Genomic tumor evolution of breast cancer

Navigating the Intricacies of Tumor Heterogeneity: An Insight into Potential Prognostic Breast Cancer Biomarkers

Breast cancer is a heterogeneous disease with diverse histological and molecular subtypes. Luminal breast tumors are the most diagnosed subtype. In luminal breast cancer, hormone receptors (including ER, PR, HER2) play a diagnostic and prognostic role. Despite the effectiveness of endocrine therapy in luminal breast tumors, tumor recurrence and resistance occur, and this may highlight evolutionary strategies for survival driven by stemness. In this review we thus consider the association between estrogen signaling and stemness in mediating tumor processes. Many studies report stemness as one of the factors promoting tumor progression. Its association with estrogen signaling warrants further investigation and provides an opportunity for the identification of novel biomarkers which may be used for diagnostic, prognostic, and therapeutic purposes. Breast cancer stem cells have been characterized (CD44+ CD24-) and their role in promoting treatment resistance and tumor recurrence widely studied; however, the complexity of tumor progression which also involve microenvironmental factors suggests the existence of more varied cell phenotypes which mediate stemness and its role in tumor progression.

Circulating tumor DNA: from discovery to clinical application in breast cancer

Breast cancer (BC) stands out as the cancer with the highest incidence of morbidity and mortality among women worldwide, and its incidence rate is currently trending upwards. Improving the efficiency of breast cancer diagnosis and treatment is crucial, as it can effectively reduce the disease burden. Circulating tumor DNA (ctDNA) originates from the release of tumor cells and plays a pivotal role in the occurrence, development, and metastasis of breast cancer. In recent years, the widespread application of high-throughput analytical technology has made ctDNA a promising biomarker for early cancer detection, monitoring minimal residual disease, early recurrence monitoring, and predicting treatment outcomes. ctDNA-based approaches can effectively compensate for the shortcomings of traditional screening and monitoring methods, which fail to provide real-time information and prospective guidance for breast cancer diagnosis and treatment. This review summarizes the applications of ctDNA in various aspects of breast cancer, including screening, diagnosis, prognosis, treatment, and follow-up. It highlights the current research status in this field and emphasizes the potential for future large-scale clinical applications of ctDNA-based approaches.

Metabolic Heterogeneity and Potential Immunotherapeutic Responses Revealed by Single-Cell Transcriptomics of Breast Cancer

BACKGROUND

Breast cancer (BC) exhibits remarkable heterogeneity. However, the transcriptomic heterogeneity of BC at the single-cell level has not been fully elucidated.

METHODS

We acquired BC samples from 14 patients. Single-cell RNA sequencing (scRNA-seq), bioinformatic analyses, along with immunohistochemistry (IHC) and immunofluorescence (IF) assays were carried out.

RESULTS

According to the scRNA-seq results, 10 different cell types were identified. We found that Cancer-Associated Fibroblasts (CAFs) exhibited distinct biological functions and may promote resistance to therapy. Metabolic analysis of tumor cells revealed heterogeneity in glycolysis, gluconeogenesis, and fatty acid synthetase reprogramming, which led to chemotherapy resistance. Furthermore, patients with multiple metastases and progression were predicted to benefit from immunotherapy based on a heterogeneity analysis of T cells and tumor cells.

CONCLUSIONS

Our findings provide a comprehensive understanding of the heterogeneity of BC, provide comprehensive insight into the correlation between cancer metabolism and chemotherapy resistance, and enable the prediction of immunotherapy responses based on T-cell heterogeneity.

