Mammary field cancerization: molecular evidence and clinical importance

Unraveling malignant phenotype of peritumoral tissue: transcriptomic insights into early-stage breast cancer

BACKGROUND

Early-stage invasive ductal carcinoma displays high survival rates due to early detection and treatments. However, there is still a chance of relapse of 3-15% after treatment. The aim of this study was to uncover the distinctive transcriptomic characteristics and monitoring prognosis potential of peritumoral tissue in early-stage cases.

METHODS

RNA was isolated from tumoral, peritumoral, and non-tumoral breast tissue from surgical resection of 10 luminal early-stage invasive ductal carcinoma patients. Transcriptome expression profiling for differentially expressed genes (DEGs) identification was carried out through microarray analysis. Gene Ontology and KEGG pathways enrichment analysis were explored for functional characterization of identified DEGs. Protein-Protein Interactions (PPI) networks analysis was performed to identify hub nodes of peritumoral tissue alterations and correlated with Overall Survival and Relapse Free Survival.

RESULTS

DEGs closely related with cell migration, extracellular matrix organization, and cell cycle were upregulated in peritumoral tissue compared to non-tumoral. Analyzing PPI networks, we observed that the proximity to tumor leads to the alteration of gene modules involved in cell proliferation and differentiation signaling pathways. In fact, in the peritumoral area were identified the top ten upregulated hub nodes including CDK1, ESR1, NOP58, PCNA, EZH2, PPP1CA, BUB1, TGFBR1, CXCR4, and CCND1. A signature performed by four of these hub nodes (CDK1, PCNA, EZH2, and BUB1) was associated with relapse events in untreated luminal breast cancer patients.

CONCLUSIONS

In conclusion, our study characterizes in depth breast peritumoral tissue providing clues on the changes that tumor signaling could cause in patients with early-stage breast cancer. We propose that the use of a four gene signature could help to predict local relapse. Overall, our results highlight the value of peritumoral tissue as a potential source of new biomarkers for early detection of relapse and improvement in invasive ductal carcinoma patient's prognosis.

Nomogram for preoperative differentiation of benign and malignant breast tumors using contrast-enhanced cone-beam breast CT (CE CB-BCT) quantitative imaging and assessment features

PURPOSE

Breast cancer's impact necessitates refined diagnostic approaches. This study develops a nomogram using radiology quantitative features from contrast-enhanced cone-beam breast CT for accurate preoperative classification of benign and malignant breast tumors.

MATERIAL AND METHODS

A retrospective study enrolled 234 females with breast tumors, split into training and test sets. Contrast-enhanced cone-beam breast CT-images were acquired using Koning Breast CT-1000. Quantitative assessment features were extracted via 3D-slicer software, identifying independent predictors. The nomogram was constructed to preoperative differentiation benign and malignant breast tumors. Calibration curve was used to assess whether the model showed favorable correspondence with pathological confirmation. Decision curve analysis confirmed the model's superiority.

RESULTS

The study enrolled 234 female patients with a mean age of 50.2 years (SD ± 9.2). The training set had 164 patients (89 benign, 75 malignant), and the test set had 70 patients (29 benign, 41 malignant). The nomogram achieved excellent predictive performance in distinguishing benign and malignant breast lesions with an AUC of 0.940 (95% CI 0.900-0.940) in the training set and 0.970 (95% CI 0.940-0.970) in the test set.

CONCLUSION

This study illustrates the effectiveness of quantitative radiology features derived from contrast-enhanced cone-beam breast CT in distinguishing between benign and malignant breast tumors. Incorporating these features into a nomogram-based diagnostic model allows for breast tumor diagnoses that are objective and possess good accuracy. The application of these insights could substantially increase reliability and efficacy in the management of breast tumors, offering enhanced diagnostic capability.

Cabergoline as a Novel Strategy for Post-Pregnancy Breast Cancer Prevention in Mice and Human

Post-pregnancy breast cancer often carries a poor prognosis, posing a major clinical challenge. The increasing trend of later-life pregnancies exacerbates this risk, highlighting the need for effective chemoprevention strategies. Current options, limited to selective estrogen receptor modulators, aromatase inhibitors, or surgical procedures, offer limited efficacy and considerable side effects. Here, we report that cabergoline, a dopaminergic agonist, reduces the risk of breast cancer post-pregnancy in a Brca1/P53-deficient mouse model, with implications for human breast cancer prevention. We show that a single dose of cabergoline administered post-pregnancy significantly delayed the onset and reduced the incidence of breast cancer in Brca1/P53-deficient mice. Histological analysis revealed a notable acceleration in post-lactational involution over the short term, characterized by increased apoptosis and altered gene expression related to ion transport. Over the long term, histological changes in the mammary gland included a reduction in the ductal component, decreased epithelial proliferation, and a lower presence of recombinant Brca1/P53 target cells, which are precursors of tumors. These changes serve as indicators of reduced breast cancer susceptibility. Additionally, RNA sequencing identified gene expression alterations associated with decreased proliferation and mammary gland branching. Our findings highlight a mechanism wherein cabergoline enhances the protective effect of pregnancy against breast cancer by potentiating postlactational involution. Notably, a retrospective cohort study in women demonstrated a markedly lower incidence of post-pregnancy breast cancer in those treated with cabergoline compared to a control group. Our work underscores the importance of enhancing postlactational involution as a strategy for breast cancer prevention, and identifies cabergoline as a promising, low-risk option in breast cancer chemoprevention. This strategy has the potential to revolutionize breast cancer prevention approaches, particularly for women at increased risk due to genetic factors or delayed childbirth, and has wider implications beyond hereditary breast cancer cases.

Contrast-enhanced CT radiomics features to preoperatively identify differences between tumor and proximal tumor-adjacent and tumor-distant tissues of resectable esophageal squamous cell carcinoma

BACKGROUND

Esophagectomy is the main treatment for esophageal squamous cell carcinoma (ESCC), and patients with histopathologically negative margins still have a relatively higher recurrence rate. Contrast-enhanced CT (CECT) radiomics might noninvasively obtain potential information about the internal heterogeneity of ESCC and its adjacent tissues. This study aimed to develop CECT radiomics models to preoperatively identify the differences between tumor and proximal tumor-adjacent and tumor-distant tissues in ESCC to potentially reduce tumor recurrence.

METHODS

A total of 529 consecutive patients with ESCC from Centers A (n = 447) and B (n = 82) undergoing preoperative CECT were retrospectively enrolled in this study. Radiomics features of the tumor, proximal tumor-adjacent (PTA) and proximal tumor-distant (PTD) tissues were individually extracted by delineating the corresponding region of interest (ROI) on CECT and applying the 3D-Slicer radiomics module. Patients with pairwise tissues (ESCC vs. PTA, ESCC vs. PTD, and PTA vs. PTD) from Center A were randomly assigned to the training cohort (TC, n = 313) and internal validation cohort (IVC, n = 134). Univariate analysis and the least absolute shrinkage and selection operator were used to select the core radiomics features, and logistic regression was performed to develop radiomics models to differentiate individual pairwise tissues in TC, validated in IVC and the external validation cohort (EVC) from Center B. Diagnostic performance was assessed using area under the receiver operating characteristics curve (AUC) and accuracy.

RESULTS

With the chosen 20, 19 and 5 core radiomics features in TC, 3 individual radiomics models were developed, which exhibited excellent ability to differentiate the tumor from PTA tissue (AUC: 0.965; accuracy: 0.965), the tumor from PTD tissue (AUC: 0.991; accuracy: 0.958), and PTA from PTD tissue (AUC: 0.870; accuracy: 0.848), respectively. In IVC and EVC, the models also showed good performance in differentiating the tumor from PTA tissue (AUCs: 0.956 and 0.962; accuracy: 0.956 and 0.937), the tumor from PTD tissue (AUCs: 0.990 and 0.974; accuracy: 0.952 and 0.970), and PTA from PTD tissue (AUCs: 0.806 and 0.786; accuracy: 0.760 and 0.786), respectively.

CONCLUSION

CECT radiomics models could differentiate the tumor from PTA tissue, the tumor from PTD tissue, and PTA from PTD tissue in ESCC.

A pan-tissue survey of mosaic chromosomal alterations in 948 individuals

Genetic mutations accumulate in an organism's body throughout its lifetime. While somatic single-nucleotide variants have been well characterized in the human body, the patterns and consequences of large chromosomal alterations in normal tissues remain largely unknown. Here, we present a pan-tissue survey of mosaic chromosomal alterations (mCAs) in 948 healthy individuals from the Genotype-Tissue Expression project, augmenting RNA-based allelic imbalance estimation with haplotype phasing. We found that approximately a quarter of the individuals carry a clonally-expanded mCA in at least one tissue, with incidence strongly correlated with age. The prevalence and genome-wide patterns of mCAs vary considerably across tissue types, suggesting tissue-specific mutagenic exposure and selection pressures. The mCA landscapes in normal adrenal and pituitary glands resemble those in tumors arising from these tissues, whereas the same is not true for the esophagus and skin. Together, our findings show a widespread age-dependent emergence of mCAs across normal human tissues with intricate connections to tumorigenesis.

