Precision medicine for metastatic breast cancer—limitations and solutions

Theranostic applications of stimulus-responsive systems based on Fe2O3

According to the interaction of nanoparticles with biological systems, enthusiasm for nanotechnology in biomedical applications has been developed in the past decades. Fe2O3 nanoparticles, as the most stable iron oxide, have special merits that make them useful widely for detecting diseases, therapy, drug delivery, and monitoring the therapeutic process. This review presents the fabrication methods of Fe2O3-based materials and their photocatalytic and magnetic properties. Then, we highlight the application of Fe2O3-based nanoparticles in diagnosis and imaging, different therapy methods, and finally, stimulus-responsive systems, such as pH-responsive, magnetic-responsive, redox-responsive, and enzyme-responsive, with an emphasis on cancer treatment. In addition, the potential of Fe2O3 to combine diagnosis and therapy within a single particle called theranostic agent will be discussed.

Utility of Cell-Free DNA Detection in Transplant Oncology

Simple Summary

Transplant oncology is an emerging field in cancer treatment that applies transplant medicine, surgery, and oncology to improve cancer patient survival and quality of life. This review aims to provide a comprehensive overview of the history and emergence of cfDNA technology, its applications to specifically monitor tumor burden at pre-and post-liver transplant stages, and evaluate transplant rejection. The use of ctDNA to evaluate transplant rejection has been extensively studied in non-hepatocellular carcinoma (HCC) diseases. Emerging studies have also investigated the use of ctDNA detection in evaluating HCC tumor burden pre-and post-surgery as well as transplant rejection. However, extensive studies still need to be conducted to evaluate the role of ctDNA detection in the medical management of transplant oncology patients.

Abstract

Transplant oncology is an emerging field in cancer treatment that applies transplant medicine, surgery, and oncology to improve cancer patient survival and quality of life. A critical concept that must be addressed to ensure the successful application of transplant oncology to patient care is efficient monitoring of tumor burden pre-and post-transplant and transplant rejection. Cell-free DNA (cfDNA) detection has emerged as a vital tool in revolutionizing the management of cancer patients who undergo organ transplantation. The advances in cfDNA technology have provided options to perform a pre-transplant evaluation of minimal residual disease (MRD) and post-transplant evaluation of cancer recurrence and transplant rejection. This review aims to provide a comprehensive overview of the history and emergence of cfDNA technology, its applications to specifically monitor tumor burden at pre-and post-transplant stages, and evaluate transplant rejection.

Biodegradable mesoporous nanocomposites with dual-targeting function for enhanced anti-tumor therapy

Tumor-associated macrophages (TAMs), the main components of infiltrating leukocytes in tumors, often play a key role in promoting cancer development and progression. The tumor-specific microenvironment forces the phenotype of tumor-infiltrating to evolve in a direction favorable to tumor development, that is, the generation of M2-like TAMs. Consequently, the dual intervention of cancer cells and tumor microenvironment has become a research hotspot in the field of tumor immunotherapy. In this contribution, we developed pH-sensitive mesoporous calcium silicate nanocomposites (MCNs) encapsulated with indocyanine green (ICG) to enable the effective combination of photothermal therapy (PTT) and photodynamic therapy (PDT) triggered by the 808 nm near-infrared (NIR) light. The mannose and hyaluronic acid-grafted MCNs specifically targeted TAMs and tumor cells and promoted cell apoptosis both in vitro and in vivo. This paper revealed that irradiation of ICG loaded MCNs with NIR can produce a potent hyperthermia and induce abundant intracellular singlet oxygen generation in the target cells. These results suggest that the novel nanoplatform is believed to facilitate the delivery of chemotherapeutic agents to the tumor microenvironment (TME) to enhance the effects of tumor treatment.

ARID1A Mutation in Metastatic Breast Cancer: A Potential Therapeutic Target

Distant metastasis is the principal cause of mortality for breast cancer patients. Targeting specific mutations that have been acquired during the evolution process of advanced breast cancer is a potential means of enhancing the clinical efficacy of treatment strategies. In metastatic breast cancer, ARID1A is the most prevalent mutation of the SWI/SNF complex, which regulates DNA repair, recombination, and gene transcription. The low expression of ARID1A is associated with poor disease-free survival and overall survival of patients with luminal A or HER2-rich breast cancer. In addition, ARID1A plays a prominent role in maintaining luminal characteristics and has an advantage for identifying responses to treatment, including endocrine therapies, HDAC inhibitors and CDK4/6 inhibitors. The therapeutic vulnerabilities initiated by ARID1A alterations encourage us to explore new approaches to cope with ARID1A mutant-related drug resistance or metastasis. In this review, we describe the mutation profiles of ARID1A in metastatic breast cancer and the structure and function of ARID1A and the SWI/SNF complex as well as discuss the potential mechanisms of ARID1A-mediated endocrine resistance and therapeutic potential.

Patient-Derived Organoids Can Guide Personalized-Therapies for Patients with Advanced Breast Cancer

Most breast cancers at an advanced stage exhibit an aggressive nature, and there is a lack of effective anticancer options. Herein, the development of patient-derived organoids (PDOs) is described as a real-time platform to explore the feasibility of tailored treatment for refractory breast cancers. PDOs are successfully generated from breast cancer tissues, including heavily treated specimens. The microtubule-targeting drug-sensitive response signatures of PDOs predict improved distant relapse-free survival for invasive breast cancers treated with adjuvant chemotherapy. It is further demonstrated that PDO pharmaco-phenotyping reflects the previous treatment responses of the corresponding patients. Finally, as clinical case studies, all patients who receive at least one drug predicate to be sensitive by PDOs achieve good responses. Altogether, the PDO model is developed as an effective platform for evaluating patient-specific drug sensitivity in vitro, which can guide personal treatment decisions for breast cancer patients at terminal stage.

The Dual Role of Circular RNAs as miRNA Sponges in Breast Cancer and Colon Cancer

Breast cancer (BC) and colon cancer (CRC) are the two most deadly cancers in the world. These cancers partly share the same genetic background and are partially regulated by the same genes. The outcomes of traditional chemoradiotherapy and surgery remain suboptimal, with high postoperative recurrence and a low survival rate. It is, therefore, urgent to innovate and improve the existing treatment measures. Many studies primarily reported that the microRNA (miRNA) sponge functions of circular RNA (circRNA) in BC and CRC have an indirect relationship between the circRNA–miRNA axis and malignant behaviors. With a covalent ring structure, circRNAs can regulate the expression of target genes in multiple ways, especially by acting as miRNA sponges. Therefore, this review mainly focuses on the roles of circRNAs as miRNA sponges in BC and CRC based on studies over the last three years, thus providing a theoretical reference for finding new therapeutic targets in the future.

PD-L1 quantification across tumor types using the reverse phase protein microarray: implications for precision medicine

BACKGROUND

Anti-programmed cell death protein 1 and programmed cell death ligand 1 (PD-L1) agents are broadly used in first-line and second-line treatment across different tumor types. While immunohistochemistry-based assays are routinely used to assess PD-L1 expression, their clinical utility remains controversial due to the partial predictive value and lack of standardized cut-offs across antibody clones. Using a high throughput immunoassay, the reverse phase protein microarray (RPPA), coupled with a fluorescence-based detection system, this study compared the performance of six anti-PD-L1 antibody clones on 666 tumor samples.

METHODS

PD-L1 expression was measured using five antibody clones (22C3, 28-8, CAL10, E1L3N and SP142) and the therapeutic antibody atezolizumab on 222 lung, 71 ovarian, 52 prostate and 267 breast cancers, and 54 metastatic lesions. To capture clinically relevant variables, our cohort included frozen and formalin-fixed paraffin-embedded samples, surgical specimens and core needle biopsies. Pure tumor epithelia were isolated using laser capture microdissection from 602 samples. Correlation coefficients were calculated to assess concordance between antibody clones. For two independent cohorts of patients with lung cancer treated with nivolumab, RPPA-based PD-L1 measurements were examined along with response to treatment.

