion (p = 0.0001). From the molecular standpoint, mismatch-repair-deficient (MMRd) tumors showed better engraftment rates: 62.1% (18/29) achieved growth vs. 40.8% (75/184) of proficient tumors (p = 0.026). A total of 84 PDX were breast models, among which 57.9% (11/19) ER-negative models grew, vs. 15.4% (10/65) of ER-positive models (p = 0.0001), also consonant with ER-negative tumors being more aggressive. BRAFmut cancers are more likely to achieve engraftment during the development of PDX models. Lastly, tumor growth rates during first passages can help establish a cutoff point for the decision-making process during PDX development, since the higher the tumor grades, the higher the likelihood of success. Conclusions: tumors with higher grade and Ki67 protein expression, lymphovascular and/or perineural invasion, with dMMR and are negative for ER expression have a higher probability of achieving growth in the process of PDX development. The use of steroids and/or antibiotics in the patient prior to sampling can also impact the likelihood of success in PDX development. Lastly, establishing a cutoff point for tumor growth rates could guide the decision-making process during PDX development.

Breast cancer brain metastasis: from etiology to state-of-the-art modeling

Currently, breast carcinoma is the most common form of malignancy and the main cause of cancer mortality in women worldwide. The metastasis of cancer cells from the primary tumor site to other organs in the body, notably the lungs, bones, brain, and liver, is what causes breast cancer to ultimately be fatal. Brain metastases occur in as many as 30% of patients with advanced breast cancer, and the 1-year survival rate of these patients is around 20%. Many researchers have focused on brain metastasis, but due to its complexities, many aspects of this process are still relatively unclear. To develop and test novel therapies for this fatal condition, pre-clinical models are required that can mimic the biological processes involved in breast cancer brain metastasis (BCBM). The application of many breakthroughs in the area of tissue engineering has resulted in the development of scaffold or matrix-based culture methods that more accurately imitate the original extracellular matrix (ECM) of metastatic tumors. Furthermore, specific cell lines are now being used to create three-dimensional (3D) cultures that can be used to model metastasis. These 3D cultures satisfy the requirement for in vitro methodologies that allow for a more accurate investigation of the molecular pathways as well as a more in-depth examination of the effects of the medication being tested. In this review, we talk about the latest advances in modeling BCBM using cell lines, animals, and tissue engineering methods.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

Conjugated Bile Acids Accelerate Progression of Pancreatic Cancer Metastasis via S1PR2 Signaling in Cholestasis

BACKGROUND

Pancreatic cancer (PC) has an extremely high mortality rate, where obstructive jaundice due to cholestasis is a classic symptom. Conjugated bile acids (CBAs) such as taurocholic acid (TCA) have been reported to activate both the ERK1/2 and AKT signaling pathways via S1P receptor 2 (S1PR2) and promote growth of cholangiocarcinoma. Thus, we hypothesize that CBAs, which accumulate in cholestasis, accelerate PC progression via S1PR2.

METHODS

Murine Panc02-luc and human AsPC-1, MIA PaCa2, and BxPC-3 cells were treated with TCA, S1PR2 agonist CYM5520, S1PR2 antagonist JTE-013, sphingosine-1-phosphate (S1P), and functional S1P receptor antagonist (except S1PR2) FTY720. Bile duct ligation (BDL) was performed on liver implantation or intraperitoneal injection of Panc02-luc cells.

RESULTS

Panc02-luc and AsPC-1 cells predominantly expressed S1PR2, and their growth and migration were stimulated by TCA or CYM5520 in dose-dependent manner, which was blocked by JTE-013. This finding was not seen in PC cell lines expressing other S1P receptors than S1PR2. Panc02-luc growth stimulation by S1P was not blocked by FTY720. BDL significantly increased PC liver metastasis compared with sham. PC peritoneal carcinomatosis was significantly worsened by BDL, confirmed by number of nodules, tumor weight, bioluminescence, Ki-67 stain, ascites, and worse survival compared with sham. CYM5520 significantly worsened PC carcinomatosis, whereas treatment with anti-S1P antibody or FTY720 also worsened progression.

