Identifying a highly-aggressive DCIS subgroup by studying intra-individual DCIS heterogeneity among invasive breast cancer patients

Differentiation of histological calcification classifications in breast cancer using ultrashort echo time and chemical shift-encoded imaging MRI

Introduction

Ductal carcinoma in situ (DCIS) accounts for 25% of newly diagnosed breast cancer cases with only 14%-53% developing into invasive ductal carcinoma (IDC), but currently overtreated due to inadequate accuracy of mammography. Subtypes of calcification, discernible from histology, has been suggested to have prognostic value in DCIS, while the lipid composition of saturated and unsaturated fatty acids may be altered in de novo synthesis with potential sensitivity to the difference between DCIS and IDC. We therefore set out to examine calcification using ultra short echo time (UTE) MRI and lipid composition using chemical shift-encoded imaging (CSEI), as markers for histological calcification classification, in the initial ex vivo step towards in vivo application.

Methods

Twenty female patients, with mean age (range) of 57 (35-78) years, participated in the study. Intra- and peri-tumoural degree of calcification and peri-tumoural lipid composition were acquired on MRI using UTE and CSEI, respectively. Ex vivo imaging was conducted on the freshly excised breast tumour specimens immediately after surgery. Histopathological analysis was conducted to determine the calcification status, Nottingham Prognostic Index (NPI), and proliferative activity marker Ki-67.

Results

Intra-tumoural degree of calcification in malignant classification (1.05 ± 0.13) was significantly higher (p = 0.012) against no calcification classification (0.84 ± 0.09). Peri-tumoural degree of calcification in malignant classification (1.64 ± 0.10) was significantly higher (p = 0.033) against no calcification classification (1.41 ± 0.18). Peri-tumoural MUFA in malignant classification (0.40 ± 0.01) was significantly higher (p = 0.039) against no calcification classification (0.38 ± 0.02). Ki-67 showed significant negative correlation against peri-tumoural MUFA (p = 0.043, ρ = -0.457), significant positive correlation against SFA (p = 0.008, ρ = 0.577), and significant negative correlation against PUFA (p = 0.002, ρ = -0.653).

Conclusion

The intra- and peri-tumoural degree of calcification and peri-tumoural MUFA are sensitive to histological calcification classes supporting future investigation into DCIS prognosis.

An extracellular matrix stiffness-induced breast cancer cell transcriptome resembles the transition from ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC)

Identifying mechanisms driving the transition from ductal carcinoma in situ (DCIS) to invasive breast cancer remains a challenge in breast cancer research. Breast cancer progression is accompanied by remodelling and stiffening of the extracellular matrix, leading to increased proliferation, survival, and migration. Here, we studied stiffness-dependent phenotypes in MCF10CA1a (CA1a) breast cancer cells cultured on hydrogels with stiffness corresponding to normal breast and breast cancer. This revealed a stiffness-associated morphology consistent with acquisition of an invasive phenotype in breast cancer cells. Surprisingly, this strong phenotypic switch was accompanied by relatively modest transcriptome-wide alterations in mRNA levels, as independently quantified using both DNA-microarrays and bulk RNA sequencing. Strikingly, however, the stiffness-dependent alterations in mRNA levels overlapped with those contrasting ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). This supports a role of matrix stiffness in driving the pre-invasive to invasive transition and suggests that mechanosignalling may be a target for prevention of invasive breast cancer.

Stage-specific protein-domain mutational profile of invasive ductal breast cancer

BACKGROUND

Understanding the mechanisms underlying the malignant progression of cancer cells is crucial for early diagnosis and therapeutic treatment for cancer. Mutational heterogeneity of breast cancer suggests that about a dozen of cancer genes consistently mutate, together with many other genes mutating occasionally, in patients.

METHODS

Using the whole-exome sequences and clinical information of 468 patients in the TCGA project data portal, we analyzed mutated protein domains and signaling pathway alterations in order to understand how infrequent mutations contribute aggregately to tumor progression in different stages.

RESULTS

Our findings suggest that while the spectrum of mutated domains was diverse, mutations were aggregated in Pkinase, Pkinase Tyr, Y-Phosphatase and Src-homology 2 domains, highlighting the genetic heterogeneity in activating the protein tyrosine kinase signaling pathways in invasive ductal breast cancer.