RESULTS

Median-center PD-L1 dynamic ranged from 0.01 to 39.37 across antibody clones. Correlation coefficients between the six antibody clones were heterogeneous (range: -0.48 to 0.95) and below 0.50 in 61% of the comparisons. In nivolumab-treated patients, RPPA-based measurement identified a subgroup of tumors, where low PD-L1 expression equated to lack of response.

CONCLUSIONS

Continuous RPPA-based measurements capture a broad dynamic range of PD-L1 expression in human specimens and heterogeneous concordance levels between antibody clones. This high throughput immunoassay can potentially identify subgroups of tumors in which low expression of PD-L1 equates to lack of response to treatment.

Great future or greedy venture: Precision medicine needs philosophy

INTRODUCTION

Over the past decade, we have witnessed the initiation and implementation of precision medicine (PM), a discipline that promises to individualize and personalize medical management and treatment, rendering them ultimately more precise and effective. Despite of the continuing advances and numerous clinical applications, the potential of PM remains highly controversial, sparking heated debates about its future.

METHOD

The present article reviews the philosophical issues and practical challenges that are critical to the feasibility and implementation of PM.

OUTCOME

The explanation and argument about the relations between PM and computability, uncertainty as well as complexity, show that key foundational assumptions of PM might not be fully validated.

CONCLUSION

The present analysis suggests that our current understanding of PM is probably oversimplified and too superficial. More efforts are needed to realize the hope that PM has elicited, rather than make the term just as a hype.

Multi-omic molecular profiling guide's efficacious treatment selection in refractory metastatic breast cancer: a prospective phase II clinical trial

This prospective phase II clinical trial (Side Out 2) explored the clinical benefits of treatment selection informed by multi‐omic molecular profiling (MoMP) in refractory metastatic breast cancers (MBCs). Core needle biopsies were collected from 32 patients with MBC at trial enrollment. Patients had received an average of 3.94 previous lines of treatment in the metastatic setting before enrollment in this study. Samples underwent MoMP, including exome sequencing, RNA sequencing (RNA‐Seq), immunohistochemistry, and quantitative protein pathway activation mapping by Reverse Phase Protein Microarray (RPPA). Clinical benefit was assessed using the previously published growth modulation index (GMI) under the hypothesis that MoMP‐selected therapy would warrant further investigation for GMI ≥ 1.3 in ≥ 35% of the patients. Of the 32 patients enrolled, 29 received treatment based on their MoMP and 25 met the follow‐up criteria established by the trial protocol. Molecular information was delivered to the tumor board in a median time frame of 14 days (11–22 days), and targetable alterations for commercially available agents were found in 23/25 patients (92%). Of the 25 patients, 14 (56%) reached GMI ≥ 1.3. A high level of DNA topoisomerase I (TOPO1) led to the selection of irinotecan‐based treatments in 48% (12/25) of the patients. A pooled analysis suggested clinical benefit in patients with high TOPO1 expression receiving irinotecan‐based regimens (GMI ≥ 1.3 in 66.7% of cases). These results confirmed previous observations that MoMP increases the frequency of identifiable actionable alterations (92% of patients). The MoMP proposed allows the identification of biomarkers that are frequently expressed in MBCs and the evaluation of their role as predictors of response to commercially available agents. Lastly, this study confirmed the role of MoMP for informing treatment selection in refractory MBC patients: more than half of the enrolled patients reached a GMI ≥ 1.3 even after multiple lines of previous therapies for metastatic disease.

Deep phenotyping of synovial molecular signatures by integrative systems analysis in rheumatoid arthritis

OBJECTIVE

RA encompasses a complex, heterogeneous and dynamic group of diseases arising from molecular and cellular perturbations of synovial tissues. The aim of this study was to decipher this complexity using an integrative systems approach and provide novel insights for designing stratified treatments.

METHODS

An RNA sequencing dataset of synovial tissues from 152 RA patients and 28 normal controls was imported and subjected to filtration of differentially expressed genes, functional enrichment and network analysis, non-negative matrix factorization, and key driver analysis. A naïve Bayes classifier was applied to the independent datasets to investigate the factors associated with treatment outcome.

RESULTS

A matrix of 1241 upregulated differentially expressed genes from RA samples was classified into three subtypes (C1-C3) with distinct molecular and cellular signatures. C3 with prominent immune cells and proinflammatory signatures had a stronger association with the presence of ACPA and showed a better therapeutic response than C1 and C2, which were enriched with neutrophil and fibroblast signatures, respectively. C2 was more occupied by synovial fibroblasts of destructive phenotype and carried highly expressed key effector molecules of invasion and osteoclastogenesis. CXCR2, JAK3, FYN and LYN were identified as key driver genes in C1 and C3. HDAC, JUN, NFKB1, TNF and TP53 were key regulators modulating fibroblast aggressiveness in C2.

CONCLUSIONS

Deep phenotyping of synovial heterogeneity captured comprehensive and discrete pathophysiological attributes of RA regarding clinical features and treatment response. This result could serve as a template for future studies to design stratified approaches for RA patients.

Low Doses of Silver Nanoparticles Selectively Induce Lipid Peroxidation and Proteotoxic Stress in Mesenchymal Subtypes of Triple-Negative Breast Cancer

Molecular profiling of tumors shows that triple-negative breast cancer (TNBC) can be stratified into mesenchymal (claudin-low breast cancer; CLBC) and epithelial subtypes (basal-like breast cancer; BLBC). Subtypes differ in underlying genetics and in response to therapeutics. Several reports indicate that therapeutic strategies that induce lipid peroxidation or proteotoxicity may be particularly effective for various cancers with a mesenchymal phenotype such as CLBC, for which no specific treatment regimens exist and outcomes are poor. We hypothesized that silver nanoparticles (AgNPs) can induce proteotoxic stress and cause lipid peroxidation to a greater extent in CLBC than in BLBC. We found that AgNPs were lethal to CLBCs at doses that had little effect on BLBCs and were non-toxic to normal breast epithelial cells. Analysis of mRNA profiles indicated that sensitivity to AgNPs correlated with expression of multiple CLBC-associated genes. There was no correlation between sensitivity to AgNPs and sensitivity to silver cations, uptake of AgNPs, or proliferation rate, indicating that there are other molecular factors driving sensitivity to AgNPs. Mechanistically, we found that the differences in sensitivity of CLBC and BLBC cells to AgNPs were driven by peroxidation of lipids, protein oxidation and aggregation, and subsequent proteotoxic stress and apoptotic signaling, which were induced in AgNP-treated CLBC cells, but not in BLBC cells. This study shows AgNPs are a specific treatment for CLBC and indicates that stratification of TNBC subtypes may lead to improved outcomes for other therapeutics with similar mechanisms of action.

Bioinformatic Exploration for Prognostic Significance of Sphingolipid Metabolism-Related Genes in Invasive Ductal Carcinoma Using the Cancer Genome Atlas Cohort

Introduction

Sphingolipid metabolism is a highly controlled process that is involved in regulating bioactive lipid signaling pathways and serves important roles in several cellular processes in breast cancer. Invasive ductal carcinoma (IDC), which is characterized by the malignant proliferation of the ductal epithelium and stromal invasion, is the most common type of breast cancer. Recent advances in genetic research have accelerated the discovery of novel prognostic factors and therapeutic targets for the disease. The aim of the present study was to investigate the expression and prognostic significance of sphingolipid metabolism-related genes in female IDC.

Methods

The present study used gene expression RNAseq data obtained from The Cancer Genome Atlas breast invasive carcinoma (TCGA BRCA) datasets.

Results

Sphingolipid metabolism-related genes exhibited dysregulated mRNA expression levels in IDC. The Student's t-test revealed that SMPDL3B, B4GALNT1, LPAR2, and LASS2 were significantly upregulated, while LASS3, LPAR1, B4GALT6, GAL3ST1, HPGD, ST8SIA1, UGT8, and S1PR1 were significantly downregulated in female IDC tissues compared with normal solid tissues. Kaplan-Meier survival analyses revealed that high SMPDL3B mRNA expression levels were associated with good prognosis in female IDC, suggesting that SMPDL3B plays a tumor suppressor role. To the best of our knowledge, the present study was the first to report that dysregulated expressions of SMPDL3B are significantly associated with age, estrogen receptor status, progesterone receptor status, and histological subtype.