CONCLUSIONS

CBAs accelerated growth of S1PR2 predominant PC both in vitro and in vivo. This finding implicates S1PR2 as a potential therapeutic target in metastatic S1PR2 predominant pancreatic cancer.

Does Primary Tumor Resection Induce Accelerated Metastasis in Breast Cancer? A Review

INTRODUCTION

Over a century of cumulative experimental results and clinical data have suggested that surgical procedures of primary tumors promote tumor progression and metastasis in breast cancer and other cancer patients, suggesting a potential interplay linking primary tumors and distant lesions that lead to metastasis development triggered by primary tumor removal. Such evidence may generate a departure in terms of our attitude toward the surgery. However, the reliability and prognostic benefits of tumor surgery, especially for chemotherapy-resistant patients, are indisputable. Thus, it is important to explore the mechanism underlying this surgery-induced cancer progression to guide individual clinical treatment and improve tumor control.

MATERIALS AND METHODS

We conducted a comprehensive review in PubMed in October 2021 to determine the article outline. Non-English and repetitive articles were excluded. The year, topic, key findings, and opinions of each article were gathered.

RESULTS

This review not only comprehensively summarizes the potential mechanisms of primary tumors interacting with the growth of metastases but also discusses whether and how surgical resection of primary lesions can trigger tumor metastasis and development. At the same time, this article also provides our understanding of clinical findings and future directions on this topic. In addition, the combination of surgery and some potentially beneficial therapeutic interventions for postoperative tumor metastasis control was also mentioned.

CONCLUSIONS

There are viewpoints supporting an acceleration of metastasis after surgery for breast cancer and fundamental research on relevant therapies, although controversial. Further attention should be focused on the gap between current preclinical data and the complicated clinical therapeutic combination during surgery in metastatic breast cancer patients.

SKOR1 mediates FER kinase-dependent invasive growth of breast cancer cells

High expression of the non-receptor tyrosine kinase FER is an independent prognostic factor that correlates with poor survival in breast cancer patients. To investigate whether the kinase activity of FER is essential for its oncogenic properties, we developed an ATP analogue-sensitive knock-in allele (FERASKI). Specific FER kinase inhibition in MDA-MB-231 cells reduces migration and invasion, as well as metastasis when xenografted into a mouse model of breast cancer. Using the FERASKI system, we identified Ski family transcriptional corepressor 1 (SKOR1) as a direct FER kinase substrate. SKOR1 loss phenocopies FER inhibition, leading to impaired proliferation, migration and invasion, and inhibition of breast cancer growth and metastasis formation in mice. We show that SKOR1 Y234, a candidate FER phosphorylation site, is essential for FER-dependent tumor progression. Finally, our work suggests that the SKOR1 Y234 residue promotes Smad2/3 signaling through SKOR1 binding to Smad3. Our study thus identifies SKOR1 as a mediator of FER-dependent progression of high-risk breast cancers.

Development of a novel BRCAness score that predicts response to PARP inhibitors

BACKGROUND

BRCAness is a characteristic feature of homologous recombination deficiency (HRD) mimicking BRCA gene mutation in breast cancer. We hypothesized that a measure to quantify BRCAness that causes synthetic lethality in BRCA mutated tumors will identify responders to PARP inhibitors.

METHODS

A total of 6753 breast cancer patients from 3 large independent cohorts were analyzed. A score was generated by transcriptomic profiling using gene set variation analysis algorithm on 34 BRCA1-mutation related genes selected by high AUC levels in ROC curve between BRCA1 mutation and wildtype breast cancer.

RESULTS

The score was significantly associated with BRCA1 mutation, high mutation load and intratumoral heterogeneity as expected, as well as with high HRD, DNA repair and MKi67 expression regardless of BRCA mutations. High BRCAness tumors enriched not only DNA repair, but also all five Hallmark cell proliferation-related gene sets. High BRCAness tumors were significantly associated with higher cytolytic activity and with higher anti-cancerous immune cell infiltration. Not only did the breast cancer cell lines with BRCA-mutation show high score, but even the other cells in human breast cancer tumor microenvironment were contributing to the score. The BRCAness score was the highest in triple-negative breast cancer consistently in all 3 cohorts. BRCAness was associated with response to chemotherapy and correlated strongly with response to PARP inhibitor in both triple-negative and ER-positive/HER2-negative breast cancer.