An in silico study on the detectability of field cancerization through parenchymal analysis of digital mammograms

BACKGROUND

Parenchymal analysis has shown promising performance for the assessment of breast cancer risk through the characterization of the texture features of mammography images. However, the working principles behind this practice are yet not well understood. Field cancerization is a phenomenon associated with genetic and epigenetic alterations in large volumes of cells, putting them on a path of malignancy before the appearance of recognizable cancer signs. Evidence suggests that it can induce changes in the biochemical and optical properties of the tissue.

PURPOSE

The aim of this work was to study whether the extended genetic mutations and epigenetic changes due to field cancerization, and the impact they have on the biochemistry of breast tissues are detectable in the radiological patterns of mammography images.

METHODS

An in silico experiment was designed, which implied the development of a field cancerization model to modify the optical tissue properties of a cohort of 60 voxelized virtual breast phantoms. Mammography images from these phantoms were generated and compared with images obtained from their non-modified counterparts, that is, without field cancerization. We extracted 33 texture features from the breast area to quantitatively assess the impact of the field cancerization model. We analyzed the similarity and statistical equivalence of texture features with and without field cancerization using the t-test, Wilcoxon sign rank test and Kolmogorov-Smirnov test, and performed a discrimination test using multinomial logistic regression analysis with lasso regularization.

RESULTS

With modifications of the optical tissue properties on 3.9% of the breast volume, some texture features started to fail to show equivalence (p < 0.05). At 7.9% volume modification, a high percent of texture features showed statistically significant differences (p < 0.05) and non-equivalence. At this level, multinomial logistic regression analysis of texture features showed a statistically significant performance in the discrimination of mammograms from breasts with and without field cancerization (AUC = 0.89, 95% CI: 0.75-1.00).

CONCLUSIONS

These results support the idea that field cancerization is a feasible underlying working principle behind the distinctive performance of parenchymal analysis in breast cancer risk assessment.

Colonic stem cells from normal tissues adjacent to tumor drive inflammation and fibrosis in colorectal cancer

BACKGROUND

In colorectal cancer (CRC), the normal tissue adjacent to tumor (NAT) communicates actively with the tumor. Adult stem cells from the colon play a crucial role in the development of the colonic epithelium. In the tumor microenvironment, however, it is unclear what changes have occurred in colonic stem cells derived from NAT.

METHODS

Using an intestinal stem cell culture system, we cultured colonic cells from NAT and paired CRC tissue, as well as cells from healthy tissue (HLT). Clonogenicity and differentiation ability were used to compare the function of clones from NAT, HLT and CRC tissues. RNA high-throughput sequencing of these clones was used to identify the molecular characteristics of NAT-derived clones. Coculture of clones from HLT and CRC was used to assess molecular changes.

RESULTS

We found that the morphological characteristics, clonogenic ability, and differentiation ability of NAT-derived clones were consistent with those of HLT-derived clones. However, NAT-derived clones changed at the molecular level. A number of genes were specifically activated in NAT. NAT-derived clones enriched pathways related to inflammation and fibrosis, including epithelial mesenchymal transition (EMT) pathway and TGF-beta signaling pathway. Our results also confirmed that NAT-derived clones could recruit fibroblasts in mice. In addition, HLT-derived clones showed high expression of FOSB when cocultured with tumor cells.

CONCLUSIONS

Our results demonstrate that colonic stem cells from NAT in the tumor microenvironment undergo changes at the molecular level, and these molecular characteristics can be maintained in vitro, which can induce fibrosis and an inflammatory response. Video Abstract.

Exploring breast tissue microbial composition and the association with breast cancer risk factors

BACKGROUND

Microbial dysbiosis has emerged as an important element in the development and progression of various cancers, including breast cancer. However, the microbial composition of the breast from healthy individuals, even relative to risk of developing breast cancer, remains unclear. Here, we performed a comprehensive analysis of the microbiota of the normal breast tissue, which was analyzed in relation to the microbial composition of the tumor and adjacent normal tissue.

METHODS

The study cohorts included 403 cancer-free women (who donated normal breast tissue cores) and 76 breast cancer patients (who donated tumor and/or adjacent normal tissue samples). Microbiome profiling was obtained by sequencing the nine hypervariable regions of the 16S rRNA gene (V1V2, V2V3, V3V4, V4V5, V5V7, and V7V9). Transcriptome analysis was also performed on 190 normal breast tissue samples. Breast cancer risk score was assessed using the Tyrer-Cuzick risk model.

RESULTS

The V1V2 amplicon sequencing resulted more suitable for the analysis of the normal breast microbiome and identified Lactobacillaceae (Firmicutes phylum), Acetobacterraceae, and Xanthomonadaceae (both Proteobacteria phylum) as the most abundant families in the normal breast. However, Ralstonia (Proteobacteria phylum) was more abundant in both breast tumors and histologically normal tissues adjacent to malignant tumors. We also conducted a correlation analysis between the microbiome and known breast cancer risk factors. Abundances of the bacterial taxa Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp. were associated with age (p < 0.0001), racial background (p < 0.0001), and parity (p < 0.0001). Finally, transcriptome analysis of normal breast tissues showed an enrichment in metabolism- and immune-related genes in the tissues with abundant Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp., whereas the presence of Ralstonia in the normal tissue was linked to dysregulation of genes involved in the carbohydrate metabolic pathway.

CONCLUSIONS

This study defines the microbial features of normal breast tissue, thus providing a basis to understand cancer-related dysbiosis. Moreover, the findings reveal that lifestyle factors can significantly affect the normal breast microbial composition.

Radiomic and deep learning characterization of breast parenchyma on full field digital mammograms and specimen radiographs: a pilot study of a potential cancer field effect

Purpose

In women with biopsy-proven breast cancer, histologically normal areas of the parenchyma have shown molecular similarity to the tumor, supporting a potential cancer field effect. The purpose of this work was to investigate relationships of human-engineered radiomic and deep learning features between regions across the breast in mammographic parenchymal patterns and specimen radiographs.

Approach

This study included mammograms from 74 patients with at least 1 identified malignant tumor, of whom 32 also possessed intraoperative radiographs of mastectomy specimens. Mammograms were acquired with a Hologic system and specimen radiographs were acquired with a Fujifilm imaging system. All images were retrospectively collected under an Institutional Review Board-approved protocol. Regions of interest (ROI) of 128 × 128    pixels were selected from three regions: within the identified tumor, near to the tumor, and far from the tumor. Radiographic texture analysis was used to extract 45 radiomic features and transfer learning was used to extract 20 deep learning features in each region. Kendall's Tau-b and Pearson correlation tests were performed to assess relationships between features in each region.

Results

Statistically significant correlations in select subgroups of features with tumor, near to the tumor, and far from the tumor ROI regions were identified in both mammograms and specimen radiographs. Intensity-based features were found to show significant correlations with ROI regions across both modalities.

Conclusions

Results support our hypothesis of a potential cancer field effect, accessible radiographically, across tumor and non-tumor regions, thus indicating the potential for computerized analysis of mammographic parenchymal patterns to predict breast cancer risk.

TCGA RNA-Seq and Tumor-Infiltrating Lymphocyte Imaging Data Reveal Cold Tumor Signatures of Invasive Ductal Carcinomas and Estrogen Receptor-Positive Human Breast Tumors

Comparative studies of immune-active hot and immune-deserted cold tumors are critical for identifying therapeutic targets and strategies to improve immunotherapy outcomes in cancer patients. Tumors with high tumor-infiltrating lymphocytes (TILs) are likely to respond to immunotherapy. We used the human breast cancer RNA-seq data from the cancer genome atlas (TCGA) and classified them into hot and cold tumors based on their lymphocyte infiltration scores. We compared the immune profiles of hot and cold tumors, their corresponding normal tissue adjacent to the tumor (NAT), and normal breast tissues from healthy individuals from the Genotype-Tissue Expression (GTEx) database. Cold tumors showed a significantly lower effector T cells, lower levels of antigen presentation, higher pro-tumorigenic M2 macrophages, and higher expression of extracellular matrix (ECM) stiffness-associated genes. Hot/cold dichotomy was further tested using TIL maps and H&E whole-slide pathology images from the cancer imaging archive (TCIA). Analysis of both datasets revealed that infiltrating ductal carcinoma and estrogen receptor ER-positive tumors were significantly associated with cold features. However, only TIL map analysis indicated lobular carcinomas as cold tumors and triple-negative breast cancers (TNBC) as hot tumors. Thus, RNA-seq data may be clinically relevant to tumor immune signatures when the results are supported by pathological evidence.

Computational modeling of locoregional recurrence with spatial structure identifies tissue-specific carcinogenic profiles

Introduction

Local and regional recurrence after surgical intervention is a significant problem in cancer management. The multistage theory of carcinogenesis precisely places the presence of histologically normal but mutated premalignant lesions surrounding the tumor - field cancerization, as a significant cause of cancer recurrence. The relationship between tissue dynamics, cancer initiation and cancer recurrence in multistage carcinogenesis is not well known.

Methods

This study constructs a computational model for cancer initiation and recurrence by combining the Moran and branching processes in which cells requires 3 or more mutations to become malignant. In addition, a spatial structure-setting is included in the model to account for positional relativity in cell turnover towards malignant transformation. The model consists of a population of normal cells with no mutation; several populations of premalignant cells with varying number of mutations and a population of malignant cells. The model computes a stage of cancer detection and surgery to eliminate malignant cells but spares premalignant cells and then estimates the time for malignant cells to re-emerge.