Conclusion

Taken together, our study indicated that SMPDL3B may have a pathophysiological role and serve as a novel prognostic biomarker in IDC.

Emerging principles of cancer biophysics

Cancer is a multi-step process where normal cells become transformed, grow, and may disseminate to establish new lesions within the body. In recent years, the physical properties of individual cells and the tissue microenvironment have been shown to be potent determinants of cancer progression. Biophysical tools have long been used to examine cell and tissue mechanics, morphology, and migration. However, exciting developments have linked these physical traits to gene expression changes that drive metastatic seeding, organ selectivity, and tumor growth. Here, we present some vignettes to address recent studies to show progress in harnessing biophysical tools and concepts to gain insights into metastasis.

Constitutive BAK/MCL1 complexes predict paclitaxel and S63845 sensitivity of ovarian cancer

We previously found that preformed complexes of BAK with antiapoptotic BCL2 proteins predict BH3 mimetic sensitivities in lymphohematopoietic cells. These complexes have not previously been examined in solid tumors or in the context of conventional anticancer drugs. Here we show the relative amount of BAK found in preformed complexes with MCL1 or BCLXL varies across ovarian cancer cell lines and patient-derived xenografts (PDXs). Cells bearing BAK/MCL1 complexes were more sensitive to paclitaxel and the MCL1 antagonist S63845. Likewise, PDX models with BAK/MCL1 complexes were more likely to respond to paclitaxel. Mechanistically, BIM induced by low paclitaxel concentrations interacted preferentially with MCL1 and displaced MCL1-bound BAK. Further studies indicated that cells with preformed BAK/MCL1 complexes were sensitive to the paclitaxel/S63845 combination, while cells without BAK/MCL1 complexes were not. Our study suggested that the assessment of BAK/MCL1 complexes might be useful for predicting response to paclitaxel alone or in combination with BH3 mimetics.

The Utility of Next-Generation Sequencing in Advanced Breast and Gynecologic Cancers

OBJECTIVES

Next-generation sequencing (NGS) has the potential to identify genetic alterations that are actionable with targeted therapy. Our objective was to identify the impact of NGS testing on advanced breast and gynecologic malignancies.

METHODS

A retrospective review of 108 patients who underwent NGS testing between 2015 and 2019 was performed. The NGS clinical action rate was calculated based on documentation of positive clinical action taken in cases with an actionable NGS result.

RESULTS

The 108 specimens tested included 35 breast cancers and 73 gynecologic malignancies, with most of the testing performed at Foundation Medicine (90%). Actionable mutation(s) were identified in 79 (73%) of 108 cases. The overall clinical action rate of NGS testing was 38% (30 of 79 cases). Overall, 47 (44%) of 108 patients died, all succumbing to disease. The average survival was 10.9 months. The survival difference between patients with actionable NGS result and targeted treatment, actionable NGS result but no targeted treatment, and patients with nonactionable NGS result was not significant (log-rank test, P = .5160).

CONCLUSIONS

NGS testing for advanced breast and gynecologic cancers at our institution has a 38% clinical action rate. However, the increased clinical action rate over the years did not translate into improved survival.

Targeted Sequencing of Taiwanese Breast Cancer with Risk Stratification by the Concurrent Genes Signature: A Feasibility Study

Breast cancer is the most common female malignancy in Taiwan, while conventional clinical and pathological factors fail to provide full explanation for prognostic heterogeneity. The aim of the study was to evaluate the feasibility of targeted sequencing combined with concurrent genes signature to identify somatic mutations with clinical significance. The extended concurrent genes signature was based on the coherent patterns between genomic and transcriptional alterations. Targeted sequencing of 61 Taiwanese breast cancers revealed 1036 variants, including 76 pathogenic and 545 likely pathogenic variants based on the ACMG classification. The most frequently mutated genes were NOTCH, BRCA1, AR, ERBB2, FANCA, ATM, and BRCA2 and the most common pathogenic deletions were FGFR1, ATM, and WT1, while BRCA1 (rs1799965), FGFR2 (missense), and BRCA1 (rs1799949) were recurrent pathogenic SNPs. In addition, 38 breast cancers were predicted into 12 high-risk and 26 low-risk cases based on the extended concurrent genes signature, while the pathogenic PIK3CA variant (rs121913279) was significantly mutated between groups. Two deleterious SH3GLB2 mutations were further revealed by multivariate Cox’s regression (hazard ratios: 29.4 and 16.1). In addition, we identified several significantly mutated or pathogenic variants associated with differentially expressed signature genes. The feasibility of targeted sequencing in combination with concurrent genes risk stratification was ascertained. Future study to validate clinical applicability and evaluate potential actionability for Taiwanese breast cancers should be initiated.

Targeted Next-Generation Sequencing of Circulating Tumor DNA Mutations among Metastatic Breast Cancer Patients

Liquid biopsy through the detection of circulating tumor DNA (ctDNA) has potential advantages in cancer monitoring and prediction. However, most previous studies in this area were performed with a few hotspot genes, single time point detection, or insufficient sequencing depth. In this study, we performed targeted next-generation sequencing (NGS) with a customized panel in metastatic breast cancer (MBC) patients. Fifty-four plasma samples were taken before chemotherapy and after the third course of treatment for detection and analysis. Paired lymphocytes were also included to eliminate clonal hematopoiesis (CH)-related alternatives. A total of 1182 nonsynonymous mutations in 419 genes were identified. More ctDNA mutations were detected in patients with tumors > 3 cm (p = 0.035) and HER2(−) patients (p = 0.029). For a single gene, the distribution of ctDNA mutations was also correlated with clinical characteristics. Multivariate regression analysis revealed that HER2 status was significantly associated with mutation burden (OR 0.02, 95% CI 0–0.62, p = 0.025). The profiles of ctDNA mutations exhibited marked discrepancies between two time points, and baseline ctDNA was more sensitive and specific than that after chemotherapy. Finally, elevated ctDNA mutation level was positively correlated with poor survival (p < 0.001). Mutations in ctDNA could serve as a potential biomarker for the evaluation, prediction, and clinical management guidance of MBC patients with chemotherapy.

Off-tumor IDO1 target engagements determine the cancer-immune set point and predict the immunotherapeutic efficacy

Background

Indoleamine-2,3-dioxygenase 1 (IDO1) has been intensively pursued as a therapeutic target to reverse the immunosuppressive cancer-immune milieu and promote tumor elimination. However, recent failures of phase III clinical trials with IDO1 inhibitors involved in cancer immunotherapies highlight the urgent need to develop appropriate methods for tracking IDO1 when the cancer-immune milieu is therapeutically modified.

Methods

We utilized a small-molecule radiotracer, ¹¹C-l-1MTrp, to quantitatively and longitudinally visualize whole-body IDO1 dynamics. Specifically, we first assessed ¹¹C-l-1MTrp in mice-bearing contralateral human tumors with distinct IDO1 expression patterns. Then, we applied ¹¹C-l-1MTrp to longitudinally monitor whole-body IDO1 variations in immunocompetent melanoma-bearing mice treated with 1-methyl-l-tryptophan plus either chemotherapeutic drugs or antibodies targeting programmedcell death 1 and cytotoxic T-lymphocyte-associated protein 4.

Results

¹¹C-l-1MTrp positron emission tomography (PET) imaging accurately delineated IDO1 expression in xenograft mouse models. Moreover, we were able to visualize dynamic IDO1 regulation in the mesenteric lymph nodes (MLNs), an off-tumor IDO1 target, where the percentage uptake of ¹¹C-l-1MTrp accurately annotated the therapeutic efficacy of multiple combination immunotherapies in preclinical models. Remarkably, ¹¹C-l-1MTrp signal intensity in the MLNs was inversely related to the specific growth rates of treated tumors, suggesting that IDO1 expression in the MLNs can serve as a new biomarker of the cancer-immune set point.

Conclusions

PET imaging of IDO1 with ¹¹C-l-1MTrp is a robust method to assess the therapeutic efficacy of multiple combinatorial immunotherapies, improving our understanding of the merit and challenges of IDO1 regimens. Further validation of this animal data in humans is ongoing. We envision that our results will provide a potential precision medicine paradigm for noninvasive visualizing each patient’s individual response in combinatorial cancer immunotherapy, and tailoring optimal personalized combination strategies.