CONCLUSIONS

We established a novel BRCAness score using BRCA-mutation-related gene expressions and found that it associates with DNA repair and predicts response to PARP inhibitors regardless of BRCA mutation.

High miR-99b expression is associated with cell proliferation and worse patient outcomes in breast cancer

Although miR-99b is a known suppressive microRNA (miRNA) in several cancers, its role in breast cancer has not been elucidated. In this study, we examined the clinical relevance of miR-99b expression in breast cancer. We analyzed miRNA and mRNA expression and their relationships with clinical parameters in 1,961 breast cancer samples from two independent large cohorts, the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas (TCGA). Several algorithms, including gene set enrichment analysis (GSEA) and xCell, have been used to investigate biological functions and the tumor microenvironment. High miR-99b expression significantly enriched the mTORC1 signaling gene set in breast cancer (NES = 1.63, FDR = 0.03, and NES = 1.58, FDR = 0.10, in METABRIC and TCGA, respectively). No other mechanisms, including the epithelial mesenchymal transition, NFκB, and TGF-β signaling, were consistently enriched in both cohorts. MiR-99b-high breast cancer was associated with high homologous recombination deficiencies, intratumor heterogeneity, and high rates of mutation and neoantigens. In agreement, miR-99b-high breast cancer was associated with increased cell proliferation, correlating with Nottingham histological grade, and significant enrichment of E2F targets, G2/M checkpoint, and mitotic spindle gene sets consistently in both cohorts (P = 0.01, P < 0.001). High miR-99b levels were also associated with low stromal cell fractions in the tumor microenvironment, including adipocytes, keratinocytes, and lymphatic endothelial cells (P < 0.001). However, in both cohorts, miR-99b expression was not associated with significant infiltration of immune cells, except dendritic cells (P = 0.006, 0.020). Finally, in both cohorts, breast cancer with high miR-99b expression was significantly associated with worse disease-free survival (DSS) and overall survival (OS), particularly in estrogen receptor (ER)-positive/human epidermal growth factor (HER)2-negative breast cancer (DSS hazard ratio (HR) 1.29, 95% confidence interval (CI) 1.10-1.51, P < 0.001 in the METABRIC cohort and HR 1.82, 95% CI 1.12-2.98, P = 0.017 in the TCGA cohort). In conclusion, breast cancer with high miR-99b expression was significantly associated with mTORC1 signaling, cell proliferation, and decreased patient survival, particularly in the ER-positive/HER2-negative subtype.

The Patient-Derived Cancer Organoids: Promises and Challenges as Platforms for Cancer Discovery

The cancer burden is rapidly increasing in most countries, and thus, new anticancer drugs for effective cancer therapy must be developed. Cancer model systems that recapitulate the biological processes of human cancers are one of the cores of the drug development process. PDCO has emerged as a unique model that preserves the genetic, physiological, and histologic characteristics of original cancer, including inter- and intratumoral heterogeneities. Due to these advantages, the PCDO model is increasingly investigated for anticancer drug screening and efficacy testing, preclinical patient stratification, and precision medicine for selecting the most effective anticancer therapy for patients. Here, we review the prospects and limitations of PDCO compared to the conventional cancer models. With advances in culture success rates, co-culture systems with the tumor microenvironment, organoid-on-a-chip technology, and automation technology, PDCO will become the most promising model to develop anticancer drugs and precision medicine.

Preclinical Models of Brain Metastases in Breast Cancer

Breast cancer remains a leading cause of mortality among women worldwide. Brain metastases confer extremely poor prognosis due to a lack of understanding of their specific biology, unique physiologic and anatomic features of the brain, and limited treatment strategies. A major roadblock in advancing the treatment of breast cancer brain metastases (BCBM) is the scarcity of representative experimental preclinical models. Current models are predominantly based on the use of animal xenograft models with immortalized breast cancer cell lines that poorly capture the disease’s heterogeneity. Recent years have witnessed the development of patient-derived in vitro and in vivo breast cancer culturing systems that more closely recapitulate the biology from individual patients. These advances led to the development of modern patient-tissue-based experimental models for BCBM. The success of preclinical models is also based on the imaging technologies used to detect metastases. Advances in animal brain imaging, including cellular MRI and multimodality imaging, allow sensitive and specific detection of brain metastases and monitoring treatment responses. These imaging technologies, together with novel translational breast cancer models based on patient-derived cancer tissues, represent a unique opportunity to advance our understanding of brain metastases biology and develop novel treatment approaches. This review discusses the state-of-the-art knowledge in preclinical models of this disease.