Multiomics insights on the onset, progression, and metastatic evolution of breast cancer

Breast cancer is the most common malignant neoplasm in women. Despite progress to date, 700,000 women worldwide died of this disease in 2020. Apparently, the prognostic markers currently used in the clinic are not sufficient to determine the most appropriate treatment. For this reason, great efforts have been made in recent years to identify new molecular biomarkers that will allow more precise and personalized therapeutic decisions in both primary and recurrent breast cancers. These molecular biomarkers include genetic and post-transcriptional alterations, changes in protein expression, as well as metabolic, immunological or microbial changes identified by multiple omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, glycomics, metabolomics, lipidomics, immunomics and microbiomics). This review summarizes studies based on omics analysis that have identified new biomarkers for diagnosis, patient stratification, differentiation between stages of tumor development (initiation, progression, and metastasis/recurrence), and their relevance for treatment selection. Furthermore, this review highlights the importance of clinical trials based on multiomics studies and the need to advance in this direction in order to establish personalized therapies and prolong disease-free survival of these patients in the future.

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.

Resistance to endocrine therapy in HR + and/or HER2 + breast cancer: the most promising predictive biomarkers

Breast cancer is the most common cancer in women. It is a heterogeneous disease, encompassing different biological subtypes that differ in histological features, outcomes, clinical behaviour and different molecular subtypes. Therapy has progressed substantially over the past years with a reduction both for locoregional and systemic therapy. Endocrine therapies have considerably reduced cancer recurrence and mortality. Despite the major diagnostic and therapeutic innovations, resistance to therapy has become a main challenge, especially in metastatic breast cancer, and became a major factor limiting the use of endocrine therapeutic agents in ER positive breast cancers. Approximately 50% of patients with ER positive metastatic disease achieve a complete or partial response with endocrine therapy. However, in the remaining patients, the benefit is limited due to resistance, intrinsic or acquired, resulting in disease progression and poor outcome.Tumour heterogeneity as well as acquired genetic changes and therapeutics pressure have been involved in the endocrine therapy resistance. Nowadays, targeted sequencing of genes involved in cancer has provided insights about genomic tumour evolution throughout treatment and resistance driver mutations. Several studies have described multiple alterations in receptor tyrosine kinases, signalling pathways such as Phosphoinositide-3-kinase-protein kinase B/Akt/mTOR (PI3K/Akt/mTOR) and Mitogen-activated protein kinase (MAPK), cell cycle machinery and their implications in endocrine treatment failure.One of the current concern in cancer is personalized therapy. The focus has been the discovery of new potentially predictive biomarkers capable to identify reliably the most appropriate therapy regimen and which patients will experience disease relapse. The major concern is also to avoid overtreatment/undertreatment and development of resistance.This review focuses on the most promising predictive biomarkers of resistance in estrogen receptor-positive breast cancer and the emerging role of circulating free-DNA as a powerful tool for longitudinal monitoring of tumour molecular profile throughout treatment.

Multiparametric Analysis of Longitudinal Quantitative MRI data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer

This study identifies physiological tumor habitats from quantitative magnetic resonance imaging (MRI) data and evaluates their alterations in response to therapy. Two models of breast cancer (BT-474 and MDA-MB-231) were imaged longitudinally with diffusion-weighted MRI and dynamic contrast-enhanced MRI to quantify tumor cellularity and vascularity, respectively, during treatment with trastuzumab or albumin-bound paclitaxel. Tumors were stained for anti-CD31, anti-Ki-67, and H&E. Imaging and histology data were clustered to identify tumor habitats and percent tumor volume (MRI) or area (histology) of each habitat was quantified. Histological habitats were correlated with MRI habitats. Clustering of both the MRI and histology data yielded three clusters: high-vascularity high-cellularity (HV-HC), low-vascularity high-cellularity (LV-HC), and low-vascularity low-cellularity (LV-LC). At day 4, BT-474 tumors treated with trastuzumab showed a decrease in LV-HC (p = 0.03) and increase in HV-HC (p = 0.03) percent tumor volume compared to control. MDA-MB-231 tumors treated with low-dose albumin-bound paclitaxel showed a longitudinal decrease in LV-HC percent tumor volume at day 3 (p = 0.01). Positive correlations were found between histological and imaging-derived habitats: HV-HC (BT-474: p = 0.03), LV-HC (MDA-MB-231: p = 0.04), LV-LC (BT-474: p = 0.04; MDA-MB-231: p < 0.01). Physiologically distinct tumor habitats associated with therapeutic response were identified with MRI and histology data in preclinical models of breast cancer.