New Insights into the Therapeutic Applications of CRISPR/Cas9 Genome Editing in Breast Cancer

Breast cancer is one of the most prevalent forms of cancer globally and is among the leading causes of death in women. Its heterogenic nature is a result of the involvement of numerous aberrant genes that contribute to the multi-step pathway of tumorigenesis. Despite the fact that several disease-causing mutations have been identified, therapy is often aimed at alleviating symptoms rather than rectifying the mutation in the DNA sequence. The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 is a groundbreaking tool that is being utilized for the identification and validation of genomic targets bearing tumorigenic potential. CRISPR/Cas9 supersedes its gene-editing predecessors through its unparalleled simplicity, efficiency and affordability. In this review, we provide an overview of the CRISPR/Cas9 mechanism and discuss genes that were edited using this system for the treatment of breast cancer. In addition, we shed light on the delivery methods—both viral and non-viral—that may be used to deliver the system and the barriers associated with each. Overall, the present review provides new insights into the potential therapeutic applications of CRISPR/Cas9 for the advancement of breast cancer treatment.

Genetic landscape of breast cancer and mutation tracking with circulating tumor DNA in Chinese women

Considerable efforts have been devoted to exploring the breast cancer mutational landscape to understand its genetic complexity. However, no studies have yet comprehensively elucidated the molecular characterization of breast tumors in Chinese women. This study aimed to determine the potential clinical utility of peripheral blood assessment for circulating tumor-derived DNA (ctDNA) and comprehensively characterize the female Chinese population’s genetic mutational spectrum. We used Omi-Seq to create cancer profiles of 273 patients enrolled at The First Affiliated Hospital of Wenzhou Medical University. The gene landscape results indicate PIK3CA and TP53 as the most frequently detected genes, followed by ERBB2, in Chinese breast cancer patients. The accuracy of ERBB2 copy number variations in tissue/formalin-fixed and paraffin-embedded samples was 95% with 86% sensitivity and 99% specificity. Moreover, mutation numbers varied between different molecular cell-free DNA subtypes, with the basal-like patients harboring a higher number of variants than the luminal patients. Furthermore, ratio changes in the max ctDNA allele fraction highly correlated with clinical response measurements, including cancer relapse and metastasis. Our data demonstrate that ctDNA characterization using the Omi-Seq platform can extend the capacity of personalized clinical cancer management.

Current updates on precision therapy for breast cancer associated brain metastasis: Emphasis on combination therapy

Cancer therapies have undergone a tremendous progress over the past decade. Precision medicine provides a more tailored approach, making the combination of existing therapies more precise. Different types of cancers are characterized by unique biomarkers that are targeted using various genomic approaches by clinicians and companies worldwide to achieve efficient treatment with minimal side effects. Precision medicine has two broad approaches namely stratified and personalized medicine. The driver mutations could vary within a subtype while the same driver mutations could be found across different subtypes. Precision medicine has recently gained a lot of importance for breast cancer therapy. Various kinds of mutations like hotspot mutations, gene alterations, gene amplification mutations are targeted to design a more specific therapy. Apart from these known gene mutations there are various unknown mutations. Thus, tumor heterogeneity can pose a challenge to precision medicine. For breast cancer, one of the most successful models developed in case of precision medicine is the anti-HER2 therapies as HER2 was considered to have the worst prognosis being highly malignant. But now due to the advent of HER2 receptor targeted therapies, it has a good prognosis. Moreover, precision medicine helps in identifying if the drug molecules being used for the treatment of one kind of cancer can be beneficial in the treatment of another kind of cancer as well, considering the signaling pathways and machinery is similar in most of the cancers. This reduces the time for new drug development and is economically more feasible. Precision medicine will prove to be very advantageous in case of brain metastasis.

A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks

Breast cancer is currently the second most common cause of cancer-related death in women. Presently, the clinical benchmark in cancer diagnosis is tissue biopsy examination. However, the manual process of histopathological analysis is laborious, time-consuming, and limited by the quality of the specimen and the experience of the pathologist. This study's objective was to determine if deep convolutional neural networks can be trained, with transfer learning, on a set of histopathological images independent of breast tissue to segment tumor nuclei of the breast. Various deep convolutional neural networks were evaluated for the study, including U-Net, Mask R-CNN, and a novel network (GB U-Net). The networks were trained on a set of Hematoxylin and Eosin (H&E)-stained images of eight diverse types of tissues. GB U-Net demonstrated superior performance in segmenting sites of invasive diseases (AJI = 0.53, mAP = 0.39 & AJI = 0.54, mAP = 0.38), validated on two hold-out datasets exclusively containing breast tissue images of approximately 7,582 annotated cells. The results of the networks, trained on images independent of breast tissue, demonstrated that tumor nuclei of the breast could be accurately segmented.

When Tissue is an Issue the Liquid Biopsy is Nonissue: A Review

Precision medicine has impacted the field of medical oncology by introducing personalized therapies, improving all measurable outcomes. This field, in turn, has expanded to obtaining and analyzing a vast and ever-increasing amount of genomic information. One technique currently applied is the liquid biopsy, which consists of detecting and isolating DNA and exosomes in cancer patients. Newly developed techniques have made it possible to use the liquid biopsy in a wide range of settings. However, challenges regarding the validation of its clinical utility exist because of a lack of standardization across different techniques and tumor types, confounder genomic information, lack of appropriate clinical trial designs, and a non-measured, and therefore not estimated, economic impact on population health. Nowadays, liquid biopsy is not routinely used, but ongoing research is increasing its popularity, and a new era in oncology is developing. Therefore, it is essential to have an in-depth understanding of the liquid biopsy technique. In this review, we summarize the leading techniques and liquid biopsy applications in cancer.

Comprehensive molecular profiling of Taiwanese breast cancers revealed potential therapeutic targets: prevalence of actionable mutations among 380 targeted sequencing analyses

BACKGROUND

Breast cancer is one of the leading causes of cancer-related deaths in women, and there is a demand in developing an Asian-based genetic profiling database for breast cancer in improving the treatment response. This study aimed to determine molecular alternations and identify potential therapeutic targets by analyzing the genetic profiling from a cohort of Taiwanese breast cancers using a commercialized next-generation sequencing (NGS) targeted panel.

METHODS

The study population comprised a broad spectrum of breast cancer patients in Taiwan, including Group 1: planned to receive first-line surgery and followed by adjuvant therapy, or early relapse within three years, Group 2: planned to receive first-line neoadjuvant therapy and followed by surgery, and Group 3: de novo stage IV, or stage IV with recurrence beyond three years. Molecular profiles were determined using Thermo Fisher™ Oncomine™ Comprehensive Assay version 3 (TMO comprehensive assay) from Formalin-Fixed Paraffin-Embedded (FFPE) tissues. Level of actionability was evaluated with the ESMO Scale of clinical actionability of molecular targets (ESCAT).

RESULTS

A total of 380 TMO comprehensive assays were conducted on 372 patients, and we presented targeted sequencing analyses of Tier I: alteration-drug match associated with improved outcome in clinical trials including ERBB2 amplification, BRCA1/2 germline mutation, PIK3CA mutation, and NTRK translocation, and Tier II: antitumor activity associated with the matched alteration-drug but lack of prospective outcome data including PTEN loss, ESR1 mutation, AKT1 mutation, and ERBB2 mutation, and Tier III: matched drug-alteration that led to clinical benefit in another tumor type including MDM2 amplification, and ERBB3 mutation. Among them, 249 (66%) showed at least one actionable alternation based on the ESCAT criteria. The most frequent impacted genes (all variants combined within each sample) were PIK3CA (38%), followed by ERBB2 (23%), ESR1 (10%), AKT1 (6%), and BRCA2 (5%), and the remaining rare variants (less than 5% of assayed cohort) were BRCA1 (3%), MDM2 (2.2%), and ERBB3 (1.1%).

CONCLUSION

Targeted sequencing of actionable genes is believed to provide clinical applicability and substantial benefits for Taiwanese breast cancer patients. A valid scale of clinical actionability should be adopted for precision medicine practice under multidisciplinary molecular tumor board.