Results

We report the cellular conditions that give rise to different patterns of cancer initiation and the conditions favoring a shorter cancer recurrence by analyzing premalignant cell types at the time of surgery. In addition, the model is fitted to disease-free clinical data of 8,957 patients in 27 different cancer types; From this fitting, we estimate the turnover rate per month, relative fitness of premalignant cells, growth rate and death rate of cancer cells in each cancer type.

Discussion

Our study provides insights into how to identify patients who are likely to have a shorter recurrence and where to target the therapeutic intervention.

Predicting hormone receptors and PAM50 subtypes of breast cancer from multi-scale lesion images of DCE-MRI with transfer learning technique

BACKGROUND

The recent development of artificial intelligence (AI) technologies coupled with medical imaging data has gained considerable attention, and offers a non-invasive approach for cancer diagnosis and prognosis. In this context, improved breast cancer (BC) molecular characteristics assessment models are foreseen to enable personalized strategies with better clinical outcomes compared to existing screening strategies. And it is a promising approach to developing models for hormone receptors (HR) and subtypes of BC patients from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data.

METHODS

In this institutional review board-approved study, 174 BC patients with both DCE-MRI and RNA-seq data in the local database were analyzed. Slice images from tumor lesions and multi-scale peri-tumor regions were used as model inputs, and five representative pre-trained transfer learning (TF) networks, such as Inception-v3 and Xception, were employed to establish prediction models. A comprehensive analysis was performed using five-fold cross-validation to avoid overfitting, and accuracy (ACC) and area under the receiver operating characteristic curve (AUROC) to evaluate model performance.

RESULTS

Xception achieved the superior results when using solely tumor regions, with highest AUROCs of 0.844 (95% CI: [0.841, 0.847]) and 0.784 (95% CI: [0.781, 0.788]) for estrogen receptor (ER) and progesterone receptor (PR), respectively, and best ACC of 0.467 (95% CI: [0.462, 0.470]) for PAM50 subtypes. A significant improvement in the model performance was observed when images of the peri-tumor region were included, with optimal results achieved using images of the tumor and the 10 mm peri-tumor regions. Xception-based TF models performed most effectively in predicting ER and PR statuses, with the AUROCs were 0.942 (95% CI: [0.940, 0.944]) and 0.920 (95% CI: [0.917, 0.922]), respectively, whereas for PAM50 subtypes, the Inception-v3-based network yielded the highest ACC as 0.742 (95% CI: [0.738, 0.746]).

CONCLUSIONS

Transfer learning analysis based on DCE-MRI data of tumor and peri-tumor regions was helpful to the non-invasive assessment of molecular characteristics of BC.

Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers.

Comparative characterization of 3D chromatin organization in triple-negative breast cancers

Triple-negative breast cancer (TNBC) is a malignant cancer subtype with a high risk of recurrence and an aggressive phenotype compared to other breast cancer subtypes. Although many breast cancer studies conducted to date have investigated genetic variations and differential target gene expression, how 3D chromatin architectures are reorganized in TNBC has been poorly elucidated. Here, using in situ Hi-C technology, we characterized the 3D chromatin organization in cells representing five distinct subtypes of breast cancer (including TNBC) compared to that in normal cells. We found that the global and local 3D architectures were severely disrupted in breast cancer. TNBC cell lines (especially BT549 cells) showed the most dramatic changes relative to normal cells. Importantly, we detected CTCF-dependent TNBC-susceptible losses/gains of 3D chromatin organization and found that these changes were strongly associated with perturbed chromatin accessibility and transcriptional dysregulation. In TNBC tissue, 3D chromatin disorganization was also observed relative to the 3D chromatin organization in normal tissues. We observed that the perturbed local 3D architectures found in TNBC cells were partially conserved in TNBC tissues. Finally, we discovered distinct tissue-specific chromatin loops by comparing normal and TNBC tissues. In this study, we elucidated the characteristics of the 3D chromatin organization in breast cancer relative to normal cells/tissues at multiple scales and identified associations between disrupted structures and various epigenetic features and transcriptomes. Collectively, our findings reveal important 3D chromatin structural features for future diagnostic and therapeutic studies of TNBC.

The 3D architecture of the genome is dramatically altered in an aggressive form of breast cancer, leading to changes in the regulation of gene expression that can fuel tumor growth. A team from South Korea, led by Hyeong-Gon Moon of Seoul National University College of Medicine and Daeyoup Lee of the Korea Advanced Institute of Science and Technology, Daejeon, detailed how chromosomes are positioned and folded within the nucleus of cell liness from five different subtypes of breast cancer. They found that triple-negative breast cancers displayed the most extreme reorganization of their genomes, a pattern also observed in biopsy tissues taken from patients with this subtype of cancer. Knowledge of these conformational changes could inform future efforts to develop therapies and diagnostics for patients with triple-negative breast tumors.

The double agents in liquid biopsy: promoter and informant biomarkers of early metastases in breast cancer

Breast cancer continues to be a major global problem with significant mortality associated with advanced stage and metastases at clinical presentation. However, several findings suggest that metastasis is indeed an early occurrence. The standard diagnostic techniques such as invasive core needle biopsy, serological protein marker assays, and non-invasive radiological imaging do not provide information about the presence and molecular profile of small fractions of early metastatic tumor cells which are prematurely dispersed in the circulatory system. These circulating tumor cells (CTCs) diverge from the primary tumors as clusters with a defined secretome comprised of circulating cell-free nucleic acids and small microRNAs (miRNAs). These circulatory biomarkers provide a blueprint of the mutational profile of the tumor burden and tumor associated alterations in the molecular signaling pathways involved in oncogenesis. Amidst the multitude of circulatory biomarkers, miRNAs serve as relatively stable and precise biomarkers in the blood for the early detection of CTCs, and promote step-wise disease progression by executing paracrine signaling that transforms the microenvironment to guide the metastatic CTCs to anchor at a conducive new organ. Random sampling of easily accessible patient blood or its serum/plasma derivatives and other bodily fluids collectively known as liquid biopsy (LB), forms an efficient alternative to tissue biopsies. In this review, we discuss in detail the divergence of early metastases as CTCs and the involvement of miRNAs as detectable blood-based diagnostic biomarkers that warrant a timely screening of cancer, serial monitoring of therapeutic response, and the dynamic molecular adaptations induced by miRNAs on CTCs in guiding primary and second-line systemic therapy.

Field cancerization in breast cancer

Breast cancer affects one in seven women worldwide during their lifetime. Widespread mammographic screening programs and education campaigns allow for early detection of the disease, often during its asymptomatic phase. Current practice in treatment and recurrence monitoring is based primarily on pathological evaluations but can also encompass genomic evaluations, both of which focus on the primary tumor. Although breast cancer is one of the most studied cancers, patients still recur at a rate of up to 15% within the first 10 years post‐surgery. Local recurrence was originally attributed to tumor cells contaminating histologically normal (HN) tissues beyond the surgical margin, but advances in technology have allowed for the identification of distinct aberrations that exist in the peri‐tumoral tissues themselves. One leading theory to explain this phenomenon is the field cancerization theory. Under this hypothesis, tumors arise from a field of molecularly altered cells that create a permissive environment for malignant evolution, which can occur with or without morphological changes. The traditional histopathology paradigm dictates that molecular alterations are reflected in the tissue phenotype. However, the spectrum of inter‐patient variability of normal breast tissue may obfuscate recognition of a cancerized field during routine diagnostics. In this review, we explore the concept of field cancerization focusing on HN peri‐tumoral tissues: we present the pathological and molecular features of field cancerization within these tissues and discuss how the use of peri‐tumoral tissues can affect research. Our observations suggest that pathological and molecular evaluations could be used synergistically to assess risk and guide the therapeutic management of patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

3D and 4D Tumorigenesis Model for the Quantitative Analysis of Cancer Cell Behavior and Screening for Anticancer Drugs

Cancer cells from cell lines and tumor biopsy tissue undergo aggregation and aggregate coalescence when dispersed in a 3D Matrigel™ matrix. Coalescence is a dynamic process mediated by a subset of cells within the population of cancer cells. In contrast, non-tumorigenic cells from normal cell lines and normal tissues do not aggregate or coalesce, nor do they possess the motile cell types that orchestrate coalescence of cancer cells. Therefore, coalescence is a cancer cell-specific phenotype that may drive tumor growth in vivo, especially in cases of field cancerization. Here, we describe a simple 3D tumorigenesis model that takes advantage of the coalescence capabilities of cancer cells and uses this feature as the basis for a screen for treatments that inhibit tumorigenesis. The screen is especially useful in testing monoclonal antibodies that target cell-cell interactions, cell-matrix interactions, cell adhesion molecules, cell surface receptors, and general cell surface markers. The model can also be used for 2D imaging in a 96-well plate for rapid screening and is adaptable for 3D high-resolution assessment. In the latter case, we show how the 3D model can be optically sectioned with differential interference contrast (DIC) optics, then reconstructed in 4D and quantitatively analyzed by computer-assisted methods, or, alternatively, imaged with confocal microscopy for 4D quantitative analysis of cancer cell interactions with normal cells within the tumor microenvironment. We demonstrate reconstructions and quantitative analyses using the advanced image analysis software J3D-DIAS 4.2, in order to illustrate the types of detailed phenotypic characterizations that have proven useful. Other software packages may be able to perform similar types of analyses.