Phylogenetic Tree Inference: A Top-Down Approach to Track Tumor Evolution

Recently, an increasing number of studies sequence multiple biopsies of primary tumors, and even paired metastatic tumors to understand heterogeneity and the evolutionary trajectory of cancer progression. Although several algorithms are available to infer the phylogeny, most tools rely on accurate measurements of mutation allele frequencies from deep sequencing, which is often hard to achieve for clinical samples (especially FFPE samples). In this study, we present a novel and easy-to-use method, PTI (Phylogenetic Tree Inference), which use an iterative top-down approach to infer the phylogenetic tree structure of multiple tumor biopsies from same patient using just the presence or absence of somatic mutations without their allele frequencies. Therefore PTI can be used in a wide range of cases even when allele frequency data is not available. Comparison with existing state-of-the-art methods, such as LICHeE, Treeomics, and BAMSE, shows that PTI achieves similar or slightly better performance within a short run time. Moreover, this method is generally applicable to infer phylogeny for any other data sets (such as epigenetics) with a similar zero and one feature-by-sample matrix.

Comprehensive and integrative analysis identifies COX7A1 as a critical methylation-driven gene in breast invasive carcinoma

Background

Aberrant DNA methylation plays a crucial part in cancer progression through the silencing of gene expression. The purpose of this article was to investigate the DNA methylation-driven genes in breast invasive carcinoma (BRCA) by using integrated bioinformatics analysis and in vitro experiments.

Methods

The methylation and expression profile data of BRCA patients were downloaded from the TCGA database. Besides, the MethylMix algorithm was performed to distinguish differentially methylation-driven genes. Moreover, methylation-specific PCR was used to test the methylation-driven genes.

Results

A total of 218 differentially expressed methylation-driven genes were obtained. Then, four of these genes were applied to establish a prognostic risk model. Moreover, we found that hypermethylation was in the CpG islands of the promoter of COX7A1 gene in BRCA tissues. Furthermore, we found that COX7A1 was significantly down-regulated BRCA tissues and the COX7A1 expression level was markedly increased in BRCA cells after 5-Aza-dC treatment.

Conclusions

Our study reveals that aberrant promoter hypermethylation is critical for COX7A1 gene silencing in BRCA and that COX7A1 emerge as a new biomarker and therapeutic target for BRCA.

Establishment and Characterization of a CTC Cell Line from Peripheral Blood of Breast Cancer Patient

Background: Circulating tumor cell (CTC)-based patient-derived cells are ideal models for investigating the molecular basis of cancer. However, the rarity and heterogeneity of CTCs as well as the difficulties of primary culture limit their practical application. Establishing efficient in vitro culture methods and functionally characterizing CTCs is essential for cancer studies. To this end, we developed an experimental protocol for the isolation, expansion, and identification of breast cancer CTCs.

Methods: The CTC-3 cell line was established from peripheral blood cells of a breast cancer patient. A karyotype analysis was performed. The molecular profile was assessed by flow cytometry, quantitative real-time PCR, and western blot. The characteristics of tumors formed by CTC-3 cells were evaluated by cell growth and tumor sphere formation assays and in a mouse xenograft model. The tumors were analyzed by immunohistochemistry, immunofluorescence analysis, and hematoxylin and eosin staining.

Results: The CTC-3 cell line showed more aggressive growth both in vitro and in vivo than the widely used MCF-7 breast cancer cell line. CTC-3 cells were also more resistant to chemotherapeutic agents, and gene profiling indicated higher expression levels of the epithelial-to-mesenchymal transition and stemness markers as compared to MCF-7 cells.

Conclusions: CTC-3 cells are a better model for investigating the malignant behavior of breast cancer than existing cell lines.