CircNR3C2 promotes HRD1-mediated tumor-suppressive effect via sponging miR-513a-3p in triple-negative breast cancer

BACKGROUND

E3 ubiquitin ligase HRD1 (HMG-CoA reductase degradation protein 1, alias synoviolin with SYVN1 as the official gene symbol) was found downregulated and acting as a tumor suppressor in breast cancer, while the exact expression profile of HRD1 in different breast cancer subtypes remains unknown. Recent studies characterized circular RNAs (circRNAs) playing an regulatory role as miRNA sponge in tumor progression, presenting a new viewpoint for the post-transcriptional regulation of cancer-related genes.

METHODS

Examination of the expression of HRD1 protein and mRNA was implemented using public microarray/RNA-sequencing datasets and breast cancer tissues/cell lines. Based on public RNA-sequencing results, online databases and enrichment/clustering analyses were used to predict the specific combinations of circRNA/miRNA that potentially govern HRD1 expression. Gain-of-function and rescue experiments in vitro and in vivo were executed to evaluate the suppressive effects of circNR3C2 on breast cancer progression through HRD1-mediated proteasomal degradation of Vimentin, which was identified using immunoblotting, immunoprecipitation, and in vitro ubiquitination assays.

RESULTS

HRD1 is significantly underexpressed in triple-negative breast cancer (TNBC) against other subtypes and has an inverse correlation with Vimentin, inhibiting the proliferation, migration, invasion and EMT (epithelial-mesenchymal transition) process of breast cancer cells via inducing polyubiquitination-mediated proteasomal degradation of Vimentin. CircNR3C2 (hsa_circ_0071127) is also remarkably downregulated in TNBC, negatively correlated with the distant metastasis and lethality of invasive breast carcinoma. Overexpressing circNR3C2 in vitro and in vivo leads to a crucial enhancement of the tumor-suppressive effects of HRD1 through sponging miR-513a-3p.

CONCLUSIONS

Collectively, we elucidated a bona fide circNR3C2/miR-513a-3p/HRD1/Vimentin axis that negatively regulates the metastasis of TNBC, suggesting that circNR3C2 and HRD1 can act as potential prognostic biomarkers. Our study may facilitate the development of therapeutic agents targeting circNR3C2 and HRD1 for patients with aggressive breast cancer.

Nexus between PI3K/AKT and Estrogen Receptor Signaling in Breast Cancer

Signaling from estrogen receptor alpha (ERα) and its ligand estradiol (E2) is critical for growth of ≈70% of breast cancers. Therefore, several drugs that inhibit ERα functions have been in clinical use for decades and new classes of anti-estrogens are continuously being developed. Although a significant number of ERα+ breast cancers respond to anti-estrogen therapy, ≈30% of these breast cancers recur, sometimes even after 20 years of initial diagnosis. Mechanism of resistance to anti-estrogens is one of the intensely studied disciplines in breast cancer. Several mechanisms have been proposed including mutations in ESR1, crosstalk between growth factor and ERα signaling, and interplay between cell cycle machinery and ERα signaling. ESR1 mutations as well as crosstalk with other signaling networks lead to ligand independent activation of ERα thus rendering anti-estrogens ineffective, particularly when treatment involved anti-estrogens that do not degrade ERα. As a result of these studies, several therapies that combine anti-estrogens that degrade ERα with PI3K/AKT/mTOR inhibitors targeting growth factor signaling or CDK4/6 inhibitors targeting cell cycle machinery are used clinically to treat recurrent ERα+ breast cancers. In this review, we discuss the nexus between ERα-PI3K/AKT/mTOR pathways and how understanding of this nexus has helped to develop combination therapies.

Unlocking the Power of Exosomes for Crossing Biological Barriers in Drug Delivery

Since the 2013 Nobel Prize was awarded for the discovery of vesicle trafficking, a subgroup of nanovesicles called exosomes has been driving the research field to a new regime for understanding cellular communication. This exosome-dominated traffic control system has increased understanding of many diseases, including cancer metastasis, diabetes, and HIV. In addition to the important diagnostic role, exosomes are particularly attractive for drug delivery, due to their distinctive properties in cellular information transfer and uptake. Compared to viral and non-viral synthetic systems, the natural, cell-derived exosomes exhibit intrinsic payload and bioavailability. Most importantly, exosomes easily cross biological barriers, obstacles that continue to challenge other drug delivery nanoparticle systems. Recent emerging studies have shown numerous critical roles of exosomes in many biological barriers, including the blood–brain barrier (BBB), blood–cerebrospinal fluid barrier (BCSFB), blood–lymph barrier (BlyB), blood–air barrier (BAB), stromal barrier (SB), blood–labyrinth barrier (BLaB), blood–retinal barrier (BRB), and placental barrier (PB), which opens exciting new possibilities for using exosomes as the delivery platform. However, the systematic reviews summarizing such discoveries are still limited. This review covers state-of-the-art exosome research on crossing several important biological barriers with a focus on the current, accepted models used to explain the mechanisms of barrier crossing, including tight junctions. The potential to design and engineer exosomes to enhance delivery efficacy, leading to future applications in precision medicine and immunotherapy, is discussed.

Analysis of N6-Methyladenosine Methyltransferase Reveals METTL14 and ZC3H13 as Tumor Suppressor Genes in Breast Cancer

Objectives

Recently, an increasing number of studies have revealed that N6-methyladenosine (m6A) functions as a significant post-transcriptional modification which plays a critical role in the occurrence and progression of enriched tumors by regulating coding and non-coding RNA biogenesis. However, the biological function of m6A in breast cancer remains largely unclear.

Materials and Methods

In this study, we used a series of bioinformatic databases and tools to jointly analyze the expression of m6A methylation transferases (METTL3, METTL14, WTAP, RBM15, RBM15B and ZC3H13) and investigate the prognostic value of METTL14 and ZC3H13 in breast cancer. Besides, we analyzed the downstream carcinogenic molecular mechanisms related to METTL14 and ZC3H13 and their relationship with immune infiltration in breast tumor tissues.

Results

The results showed that METTL14 and ZC3H13 were the down-regulated m6A methylation transferases in breast cancer. Survival outcome analysis suggested that abnormally low expression of METTL14 and ZC3H13 could predict unfavorable prognosis in four breast cancer subtypes. Moreover, their down-regulation was associated with ER-, PR- and triple-negative breast cancer patients, as well as tumor progression (increased Scarff, Bloom and Richardson grade status and Nottingham Prognostic Index classification). Co-expression analysis revealed that METTL14 and ZC3H13 had a strong positive correlation with APC, an antagonist of the Wnt signaling pathway, indicating they might cooperate in regulating proliferation, invasion, and metastasis of tumor cells. METTL14, ZC3H13, and APC expression levels had significant positive correlation with infiltrating levels of CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells, and negative correlation with Treg cells in breast cancer.

Conclusions

This study demonstrated that down-regulation of METTL14 and ZC3H13 which act as two tumor suppressor genes was found in breast cancer and predicted poor prognosis. Their abnormal expression promoted breast cancer invasion by affecting pathways related to tumor progression and mediating immunosuppression.

Hypoxia-Associated Prognostic Markers and Competing Endogenous RNA Co-Expression Networks in Breast Cancer

Objective

Many primary tumors have insufficient supply of molecular oxygen, called hypoxia. Hypoxia is one of the leading characteristics of solid tumors resulting in a higher risk of local failure and distant metastasis. It is quite necessary to investigate the hypoxia associated molecular hallmarks in breast cancer.

Materials and Methods

According to the published studies, we selected 13 hypoxia related gene expression signature to define the hypoxia status of breast cancer using ConsensusClusterPlus package based on the data from The Cancer Genome Atlas (TCGA). Subsequently, we characterized the infiltration of 24 immune cell types under different hypoxic conditions. Furthermore, the differentially expressed hypoxia associated microRNAs, mRNAs and related signaling pathways were analyzed and depicted. On this basis, a series of prognostic markers related to hypoxia were identified and ceRNA co-expression networks were constructed.