Conflicting roles of EGFR expression by subtypes in breast cancer

Epidermal growth factor receptor (EGFR) is one of the receptors that belong to the epidermal growth factor family of receptor tyrosine kinases (ErbBs). Several malignancies including breast cancer that express EGFR have poor prognosis. Our study examined the EGFR expression among 5176 breast cancer patients from GSE96058 and METABRIC cohorts and the contribution of tumor immune microenvironment in different subtypes. We found that among different breast cancer subtypes, EGFR expression in TNBC was the highest compared to other subtypes. EGFR high ER-positive/HER2-negative breast cancer had significantly higher survival compared to EGFR low ER-positive/HER2-negative breast cancer. It was also associated with high level of intratumor heterogeneity and homologous recombination defects (HRD). This group was also enriched in immune-related gene sets. On the other hand, low EGFR tumor was enriched in cell proliferation-related gene sets. However, these findings were not observed in TNBC. Interestingly, there was a greater infiltration of anti-cancer immune cells in high EGFR ER-positive/HER2-negative breast cancers, while, TNBC with higher EGFR expression had lower fraction of immune cells along with low level of cytolytic activity. Tumor cells have significantly higher EGFR expression compared to immune cells in single cell sequencing data. There was higher expression of immune checkpoint molecules in high EGFR ER-positive/HER2-negative breast cancer but lower expression in TNBC. High EGFR metastatic tumor was significantly associated with worse survival, but no association with infiltrating immune cells was observed. Our study shows that higher EGFR expression in ER-positive/HER2-negative breast cancer is associated with improved outcomes and an anti-cancer immune microenvironment.

A method for the efficient iron-labeling of patient-derived xenograft cells and cellular imaging validation

There is momentum towards implementing patient-derived xenograft models (PDX) in cancer research to reflect the histopathology, tumor behavior, and metastatic properties observed in the original tumor. To study PDX cells preclinically, we used both bioluminescence imaging (BLI) to evaluate cell viability and magnetic particle imaging (MPI), an emerging imaging technology to allow for detection and quantification of iron nanoparticles. The goal of this study was to develop the first successful iron labeling method of breast cancer cells derived from patient brain metsastases and validate this method with imaging during tumor development. The overall workflow of this labeling method is as follows: adherent and non-adherent luciferase expressing human breast cancer PDX cells (F2-7) are dissociated and concurrently labeled after incubation with micron-sized iron oxide particles (MPIO; 25 μg Fe/ml), with labeling validated by cellular imaging with MPI and BLI. In this study, NOD/SCID/ILIIrg^-/- (n = 5) mice Received injections of 1 × 10⁶ iron-labeled F2-7 cells into the fourth mammary fat pad (MFP). BLI was performed longitudinally to day 49 and MPI was performed up to day 28. In vivo BLI revealed that signal increased over time with tumor development. MPI revealed decreasing signal in the tumors over time. Here, we demonstrate the first application of MPI to monitor the growth of a PDX MFP tumor and the first successful labeling of PDX cells with iron oxide particles. Imaging of PDX cells provides a powerful system to better develop personalized therapies targeting breast cancer brain metastasis.

Patient-Derived Xenograft Models in Cervical Cancer: A Systematic Review

BACKGROUND

Patient-derived xenograft (PDX) models have been a focus of attention because they closely resemble the tumor features of patients and retain the molecular and histological features of diseases. They are promising tools for translational research. In the current systematic review, we identify publications on PDX models of cervical cancer (CC-PDX) with descriptions of main methodological characteristics and outcomes to identify the most suitable method for CC-PDX.

METHODS

We searched on PubMed to identify articles reporting CC-PDX. Briefly, the main inclusion criterion for papers was description of PDX created with fragments obtained from human cervical cancer specimens, and the exclusion criterion was the creation of xenograft with established cell lines.