A five-lncRNA model predicting overall survival in gastric cancer compared with normal tissues

Aims: In cancer research, normal tissues adjacent to the tumor are usually defined as controls to compare with tumor samples, in order to screen out cancer-related genes. Although there is no obvious difference in pathology between normal tissues adjacent to the tumor and healthy tissues, there are significant changes at the molecular level. We aim to explore more potential tumor biomarkers using healthy tissues as controls rather than normal tissues adjacent to the tumor.

Methods: Here we combine the Genotype-Tissue Expression project and The Cancer Genome Atlas for differential gene analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were applied in order to predict the biological effects of related lncRNAs.

Results: We established a 5-lncRNA prognosis model with an AUC value of 0.815. Pathway analysis indicated that 5-lncRNA mainly affected tissue carcinogenesis through PI3K-AKT signaling pathway, Focal adhesion, MAPK signaling pathway.

Conclusion: The 5-lncRNA prognostic model we set up is more conducive to assess the overall survival time of gastric cancer patients.

Mathematical Modeling of Locoregional Recurrence Caused by Premalignant Lesions Formed Before Initial Treatment

Locoregional recurrence after surgery is a major unresolved issue in cancer treatment. Premalignant lesions are considered a cause of cancer recurrence. A study showed that premalignant lesions surrounding the primary tumor drove a high local cancer recurrence rate after surgery in head and neck cancer. Based on the multistage theory of carcinogenesis, cells harboring an intermediate number of mutations are not cancer cells yet but have a higher risk of becoming cancer than normal cells. This study constructed a mathematical model for cancer initiation and recurrence by combining the Moran and branching processes in which cells require two specific mutations to become malignant. There are three populations in this model: (i) normal cells with no mutation, (ii) premalignant cells with one mutation, and (iii) cancer cells with two mutations. The total number of healthy tissue is kept constant to represent homeostasis, and there is a rare chance of mutation every time a cell divides. If a cancer cell with two mutations arises, the cancer population proliferates, violating the homeostatic balance of the tissue. Once the number of cancer cells reaches a certain size, we conduct computational resection and remove the cancer cell population, keeping the ratio of normal and premalignant cells in the tissue unchanged. After surgery, we considered tissue dynamics and eventually observed the second appearance of cancer cells as recurrence. Consequently, we computationally revealed the conditions where the time to recurrence became short by parameter sensitivity analysis. Particularly, when the premalignant cells’ fitness is higher than normal cells, the proportion of premalignant cells becomes large after the surgical resection. Moreover, the mathematical model was fitted to clinical data on disease-free survival of 1,087 patients in 23 cancer types from the TCGA database. Finally, parameter values of tissue dynamics are estimated for each cancer type, where the likelihood of recurrence can be elucidated. Thus, our approach provides insights into the concept to identify the patients likely to experience recurrence as early as possible.

Molecular markers of risk of subsequent invasive breast cancer in women with ductal carcinoma in situ: protocol for a population-based cohort study

INTRODUCTION

Ductal carcinoma in situ (DCIS) of the breast is a non-obligate precursor of invasive breast cancer (IBC). Many DCIS patients are either undertreated or overtreated. The overarching goal of the study described here is to facilitate detection of patients with DCIS at risk of IBC development. Here, we propose to use risk factor data and formalin-fixed paraffin-embedded (FFPE) DCIS tissue from a large, ethnically diverse, population-based cohort of 8175 women with a first diagnosis of DCIS and followed for subsequent IBC to: identify/validate miRNA expression changes in DCIS tissue associated with risk of subsequent IBC; evaluate ipsilateral IBC risk in association with two previously identified marker sets (triple immunopositivity for p16, COX-2, Ki67; Oncotype DX Breast DCIS score); examine the association of risk factor data with IBC risk.

METHODS AND ANALYSIS

We are conducting a series of case-control studies nested within the cohort. Cases are women with DCIS who developed subsequent IBC; controls (2/case) are matched to cases on calendar year of and age at DCIS diagnosis. We project 485 cases/970 controls in the aim focused on risk factors. We estimate obtaining FFPE tissue for 320 cases/640 controls for the aim focused on miRNAs; of these, 173 cases/346 controls will be included in the aim focused on p16, COX-2 and Ki67 immunopositivity, and of the latter, 156 case-control pairs will be included in the aim focused on the Oncotype DX Breast DCIS score®. Multivariate conditional logistic regression will be used for statistical analyses.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the Institutional Review Boards of Albert Einstein College of Medicine (IRB 2014-3611), Kaiser Permanente Colorado, Kaiser Permanente Hawaii, Henry Ford Health System, Mayo Clinic, Marshfield Clinic Research Institute and Hackensack Meridian Health, and from Lifespan Research Protection Office. The study results will be presented at meetings and published in peer-reviewed journals.

The cell of cancer origin provides the most reliable roadmap to its diagnosis, prognosis (biology) and therapy

Cancers arise from single transformed cells from virtually every organ of the body, divide in a relatively uncontrolled manner, and metastasize widely. A search for a "magic bullet" to precisely diagnose, characterize, and ultimately treat cancer has largely failed because cancer cells do not differ significantly from their organ-specific cells of origin. Instead of searching for genomic, epigenetic, transcriptional, and translational differences between cancers and their cells of origin, we should paradoxically focus on what cancer cells have in common with their untransformed cells of origin. This redirected search will lead to improved diagnostic and therapeutic strategies where therapeutic index considerations and drug-limiting toxicities can largely be circumvented. We cite three cancer examples that illustrate this paradigm-shifting strategy: pseudomyxoma peritonei (PP), metastasis of unknown origin (cancers of unknown primary) (MUO), and cancers that arise from potentially dispensable organs (CAD). In each of these examples, the cell of cancer origin still provides the most reliable road map to its diagnosis, prognosis (biology), and therapy.

Cytochrome P450 1B1 Overexpression in Cervical Cancers: Cross-sectional Study

Background

Current standard treatments for patients with recurrent cervical cancer are not very effective and are associated with severe toxicity. Recently, the rational approach for the discovery of new therapies for cervical cancer is based on the alterations in the molecular biology of cancer cells. One of the emerging molecular changes in cancer cells is the aberrant expression of cytochrome P450 1B1 (CYP1B1). This unique enzyme has been reported to be selectively overexpressed in several cancers.

Objective

The aim of this study was to examine CYP1B1 expression in cervical cancers and to assess the enzyme’s relationship with several clinicopathological features.

Methods

Immunohistochemistry was performed to examine CYP1B1 expression in 100 patient samples with cervical cancer and 10 patient samples with normal healthy cervical tissues.

Results

CYP1B1 was expressed in the majority of the cervical cancer samples (91/100, 91.0%) but not in normal healthy cervical samples. The difference in the expression of CYP1B1 between healthy and tumorous cervical tissues was significant (P=.01). Moreover, the frequency of CYP1B1 expression was found to be significantly higher in patients with advanced grades of the disease (P=.03) and in patients having metastasis to the lymph nodes (P=.01). Surprisingly, there was a significantly higher expression of CYP1B1 in patients with a high prevalence of human papilloma virus 16/18 (P=.04).

Conclusions

The differential profile of CYP1B1 expression between cervical cancer tissues and normal cervical tissues suggests that CYP1B1 may be used as a target for future therapeutic exploitations.

Co-Deregulated miRNA Signatures in Childhood Central Nervous System Tumors: In Search for Common Tumor miRNA-Related Mechanics

Simple Summary

Childhood tumors of the central nervous system (CNS) constitute a grave disease and their diagnosis is difficult to be handled. To gain better knowledge of the tumor’s biology, it is essential to understand the underlying mechanisms of the disease. MicroRNAs (miRNAs) are small noncoding RNAs that are dysregulated in many types of CNS tumors and regulate their occurrence and development through specific signal pathways. However, different types of CNS tumors’ area are characterized by different deregulated miRNAs. Here, we hypothesized that CNS tumors could have commonly deregulated miRNAs, i.e., miRNAs that are simultaneously either upregulated or downregulated in all tumor types compared to the normal brain tissue, irrespectively of the tumor sub-type and/or diagnosis. The only criterion is that they are present in brain tumors. This approach could lead us to the discovery of miRNAs that could be used as pan-CNS tumoral therapeutic targets, if successful.

Abstract

Despite extensive experimentation on pediatric tumors of the central nervous system (CNS), related to both prognosis, diagnosis and treatment, the understanding of pathogenesis and etiology of the disease remains scarce. MicroRNAs are known to be involved in CNS tumor oncogenesis. We hypothesized that CNS tumors possess commonly deregulated miRNAs across different CNS tumor types. Aim: The current study aims to reveal the co-deregulated miRNAs across different types of pediatric CNS tumors. Materials: A total of 439 CNS tumor samples were collected from both in-house microarray experiments as well as data available in public databases. Diagnoses included medulloblastoma, astrocytoma, ependydoma, cortical dysplasia, glioblastoma, ATRT, germinoma, teratoma, yoc sac tumors, ocular tumors and retinoblastoma. Results: We found miRNAs that were globally up- or down-regulated in the majority of the CNS tumor samples. MiR-376B and miR-372 were co-upregulated, whereas miR-149, miR-214, miR-574, miR-595 and miR-765 among others, were co-downregulated across all CNS tumors. Receiver-operator curve analysis showed that miR-149, miR-214, miR-574, miR-595 and miR765 could distinguish between CNS tumors and normal brain tissue. Conclusions: Our approach could prove significant in the search for global miRNA targets for tumor diagnosis and therapy. To the best of our knowledge, there are no previous reports concerning the present approach.