Cell-free tumour DNA testing for early detection of cancer - a potential future tool

In recent years, detection of cell-free tumour DNA (ctDNA) or liquid biopsy has emerged as an attractive noninvasive methodology to detect cancer-specific genetic aberrations in plasma, and numerous studies have reported on the feasibility of ctDNA in advanced cancer. In particular, ctDNA assays can capture a more 'global' portrait of tumour heterogeneity, monitor therapy response, and lead to early detection of resistance mutations. More recently, ctDNA analysis has also been proposed as a promising future tool for detection of early cancer and/or cancer screening. As the average proportion of mutated DNA in plasma is very low (0.4% even in advanced cancer), exceedingly sensitive techniques need to be developed. In addition, as tumours are genetically heterogeneous, any screening test needs to assay multiple genetic targets in order to increase the chances of detection. Further research on the genetic progression from normal to cancer cells and their release of ctDNA is imperative in order to avoid overtreating benign/indolent lesions, causing more harm than good by early diagnosis. More knowledge on the sources and elimination of cell-free DNA will enable better interpretation in older individuals and those with comorbidities. In addition, as white blood cells are the major source of cell-free DNA in plasma, it is important to distinguish acquired mutations in leukocytes (benign clonal haematopoiesis) from an upcoming haematological malignancy or other cancer. In conclusion, although many studies report encouraging results, further technical development and larger studies are warranted before applying ctDNA analysis for early cancer detection in the clinic.

Multiplex assay for multiomics advances in personalized-precision medicine

Building the future of precision medicine is the main focus in cancer domain. Clinical trials are moving toward an array of studies that are more adapted to precision medicine. In this domain, there is an enhanced need for biomarkers, monitoring devices, and data-analysis methods. Omics profiling using whole genome, epigenome, transcriptome, proteome, and metabolome can offer detailed information of the human body in an integrative manner. Omes profiles reflect more accurately real-time physiological status. Personalized omics analyses both disease as a whole and the main disease processes, for a better understanding of the individualized health. Through this, multi-omic approaches for health monitoring, preventative medicine, and personalized treatment can be targeted simultaneously and can lead clinicians to have a comprehensive view on the diseasome.

Breast tumor cell hybrids form spontaneously in vivo and contribute to breast tumor metastases

Cancer cell fusion was suggested as a mechanism of metastasis about a century ago. Since then, many additional modes of material transfer (i.e., tunneling nanotubes, and exosomes) to generate cell hybrids have been identified. However, studies documenting spontaneous tumor hybrid formation in vivo as a mechanism that enables metastasis are still lacking. Here, we tested whether spontaneous hybrid formation in vivo contributes to bona fide metastatic tumors. We first used single cell RNASeq to analyze the gene expression profile of spontaneously formed cancer cell-stromal hybrids, and results revealed that hybrids exhibit a clustering pattern that is distinct from either parental cell and suggestive of substantial diversity of individual hybrids. Despite the newly gained diversity, hybrids can retain expression of critical genes of each parental cell. To assess the biological impact of cancer cell hybrids in vivo, we transfected murine mammary tumor cells, isolated from FVB/N-Tg(MMTV-PyVT)634Mul/J mice (PyVT) with Cre recombinase prior to injection to the murine fat pad of FVB.129S6(B6)-Gt(ROSA)26Sor^tm1(Luc)Kael/J mice such that luciferase expression is induced with hybrid formation; luciferase expression was tracked for up to four months. We observed that hybrid formation occurs spontaneously in vivo and that a significantly higher number of hybrids reside in metastases compared to the primary tumor, supporting the possibility that hybrids can emerge from the primary tumor and proliferate to help create a new tumor at a distant site. Additional studies are now warranted to delineate the mechanisms of cancer cell hybrid transit to metastases since drugs to inhibit hybrid formation might prevent metastatic spread.

