Potential biomarkers of ductal carcinoma in situ progression

Association between long-term use of calcium channel blockers (CCB) and the risk of breast cancer: a retrospective longitudinal observational study protocol

INTRODUCTION

Calcium channel blockers (CCB), a commonly prescribed antihypertensive (AHT) medicine, may be associated with increased risk of breast cancer. The proposed study aims to examine whether long-term CCB use is associated with the development of breast cancer and to characterise the dose-response nature of any identified association, to inform future hypertension management.

METHODS AND ANALYSIS

The study will use data from 2 of Australia's largest cohort studies; the Australian Longitudinal Study on Women's Health, and the 45 and Up Study, combined with the Rotterdam Study. Eligible women will be those with diagnosed hypertension, no history of breast cancer and no prior CCB use at start of follow-up (2004-2009). Cumulative dose-duration exposure to CCB and other AHT medicines will be captured at the earliest date of: the outcome (a diagnosis of invasive breast cancer); a competing risk event (eg, bilateral mastectomy without a diagnosis of breast cancer, death prior to any diagnosis of breast cancer) or end of follow-up (censoring event). Fine and Gray competing risks regression will be used to assess the association between CCB use and development of breast cancer using a generalised propensity score to adjust for baseline covariates. Time-varying covariates related to interaction with health services will also be included in the model. Data will be harmonised across cohorts to achieve identical protocols and a two-step random effects individual patient-level meta-analysis will be used.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the following Human research Ethics Committees: Curtin University (ref No. HRE2022-0335), NSW Population and Health Services Research Ethics Committee (2022/ETH01392/2022.31), ACT Research Ethics and Governance Office approval under National Mutual Acceptance for multijurisdictional data linkage research (2022.STE.00208). Results of the proposed study will be published in high-impact journals and presented at key scientific meetings.

TRIAL REGISTRATION NUMBER

NCT05972785.

Artificial intelligence-based morphometric signature to identify ductal carcinoma in situ with low risk of progression to invasive breast cancer

Ductal carcinoma in situ (DCIS) may progress to ipsilateral invasive breast cancer (iIBC), but often never will. Because DCIS is treated as early breast cancer, many women with harmless DCIS face overtreatment. To identify these women that may forego treatment, we hypothesized that DCIS morphometric features relate to the risk of subsequent iIBC. We developed an artificial intelligence-based DCIS morphometric analysis pipeline (AIDmap) to detect DCIS as a pathologist and measure morphological structures in hematoxylin-eosin-stained (H&E) tissue sections. These were from a case-control study of patients diagnosed with primary DCIS, treated by breast-conserving surgery without radiotherapy. We analyzed 689 WSIs of DCIS of which 226 were diagnosed with subsequent iIBC (cases) and 463 were not (controls). The distribution of 15 duct morphological measurements in each H&E was summarized in 55 morphometric variables. A ridge regression classifier with cross validation predicted 5-years-free of iIBC with an area-under the curve of 0.65 (95% CI 0.55-0.76). A morphometric signature based on the 30 variables most associated with outcome, identified lesions containing small-sized ducts, low number of cells and low DCIS/stroma area ratio. This signature was associated with lower iIBC risk in a multivariate regression model including grade, ER, HER2 and COX-2 expression (HR = 0.56; 95% CI 0.28-0.78). AIDmap has potential to identify harmless DCIS that may not need treatment.

Is it Time to Retire the Term of Low-Grade Ductal Carcinoma in Situ and Replace it With Ductal Neoplasia?