Zinc stable isotope analysis reveals Zn dyshomeostasis in benign tumours, breast cancer, and adjacent histologically normal tissue

The disruption of Zn homeostasis has been linked with breast cancer development and progression. To enhance our understanding of changes in Zn homeostasis both inside and around the tumour microenvironment, Zn concentrations and isotopic compositions (δ66Zn) were determined in benign (BT) and malignant (MT) tumours, healthy tissue from reduction mammoplasty (HT), and histologically normal tissue adjacent to benign (NAT(BT)) and malignant tumours (NAT(MT)). Mean Zn concentrations in NAT(BT) are 5.5 µg g-1 greater than in NAT(MT) (p = 0.00056) and 5.1 µg g-1 greater than in HT (p = 0.0026). Zinc concentrations in MT are 12.9 µg g-1 greater than in HT (p = 0.00012) and 13.3 µg g-1 greater than in NAT(MT) (p < 0.0001), whereas δ66Zn is 0.17‰ lower in MT than HT (p = 0.017). Benign tumour Zn concentrations are also elevated compared to HT (p = 0.00013), but are not significantly elevated compared to NAT(BT) (p = 0.32). The δ66Zn of BT is 0.15‰ lower than in NAT(BT) (p = 0.045). The similar light δ66Zn of BT and MT compared to HT and NAT may be related to the isotopic compensation of increased metallothionein (64Zn-rich) expression by activated matrix metalloproteinase (66Zn-rich) in MT, and indicates a resultant 66Zn-rich reservoir may exist in patients with breast tumours. Zinc isotopic compositions thus show promise as a potential diagnostic tool for the detection of breast tumours. The revealed differences of Zn accumulation in healthy and tumour-adjacent tissues require additional investigation.

An introduction to the Cyrcadia Breast Monitor: A wearable breast health monitoring device

BACKGROUND

The most common breast cancer detection modalities are generally limited by radiation exposure, discomfort, high costs, inter-observer variabilities in image interpretation, and low sensitivity in detecting cancer in dense breast tissue. Therefore, there is a clear need for an affordable and effective adjunct modality that can address these limitations. The Cyrcadia Breast Monitor (CBM) is a non-invasive, non-compressive, and non-radiogenic wearable device developed as an adjunct to current modalities to assist in the detection of breast tissue abnormalities in any type of breast tissue.

METHODS

The CBM records thermodynamic metabolic data from the breast skin surface over a period of time using two wearable biometric patches consisting of eight sensors each and a data recording device. The acquired multi-dimensional temperature time series data are analyzed to determine the presence of breast tissue abnormalities. The objective of this paper is to present the scientific background of CBM and also to describe the history around the design and development of the technology.

RESULTS

The results of using the CBM device in the initial clinical studies are also presented. Twenty four-hour long breast skin temperature circadian rhythm data was collected from 93 benign and 108 malignant female study subjects in the initial clinical studies. The predictive model developed using these datasets could differentiate benign and malignant lesions with 78% accuracy, 83.6% sensitivity and 71.5% specificity. A pilot study of 173 female study subjects is underway, in order to validate this predictive model in an independent test population.

CONCLUSIONS

The results from the initial studies indicate that the CBM may be valuable for breast health monitoring under physician supervision for confirmation of any abnormal changes, potentially prior to other methods, such as, biopsies. Studies are being conducted and planned to validate the technology and also to evaluate its ability as an adjunct breast health monitoring device for identifying abnormalities in difficult-to-diagnose dense breast tissue.

Why is cancer so common a disease in people yet so rare at a cellular level?

Cancers are common diseases in people and yet, on a cellular level, are quite rare. The vast majority of both sporadic, spontaneous cancers and inherited germline cancers arise in single foci from singly transformed cells despite the fact that, in the former, carcinogenic factors bathe fields of millions of potential target cells and, in the latter, the predisposing germline mutations are present in every cell of a given organ and, in fact, every cell of the body. Although the multi-hit theory of carcinogenesis has been invoked to explain such things as cancer latency, which is the period between cancer initiation and emergence and the cancer-aging relationship where an accumulation of "hits" over a period of time are necessary for cancer emergence, the multi-hit theory falls short in explaining the rareness of transformation at a cellular level. This is so because many cancers are not due to multiple hits, and even for those that are, it would be expected that many cells would be exposed to those factors inducing the hits. Although the tumor stem/progenitor cell compartmental theory of tumorigenesis characterizes a tumor compartment that is capable of self-renewal and multipotency, accounting for cancer relapses and recurrences, this compartmental theory alone cannot account for the rareness of initial transformation at a cellular level as the cancer stem/progenitor cell compartment is already transformed and considerable in size. This study advances a different and novel hypothesis that oncogenesis is regulated and ultimately determined by a cell of origin's critical state of differentiation. Before and after this critical state of differentiation has been reached, target cells cannot transform and give rise to cancer even when they receive the necessary carcinogenic insults or have the requisite transforming tumor suppressor genes or oncogenes. As support for this hypothesis, the study cites preliminary evidence using oncogene-containing transgenic mice that develop mammary carcinomas, to derive tail vein fibroblasts converted to iPSCs which, when left undifferentiated, and injected into the cleared fat pads of non-transgenic background mice give rise to mammary gland ontogeny and mammary gland carcinogenesis. However, when first differentiated in vitro into multiply different non-mammary lineages prior to injection, they fail to do so. The hypothesis has widespread implications for chemopreventive strategies.

Field cancerization in the understanding of parenchymal analysis of mammograms for breast cancer risk assessment

In recent years, mammographic image analysis has shown great potential for breast cancer risk assessment. The aim of risk assessment is to predict how likely a woman is to develop breast cancer in the future. Several studies suggest that computerized parenchymal analysis of mammograms can be utilized as an independent imaging biomarker of breast cancer. Parenchymal analysis consists of the quantitative assessment of visual texture patterns in mammograms to infer the level of risk. In spite of substantial evidence of the association between parenchymal patterns and breast cancer risk, its biological foundations remain poorly understood. In this work, we draw a hypothesis that links the field cancerization (FC) with breast cancer risk assessment based on the parenchymal analysis. In the literature, the FC is interpreted as a biochemical anomaly amplification in otherwise healthy cells due to the effect of pre-cancerous transformed cells in surrounding regions. Our hypothesis is that these biochemical anomaly amplifications change the cellular micro-environment which, in turn, alter tissue responses to X-ray radiation. As a result, it is reasonable to think that these changes influence the interaction of X-rays with parenchymal - the functional - breast tissue thus enabling cancer prediction by analyzing X-ray images of the breast. We believe that our hypothesis provides an actionable explanation as to how computerized parenchymal analysis of apparently normal mammograms can be successfully utilized for the stratification of breast cancer risk.

Diagnosis of Benign and Malignant Breast Lesions on DCE-MRI by Using Radiomics and Deep Learning With Consideration of Peritumor Tissue

BACKGROUND

Computer-aided methods have been widely applied to diagnose lesions detected on breast MRI, but fully-automatic diagnosis using deep learning is rarely reported.

PURPOSE

To evaluate the diagnostic accuracy of mass lesions using region of interest (ROI)-based, radiomics and deep-learning methods, by taking peritumor tissues into consideration.

STUDY TYPE

Retrospective.

POPULATION

In all, 133 patients with histologically confirmed 91 malignant and 62 benign mass lesions for training (74 patients with 48 malignant and 26 benign lesions for testing).

FIELD STRENGTH/SEQUENCE

3T, using the volume imaging for breast assessment (VIBRANT) dynamic contrast-enhanced (DCE) sequence.

ASSESSMENT

3D tumor segmentation was done automatically by using fuzzy-C-means algorithm with connected-component labeling. A total of 99 texture and histogram parameters were calculated for each case, and 15 were selected using random forest to build a radiomics model. Deep learning was implemented using ResNet50, evaluated with 10-fold crossvalidation. The tumor alone, smallest bounding box, and 1.2, 1.5, 2.0 times enlarged boxes were used as inputs.

STATISTICAL TESTS

The malignancy probability was calculated using each model, and the threshold of 0.5 was used to make a diagnosis.

RESULTS

In the training dataset, the diagnostic accuracy was 76% using three ROI-based parameters, 84% using the radiomics model, and 86% using ROI + radiomics model. In deep learning using the per-slice basis, the area under the receiver operating characteristic (ROC) was comparable for tumor alone, smallest and 1.2 times box (AUC = 0.97-0.99), which were significantly higher than 1.5 and 2.0 times box (AUC = 0.86 and 0.71, respectively). For per-lesion diagnosis, the highest accuracy of 91% was achieved when using the smallest bounding box, and that decreased to 84% for tumor alone and 1.2 times box, and further to 73% for 1.5 times box and 69% for 2.0 times box. In the independent testing dataset, the per-lesion diagnostic accuracy was also the highest when using the smallest bounding box, 89%.