CONCLUSIONS

The study provides new clues to the functional role of infrequent mutations in protein domain regions in different stages for invasive ductal breast cancer, yielding biological insights into metastasis for invasive ductal breast cancer.

Discordant Marker Expression Between Invasive Breast Carcinoma and Corresponding Synchronous and Preceding DCIS

Ductal carcinoma in situ (DCIS) is considered a potential precursor of invasive breast carcinoma (IBC). Studies aiming to find markers involved in DCIS progression generally have compared characteristics of IBC lesions with those of adjacent synchronous DCIS lesions. The question remains whether synchronous DCIS and IBC comparisons are a good surrogate for primary DCIS and subsequent IBC. In this study, we compared both primary DCIS and synchronous DCIS with the associated IBC lesion, on the basis of immunohistochemical marker expression. Immunohistochemical analysis of ER, PR, HER2, p53, and cyclo-oxygenase 2 (COX-2) was performed for 143 primary DCIS and subsequent IBC lesions, including 81 IBC lesions with synchronous DCIS. Agreement between DCIS and IBC was assessed using kappa, and symmetry tests were performed to assess the pattern in marker conversion. The primary DCIS and subsequent IBC more often showed discordant marker expression than synchronous DCIS and IBC. Strikingly, 18 of 49 (36%) women with HER2-positive primary DCIS developed an HER2-negative IBC. Such a difference in HER2 expression was not observed when comparing synchronous DCIS and IBC. The frequency of discordant marker expression did not increase with longer time between primary DCIS and IBC. In conclusion, comparison of primary DCIS and subsequent IBC yields different results than a comparison of synchronous DCIS and IBC, in particular with regard to HER2 status. To gain more insight into the progression of DCIS to IBC, it is essential to focus on the relationship between primary DCIS and subsequent IBC, rather than comparing IBC with synchronous DCIS.

Application of breast cancer diagnosis based on a combination of convolutional neural networks, ridge regression and linear discriminant analysis using invasive breast cancer images processed with autoencoders

Invasive ductal carcinoma cancer, which invades the breast tissues by destroying the milk channels, is the most common type of breast cancer in women. Approximately, 80% of breast cancer patients have invasive ductal carcinoma and roughly 66.6% of these patients are older than 55 years. This situation points out a powerful relationship between the type of breast cancer and progressed woman age. In this study, the classification of invasive ductal carcinoma breast cancer is performed by using deep learning models, which is the sub-branch of artificial intelligence. In this scope, convolutional neural network models and the autoencoder network model are combined. In the experiment, the dataset was reconstructed by processing with the autoencoder model. The discriminative features obtained from convolutional neural network models were utilized. As a result, the most efficient features were determined by using the ridge regression method, and classification was performed using linear discriminant analysis. The best success rate of classification was achieved as 98.59%. Consequently, the proposed approach can be admitted as a successful model in the classification.

Reliability of preoperative breast biopsies showing ductal carcinoma in situ and implications for non-operative treatment: a cohort study

PURPOSE

The future of non-operative management of DCIS relies on distinguishing lesions requiring treatment from those needing only active surveillance. More accurate preoperative staging and grading of DCIS would be helpful. We identified determinants of upstaging preoperative breast biopsies showing ductal carcinoma in situ (DCIS) to invasive breast cancer (IBC), or of upgrading them to higher-grade DCIS, following examination of the surgically excised specimen.

METHODS

We studied all women with DCIS at preoperative biopsy in a large specialist cancer centre during 2000-2014. Information from clinical records, mammography, and pathology specimens from both preoperative biopsy and excised specimen were abstracted. Women suspected of having IBC during biopsy were excluded.

RESULTS

Among 606 preoperative biopsies showing DCIS, 15.0% (95% confidence interval 12.3-18.1) were upstaged to IBC and a further 14.6% (11.3-18.4) upgraded to higher-grade DCIS. The risk of upstaging increased with presence of a palpable lump (21.1% vs 13.0%, pdifference = 0.04), while the risk of upgrading increased with presence of necrosis on biopsy (33.0% vs 9.5%, pdifference < 0.001) and with use of 14G core-needle rather than 9G vacuum-assisted biopsy (22.8% vs 7.0%, pdifference < 0.001). Larger mammographic size increased the risk of both upgrading (pheterogeneity = 0.01) and upstaging (pheterogeneity = 0.004).