As the leading cause of cancer morbidity and the second leading cause of cancer mortality among women, breast cancer continues to remain a major global public health problem. Consequently, significant attention has been directed toward early breast cancer detection and prevention. As a result, the number of image-detected biopsies has increased, and minimally invasive diagnostic procedures have almost replaced open surgical biopsies. Therefore, pathologists are expected to provide more information with less tissue and diagnose increasing numbers of atypical proliferative breast lesions, in situ lesions, and small breast carcinomas. This is a difficult task, as reflected by continuous reports highlighting the challenges associated with morphologic distinction between atypical ductal hyperplasia and low-grade ductal carcinoma in situ. The current interobserver variability among pathologists to accurately define these two entities often leads to silent overdiagnosis and overtreatment. Up to now, there are no reproducible morphologic features and/or any reliable biomarkers that can accurately separate the above-mentioned entities. Despite these reports, patients diagnosed with low-grade ductal carcinoma in situ are subject to cancer therapy regardless of the fact that low-grade ductal carcinoma in situ is known to be an indolent lesion. Studies have shown that low and high-grade ductal carcinoma in situ are genetically different forms of breast cancer precursors; however, the term ductal carcinoma in situ is followed by cancer therapy regardless of the grade and biology of the tumor. In contrast, patients with the diagnoses of atypical ductal hyperplasia do not undergo cancer therapy. In the current article, attempts are made to highlight the continuous dilemma in distinction between atypical ductal hyperplasia and low-grade ductal carcinoma in situ. Going forward, we suggest that low-grade ductal carcinoma in situ be referred to as ductal neoplasia. This alternative terminology allows for different management and follow-up strategies by eliminating the word carcinoma.

SFRP1 Expression is Inversely Associated With Metastasis Formation in Canine Mammary Tumours

BACKGROUND

Canine mammary tumours (CMTs) are the most frequent tumours in intact female dogs and show strong similarities with human breast cancer. In contrast to the human disease there are no standardised diagnostic or prognostic biomarkers available to guide treatment. We recently identified a prognostic 18-gene RNA signature that could stratify human breast cancer patients into groups with significantly different risk of distant metastasis formation. Here, we assessed whether expression patterns of these RNAs were also associated with canine tumour progression.

METHOD

A sequential forward feature selection process was performed on a previously published microarray dataset of 27 CMTs with and without lymph node (LN) metastases to identify RNAs with significantly differential expression to identify prognostic genes within the 18-gene signature. Using an independent set of 33 newly identified archival CMTs, we compared expression of the identified prognostic subset on RNA and protein basis using RT-qPCR and immunohistochemistry on FFPE-tissue sections.

RESULTS

While the 18-gene signature as a whole did not have any prognostic power, a subset of three RNAs: Col13a1, Spock2, and Sfrp1, together completely separated CMTs with and without LN metastasis in the microarray set. However, in the new independent set assessed by RT-qPCR, only the Wnt-antagonist Sfrp1 showed significantly increased mRNA abundance in CMTs without LN metastases on its own (p = 0.013) in logistic regression analysis. This correlated with stronger SFRP1 protein staining intensity of the myoepithelium and/or stroma (p < 0.001). SFRP1 staining, as well as β-catenin membrane staining, was significantly associated with negative LN status (p = 0.010 and 0.014 respectively). However, SFRP1 did not correlate with β-catenin membrane staining (p = 0.14).

CONCLUSION

The study identified SFRP1 as a potential biomarker for metastasis formation in CMTs, but lack of SFRP1 was not associated with reduced membrane-localisation of β-catenin in CMTs.

Dendritic Cell Subpopulations Are Associated with Morphological Features of Breast Ductal Carcinoma In Situ

Ductal carcinoma in situ (DCIS) is the preinvasive form of breast cancer (BC). It is disputed whether all cases of DCIS require extensive treatment as the overall risk of progression to BC is estimated at 40%. Therefore, the crucial objective for researchers is to identify DCIS with significant risk of transformation into BC. Dendritic cells (DC) are professional antigen presenting cells and as such play a pivotal role in the formation of immune cells that infiltrate in breast tumors. The aim of this study was to investigate the relationship between the density of DCs with different superficial antigens (CD1a, CD123, DC-LAMP, DC-SIGN) and various histopathological characteristics of DCIS. Our evaluation indicated that CD123⁺ and DC-LAMP⁺ cells were strongly associated with maximal tumor size, grading and neoductgenesis. Together with CD1a⁺ cells, they were negatively correlated with hormonal receptors expression. Furthermore, the number of DC-LAMP⁺ cells was higher in DCIS with comedo necrosis, ductal spread, lobular cancerization as well as comedo-type tumors, while CD1a⁺ cells were abundant in cases with Paget disease. We concluded that different subpopulations of DCs relate to various characteristics of DCIS. Of the superficial DCs markers, DC-LAMP seems particularly promising as a target for further research in this area.