Results

Two subgroups (cluster1 and cluster2) were identified and the 13 hypoxia related gene signature were all up-regulated in cluster1. Thus, we defined the cluster1 as “hypoxic subgroup” compared with cluster2. The infiltration of CD8+ T cell and CD4+ T cell were lower in cluster1 while the nTreg cell and iTreg cell were higher, indicating that there was immunosuppressive status in cluster1. We observed widespread hypoxia-associated dysregulation of microRNAs and mRNAs. Next, a risk signature for predicting prognosis of breast cancer patients was established based on 12 dysregulated hypoxia associated prognostic genes. Two microRNAs, hsa-miR-210-3p and hsa-miR-190b, with the most significant absolute logFC value were related to unfavorable and better prognosis, respectively. Several long non-coding RNAs were predicted to be microRNA targets and positively correlated with two selected mRNAs, CPEB2 and BCL11A. Predictions based on the LINC00899/PSMG3-AS1/PAXIP1-AS1- hsa-miR-210-3p-CPEB2 and SNHG16- hsa-miR-190b-BCL11A ceRNA regulation networks indicated that the two genes might act as tumor suppressor and oncogene, respectively.

Conclusion

Hypoxia plays an important role in the initiation and progression of breast cancer. Our research provides potential mechanisms into molecular-level understanding of tumor hypoxia.

Breast Subtypes and Prognosis of Breast Cancer Patients With Initial Bone Metastasis: A Population-Based Study

Background

Metastatic breast cancer (MBC) is a highly heterogeneous disease and bone is one of the most common metastatic sites. This retrospective study was conducted to investigate the clinical features, prognostic factors and benefits of surgery of breast cancer patients with initial bone metastases.

Methods

From 2010 to 2015, 6,860 breast cancer patients diagnosed with initial bone metastasis were analyzed from Surveillance, Epidemiology, and End Results (SEER) database. Univariate and Multivariable analysis were used to identify prognostic factors. A nomogram was performed based on the factors selected from cox regression result. Survival curves were plotted according to different subtypes, metastatic burdens and risk groups differentiated by nomogram.

Results

Hormone receptor (HR) positive/human epidermal growth factor receptor 2 (HER2) positive patients showed the best outcome compared to other subtypes. Patients of younger age (<60 years old), white race, lower grade, lower T stage (<=T2), not combining visceral metastasis tended to have better outcome. About 37% (2,249) patients received surgery of primary tumor. Patients of all subtypes could benefit from surgery. Patients of bone-only metastases (BOM), bone and liver metastases, bone and lung metastases also showed superior survival time if surgery was performed. However, patients of bone and brain metastasis could not benefit from surgery (p = 0.05). The C-index of nomogram was 0.66. Cutoff values of nomogram point were identified as 87 and 157 points, which divided all patients into low-, intermediate- and high-risk groups. Patients of all groups showed better overall survival when receiving surgery.

Conclusion

Our study has provided population-based prognostic analysis in patients with initial bone metastatic breast cancer and constructed a predicting nomogram with good accuracy. The finding of potential benefit of surgery to overall survival will cast some lights on the treatment tactics of this group of patients.

Identification of prognostic mRNAs in metastatic cutaneous melanoma

Cutaneous melanoma is the most common cause of skin cancer-related deaths worldwide. There is an urgent need to identify prognostic biomarkers to facilitate decision-making for treatment of metastatic cutaneous melanoma. Gene expression microarrays and RNA-seq technology have recently improved or changed current prognostic and therapeutic strategies for several cancers. However, according to the current melanoma staging system, prognosis is almost entirely dependent on clinicopathological features. To identify novel prognostic biomarkers, we investigated gene expression and clinical data for patients with cutaneous melanoma from three cohorts of The Cancer Genome Atlas and Gene Expression Omnibus. Kaplan-Meier survival analysis using median values of each gene as cutoff value revealed that nine genes (ABCC3, CAPS2, CCR6, CDCA8, CLU, DPF1, PTK2B, SATB1, and SYNE1) were statistically significant prognostic biomarkers of metastatic cutaneous melanoma in all three independent cohorts. Low expression of two genes (CDCA8 and DPF1) and high expression of seven genes (ABCC3, CAPS2, CCR6, CLU, PTK2B, SATB1, and SYNE) were significantly associated with positive metastatic cutaneous melanoma prognoses. In conclusion, we suggest nine novel prognostic biomarkers for cutaneous metastatic melanoma.

Integrated Wound Recognition in Bandages for Intelligent Treatment

The mismatch between irregular wounds and fixed dressings is an important but long-neglected problem in wound management, which may cause imprecise or incomplete care outcomes. Continuous advances in the internet, Internet of Things, and materials science put forward higher requirements in precise wound treatment. Herein, an integrated wound recognition strategy is demonstrated by extracting digital geometric information of specific irregular wounds. Such online wound image scanning and recognition integrated with offline intelligent material fabrication can greatly reduce incomplete wound closure or potential irritation toward normal tissue around the wound site. As a proof-of-concept, an active matrix of Ag-modified gelatin on bandages demonstrates promising antibacterial properties for practical application. In vivo mouse experiment reveals that wound-customized bands enable precisely fitting in the irregular wound bed, resulting in accelerating wound healing efficiency. Such wound recognitions in a bandage involve multidisciplinary technology including image identification, computer modeling nanomaterial fabrication and modification, presenting a broad potential of personalized wound healthcare for a wide variety of clinical applications.

Detecting Vasodilation as Potential Diagnostic Biomarker in Breast Cancer Using Deep Learning-Driven Thermomics

Breast cancer is the most common cancer in women. Early diagnosis improves outcome and survival, which is the cornerstone of breast cancer treatment. Thermography has been utilized as a complementary diagnostic technique in breast cancer detection. Artificial intelligence (AI) has the capacity to capture and analyze the entire concealed information in thermography. In this study, we propose a method to potentially detect the immunohistochemical response to breast cancer by finding thermal heterogeneous patterns in the targeted area. In this study for breast cancer screening 208 subjects participated and normal and abnormal (diagnosed by mammography or clinical diagnosis) conditions were analyzed. High-dimensional deep thermomic features were extracted from the ResNet-50 pre-trained model from low-rank thermal matrix approximation using sparse principal component analysis. Then, a sparse deep autoencoder designed and trained for such data decreases the dimensionality to 16 latent space thermomic features. A random forest model was used to classify the participants. The proposed method preserves thermal heterogeneity, which leads to successful classification between normal and abnormal subjects with an accuracy of 78.16% (73.3-81.07%). By non-invasively capturing a thermal map of the entire tumor, the proposed method can assist in screening and diagnosing this malignancy. These thermal signatures may preoperatively stratify the patients for personalized treatment planning and potentially monitor the patients during treatment.

Assessment of circulating HISLA as a potential biomarker for breast cancer diagnosis and prognosis

Breast cancer (BC) is the most frequently encountered and aggressive type of malignant tumor and affects the health of females across the globe. Approximately 30% of patients that are newly diagnosed have a high risk of subsequent metastasis and relapse. HIF-1α-stabilizing long noncoding RNA (HISLA) packaged in exosome has been recently identified and revealed as an important oncogenic gene in promoting BC progress. Thus, we sought to investigate whether serum circulating HISLA was involved in dynamics underlying its applicability for the diagnosis and prognosis of BC. We assessed serum HISLA expression in 40 patients with BC and 20 healthy controls to investigate its roles in BC using quantitative real-time polymerase chain reaction (qRT-PCR). We also assessed measures of correlation of clinical and pathological parameters with prognoses of BC patients. Our findings suggested that serum HISLA expression in BC patients was significantly higher than in healthy controls. Furthermore, high expression of serum HISLA was positively associated with advanced stage lymph node metastasis. Expression of HISLA was reduced in postoperative BC patients' serum samples, compared with preoperative serum samples. Pearson correlation assessments indicated significant correlation between serum HISLA expression and the tissue sample HISLA expression in BC patients. Our findings suggested that serum HISLA may serve as newfound biomarker which could help to improve diagnoses and prognoses for BC-afflicted patients.