RESULTS

After the search process, 10 studies were found and included in the systematic review. Among 98 donor patients, 61 CC-PDX were established, and the overall success rate was 62.2%. The success rate in each article ranged from 0% to 75% and was higher when using severe immunodeficient mice such as severe combined immunodeficient (SCID), nonobese diabetic (NOD) SCID, and NOD SCID gamma (NSG) mice than nude mice. Subrenal capsule implantation led to a higher engraftment rate than orthotopic and subcutaneous implantation. Fragments with a size of 1-3 mm3 were suitable for CC-PDX. No relationship was found between the engraftment rate and characteristics of the tumor and donor patient, including histology, staging, and metastasis. The latency period varied from 10 days to 12 months. Most studies showed a strong similarity in pathological and immunohistochemical features between the original tumor and the PDX model.

CONCLUSION

Severe immunodeficient mice and subrenal capsule implantation led to a higher engraftment rate; however, orthotopic and subcutaneous implantation were alternatives. When using nude mice, subrenal implantation may be better. Fragments with a size of 1-3 mm3 were suitable for CC-PDX. Few reports have been published about CC-PDX; the results were not confirmed because of the small sample size.

Breast cancer brain metastasis: insight into molecular mechanisms and therapeutic strategies

Breast cancer is one of the most prevalent malignancies in women worldwide. Early-stage breast cancer is considered a curable disease; however, once distant metastasis occurs, the 5-year overall survival rate of patients becomes significantly reduced. There are four distinct metastatic patterns in breast cancer: bone, lung, liver and brain. Among these, breast cancer brain metastasis (BCBM) is the leading cause of death; it is highly associated with impaired quality of life and poor prognosis due to the limited permeability of the blood-brain barrier and consequent lack of effective treatments. Although the sequence of events in BCBM is universally accepted, the underlying mechanisms have not yet been fully elucidated. In this review, we outline progress surrounding the molecular mechanisms involved in BCBM as well as experimental methods and research models to better understand the process. We further discuss the challenges in the management of brain metastases, as well as providing an overview of current therapies and highlighting innovative research towards developing novel efficacious targeted therapies.

The In Vivo Selection Method in Breast Cancer Metastasis

Metastasis is a complex event in cancer progression and causes most deaths from cancer. Repeated transplantation of metastatic cancer cells derived from transplanted murine organs can be used to select the population of highly metastatic cancer cells; this method is called as in vivo selection. The in vivo selection method and highly metastatic cancer cell lines have contributed to reveal the molecular mechanisms of cancer metastasis. Here, we present an overview of the methodology for the in vivo selection method. Recent comparative analysis of the transplantation methods for metastasis have revealed the divergence of metastasis gene signatures. Even cancer cells that metastasize to the same organ show various metastatic cascades and gene expression patterns by changing the transplantation method for the in vivo selection. These findings suggest that the selection of metastasis models for the study of metastasis gene signatures has the potential to influence research results. The study of novel gene signatures that are identified from novel highly metastatic cell lines and patient-derived xenografts (PDXs) will be helpful for understanding the novel mechanisms of metastasis.

Th2 cell infiltrations predict neoadjuvant chemotherapy response of estrogen receptor-positive breast cancer

Background

High infiltration of Th2 is linked to breast cancer progression and metastasis through the induction of cytokine release and T-cell anergy. The estrogen receptor (ER)-positive subtype, which accounts for 70% of breast cancer, is known to respond less to neoadjuvant chemotherapy (NAC) due to its low potential for proliferation. We hypothesized that Th2 high tumors are highly proliferative, and thus more likely to respond to NAC in ER-positive breast cancer.

Methods

We obtained clinicopathological data and overall survival information on 1,069 breast cancer patients from The Cancer Genome Atlas (TCGA). Computational algorithms and CIBERSORT were used to estimate immune cell infiltration. Additionally, xCell was used for validation.

Results

Th2 high tumors did not consistently associate with an unfavorable immune cell composition and tumor immune microenvironment but were found to be significantly elevated in the cancer stage. Th2 high tumors also correlated with high Nottingham pathological grade, as well as with Ki-67 and proliferation score in ER-positive subtypes. High Th2 tumors achieved a pathological complete response (pCR) significantly higher in ER-positive breast cancer.

