Characteristics and prognosis of 17 special histologic subtypes of invasive breast cancers according to World Health Organization classification: comparative analysis to invasive carcinoma of no special type

Long-term outcome of invasive pure micropapillary breast cancer compared with invasive mixed micropapillary and invasive ductal breast cancer: a matched retrospective study

PURPOSE

Data on the prognostic impact of the micropapillary component in breast cancer are limited. The purpose of this study was to investigate the clinicopathological characteristics and long-term outcomes of pure and mixed invasive micropapillary breast cancer (IMPC) patients compared to invasive ductal cancer (IDC) patients.

METHODS

This retrospective study analysed all IMPC and IDC patients treated at the European Institute of Oncology (IEO) between 1997 and 2019. The overall cohort of IMPC patients was divided in two groups, pure and mixed IMPC. Each patient with mixed or pure IMPC was matched with one patient with IDC, based on year of surgery, age, pT, pN, and molecular subtype.

RESULTS

A total of 30,115 IDC, 120 pure IMPC and 150 mixed IMPC patients were considered eligible. Compared to IDC, pure and mixed IMPC patients presented a higher rate of locally advanced disease (pT2-T3, pN2-N3), vascular invasion, and Luminal B subtype. After matching, pure and mixed IMPC showed a significant higher rate of vascular invasion compared to IDC patients (p < 0.001). Invasive disease-free survival was better in IDC compared to pure IMPC patients (p = 0.11). Long-term overall survival was significantly worse in pure IMPC group compared to IDC group (p = 0.004), being instead similar between mixed IMPC vs matched IDC (p = 0.07).

CONCLUSION

These real-world data reported the worse prognosis of pure IMPC compared to IDC, highlighting the peculiar prognostic value of the micropapillary subtype itself in the decision-making process of IMPC management. An accurate pre-surgical diagnostic evaluation and a multidisciplinary approach are pivotal to best personalize its treatment.

Development and validation of a nomogram for predicting rapid relapse in triple-negative breast cancer patients treated with neoadjuvant chemotherapy

Background

Triple-negative breast cancer (TNBC) accounts for disproportionately poor outcomes in breast cancer, driven by a subset of rapid-relapse TNBC (rrTNBC) with marked chemoresistance, rapid metastatic spread, and poor survival. This study aimed to develop and validate a nomogram based on clinicopathological characteristics to predict rapid relapse in TNBC patients treated with neoadjuvant chemotherapy (NAC) first.

Methods

The clinicopathological data of 504 TNBC patients treated with NAC first in Tianjin Medical University Cancer Hospital were analyzed retrospectively, with 109 rapid relapsed patients, and 395 non-rapid relapsed patients, respectively. Based on clinicopathologic characteristics, and follow-up data were analyzed. The independent predictors of clinicopathological characteristics were identified by logistic regression analysis and then used to build a nomogram. The concordance index (C-index), the area under the curve (AUC) of receiver operating characteristic (ROC), and calibration plots were used to evaluate the performance of the model.

Results

Univariate and multivariate logistic regression analyses showed that age at diagnosis (age≥50 years, OR = 0.325,95% CI:0.137-0.771), Nodal staging (N3 staging, OR = 13.669,95% CI:3.693-50.592),sTIL expression levels (sTIL intermediate expression, OR = 0.272,95% CI:0.109-0.678; sTIL high expression, OR = 0.169,95% CI:0.048-0.594), and NAC response (ORR, OR = 0.059,95% CI:0.024-0.143) were independent predictors of rapid relapse in TNBC patients treated with NAC firstly. Among these independent predictors, age ≥ 50 years, sTIL intermediate expression, sTIL high expression, and ORR in NAC were independent protective factors for rapid relapse in TNBC NAC patients. N3 staging was an independent risk factor for rapid relapse in TNBC NAC patients. The ROC curve, calibration curve, and decision curve analysis were used to validate the model. The C-Index of the training sets and validation sets were 0.938 and 0.910, respectively. The Brier scores of the training sets and validation sets were 0.076 and 0.097, respectively.

Conclusion

This study developed and verified a nomogram for predicting rapid relapse in TNBC NAC patients, and the predictive model had high discrimination and accuracy.