Expression of HER2 and BRCA1 Correlates with Prognosis in Patients with Breast Cancer After Radiotherapy: A Case-Control Study

Background: This study aims to explore the associations of human epidermal growth factor receptor 2 (HER2) and breast cancer susceptibility gene 1 (BRCA1) expression levels with prognosis and radiation sensitivity in patients with breast cancer. Methods: Breast cancer tissues, adjacent normal breast tissues, and benign breast lesions were initially obtained from 256 breast cancer patients as well as an additional 245 patients with breast lesions. Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was conducted to assess the expression of HER2 and BRCA1 in the collected tissues. Immunohistochemistry was performed to examine HER2 and BRCA1-positive expression levels in the tissues. The relationship between HER2 and BRCA1 expression levels and radiation sensitivity as well breast cancer prognosis was assessed by the Spearman correlation analysis and Kaplan-Meier survival analysis. Results: Compared with adjacent normal breast tissues and benign breast lesions, the breast cancer tissues exhibited high expression of HER2 mRNA and protein and low expression of BRCA1 mRNA and protein. Patients with positive HER2 expression had a significantly shorter survival time, and survival time of patients with positive BRCA1 expression was markedly longer, which were consistent with RT-qPCR results. After radiotherapy, the local failure rate of HER2-positive patients was higher than that of the negative ones, while that of BRCA1-positive patients was lower than that of the negative ones. Conclusions: This study suggested that breast cancer patients with high HER2 expression and low BRCA1 expression were less sensitive to radiotherapy with poor prognosis in breast cancer.

Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrate robust, sensitive, and reproducible data generation across eleven international sites on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

Detection of genomic alterations in breast cancer with circulating tumour DNA sequencing

Analysis of circulating cell-free DNA (cfDNA) has opened new opportunities for characterizing tumour mutational landscapes with many applications in genomic-driven oncology. We developed a customized targeted cfDNA sequencing approach for breast cancer (BC) using unique molecular identifiers (UMIs) for error correction. Our assay, spanning a 284.5 kb target region, is combined with a novel freely-licensed bioinformatics pipeline that provides detection of low-frequency variants, and reliable identification of copy number variations (CNVs) directly from plasma DNA. We first evaluated our pipeline on reference samples. Then in a cohort of 35 BC patients our approach detected actionable driver and clonal variants at low variant frequency levels in cfDNA that were concordant (77%) with sequencing of primary and/or metastatic solid tumour sites. We also detected ERRB2 gene CNVs used for HER2 subtype classification with 80% precision compared to immunohistochemistry. Further, we evaluated fragmentation profiles of cfDNA in BC and observed distinct differences compared to data from healthy individuals. Our results show that the developed assay addresses the majority of tumour associated aberrations directly from plasma DNA, and thus may be used to elucidate genomic alterations in liquid biopsy studies.

NSD3-Induced Methylation of H3K36 Activates NOTCH Signaling to Drive Breast Tumor Initiation and Metastatic Progression

Histone methyltransferase NSD3 is frequently dysregulated in human cancers, yet the epigenetic role of NSD3 during cancer development remains elusive. Here we report that NSD3-induced methylation of H3K36 is crucial for breast tumor initiation and metastasis. In patients with breast cancer, elevated expression of NSD3 was associated with recurrence, distant metastasis, and poor survival. In vivo, NSD3 promoted malignant transformation of mammary epithelial cells, a function comparable to that of HRAS. Furthermore, NSD3 expanded breast cancer-initiating cells and promoted epithelial-mesenchymal transition to trigger tumor invasion and metastasis. Mechanistically, the long isoform (full-length transcript) of NSD3, but not its shorter isoform lacking a catalytic domain, cooperated with EZH2 and RNA polymerase II to stimulate H3K36me2/3-dependent transactivation of genes associated with NOTCH receptor cleavage, leading to nuclear accumulation of NICD and NICD-mediated transcriptional repression of E-cadherin. Furthermore, mice harboring primary and metastatic breast tumors with overexpressed NSD3 showed sensitivity to NOTCH inhibition. Together, our findings uncover the critical epigenetic role of NSD3 in the modulation of NOTCH-dependent breast tumor progression, providing a rationale for targeting the NSD3-NOTCH signaling regulatory axis in aggressive breast cancer. SIGNIFICANCE: This study demonstrates the functional significance of histone methyltransferase NSD3 in epigenetic regulation of breast cancer stemness, EMT, and metastasis, suggesting NSD3 as an actionable therapeutic target in metastatic breast cancer.

High expression of UNC5B enhances tumor proliferation, increases metastasis, and worsens prognosis in breast cancer

UNC-5 Homolog B (UNC5B) is a member of the dependence receptor family that regulates cell survival and apoptosis in a ligand-dependent manner. UNC5B plays an important role in the development of multiple cancers, including colorectal, bladder, and thyroid cancer. However, the exact expression pattern and mechanism of UNC5B in breast cancer have not been well elucidated. Here, we showed that UNC5B expression was significantly upregulated in breast cancer using bioinformatics analysis and experimental validation. High UNC5B expression was correlated with poor overall survival in breast cancer patients. UNC5B knockdown inhibited breast cancer cell proliferation and metastasis and compromised PI3K/Akt signaling activation. In summary, UNC5B is a promising diagnostic and prognostic biomarker and targeting UNC5B is a potential strategy for individualized breast cancer treatment.

Visualization of human T lymphocyte-mediated eradication of cancer cells in vivo

Lymphocyte-based immunotherapy has emerged as a breakthrough in cancer therapy for both hematologic and solid malignancies. In a subpopulation of cancer patients, this powerful therapeutic modality converts malignancy to clinically manageable disease. However, the T cell- and chimeric antigen receptor T (CAR-T) cell-mediated antimetastatic activity, especially their impacts on microscopic metastatic lesions, has not yet been investigated. Here we report a living zebrafish model that allows us to visualize the metastatic cancer cell killing effect by tumor- infiltrating lymphocytes (TILs) and CAR-T cells in vivo at the single-cell level. In a freshly isolated primary human melanoma, specific TILs effectively eliminated metastatic cancer cells in the living body. This potent metastasis-eradicating effect was validated using a human lymphoma model with CAR-T cells. Furthermore, cancer-associated fibroblasts protected metastatic cancer cells from T cell-mediated killing. Our data provide an in vivo platform to validate antimetastatic effects by human T cell-mediated immunotherapy. This unique technology may serve as a precision medicine platform for assessing anticancer effects of cellular immunotherapy in vivo before administration to human cancer patients.

Clinical implications of prospective genomic profiling of metastatic breast cancer patients

Background

Metastatic breast cancer remains incurable. Next-generation sequencing (NGS) offers the ability to identify actionable genomic alterations in tumours which may then be matched with targeted therapies, but the implementation and utility of this approach is not well defined for patients with metastatic breast cancer.

Methods

We recruited patients with advanced breast cancer of any subtype for prospective targeted NGS of their most recent tumour samples, using a panel of 108 breast cancer-specific genes. Genes were classified as actionable or non-actionable using the European Society of Medical Oncology Scale for Clinical Actionability of Molecular Targets (ESCAT) guidelines.

Results

Between February 2014 and May 2019, 322 patients were enrolled onto the study, with 72% (n = 234) of patients successfully sequenced (n = 357 samples). The majority (74%, n = 171) of sequenced patients were found to carry a potentially actionable alteration, the most common being a PIK3CA mutation. Forty-three percent (n = 74) of patients with actionable alterations were referred for a clinical trial or referred for confirmatory germline testing or had a change in therapy outside of clinical trials. We found alterations in AKT1, BRCA2, CHEK2, ESR1, FGFR1, KMT2C, NCOR1, PIK3CA and TSC2 to be significantly enriched in our metastatic population compared with primary breast cancers. Concordance between primary and metastatic samples for key driver genes (TP53, ERBB2 amplification) was > 75%. Additionally, we found that patients with a higher number of mutations had a significantly worse overall survival.

Conclusion

Genomic profiling of patients with metastatic breast cancer can have clinical implications and should be considered in all suitable patients.

CircZFR functions as a sponge of miR-578 to promote breast cancer progression by regulating HIF1A expression

BACKGROUND

Breast cancer (BC) is the most common malignancy among women. Emerging studies have demonstrated that circular RNA (circRNA) zinc finger RNA binding protein (circZFR) serves as a crucial regulator in many human cancers. However, the role and mechanism of circZFR in BC tumorigenesis remain unclear.