Proteomics-Based Identification of Dysregulated Proteins and Biomarker Discovery in Invasive Ductal Carcinoma, the Most Common Breast Cancer Subtype

Invasive ductal carcinoma (IDC) is the most common histological subtype of malignant breast cancer (BC), and accounts for 70–80% of all invasive BCs. IDC demonstrates great heterogeneity in clinical and histopathological characteristics, prognoses, treatment strategies, gene expressions, and proteomic profiles. Significant proteomic determinants of the progression from intraductal pre-invasive malignant lesions of the breast, which characterize a ductal carcinoma in situ (DCIS), to IDC, are still poorly identified, validated, and clinically applied. In the era of “6P” medicine, it remains a great challenge to determine which patients should be over-treated versus which need to be actively monitored without aggressive treatment. The major difficulties for designating DCIS to IDC progression may be solved by understanding the integrated genomic, transcriptomic, and proteomic bases of invasion. In this review, we showed that multiple proteomics-based techniques, such as LC–MS/MS, MALDI-ToF MS, SELDI-ToF-MS, MALDI-ToF/ToF MS, MALDI-MSI or MasSpec Pen, applied to in-tissue, off-tissue, BC cell lines and liquid biopsies, improve the diagnosis of IDC, as well as its prognosis and treatment monitoring. Classic proteomics strategies that allow the identification of dysregulated protein expressions, biological processes, and interrelated pathway analyses based on aberrant protein–protein interaction (PPI) networks have been improved to perform non-invasive/minimally invasive biomarker detection of early-stage IDC. Thus, in modern surgical oncology, highly sensitive, rapid, and accurate MS-based detection has been coupled with “proteome point sampling” methods that allow for proteomic profiling by in vivo “proteome point characterization”, or by minimal tissue removal, for ex vivo accurate differentiation and delimitation of IDC. For the detection of low-molecular-weight proteins and protein fragments in bodily fluids, LC–MS/MS and MALDI-MS techniques may be coupled to enrich and capture methods which allow for the identification of early-stage IDC protein biomarkers that were previously invisible for MS-based techniques. Moreover, the detection and characterization of protein isoforms, including posttranslational modifications of proteins (PTMs), is also essential to emphasize specific molecular mechanisms, and to assure the early-stage detection of IDC of the breast.

Different situations of identifying second primary malignant tumors in lymphoma patients with synchronous solid tumors

BACKGROUND

To our knowledge, the different situations of identifying second primary malignant tumors (SPMTs) in lymphoma patients with synchronous solid tumors remain to be comprehensively investigated.

METHODS

We retrospectively collected information pertaining to lymphoma patients with synchronous solid tumors (diagnosed within 6 months) at Peking University Cancer Hospital & Institute between 2009 and 2019. The non-parametric Aalen-Johansen estimator was applied to calculate cumulative incidence function in the competing risk model. Furthermore, propensity score-matched analysis was performed to compare survival differences in lymphoma patients with or without synchronous solid tumors.