Integrative radiomics clustering analysis to decipher breast cancer heterogeneity and prognostic indicators through multiparametric MRI

Breast cancer diagnosis and treatment have been revolutionized by multiparametric Magnetic Resonance Imaging (mpMRI), encompassing T2-weighted imaging (T2WI), Diffusion-weighted imaging (DWI), and Dynamic Contrast-Enhanced MRI (DCE-MRI). We conducted a retrospective analysis of mpMRI data from 194 breast cancer patients (September 2019 to October 2023). Using 'pyradiomics' for radiomics feature extraction and MOVICS for unsupervised clustering. Interestingly, we identified two distinct patient clusters associated with significant differences in molecular subtypes, particularly in Luminal A subtype distribution (p = 0.03), estrogen receptor (ER) (p = 0.01), progesterone receptor (PR) (p = 0.04), mean tumor size (p < 0.01), lymph node metastasis (LNM) (p = 0.01), and edema (p < 0.01). Our study emphasizes mpMRI's potential in breast cancer by using radiomics-based cluster analysis to categorize tumors, uncovering heterogeneity, and aiding in personalized treatment strategies.

Biomarker-specific biosensors revolutionise breast cancer diagnosis

Breast cancer is the most common cancer among women across the globe. In order to treat breast cancer successfully, it is crucial to conduct a comprehensive assessment of the condition during its initial stages. Although mammogram screening has long been a common method of breast cancer screening, high rates of type I error and type II error results as well as radiation exposure have always been of concern. The outgrowth cancer mortality rate is primarily due to delayed diagnosis, which occurs most frequently in a metastatic III or IV stage, resulting in a poor prognosis after therapy. Traditional detection techniques require identifying carcinogenic properties of cells, such as DNA or RNA alterations, conformational changes and overexpression of certain proteins, and cell shape, which are referred to as biomarkers or analytes. These procedures are complex, long-drawn-out, and expensive. Biosensors have recently acquired appeal as low-cost, simple, and super sensitive detection methods for analysis. The biosensor approach requires the existence of biomarkers in the sample. Thus, the development of novel molecular markers for diverse forms of cancer is a rising complementary affair. These biosensor devices offer two major advantages: (1) a tiny amount of blood collected from the patient is sufficient for analysis, and (2) it could help clinicians swiftly select and decide on the best therapy routine for the individual. This review will include updates on prospective cancer markers and biosensors in cancer diagnosis, as well as the associated detection limitations, with a focus on biosensor development for marker detection.

Lobular-Like Features and Outcomes of Mixed Invasive Ductolobular Breast Cancer (MIDLC): Insights from 54,403 Stage I-III MIDLC Patients

BACKGROUND

Mixed invasive ductolobular breast cancer (MIDLC) is a rare histological subtype of breast cancer (BC), with components of both invasive ductal cancer (IDC) and invasive lobular cancer (ILC). Its clinicopathological features and outcomes have not been well characterized.

METHOD

The National Cancer Database 2010-2017 was reviewed to identify women with stage I-III BCs. Univariate analysis was performed using Chi-square or Wilcoxon rank-sum tests and multivariable analysis with logistic regression to predict surgical decisions. Survival was assessed using multivariable Cox proportional hazards regression analysis.

RESULTS

We identified 955,828 women with stage I-III BCs (5.7% MIDLC, 10.3% ILC, and 84.0% IDC). MIDLC was more like ILC than IDC in terms of multicentricity (14.2% MIDLC, 13.0% ILC, 10.0% IDC), hormone receptor positivity (96.6% MIDLC, 98.2% ILC, 81.2% IDC), and use of neoadjuvant chemotherapy (NAC; 5.8% MIDLC, 5.2% ILC, 10.8% IDC). 744,607 women underwent upfront surgery. The mastectomy rates were 42.3% for MIDLC, 46.5% for ILC, and 33.3% for IDC (all p < 0.001). With 5.5 years of median follow-up, the adjusted overall survival in the upfront surgery hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) biological subgroup was better in MIDLC (hazard ratio 0.88, p < 0.001) and ILC (hazard ratio 0.91, p < 0.001) than in IDC. Like ILC, MIDLC also had a lower pathological complete response to NAC than IDC (12.3% MIDLC, 7.3% ILC, 28.6% IDC).

CONCLUSIONS

MIDLC displays a mixed pattern of characteristics favoring features of ILC compared with IDC, with favorable 5-year overall survival compared with IDC within the HR+/HER2- subtype who underwent upfront surgery.

Spatial -omics technologies: the new enterprise in 3D breast cancer models

The fields of tissue bioengineering, -omics, and spatial biology are advancing rapidly, each offering the opportunity for a paradigm shift in breast cancer research. However, to date, collaboration between these fields has not reached its full potential. In this review, we describe the most recently generated 3D breast cancer models regarding the biomaterials and technological platforms employed. Additionally, their biological evaluation is reported, highlighting their advantages and limitations. Specifically, we focus on the most up-to-date -omics and spatial biology techniques, which can generate a deeper understanding of the biological relevance of bioengineered 3D breast cancer in vitro models, thus paving the way towards truly clinically relevant microphysiological systems, improved drug development success rates, and personalised medicine approaches.