Limited utility of tissue micro-arrays in detecting intra-tumoral heterogeneity in stem cell characteristics and tumor progression markers in breast cancer

Background

Intra-tumoral heterogeneity has been recently addressed in different types of cancer, including breast cancer. A concept describing the origin of intra-tumoral heterogeneity is the cancer stem-cell hypothesis, proposing the existence of cancer stem cells that can self-renew limitlessly and therefore lead to tumor progression. Clonal evolution in accumulated single cell genomic alterations is a further possible explanation in carcinogenesis. In this study, we addressed the question whether intra-tumoral heterogeneity can be reliably detected in tissue-micro-arrays in breast cancer by comparing expression levels of conventional predictive/prognostic tumor markers, tumor progression markers and stem cell markers between central and peripheral tumor areas.

Methods

We analyzed immunohistochemical expression and/or gene amplification status of conventional prognostic tumor markers (ER, PR, HER2, CK5/6), tumor progression markers (PTEN, PIK3CA, p53, Ki-67) and stem cell markers (mTOR, SOX2, SOX9, SOX10, SLUG, CD44, CD24, TWIST) in 372 tissue-micro-array samples from 72 breast cancer patients. Expression levels were compared between central and peripheral tumor tissue areas and were correlated to histopathological grading. 15 selected cases additionally underwent RNA sequencing for transcriptome analysis.

Results

No significant difference in any of the analyzed between central and peripheral tumor areas was seen with any of the analyzed methods/or results that showed difference. Except mTOR, PIK3CA and SOX9 (nuclear) protein expression, all markers correlated significantly (p < 0.05) with histopathological grading both in central and peripheral areas.

Conclusion

Our results suggest that intra-tumoral heterogeneity of stem-cell and tumor-progression markers cannot be reliably addressed in tissue-micro-array samples in breast cancer. However, most markers correlated strongly with histopathological grading confirming prognostic information as expression profiles were independent on the site of the biopsy was taken.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1495-6) contains supplementary material, which is available to authorized users.

MicroRNA-588 is downregulated and may have prognostic and functional roles in human breast cancer

Background

We explored the expression pattern, prognostic potential, and functional role of microRNA-588 (miR-588) in human breast cancer (BC).

Material/Methods

The expression pattern of miR-588 was assessed by qPCR in BC cell lines and human BC carcinomas. The correlations between miR-588 and BC patients’ clinicopathological characteristics, as well as BC patients’ overall survival, were statistically assessed. In in vitro culture, MCF-7 and MDA-MB-231 cells were infected with lentivirus to overexpress endogenous miR-588. The subsequent effects of miR-588 upregulation on BC cell proliferation and cisplatin chemosensitivity were examined.

Results

miR-588 was found to be significantly downregulated in both BC cell lines and carcinoma tissues of BC patients. Low expression of miR-588 was closely correlated with BC patients’ poor prognosis of TNM stage, lymph node metastasis, and estrogen receptor status. In addition, patients with low miR-588-expressing carcinomas had much shorter overall survival. In MCF-7 and MDA-MB-231 cells, lentiviral infection induced significant miR-588 upregulation, and miR-588 upregulation had an anti-tumor effect in BC cells by significantly inhibiting cancer proliferation and increasing cisplatin chemosensitivity.

Conclusions

miR-588 is downregulated in BC and its aberrant expression is closely associated with patients’ poor prognosis and overall survival, thus suggesting a biomarker role. miR-588 also has anti-tumor function in BC, making it a potential therapeutic target for BC treatment.