Conclusions

In conclusion, high levels of Th2 are associated with aggressive features of breast cancer. Th2 levels may be a biomarker in patient selection for NAC in ER-positive breast cancer.

The Essential Factors of Establishing Patient-derived Tumor Model

Establishing an applicable preclinical model is vital for translational cancer research. Patient-derived xenograft has been important preclinical model systems and widely used for cancer research. Patient-derived xenograft models that represent the tumors of the patients are necessary to better translate research discoveries and to test potential therapeutic approaches. However, research in this field is hampered by the limited engraftment rate. In this review, we go over a large number of researches on patient-derived xenograft transplantation and firstly systematically summarize the main factors in methodology to successfully establish models. These results will be applied to the development of patient-derived xenograft leading to better preclinical research.

Degree of Early Estrogen Response Predict Survival after Endocrine Therapy in Primary and Metastatic ER-Positive Breast Cancer

Simple Summary

Over 70% of breast cancer patients in the US have estrogen receptor (ER)-positive tumors. A better predictive biomarker of endocrine therapy would be useful to improve patient compliance. We found that estrogen response early score generated by a GSEA algorithm was significantly associated with immune cell infiltrations, patient survival, and endocrine therapy response in ER-positive breast cancer. Furthermore, the score may be a useful tool to predict response to endocrine therapy in both primary and metastatic breast cancer compared to ER gene expression. This study demonstrates that the estrogen response early score may be a useful prognostic and predicative biomarker in patients with either primary or metastatic breast cancer.

Abstract

Endocrine therapy is the gold-standard treatment for ER-positive/HER2-negative breast cancer. Although its clear benefit, patient compliance is poor (50–80%) due to its long administration period and adverse effects. Therefore, a predictive biomarker that can predict whether endocrine therapy is truly beneficial may improve patient compliance. In this study, we use estrogen response early gene sets of gene set enrichment assay algorithm as the score. We hypothesize that the score could predict the response to endocrine therapy and survival of breast cancer patients. A total of 6549 breast cancer from multiple patient cohorts were analyzed. The score was highest in ER-positive/HER2-negative compared to the other subtypes. Earlier AJCC stage, as well as lower Nottingham pathological grade, were associated with a high score. Low score tumors enriched only allograft rejection gene set, and was significantly infiltrated with immune cells, and high cytolytic activity score. A low score was significantly associated with a worse response to endocrine therapy and worse survival in both primary and metastatic breast cancer patients. The hazard ratio was double that of ESR1 expression. In conclusion, the estrogen response early score predicts response to endocrine therapy and is associated with survival in primary and metastatic breast cancer.

Clinical relevance of tumor microenvironment: immune cells, vessels, and mouse models

The tumor microenvironment (TME) plays a crucial role in tumor progression, therapeutic response, and patient outcomes. TME includes immune cells, blood and lymphatic vessels, and so on. There are anti-cancer and pro-cancer immune cells. In general, infiltration of anti-cancer immune cells, such as cytotoxic T cells (CTLs), is associated with a favorable patient prognosis. In contrast, infiltration of pro-cancer immune cells, such as regulatory T cells (Tregs), tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs), is associated with a worse prognosis. However, some immune cells, which play an ambivalent role in cancer immunity, have demonstrated contradictory impacts on patient prognosis. Blood and lymphatic vessels play crucial roles in TME not only as delivery and draining systems of fluid and molecules, but also allowing cancer cells access to systematic circulation to metastasize. Angiogenesis promotes cancer aggressiveness and is associated with a worse prognosis. Its targeted therapy shows a benefit in some cancers, however, because the target can vary by caner type, a benefit of anti-angiogenesis therapy is limited in the current standard of care. Lymphangiogenesis plays a role in lymph node metastasis, thus, it is associated with a poor prognosis in some cancers. To study TME, the mouse model is one of the most commonly used tools. The choice of appropriate mouse model depends on the hypothesis being tested and the scientific question being asked. Here, we review recent studies that investigated the clinical relevance of TME components and introduce mouse models to study TME.