Clinicopathological Characteristics and Prognosis of Triple-Negative Apocrine Carcinoma: A Case-Control Study

Background

With a prevalence of only 1% among all breast cancers in Japan, apocrine carcinoma (AC) is a rare type of breast cancer, and its clinicopathological characteristics remain unclear. The aim of this study was to evaluate the characteristics and prognosis of AC, in relation to the presence or absence of androgen receptor (AR).

Methods

We conducted a retrospective multi-center case-control study (Yokohama Clinical Oncology Group (YCOG): YCOG1701 study) in Japan. A total of 53 patients were registered who were diagnosed with AC between 2000 and 2017 in YCOG-affiliated hospitals.

Results

The median age of the patients was 67 (43 - 94) years, and the median observation time was 6.1 years. Among the 53 cases, 24 had triple-negative pure AC (TN-PAC; AR-positive), whereas 29 had other types of AC (other-AC; estrogen receptor-positive and/or human epidermal growth factor receptor 2-positive or AR-negative). Tumor size was smaller (1.4 vs. 2.1 cm, P = 0.024) and metastasis occurred in fewer nodes (12.5% vs. 37.9%, P = 0.036) in the TN-PAC group than in the other-AC group. The number of patients who were administered perioperative adjuvant chemotherapy did not significantly differ between the two groups (TN-PAC/other-AC = 50.0%/55.2%, P = 0.525); however, there was no recurrence in the TN-PAC group, compared to five cases with relapse in the other-AC group.

Conclusions

AR-positive AC patients showed a favorable prognosis without adjuvant chemotherapy, even with the TN subtype. A clinical trial exploring the possibility of treatment de-escalation is anticipated.

Impact of Imaging Biomarkers and AI on Breast Cancer Management: A Brief Review

Breast cancer stands out as the most frequently identified malignancy, ranking as the fifth leading cause of global cancer-related deaths. The American College of Radiology (ACR) introduced the Breast Imaging Reporting and Data System (BI-RADS) as a standard terminology facilitating communication between radiologists and clinicians; however, an update is now imperative to encompass the latest imaging modalities developed subsequent to the 5th edition of BI-RADS. Within this review article, we provide a concise history of BI-RADS, delve into advanced mammography techniques, ultrasonography (US), magnetic resonance imaging (MRI), PET/CT images, and microwave breast imaging, and subsequently furnish comprehensive, updated insights into Molecular Breast Imaging (MBI), diagnostic imaging biomarkers, and the assessment of treatment responses. This endeavor aims to enhance radiologists' proficiency in catering to the personalized needs of breast cancer patients. Lastly, we explore the augmented benefits of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in segmenting, detecting, and diagnosing breast cancer, as well as the early prediction of the response of tumors to neoadjuvant chemotherapy (NAC). By assimilating state-of-the-art computer algorithms capable of deciphering intricate imaging data and aiding radiologists in rendering precise and effective diagnoses, AI has profoundly revolutionized the landscape of breast cancer radiology. Its vast potential holds the promise of bolstering radiologists' capabilities and ameliorating patient outcomes in the realm of breast cancer management.

Invasive breast carcinoma of no special type with medullary pattern: A case report at a tertiary facility in Tanzania

Key Clinical Message

Describes a rare form of invasive breast cancer of no special type.Not a distinct morphological subtype.Characterized by dense lymphoid infiltrate, syncytial growth, pushing borders, and cells with high-grade nuclei.Clinically aggressive but carries a better prognosis than other more frequent invasive breast carcinomas.

Abstract

Invasive breast carcinoma of no special type with medullary pattern (BCNST-MP) is a rare form of breast tumor, accounting for less than 5% of all invasive breast carcinomas. Its diagnosis is based on histologic criteria. Historically, this tumor was known as medullary carcinoma. Poor morphological reproducibility led to re-classification. Despite having an aggressive biological behavior, these tumors usually carry a better prognosis compared with other more frequent forms of invasive breast carcinomas. Herein, we present a case of BCNST-MP in a 58-year-old African female, successfully treated in our institution through chemo-radiation, hormonal therapy and surgery.

Classifying invasive lobular carcinoma as special type breast cancer may be reducing its treatment success: A comparison of survival among invasive lobular carcinoma, invasive ductal carcinoma, and no-lobular special type breast cancer

PURPOSE

The literature contains different information about the prognosis of invasive lobular carcinoma of breast cancer (BC). We aimed to address the inconsistency by comparatively examining the clinical features and prognosis of invasive lobular carcinoma patients in our university and to report our experience by dividing our patients into various subgroups.