DATA CONCLUSION

Deep learning using ResNet50 achieved a high diagnostic accuracy. Using the smallest bounding box containing proximal peritumor tissue as input had higher accuracy compared to using tumor alone or larger boxes.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2.

Gastric Normal Adjacent Mucosa Versus Healthy and Cancer Tissues: Distinctive Transcriptomic Profiles and Biological Features

Gastric cancer (GC) is a leading cause of cancer-related deaths in the world. Molecular heterogeneity is a major determinant for the clinical outcomes and an exhaustive tumor classification is currently missing. Histologically normal tissue adjacent to the tumor (NAT) is commonly used as a control in cancer studies, nevertheless a recently published paper described the unique characteristics of the NAT in several tumor types. Little is known about the global gene expression profile of gastric NAT (gNAT) which could be an effective tool for a more realistic definition of GC molecular signature. Here, we integrated data of 512 samples from the Genotype-Tissue Expression project (GETx) and The Cancer Genome Atlas (TCGA) to analyze the transcriptome of healthy gastric tissues, gNAT, and GC samples. We validated TCGA-GETx data mining through inHouse gNAT and GC expression dataset. Differential gene expression together with pathway enrichment analyses, indeed, led to different results when using the gNAT or the healthy tissue as control. Based on our analyses, gNAT showed a peculiar gene signature and biological features, like the estrogen receptor pathways activation, suggesting a molecular behavior partially different from both healthy and GC tissues. Therefore, using gNAT as healthy control tissue in the characterization of tumor associated biological processes and pathways could lead to suboptimal results.

Reciprocal signaling and direct physical interactions between fibroblasts and breast cancer cells in a 3D environment

Tumorigenic cells undergo cell aggregation and aggregate coalescence in a 3D Matrigel environment. Here, we expanded this 3D platform to assess the interactions of normal human dermal fibroblasts (NHDFs) and human primary mammary fibroblasts (HPMFs) with breast cancer-derived, tumorigenic cells (MDA-MB-231). Medium conditioned by MDA-MB-231 cells activates both types of fibroblasts, imbuing them with the capacity to accelerate the rate of aggregation and coalescence of MDA-MB-231 cells more than four fold. Acceleration is achieved 1) by direct physical interactions with MDA-MB-231 cells, in which activated fibroblasts penetrate the MDA-MB-231/Matrigel 3D environment and function as supporting scaffolds for MDA-MB-231 aggregation and coalescence, and 2) through the release of soluble accelerating factors, including matrix metalloproteinase (MMPs) and, in the case of activated NHDFs, SDF-1α/CXCL12. Fibroblast activation includes changes in morphology, motility, and gene expression. Podoplanin (PDPN) and fibroblast activation protein (FAP) are upregulated by more than nine-fold in activated NHDFs while activated HPMFs upregulate FAP, vimentin, desmin, platelet derived growth factor receptor A and S100A4. Overexpression of PDPN, but not FAP, in NHDF cells in the absence of MDA-MB-231-conditioned medium, activates NHDFs. These results reveal that complex reciprocal signaling between fibroblasts and cancer cells, coupled with their physical interactions, occurs in a highly coordinated fashion that orchestrates aggregation and coalescence, behaviors specific to cancer cells in a 3D environment. These in vitro interactions may reflect events involved in early tumorigenesis, particularly in cases of field cancerization, and may represent a new mechanism whereby cancer-associated fibroblasts (CAFs) promote tumor growth.

Leveraging Spatial Variation in Tumor Purity for Improved Somatic Variant Calling of Archival Tumor Only Samples

Archival tumor samples represent a rich resource of annotated specimens for translational genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available in the retrospective setting, making it difficult to distinguish between true somatic variants and individual-specific germline variants. Archival sections often contain adjacent normal tissue, but this tissue can include infiltrating tumor cells. As existing comparative somatic variant callers are designed to exclude variants present in the normal sample, a novel approach is required to leverage adjacent normal tissue with infiltrating tumor cells for somatic variant calling. Here we present lumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient, built upon our previous single sample tumor only variant caller lumosVar 1.0. The approach assumes that the allelic fraction of somatic variants and germline variants follow different patterns as tumor content and copy number state change. lumosVar 2.0 estimates allele specific copy number and tumor sample fractions from the data, and uses a to model to determine expected allelic fractions for somatic and germline variants and to classify variants accordingly. To evaluate the utility of lumosVar 2.0 to jointly call somatic variants with tumor and adjacent normal samples, we used a glioblastoma dataset with matched high and low tumor content and germline whole exome sequencing data (for true somatic variants) available for each patient. Both sensitivity and positive predictive value were improved when analyzing the high tumor and low tumor samples jointly compared to analyzing the samples individually or in-silico pooling of the two samples. Finally, we applied this approach to a set of breast and prostate archival tumor samples for which tumor blocks containing adjacent normal tissue were available for sequencing. Joint analysis using lumosVar 2.0 detected several variants, including known cancer hotspot mutations that were not detected by standard somatic variant calling tools using the adjacent tissue as presumed normal reference. Together, these results demonstrate the utility of leveraging paired tissue samples to improve somatic variant calling when a constitutional sample is not available.

Bovine leukemia virus DNA associated with breast cancer in women from South Brazil

Breast cancer is a neoplastic condition with a high morbidity and mortality amongst women worldwide. Recent data linking bovine leukemia virus (BLV) with breast cancer has been contested already. Our study investigated the presence of BLV genome in healthy (n = 72) and cancerous (n = 72) paraffin-embedded samples of breast tissues from women in south Brazil. BLV DNA was found most frequently (30.5%) in breast cancer tissue than in healthy breast (13.9%) (Odds ratio = 2.73; confidence interval = 1.18-6.29; p = 0.027). In contrast, antibodies to BLV were found in a very small percentage of healthy blood donors. There was no association between BLV DNA and other tumor prognostic biological markers such as hormonal receptors, HER2 oncoprotein, proliferation index, metastasis in sentinels lymph nodes, and tumor grade and size. Our findings suggest that BLV should be considered a potential predisposing factor to breast cancer in women.

A genomic ruler to assess oncogenic transition between breast tumor and stroma

Background

Cancers induce gene expression alterations in stroma surrounding tumors that supports cancer progression. However, it is actually not at all known the extent of altered stromal gene expression enacted by tumors nor the extent to which altered stromal gene expression penetrates the stromal tissue. Presently, post-surgical “tumor-free” stromal tissue is determined to be cancer-free based on solely on morphological normality—a criteria that has not changed in more than 100 years despite the existence of sophisticated gene expression data to the contrary. We therefore investigated the extent to which breast tumors alter stromal gene expression in three dimensions in women undergoing mastectomy with the intent of providing a genomic determination for development of future risk of recurrence criteria, and to inform the need for adjuvant full-breast irradiation.

Methods and findings

Genome-wide gene expression changes were determined in histopathologically normal breast tissue in 33 women undergoing mastectomy for stage II and III primary invasive ductal carcinoma at serial distances in three dimensions from the tumor. Gene expression was determined by genome-wide mRNA analysis and subjected to metagene mRNA characterization. Tumor-like gene expression signatures in stroma were identified that surprisingly transitioned to a plastic, normalizing homeostatic signature with distance from tumor. Stroma closest to tumor displayed a pronounced tumor-like signature enriched in cancer-promoting pathways involved in disruption of basement membrane, cell migration and invasion, WNT signaling and angiogenesis. By 2 cm from tumor in all dimensions, stromal tissues were in transition, displaying homeostatic and tumor suppressing gene activity, while also expressing cancer supporting pathways.

Conclusions

The dynamics of gene expression in the post-tumor breast stroma likely co-determines disease outcome: reversion to normality or transition to transformation in morphologically normal tissue. Our stromal genomic signature may be important for personalizing surgical and adjuvant therapeutic decisions and risk of recurrence.

Quantitative analysis of peri-tumor fat in different molecular subtypes of breast cancer

BACKGROUND AND PURPOSES

The aim of this study was to develop morphological analytic methods to analyze the tumor-fat interface and in different peritumoral shells away from the tumor, and to compare the results among three molecular subtypes of breast cancer.

MATERIALS AND METHODS

A total of 102 women (mean age 48.5 y/o) with solitary well-defined breast cancers were analyzed, including 46 human epidermal growth factor receptor 2 (HER2) (+), 46 HER2(-) hormonal receptor (HR) (+), and 10 triple negative (TN) breast cancers. The tumor lesion, the breast, the fibroglandular and fatty tissue were segmented using well-established methods. The whole breast fat percentage and the peri-tumor interface fat percentage were measured. Three shells (SH1, SH2, SH3) surrounding the convex hall of the three dimensional (3D) tumor were defined and in each shell the volumetric percentage of fat was calculated. The peri-tumor interface fat percentage and the volumetric percentage of fat in the three peri-tumoral shells were compared among different subtypes.

RESULTS

In the TN group, the fat percentage on the tumor boundary was 43 ± 20% and 78 ± 12% for two dimensional (2D) and 3D measurement, respectively, which were the highest among the three subtypes but not significantly different. The fat percentage in SH2 and SH3 in the TN group was 82 ± 7% and 85 ± 7%, which was significantly higher compared to the two other two subtypes. The results remained after controlling for the whole breast fat percentage.