METHODS

The levels of circZFR, miR-578 and hypoxia-inducible factor 1α (HIF1A) were detected by quantitative real-time polymerase chain reaction (qRT-PCR) or western blot. Cell viability, colony formation, apoptosis, migration and invasion capacities in vitro were determined by using the Cell Counting Kit-8 (CCK-8), standard colony formation, flow cytometry and transwell assays, respectively. Glucose uptake, lactate product and adenosine triphosphate (ATP) levels of cells in vitro were measured using the commercial human assay kits. Targeted relationships among circZFR, miR-578 and HIF1A in BC cell lines were verified by dual-luciferase reporter and RNA pulldown assays. Animal studies were performed to assess the effect of circZFR on tumor growth in vivo.

RESULTS

Our data indicated that circZFR was overexpressed in BC tissues and cells, and the increased circZFR level predicted poor prognosis of BC patients. CircZFR silencing or miR-578 overexpression repressed BC cell viability, colony formation, migration, invasion, and glycolysis and enhanced cell apoptosis in vitro. CircZFR silencing also hampered tumor growth in vivo. Mechanistically, circZFR acted as a sponge of miR-578, and circZFR silencing hindered BC cell malignant behaviors by miR-578. HIF1A was a functional target of miR-578 in regulating BC cell viability, colony formation, migration, invasion, glycolysis and apoptosis in vitro. Furthermore, circZFR modulated HIF1A expression through sponging miR-578.

CONCLUSION

Our findings first identified that the silencing of circZFR suppressed BC malignant progression in vitro via the regulation of the miR-578/HIF1A axis, providing evidence for the crucial involvement of circZFR in BC pathogenesis.

circIQCH sponges miR-145 to promote breast cancer progression by upregulating DNMT3A expression

As a unique type of RNA, circular RNAs (circRNAs) are important regulators of multiple biological processes in the progression of cancer. However, the potential role of most circRNAs in breast cancer lung metastasis is still unknown. In this study, we characterized and further investigated circIQCH (hsa_circ_0104345) by analyzing the circRNA microarray profiling in our previous study. circIQCH was upregulated in breast cancer tissues, especially in the metastatic sites. CCK-8, transwell, wound-healing and mouse xenograft assays were carried out to investigate the functions of circIQCH. Knockdown of circIQCH inhibited breast cancer cell proliferation and migration to lung. Moreover, luciferase reporter assays and RNA immunoprecipitation assays were performed to elucidate the underlying molecular mechanism of circIQCH. The results showed that circIQCH sponges miR-145 and promotes breast cancer progression by upregulating DNMT3A. In summary, our study demonstrated the pivotal role of circIQCH-miR-145-DNMT3A axis in breast cancer growth and metastasis via the mechanism of competing endogenous RNAs. Thus, circIQCH could be a potential therapeutic target for breast cancer.

Development and Challenges of the Discovery of HER2 Inhibitors

The treatment of cancer has always been a major problem in the world. Some cancers cannot be treated with surgery, but only with cancer drugs. Among many cancer drugs, small molecule inhibitors play an irreplaceable role. HER2 is one of the HER families, and the development of HER2 inhibitors has made a huge contribution to the treatment of cancer. Some HER2 inhibitors are already on the market, and some HER2 inhibitors are undergoing clinical research. The design, synthesis and development of new HER2 inhibitors targeting different targets are also ongoing, and some are even under clinical research. The HER2 inhibitors that are on the market have developed resistance, which brings great challenges to the HER2 inhibitor development in the future. This article reviews the development and challenges of the discovery of HER2 inhibitors.

Significance of human microbiome in breast cancer: Tale of an invisible and an invincible

The human microbiome is a mysterious treasure of the body playing endless important roles in the well-being of the host metabolism, digestion, and immunity. On the other hand, it actively participates in the development of a variety of pathological conditions including cancer. With the Human Microbiome Project initiative, metagenomics, and next-generation sequencing technologies in place, the last decade has witnessed immense explorations and investigations on the enigmatic association of breast cancer with the human microbiome. However, the connection between the human microbiome and breast cancer remains to be explored in greater detail. In fact, there are several emerging questions such as whether the host microbiota contributes to disease initiation, or is it a consequence of the disease is an irrevocably important question that demands a valid answer. Since the microbiome is an extremely complex community, gaps still remain on how this vital microbial organ plays a role in orchestrating breast cancer development. Nevertheless, undeniable evidence from studies has pinpointed the presence of specific microbial elements of the breast and gut to play a role in governing breast cancer. It is still unclear if an alteration in microbiome/dysbiosis leads to breast cancer or is it vice versa. Though specific microbial signatures have been detected to be associated with various breast cancer subtypes, the structure and composition of a core "healthy" microbiome is yet to be established. Probiotics seem to be a promising antidote for targeted prevention and treatment of breast cancer. Interestingly, these microbial communities can serve as potential biomarkers for prognosis, diagnosis, and treatment of breast cancer, thereby leading to the rise of a completely new era of personalized medicine. This review is a humble attempt to summarize the research findings on the human microbiome and its relation to breast cancer.

Big data-driven precision medicine: Starting the custom-made era of iatrology

Precision medicine is a new therapeutic concept and method emerging in recent years. The rapid development of precision medicine is driven by the development of omics related technology, biological information and big data science. Precision medicine is provided to implement precise and personalized treatment for diseases and specific patients. Precision medicine is commonly used in the diagnosis, treatment and prevention of various diseases. This review introduces the application of precision medicine in eight systematic diseases of the human body, and systematically presenting the current situation of precision medicine. At the same time, the shortcomings and limitations of precision medicine are pointed out. Finally, we prospect the development of precision medicine.

Computer-Aided Ligand Discovery for Estrogen Receptor Alpha

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

Molecular and functional extracellular vesicle analysis using nanopatterned microchips monitors tumor progression and metastasis

Longitudinal cancer monitoring is crucial to clinical implementation of precision medicine. There is growing evidence indicating important functions of extracellular vesicles (EVs) in tumor progression and metastasis, including matrix remodeling via transporting matrix metalloproteases (MMPs). However, the clinical relevance of EVs remains largely undetermined, partially owing to challenges in EV analysis. Distinct from existing technologies mostly focused on characterizing molecular constituents of EVs, here we report a nanoengineered lab-on-a-chip system that enables integrative functional and molecular phenotyping of tumor-associated EVs. A generalized, high-resolution colloidal inkjet printing method was developed to allow robust and scalable manufacturing of three-dimensional (3D) nanopatterned devices. With this nanochip platform, we demonstrated integrative analysis of the expression and proteolytic activity of MMP14 on EVs to detect in vitro cell invasiveness and monitor in vivo tumor metastasis, using cancer cell lines and mouse models. Analysis of clinical plasma specimen showed that our technology could be used for cancer detection including accurate classification of age-matched controls and patients with ductal carcinoma in situ, invasive ductal carcinoma, or locally metastatic breast cancer in a training cohort (n = 30, 96.7% accuracy) and an independent validation cohort (n = 70, 92.9% accuracy). With clinical validation, our technology could provide a useful liquid biopsy tool to improve cancer diagnostics and real-time surveillance of tumor evolution in patients to inform personalized therapy.

Decellularized Extracellular Matrix for Bioengineering Physiomimetic 3D in Vitro Tumor Models

Recent advances in the extraction and purification of decellularized extracellular matrix (dECM) obtained from healthy or malignant tissues open new avenues for engineering physiomimetic 3D in vitro tumor models, which closely recapitulate key biomolecular hallmarks and the dynamic cancer cell-ECM interactions in the tumor microenvironment. We review current and upcoming methodologies for chemical modification of dECM-based biomaterials and advanced bioprocessing into organotypic 3D solid tumor models. A comprehensive review of disruptive advances and shortcomings of exploring dECM-based biomaterials for recapitulating the native tumor-supporting matrix is also provided. We hope to drive the discussion on how 3D dECM testing platforms can be leveraged for generating microphysiological tumor surrogates that generate more robust and predictive data on therapeutic bioperformance.