RESULTS

Thirty-eight patients were enrolled. There were three situations of identifying SPMTs. First, in 15 patients (39.5%), SPMTs were identified before the initiation of any treatment. Among them, priority was given to anti-lymphoma treatment in case of only three patients. Second, in 17 patients (44.7%), SPMTs were unexpectedly detected on surgical specimen assessment; of them, 13 received anti-lymphoma treatment after surgery. Third, in six patients (15.8%), SPMTs were identified after the outset of treatment for the primary tumor; in this population, three of four patients with lymphoma switched toward the treatment plan for SPMTs. The 5-year overall survival was 58.7%. The cumulative incidence function within 5 years was 26.6% for lymphoma and 14.7% for other solid tumors. The early identification of SPMTs was associated with better outcomes (p = 0.048). After balancing the baseline characteristics, no differences in survival were observed between lymphoma patients with and without synchronous solid tumors (p = 0.664).

CONCLUSIONS

This is the first study to present the different situations of identifying SPMTs in lymphoma patients with synchronous solid tumors. In only <50% patients, SPMTs were identifiable at baseline. SPMT identification at different situations may make it difficult to choose the optimal therapeutic option, which may consequently impact patient survival.

Learning to distinguish progressive and non-progressive ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) is a non-invasive breast neoplasia that accounts for 25% of all screen-detected breast cancers diagnosed annually. Neoplastic cells in DCIS are confined to the ductal system of the breast, although they can escape and progress to invasive breast cancer in a subset of patients. A key concern of DCIS is overtreatment, as most patients screened for DCIS and in whom DCIS is diagnosed will not go on to exhibit symptoms or die of breast cancer, even if left untreated. However, differentiating low-risk, indolent DCIS from potentially progressive DCIS remains challenging. In this Review, we summarize our current knowledge of DCIS and explore open questions about the basic biology of DCIS, including those regarding how genomic events in neoplastic cells and the surrounding microenvironment contribute to the progression of DCIS to invasive breast cancer. Further, we discuss what information will be needed to prevent overtreatment of indolent DCIS lesions without compromising adequate treatment for high-risk patients.

Breast cancer stage prediction: a computational approach guided by transcriptome analysis

Breast cancer is the second leading cancer among women in terms of mortality rate. In recent years, its incidence frequency has been continuously rising across the globe. In this context, the new therapeutic strategies to manage the deadly disease attracts tremendous research focus. However, finding new prognostic predictors to refine the selection of therapy for the various stages of breast cancer is an unattempted issue. Aberrant expression of genes at various stages of cancer progression can be studied to identify specific genes that play a critical role in cancer staging. Moreover, while many schemes for subtype prediction in breast cancer have been explored in the literature, stage-wise classification remains a challenge. These observations motivated the proposed two-phased method: stage-specific gene signature selection and stage classification. In the first phase, meta-analysis of gene expression data is conducted to identify stage-wise biomarkers that were then used in the second phase of cancer classification. From the analysis, 118, 12 and 4 genes respectively in stage I, stage II and stage III are determined as potential biomarkers. Pathway enrichment, gene network and literature analysis validate the significance of the identified genes in breast cancer. In this study, machine learning methods were combined with principal component and posterior probability analysis. Such a scheme offers a unique opportunity to build a meaningful model for predicting breast cancer staging. Among the machine learning models compared, Support Vector Machine (SVM) is found to perform the best for the selected datasets with an accuracy of 92.21% during test data evaluation. Perhaps, biomarker identification performed here for stage-specific cancer treatment would be a meaningful step towards predictive medicine. Significantly, the determination of correct cancer stage using the proposed 134 gene signature set can possibly act as potential target for breast cancer therapeutics.

Gene expression signatures of individual ductal carcinoma in situ lesions identify processes and biomarkers associated with progression towards invasive ductal carcinoma

Ductal carcinoma in situ (DCIS) is considered a non-invasive precursor to breast cancer, and although associated with an increased risk of developing invasive disease, many women with DCIS will never progress beyond their in situ diagnosis. The path from normal duct to invasive ductal carcinoma (IDC) is not well understood, and efforts to do so are hampered by the substantial heterogeneity that exists between patients, and even within patients. Here we show gene expression analysis from > 2,000 individually micro-dissected ductal lesions representing 145 patients. Combining all samples into one continuous trajectory we show there is a progressive loss in basal layer integrity heading towards IDC, coupled with two epithelial to mesenchymal transitions, one early and a second coinciding with the convergence of DCIS and IDC expression profiles. We identify early processes and potential biomarkers, including CAMK2N1, MNX1, ADCY5, HOXC11 and ANKRD22, whose reduced expression is associated with the progression of DCIS to invasive breast cancer.