CONCLUSIONS

The risk of upstaging of DCIS in preoperative biopsies is lower than previously estimated and justifies conducting randomized clinical trials testing the safety of active surveillance for lower grade DCIS. Selection of women with low grade DCIS for such trials, or for active surveillance, may be improved by consideration of the additional factors identified in this study.

Ductal carcinoma in situ: to treat or not to treat, that is the question

Ductal carcinoma in situ (DCIS) now represents 20-25% of all 'breast cancers' consequent upon detection by population-based breast cancer screening programmes. Currently, all DCIS lesions are treated, and treatment comprises either mastectomy or breast-conserving surgery supplemented with radiotherapy. However, most DCIS lesions remain indolent. Difficulty in discerning harmless lesions from potentially invasive ones can lead to overtreatment of this condition in many patients. To counter overtreatment and to transform clinical practice, a global, comprehensive and multidisciplinary collaboration is required. Here we review the incidence of DCIS, the perception of risk for developing invasive breast cancer, the current treatment options and the known molecular aspects of progression. Further research is needed to gain new insights for improved diagnosis and management of DCIS, and this is integrated in the PRECISION (PREvent ductal Carcinoma In Situ Invasive Overtreatment Now) initiative. This international effort will seek to determine which DCISs require treatment and prevent the consequences of overtreatment on the lives of many women affected by DCIS.

Ectopic expression of PLC-β2 in non-invasive breast tumor cells plays a protective role against malignant progression and is correlated with the deregulation of miR-146a

Cells in non‐invasive breast lesions are widely believed to possess molecular alterations that render them either susceptible or refractory to the acquisition of invasive capability. One such alteration could be the ectopic expression of the β2 isoform of phosphoinositide‐dependent phospholipase C (PLC‐β2), known to counteract the effects of hypoxia in low‐invasive breast tumor‐derived cells. Here, we studied the correlation between PLC‐β2 levels and the propensity of non‐invasive breast tumor cells to acquire malignant features. Using archival FFPE samples and DCIS‐derived cells, we demonstrate that PLC‐β2 is up‐regulated in DCIS and that its forced down‐modulation induces an epithelial‐to‐mesenchymal shift, expression of the cancer stem cell marker CD133, and the acquisition of invasive properties. The ectopic expression of PLC‐β2 in non‐transformed and DCIS‐derived cells is, to some extent, dependent on the de‐regulation of miR‐146a, a tumor suppressor miRNA in invasive breast cancer. Interestingly, an inverse relationship between the two molecules, indicative of a role of miR‐146a in targeting PLC‐β2, was not detected in primary DCIS from patients who developed a second invasive breast neoplasia. This suggests that alterations of the PLC‐β2/miR‐146a relationship in DCIS may constitute a molecular risk factor for the appearance of new breast lesions. Since neither traditional classification systems nor molecular characterizations are able to predict the malignant potential of DCIS, as is possible for invasive ductal carcinoma (IDC), we propose that the assessment of the PLC‐β2/miR‐146a levels at diagnosis could be beneficial for identifying whether DCIS patients may have either a low or high propensity for invasive recurrence.

Intratumoral Heterogeneity in Ductal Carcinoma In Situ: Chaos and Consequence

Ductal carcinoma in situ (DCIS) is a non-invasive proliferative growth in the breast that serves as a non-obligate precursor to invasive ductal carcinoma. The widespread adoption of screening mammography has led to a steep increase in the detection of DCIS, which now comprises approximately 20% of new breast cancer diagnoses in the United States. Interestingly, the intratumoral heterogeneity (ITH) that has been observed in invasive breast cancers may have been established early in tumorigenesis, given the vast and varied ITH that has been detected in DCIS. This review will discuss the intratumoral heterogeneity of DCIS, focusing on the phenotypic and genomic heterogeneity of tumor cells, as well as the compositional heterogeneity of the tumor microenvironment. In addition, we will assess the spatial heterogeneity that is now being appreciated in these lesions, and summarize new approaches to evaluate heterogeneity of tumor and stromal cells in the context of their spatial organization. Importantly, we will discuss how a growing understanding of ITH has led to a more holistic appreciation of the complex biology of DCIS, specifically its evolution and natural history. Finally, we will consider ways in which our knowledge of DCIS ITH might be translated in the future to guide clinical care for DCIS patients.