CONCLUSIONS

This study provided a feasible method for quantitative analysis of peri-tumoral tissue characteristics. Because of small patient number, the finding that TN tumors had the highest peri-tumor fat content among the three subtypes needs to be further verified with a large cohort study.

Aberrant DNA methylation of the p16, APC, MGMT, TIMP3 and CDH1 gene promoters in tumours and the surgical margins of patients with oral cavity cancer

Oral cavity cancer is a type of head and neck squamous cell carcinoma (HNSCC) and contributes to significant morbidity and mortality each year. An epigenetic pathway of transcriptional inactivation for many genes has been described in various cancers, including HNSCC. For our study, we selected genes for which silencing caused by hypermethylation can promote cancer development. In 75 primary HNSCC tumours and paired surgical margins, we investigated the methylation status of the p16, APC, MGMT, TIMP3 and CDH1 gene promoters by methylation-specific PCR after bisulphite treatment. The promoter methylation rates of p16, APC, MGMT, TIMP3 and CDH1 in tumours were 58.67%, 49.33%, 58.67%, 50.67%, and 57.33% and 50.67%, 41.33%, 37.33%, 42.67%, and 25.33% in the surgical margin, respectively. Our observations confirm the presence of epigenetic changes not only in the cancer cells, but also in the surrounding mucosa and represent a basis for further analysis to unravel these complicated issues. Appropriate cancer risk assessment based on epigenetic alterations in surgical margins may influence a patient's diagnosis and cure.

FFPE breast tumour blocks provide reliable sources of both germline and malignant DNA for investigation of genetic determinants of individual tumour responses to treatment

Background

Bio-banked formalin-fixed paraffin-embedded (FFPE) tissues provide an excellent opportunity for translational genomic research. Historically matched blood has not always been collected as a source of germline DNA. This project aimed to establish if normal FFPE breast tissue could be used as an alternative to blood.

Methods

Exome sequencing was carried out on matched tumour tissue, normal breast tissue and blood on five patients in the START trial. Retrieved samples had been archived at different centres for at least 13 years. Following tissue macro-dissection and DNA extraction, targeted exome capture was performed using SureSelect Human All Exome v5 reagents (Agilent). Illumina paired-end libraries were prepared from the captured target regions and sequenced on a HiSeq2500 (Illumina) acquiring 2 × 75 bp reads. Somatic variants were called using the MuTect software analysis tool and copy number abnormalities (CNA) were identified using CNVkit. Targeted sequencing and droplet digital PCR were used to validate somatic variants and CNA, respectively.

Results

Overlap of somatic variants and CNA called on tumour versus blood and tumour versus normal breast tissue was good. Agreement in somatic variant calling ranged from 76.9 to 93.6%. Variants with an allele frequency lower than 10% were more difficult to validate irrespective of the type of germline DNA used. Pearson’s correlation coefficients for paired comparisons of CNA using blood or normal tissue as reference ranged from 0.70 to 0.94.

Conclusions

There is good correlation between the somatic mutations and CNA called using archived blood or normal breast tissue as germline reference material.

Electronic supplementary material

The online version of this article (10.1007/s10549-018-4798-7) contains supplementary material, which is available to authorised users.

Cancer-associated fibroblasts in tumor microenvironment - Accomplices in tumor malignancy

There is much cellular heterogeneity in the tumor microenvironment. The tumor epithelia and stromal cells co-evolve, and this reciprocal relationship dictates almost every step of cancer development and progression. Despite this, many anticancer therapies are designed around druggable features of tumor epithelia, ignoring the supportive role of stromal cells. Cancer-associated fibroblasts (CAFs) are the dominant cell type within the reactive stroma of many tumor types. Numerous previous studies have highlighted a pro-tumorigenic role for CAFs via secretion of various growth factors, cytokines, chemokines, and the degradation of extracellular matrix. Recent works showed that CAFs secrete H₂O₂ to effect stromal-mediated field cancerization, transform primary epithelial cells, and aggravate cancer cell aggressiveness, in addition to inflammatory and mitogenic factors. Molecular characterization of CAFs also underscores the importance of Notch and specific nuclear receptor signaling in the activation of CAFs. This review consolidates recent findings of CAFs and highlights areas for future investigations.

Precancer in ulcerative colitis: the role of the field effect and its clinical implications

Cumulative evidence indicates that a significant proportion of cancer evolution may occur before the development of histological abnormalities. While recent improvements in DNA sequencing technology have begun to reveal the presence of these early preneoplastic clones, the concept of 'premalignant field' was already introduced by Slaughter more than half a century ago. Also referred to as 'field effect', 'field defect' or 'field cancerization', these terms describe the phenomenon by which molecular alterations develop in normal-appearing tissue and expand to form premalignant patches with the potential to progress to dysplasia and cancer. Field effects have been well-characterized in ulcerative colitis, an inflammatory bowel disease that increases the risk of colorectal cancer. The study of the molecular alterations that define these fields is informative of mechanisms of tumor initiation and progression and has provided potential targets for early cancer detection. Herein, we summarize the current knowledge about the molecular alterations that comprise the field effect in ulcerative colitis and the clinical utility of these fields for cancer screening and prevention.

Comprehensive analysis of normal adjacent to tumor transcriptomes

Histologically normal tissue adjacent to the tumor (NAT) is commonly used as a control in cancer studies. However, little is known about the transcriptomic profile of NAT, how it is influenced by the tumor, and how the profile compares with non-tumor-bearing tissues. Here, we integrate data from the Genotype-Tissue Expression project and The Cancer Genome Atlas to comprehensively analyze the transcriptomes of healthy, NAT, and tumor tissues in 6506 samples across eight tissues and corresponding tumor types. Our analysis shows that NAT presents a unique intermediate state between healthy and tumor. Differential gene expression and protein–protein interaction analyses reveal altered pathways shared among NATs across tissue types. We characterize a set of 18 genes that are specifically activated in NATs. By applying pathway and tissue composition analyses, we suggest a pan-cancer mechanism of pro-inflammatory signals from the tumor stimulates an inflammatory response in the adjacent endothelium.

Normal tissue adjacent to the tumour (NAT) is often used as a control in cancer studies. Here, the authors analyse across cancer types the transcriptomes of healthy, NAT, and tumour tissues, and find that NAT presents a unique state, potentially due to inflammatory response of the NAT to the tumour tissue.

What influences preneoplastic colorectal lesion recurrence?

The hypothesis of the local recurrence of preneoplastic lesions was first put forward in the 1950s. Disease recurrence may result from an inherent imbalance in cell proliferation that promotes carcinogenesis in apparently normal mucosa. Our review sheds light on how early preneoplastic lesions could be used to diagnose relapsed preneoplastic and, developing neoplastic lesions. We focus in detail on the clinical-pathological and molecular features of adenoma subtypes and their role in relapsed adenoma and their development into colorectal carcinoma. Moreover, we include the data available on microbiota and its metabolites and their role in recurrence. We strongly believe that a significant improvement could be achieved in colorectal screening by introducing personalized endoscopic surveillance for polyp-bearing patients on the basis of the presence of molecular markers that are predictive of recurrence.

Expression of ezrin and moesin in primary breast carcinoma and matched lymph node metastases

Ezrin, radixin, moesin (ERM) are important membrane-cytoskeletal crosslinkers and are suggested to play important role in cancer progression and metastasis. Even though ERM proteins were generally considered to be functionally redundant and the most studied was ezrin, recent studies highlight their distinct roles in metastatic process. Little information is available regarding the role of individual ERM proteins and their phosphorylated forms in human breast cancer. Our study is the first to examine expression of ezrin, moesin and their phosphorylated forms in primary breast tumors and matched lymph node metastases (LNMs) and their correlation with clinicopathological variables. A total of 88 primary breast cancer, 91 LNMs, 54 intraductal carcinoma and 26 normal adjacent breast tissue samples from tissue microarrays were studied. Expression was determined by immunohistochemistry, the intensity and number of positive cells was scored. Statistical analysis of protein expression and patients' age, tumor grade and hormonal status was performed. No statistical significant difference was found in ezrin, moesin, p-ezrinTyr353 and pan-p-ezrinThr567/radixinThr564/moesinThr558 expression between primary tumors and LNMs. Even though it was not significant, moesin expression varied between primary tumors, intraductal carcinoma, normal breast adjacent tissue and LNMs. A significant positive correlation between moesin and tumor grade has been proven. Even though primary tumors and matched LNMs did not show different expression patterns, moesin correlated significantly with higher tumor grade. Its positivity in intraductal carcinoma and normal breast tissue adjacent to cancer might indicate its role in tumor intiation/progression.

Hypermethylation of CDKN2A exon 2 in tumor, tumor-adjacent and tumor-distant tissues from breast cancer patients

BACKGROUND

Breast carcinogenesis is a multistep process involving genetic and epigenetic changes. Tumor tissues are frequently characterized by gene-specific hypermethylation and global DNA hypomethylation. Aberrant DNA methylation levels have, however, not only been found in tumors, but also in tumor-surrounding tissue appearing histologically normal. This phenomenon is called field cancerization. Knowledge of the existence of a cancer field and its spread are of clinical relevance. If the tissue showing pre-neoplastic lesions is not removed by surgery, it may develop into invasive carcinoma.