Expression of CIB1 correlates with colorectal liver metastases but not with peritoneal carcinomatosis

BACKGROUND

Molecular differences in colorectal cancer (CRC) are associated with the metastatic route. Patient survival is mainly driven by metastatic spread thus it is imperative to understand its key drivers to develop biomarkers for risk stratification, follow-up protocols and personalized therapy. Thus, this study aimed to identify genes associated with the metastatic route in CRC.

MATERIAL AND METHODS

CRC patients resected at our clinic from 2005 to 2014 and with a minimum 5-year follow-up were included in this analysis and grouped into CRC with hepatic (HEP), peritoneal (PER) or without distant metastases (M0), and HEP/PER. Firstly, tumor RNA of 6 patients each was isolated by microdissection from formalin-fixed paraffin-embedded specimens and analyzed by a NanoString analysis. Subsequently, these results were validated with immunohistochemistry and correlated to clinicopathological parameters in a larger collective of CRC patients (HEP n = 51, PER n = 44, M0 n = 47, HEP/PER n = 28).

RESULTS

Compared to M0, HEP tumors showed 20 differentially expressed genes associated with epithelial-mesenchymal transition (EMT) and angiogenesis. Compared to M0, PER tumors had 18 differentially expressed genes. The finding of different gene signatures was supported by the multidimensional principal component clustering analysis. Tumor perforation did not influence the metastatic route. CIB1 was homogenously and significantly overexpressed in HEP compared to M0 (p < 0.001), but not in PER. Furthermore, immunohistochemical validation demonstrated that the mean CIB1 expression in HEP was 80% higher than in M0 (p < 0.001).

CONCLUSION

Gene expression analysis revealed that CIB1 is significantly overexpressed in CRC leading to liver metastases compared to M0 and PER. Thus, the present results suggest that CIB1 may play a crucial role for hematogenous spread to the liver but not for peritoneal carcinomatosis. Consequently, CIB1 seems to be a promising prognostic marker and a potential tool for future targeted therapies as well as early diagnostics and follow-up.

The systemic administration of neural stem cells expressing an inducible and soluble form of growth arrest specific 1 inhibits mammary gland tumor growth and the formation of metastases

BACKGROUND AIMS

Metastasis to different organs is the major cause of death in breast cancer patients. The poor clinical prognosis and lack of successful treatments for metastatic breast cancer patients demand the development of new tumor-selective therapies. Thus, it is necessary to develop treatments capable of releasing therapeutic agents to both primary tumors and metastases that avoid toxic side effects in normal tissue, and neural stem cells are an attractive vehicle for tracking tumor cells and delivering anti-cancer agents. The authorspreviously demonstrated that a soluble form of growth arrest specific 1 (GAS1) inhibits the growth of triple-negative breast tumors and glioblastoma.

METHODS

In this study, the authors engineered ReNcell CX (EMD Millipore, Temecula, CA, USA) neural progenitor cells to express truncated GAS1 (tGAS1) under a tetracycline/on inducible system using lentiviral vectors.

RESULTS

Here the authors show that treatment with ReNcell-tGAS1 in combination with tetracycline decreased primary tumor growth and inhibited the formation of metastases in tumor-bearing mice by diminishing the phosphorylation of AKT and ERK1/2 in orthotopic mammary gland tumors. Moreover, the authors observed that ReNcell-tGAS1 prolonged the survival of 4T1 tumor-bearing mice.

CONCLUSIONS

These data suggest that the delivery of tGAS1 by ReNcell cells could be an effective adjuvant for the treatment of triple-negative breast cancer.