Single-cell heterogeneity in ductal carcinoma in situ of breast

Heterogeneous patterns of mutations and RNA expression have been well documented in invasive cancers. However, technological challenges have limited the ability to study heterogeneity of protein expression. This is particularly true for pre-invasive lesions such as ductal carcinoma in situ of the breast. Cell-level heterogeneity in ductal carcinoma in situ was analyzed in a single 5 μm tissue section using a multiplexed immunofluorescence analysis of 11 disease-related markers (EGFR, HER2, HER4, S6, pmTOR, CD44v6, SLC7A5 and CD10, CD4, CD8 and CD20, plus pan-cytokeratin, pan-cadherin, DAPI, and Na+K+ATPase for cell segmentation). Expression was quantified at cell level using a single-cell segmentation algorithm. K-means clustering was used to determine co-expression patterns of epithelial cell markers and immune markers. We document for the first time the presence of epithelial cell heterogeneity within ducts, between ducts and between patients with ductal carcinoma in situ. There was moderate heterogeneity in a distribution of eight clusters within each duct (average Shannon index 0.76; range 0-1.61). Furthermore, within each patient, the average Shannon index across all ducts ranged from 0.33 to 1.02 (s.d. 0.09-0.38). As the distribution of clusters within ducts was uneven, the analysis of eight ducts might be sufficient to represent all the clusters ie within- and between-duct heterogeneity. The pattern of epithelial cell clustering was associated with the presence and type of immune infiltrates, indicating a complex interaction between the epithelial tumor and immune system for each patient. This analysis also provides the first evidence that simultaneous analysis of both the epithelial and immune/stromal components might be necessary to understand the complex milieu in ductal carcinoma in situ lesions.

Histogram analysis of volume-based apparent diffusion coefficient in breast cancer

Background Breast cancer is a heterogeneous disease. Recent studies showed that apparent diffusion coefficient (ADC) values have various association with tumor aggressiveness and prognosis. Purpose To evaluate the value of histogram analysis of ADC values obtained from the whole tumor volume in invasive ductal cancer (IDC) and ductal carcinoma in situ (DCIS). Material and Methods This retrospective study included 201 patients with confirmed DCIS (n = 37) and IDC (n = 164). The IDC group was divided into two groups based on the presence of a DCIS component: IDC-DCIS (n = 76) and pure IDC (n = 88). All patients underwent preoperative breast magnetic resonance imaging (MRI) with diffusion-weighted images at 3.0 T. Histogram parameters of cumulative ADC values, skewness, and kurtosis were calculated and statistically analyzed. Results The differences between DCIS, IDC-DCIS, and pure IDC were significant in all percentiles of ADC values, in descending order of DCIS, IDC-DCIS, and pure IDC. IDC showed significantly lower ADC values than DCIS, and ADC50 was the best indicator for discriminating IDC from DCIS, with a threshold of 1.185 × 10^-3 mm²/s (sensitivity of 82.9%, specificity of 75.7%). However, multivariate analysis of obtained ADC values showed no significant differences between DCIS, IDC-DCIS, and pure IDC ( P > 0.05). Conclusion Volume-based ADC values showed association with heterogeneity of breast cancer. However, there was no additional diagnostic performance in histogram analysis for differentiating between DCIS, IDC-DCIS, and pure IDC.

Pathology of healing: what else might we look at?