Metastatic genes targeted by an antioxidant in an established radiation- and estrogen-breast cancer model

Breast cancer remains the second most common disease worldwide. Radiotherapy, alone or in combination with chemotherapy, is widely used after surgery as a treatment for cancer with proven therapeutic efficacy manifested by reduced incidence of loco-regional and distant recurrences. However, clinical evidence indicates that relapses occurring after radiotherapy are associated with increased metastatic potential and poor prognosis in the breast. Among the anticarcinogenic and antiproliferative agents, curcumin is a well-known major dietary natural yellow pigment derived from the rhizome of the herb Curcuma longa (Zingiberaceae). The aim of the present study was to analyze the differential expression of metastatic genes in radiation- and estrogen-induced breast cancer cell model and the effect of curcumin on such metastatic genes in breast carcinogenesis. Expression levels of TGF-α and TGFβ1 genes were upregulated in MCF-10F and downregulated in Tumor2 cell lines treated with curcumin. Expression levels of other genes such as caspase 9 and collagen 4 A2 were upregulated in both MCF-10F and Tumor2-treated cell lines. Integrin α5 and cathepsin B and D decreased its expression in Tumor2, whereas E-Cadherin, c-myc and CD44 expressions were only increased in MCF-10F. It can be concluded that metastatic genes can be affected by curcumin in cancer progression and such substance can be used in breast cancer patients with advanced disease without side-effects commonly observed with therapeutic drugs.

Methylation of DACT2 promotes breast cancer development by activating Wnt signaling

Breast cancer is the most common malignant tumor in women worldwide. To explore the role of DACT2 in breast cancer, 5 cell lines and 153 cases of primary cancer were studied. The expression of DACT2 was detected in BT474, MDA-MB-231 and BT549 cells, while no expression was found in MDA-MB-468 and HBL100 cells. Complete methylation of DACT2 was found in MDA-MB-468 and HBL100 cells, partial methylation was observed in BT474 and BT549 cells, and no methylation was detected in MDA-MB-231 cells. Restoration of DACT2 expression was induced by 5-Aza in MDA-MB-468 and HBL100 cells. DACT2 was methylated in 49.7% (76/153) of primary breast cancer samples. Methylation of DACT2 was significantly associated with tumor size (P < 0.05). Reduced DACT2 expression was significantly associated with promoter region methylation in primary breast cancer (P < 0.05). DACT2 suppressed breast cancer cell growth and induced G1/S phase arrest in breast cancer cells. DACT2 inhibited Wnt/β-catenin signaling in human breast cancer cells and suppressed breast cancer cell tumor growth in xenograft mice. In conclusion, our results demonstrate that DACT2 is frequently methylated in human breast cancer, methylation of DACT2 activates Wnt signaling, and DACT2 suppresses breast cancer cell growth both in vitro and in vivo.

Advances in Circulating Tumor DNA Analysis

The analysis of cell-free circulating tumor DNA (ctDNA) is a very promising tool and might revolutionize cancer care with respect to early detection, identification of minimal residual disease, assessment of treatment response, and monitoring tumor evolution. ctDNA analysis, often referred to as "liquid biopsy" offers what tissue biopsies cannot-a continuous monitoring of tumor-specific changes during the entire course of the disease. Owing to technological improvements, efforts for the establishment of preanalytical and analytical benchmark, and the inclusion of ctDNA analyses in clinical trial, an actual clinical implementation has come within easy reach. In this chapter, recent advances of the analysis of ctDNA are summarized starting from the discovery of cell-free DNA, to methodological approaches and the clinical applicability.

Mechanisms Behind the Resistance to Trastuzumab in HER2-Amplified Breast Cancer and Strategies to Overcome It

The introduction of trastuzumab therapy markedly improved the poor prognosis associated with HER2-amplified breast cancers. Despite this, the presence of primary and acquired resistance to trastuzumab treatment remains a significant common challenge. The identification of resistance mechanisms and the incorporation of new drugs that achieve a better blockade of HER family receptors signaling have resulted in improved outcomes. The phosphatidylinositol 3′-kinase/protein kinase B/mammalian target of rapamycin pathway, cross-talk with estrogen receptors, immune response, cell cycle control mechanisms, and other tyrosine kinase receptors such as insulin-like growth factor I receptor are potential pathways involved in trastuzumab resistance. Different therapeutic interventions targeting these pathways are currently under evaluation.