METHODS

We investigated the prevalence of gene-specific and global DNA methylation changes in tumor-adjacent and tumor-distant tissues in comparison to tumor tissues from the same breast cancer patients (n = 18) and normal breast tissues from healthy women (n = 4). Methylation-sensitive high resolution melting (MS-HRM) analysis was applied to determine methylation levels in the promoters of APC, BRCA1, CDKN2A (p16), ESR1, HER2/neu and PTEN, in CDKN2A exon 2 and in LINE-1, as indicator for the global DNA methylation extent. The methylation status of the ESR2 promoter was determined by pyrosequencing.

RESULTS

Tumor-adjacent and tumor-distant tissues frequently showed pre-neoplastic gene-specific and global DNA methylation changes. The APC promoter (p = 0.003) and exon 2 of CDKN2A (p < 0.001) were significantly higher methylated in tumors than in normal breast tissues from healthy women. For both regions, significant differences were also found between tumor and tumor-adjacent tissues (p = 0.001 and p < 0.001, respectively) and tumor and tumor-distant tissues (p = 0.001 and p < 0.001, respectively) from breast cancer patients. In addition, tumor-adjacent (p = 0.002) and tumor-distant tissues (p = 0.005) showed significantly higher methylation levels of CDKN2A exon 2 than normal breast tissues serving as control. Significant correlations were found between the proliferative activity and the methylation status of CDKN2A exon 2 in tumor (r = -0.485, p = 0.041) and tumor-distant tissues (r = -0.498, p = 0.036).

CONCLUSIONS

From our results we can conclude that methylation changes in CDKN2A exon 2 are associated with breast carcinogenesis. Further investigations are, however, necessary to confirm that hypermethylation of CDKN2A exon 2 is associated with tumor proliferative activity.

Melanoma cells undergo aggressive coalescence in a 3D Matrigel model that is repressed by anti-CD44

Using unique computer-assisted 3D reconstruction software, it was previously demonstrated that tumorigenic cell lines derived from breast tumors, when seeded in a 3D Matrigel model, grew as clonal aggregates which, after approximately 100 hours, underwent coalescence mediated by specialized cells, eventually forming a highly structured large spheroid. Non-tumorigenic cells did not undergo coalescence. Because histological sections of melanomas forming in patients suggest that melanoma cells migrate and coalesce to form tumors, we tested whether they also underwent coalescence in a 3D Matrigel model. Melanoma cells exiting fragments of three independent melanomas or from secondary cultures derived from them, and cells from the melanoma line HTB-66, all underwent coalescence mediated by specialized cells in the 3D model. Normal melanocytes did not. However, coalescence of melanoma cells differed from that of breast-derived tumorigenic cell lines in that they 1) coalesced immediately, 2) underwent coalescence as individual cells as well as aggregates, 3) underwent coalescence far faster and 4) ultimately formed long, flat, fenestrated aggregates that were extremely dynamic. A screen of 51 purified monoclonal antibodies (mAbs) targeting cell surface-associated molecules revealed that two mAbs, anti-beta 1 integrin/(CD29) and anti-CD44, blocked melanoma cell coalescence. They also blocked coalescence of tumorigenic cells derived from a breast tumor. These results add weight to the commonality of coalescence as a characteristic of tumorigenic cells, as well as the usefulness of the 3D Matrigel model and software for both investigating the mechanisms regulating tumorigenesis and screening for potential anti-tumorigenesis mAbs.

Tumor-induced Stromal STAT1 Accelerates Breast Cancer via Deregulating Tissue Homeostasis

The tumor microenvironment (TME), the dynamic tissue space in which the tumor exists, plays a significant role in tumor initiation, and is a key contributor in cancer progression; however, little is known about tumor-induced changes in the adjacent tissue stroma. Herein, tumor-induced changes in the TME were explored at the morphologic and molecular level to further understand cancer progression. Tumor-adjacent mammary glands (TAG) displayed altered branching morphology, expansion of myofibroblasts, and increased mammosphere formation, broadly suggesting a tumor-induced field effect. FACS analysis of TAGs demonstrated an increased number of Lin^-CD24⁺/CD49⁺ enriched mammary gland stem cells (MaSC), suggesting deregulated tissue homeostasis in TAGs. Comparative transcriptome analysis of TAGs and contralateral control glands coupled with meta-analysis on differentially expressed genes with two breast cancer stromal patient microarray datasets identified shared upregulation of STAT1. Knockdown of STAT1 in cancer-associated fibroblast (CAF) cocultured with human breast cancer cells altered cancer cell proliferation, indicating a role for STAT1 as a stromal contributor of tumorigenesis. Furthermore, depletion of STAT1 in CAFs significantly reduced periductal reactive fibrosis and delayed early breast cancer progression in vivo Finally, cotreatment with fludarabine, a FDA-approved STAT1 activation inhibitor and DNA synthesis inhibitor, in combination with doxorubicin, showed enhanced therapeutic efficacy in treating mouse mammary gland tumors. Taken together, these results demonstrate that stromal STAT1 expression promotes tumor progression and is a potential therapeutic target for breast cancer.Implications: Tumors induce stromal STAT1-dependent cytokine secretion that promotes tumor cell proliferation and can be targeted using clinically-approved inhibitors of STAT1. Mol Cancer Res; 15(5); 585-97. ©2017 AACR.

Could field cancerization be interpreted as a biochemical anomaly amplification due to transformed cells?

Field cancerization is a concept used to explain cellular and molecular alterations in tissue associated to neoplasia and cancer. This effect was proposed by Slaughter in order to explain the development of multiple primary tumors and locally recurrent cancer. The particular changes associated with this effect, in each type of cancer, have been detected even at distances greater than 10cm off the tumor, in areas classified as normal by histopathological studies. Early detection of lung, colon, and ovary cancer has been reported by the use of Partial Wave Microscopy Spectroscopy (PWS) and has been explained in terms of the field cancerization effect. Until now, field cancerization has been studied as a field effect and we hypothesize that it can be understood as an amplifying effect of biochemical abnormalities in cells, which leads us to ask the question: Could field cancerization be interpreted as a biochemical anomaly amplification due to transformed cells? We propose this question because the biochemical changes due to field cancerization alter the dynamics of molecules and cells in abnormal tissues in comparison to normal ones, these alterations modify the interaction of intracellular and extracellular medium, as well as cellular movement. We hypothesize that field cancerization when interpreted as an amplification effect can be used for the early detection of cancer by measuring the change of cell dynamics.

Quantifying the Dynamics of Field Cancerization in Tobacco-Related Head and Neck Cancer: A Multiscale Modeling Approach

High rates of local recurrence in tobacco-related head and neck squamous cell carcinoma (HNSCC) are commonly attributed to unresected fields of precancerous tissue. Because they are not easily detectable at the time of surgery without additional biopsies, there is a need for noninvasive methods to predict the extent and dynamics of these fields. Here, we developed a spatial stochastic model of tobacco-related HNSCC at the tissue level and calibrated the model using a Bayesian framework and population-level incidence data from the Surveillance, Epidemiology, and End Results (SEER) registry. Probabilistic model analyses were performed to predict the field geometry at time of diagnosis, and model predictions of age-specific recurrence risks were tested against outcome data from SEER. The calibrated models predicted a strong dependence of the local field size on age at diagnosis, with a doubling of the expected field diameter between ages at diagnosis of 50 and 90 years, respectively. Similarly, the probability of harboring multiple, clonally unrelated fields at the time of diagnosis was found to increase substantially with patient age. On the basis of these findings, we hypothesized a higher recurrence risk in older than in younger patients when treated by surgery alone; we successfully tested this hypothesis using age-stratified outcome data. Further clinical studies are needed to validate the model predictions in a patient-specific setting. This work highlights the importance of spatial structure in models of epithelial carcinogenesis and suggests that patient age at diagnosis may be a critical predictor of the size and multiplicity of precancerous lesions. Cancer Res; 76(24); 7078-88. ©2016 AACR.

Signatures of post-zygotic structural genetic aberrations in the cells of histologically normal breast tissue that can predispose to sporadic breast cancer

Sporadic breast cancer (SBC) is a common disease without robust means of early risk prediction in the population. We studied 282 females with SBC, focusing on copy number aberrations in cancer-free breast tissue (uninvolved margin, UM) outside the primary tumor (PT). In total, 1162 UMs (1–14 per breast) were studied. Comparative analysis between UM(s), PT(s), and blood/skin from the same patient as a control is the core of the study design. We identified 108 patients with at least one aberrant UM, representing 38.3% of cases. Gains in gene copy number were the principal type of mutations in microscopically normal breast cells, suggesting that oncogenic activation of genes via increased gene copy number is a predominant mechanism for initiation of SBC pathogenesis. The gain of ERBB2, with overexpression of HER2 protein, was the most common aberration in normal cells. Five additional growth factor receptor genes (EGFR, FGFR1, IGF1R, LIFR, and NGFR) also showed recurrent gains, and these were occasionally present in combination with the gain of ERBB2. All the aberrations found in the normal breast cells were previously described in cancer literature, suggesting their causative, driving role in pathogenesis of SBC. We demonstrate that analysis of normal cells from cancer patients leads to identification of signatures that may increase risk of SBC and our results could influence the choice of surgical intervention to remove all predisposing cells. Early detection of copy number gains suggesting a predisposition toward cancer development, long before detectable tumors are formed, is a key to the anticipated shift into a preventive paradigm of personalized medicine for breast cancer.