Several aspects of the article by Morita et al. (Cancer Medicine 5:1607‐18, 2016), examining the spontaneous healing phenomenon with reference to tumor infiltrating lymphocytes (TILs), require clarification. The concept of “healing”, which can perhaps be more accurately termed “regressive change”, remains controversial due to a lack of concrete evidence. Since regressive change is characterized by fibrosis and lymphocytes, a cancer nest that appears to lack a distinct basement membrane, surrounded only by lymphocytes, as in Morita et al's Figure 2F, should be meticulously examined because the appearance may correspond to a tumor having just completed the process of invasion. In our experience, a layer of myoepithelial cells in such foci is often difficult to detect even with immunohistochemistry. Thus, we suggest evaluating the viability of cancer cells within the nest by employing several markers, such as Ki67 and apoptotic markers, to judge whether the tumor is intraductal. It might also be useful to compare cases with versus without regressive change to elucidate the biology of such tumors. For these reasons, a tumor, floating within a pool of TILs and lacking obvious fibrous bands, might be an interesting material to examine in future studies.

Different Biological Action of Oleic Acid in ALDHhigh and ALDHlow Subpopulations Separated from Ductal Carcinoma In Situ of Breast Cancer

The mechanisms underlying breast cancer progression of ductal carcinoma in situ (DCIS) associated with fatty acids are largely unknown. In the present study, we compared the action of oleic acid (OA) on two human DCIS cell lines, MCF10DCIS.COM (ER/PR/HER2-negative) and SUM225 (HER2 overexpressed). OA led to a significant increase in proliferation, migration, lipid accumulation and the expression of lipogenic proteins, such as SREBP-1, FAS and ACC-1, in MCF10DCIS.COM cells but not SUM225 cells. The ALDH^high subpopulation analyzed by the ALDEFLUOR assay was approximately 39.2±5.3% of MCF10DCIS.COM cells but was small (3.11±0.9%) in SUM225 cells. We further investigated the different biological action of OA in the distinct ALDH^low and ALDH^high subpopulations of MCF10DCIS.COM cells. OA led to an increase in the expression of ALDH1A1, ALDH1A2 and ALDH1A3 in MCF10DCIS.COM cells. SREBP-1 and ACC-1 were highly expressed in ALDH^high cells relative to ALDH^low cells, whereas FAS was higher in ALDH^low cells. In the presence of OA, ALDH^high cells were more likely to proliferate and migrate and displayed significantly high levels of SREBP-1 and FAS and strong phosphorylation of FAK and AKT relative to ALDH^low cells. This study suggests that OA could be a critical risk factor to promote the proliferation and migration of ALDH^high cells in DCIS, leading to breast cancer progression.

An Anthropometric-Based Subject-Specific Finite Element Model of the Human Breast for Predicting Large Deformations

The large deformation of the human breast threatens proper nodules tracking when the subject mammograms are used as pre-planning data for biopsy. However, techniques capable of accurately supporting the surgeons during biopsy are missing. Finite element (FE) models are at the basis of currently investigated methodologies to track nodules displacement. Nonetheless, the impact of breast material modeling on the mechanical response of its tissues (e.g., tumors) is not clear. This study proposes a subject-specific FE model of the breast, obtained by anthropometric measurements, to predict breast large deformation. A healthy breast subject-specific FE parametric model was developed and validated by Cranio-caudal (CC) and Medio-Lateral Oblique (MLO) mammograms. The model was successively modified, including nodules, and utilized to investigate the effect of nodules size, typology, and material modeling on nodules shift under the effect of CC, MLO, and gravity loads. Results show that a Mooney–Rivlin material model can estimate healthy breast large deformation. For a pathological breast, under CC compression, the nodules displacement is very close to zero when a linear elastic material model is used. Finally, when nodules are modeled, including tumor material properties, under CC, or MLO or gravity loads, nodules shift shows ~15% average relative difference.

Cancer statistics: Breast cancer in situ

An estimated 60,290 new cases of breast carcinoma in situ are expected to be diagnosed in 2015, and approximately 1 in 33 women is likely to receive an in situ breast cancer diagnosis in her lifetime. Although in situ breast cancers are relatively common, their clinical significance and optimal treatment are topics of uncertainty and concern for both patients and clinicians. In this article, the American Cancer Society provides information about occurrence and treatment patterns for the 2 major subtypes of in situ breast cancer in the United States-ductal carcinoma in situ and lobular carcinoma in situ-using data from the North American Association of Central Cancer Registries and the 13 oldest Surveillance, Epidemiology, and End Results registries. The authors also present an overview of in situ breast cancer detection, treatment, risk factors, and prevention and discuss research needs and initiatives.