PATIENTS AND METHODS

Records of patients with BC admitted to Trakya University School of Medicine Department of Oncology between July 1999 and December 2021 were reviewed. The patients were divided into three groups (No-Special Type BC, Invasive Lobular Special Type BC, No-Lobular Special Type BC). Patient characteristics, treatment methods and oncological results are presented. Survival curves were generated using the Kaplan-Meier method. Statistical significance of survival among the selected variables was compared by using the log-rank test.

RESULTS

The patients in our study consisted of 2142 female and 15 male BC patients. There were 1814 patients with No-Special Type BC, 193 patients with Invasive Lobular Special Type BC, and 150 patients with No-Lobular Special Type BC. The duration of disease-free survival (DFS) was 226.5 months for the No-Special Type BC group, 216.7 months for the No-Lobular Special Type BC group, and 197.2 months for the Invasive Lobular Special Type BC group, whereas the duration of overall survival (OS) was 233.2 months for the No-Special Type BC group, 227.9 for the No-Lobular Special Type BC group, and 209.8 for the Invasive Lobular Special Type BC group. The duration of both DFS and OS was the lowest in the Invasive Lobular Special Type BC group. Multivariate factors that were significant risk factors for OS were Invasive Lobular Special Type BC histopathology (p = .045), T stage, N stage, stage, skin infiltration, positive surgical margins, high histological grade, and mitotic index. Modified radical mastectomy, chemotherapy, radiotherapy and use of tamoxifen and aromatase inhibitors for more than 5 years were significant protective factors for overall survival.

CONCLUSION

The histopathological subgroup with the worst prognosis in our study was Invasive Lobular Special Type BC. Duration of DFS and OS were significantly shorter in Invasive Lobular Special Type BC than No-Lobular Special Type BC group. The classification of Invasive Lobular BC under the title of Special Type BC should be reconsidered and a more accurate treatment and follow-up process may be required.

Outcomes in breast cancer-does ethnicity matter?

Ethnic or racial differences in breast cancer (BC) survival outcomes have been reported, but current data are largely restricted to comparisons between African Americans and non-Hispanic whites. Most analyses have traditionally been based on self-reported race which may not always be accurate, or are oversimplified in their classification. With increasing globalization, quantification of the genetic ancestry from genomic data may offer a solution to infer the complex makeup from admixture of races. Focusing on the larger and the latest studies, we will discuss recent findings on the differing host and tumor biology that may be driving these disparities, in addition to the extrinsic environmental or lifestyle factors. Socioeconomic disparities with lower cancer literacy may lead to late presentation, poorer adherence to treatment, and other lifestyle factors such as unhealthy diet, obesity, and inadequate physical activity. These hardships may also result in greater allostatic load, which is in turn associated with aggressive BC features in disadvantaged populations. Epigenetic reprogramming may mediate the effects of the environment or lifestyle factors on gene expression, with ensuing differences in BC characteristics and outcome. There is increasing evidence that germline genetics can influence somatic gene alterations or expression, as well as modulate the tumor or immune microenvironment. Although the precise mechanisms remain elusive, this may account for the varying distribution of different BC subtypes across ethnicities. These gaps in our knowledge highlight the need to interrogate the multiomics landscape of BC in diverse populations, ideally in large-scale collaborative settings with standardized methodology for the comparisons to be statistically robust. Together with improving BC awareness and access to good quality health care, a holistic approach with insights of the biological underpinnings is much needed to eradicate ethnic disparities in BC outcomes.

Overdiagnosis Due to Screening Mammography for Breast Cancer among Women Aged 40 Years and Over: A Systematic Review and Meta-Analysis

The current systematic review and meta-analysis was conducted to estimate the incidence of overdiagnosis due to screening mammography for breast cancer among women aged 40 years and older. A PRISMA systematic search appraisal and meta-analysis were conducted. A systematic literature search of English publications in PubMed, Web of Science, EMBASE, Scopus, and Google Scholar was conducted without regard to the region or time period. Generic, methodological, and statistical data were extracted from the eligible studies. A meta-analysis was completed by utilizing comprehensive meta-analysis software. The effect size estimates were calculated using the fail-safe N test. The funnel plot and the Begg and Mazumdar rank correlation tests were employed to find any potential bias among the included articles. The strength of the association between two variables was assessed using Kendall’s tau. Heterogeneity was measured using the I-squared (I2) test. The literature search in the five databases yielded a total of 4214 studies. Of those, 30 articles were included in the final analysis, with sample sizes ranging from 451 to 1,429,890 women. The vast majority of the articles were retrospective cohort designs (24 articles). The age of the recruited women ranged between 40 and 89 years old. The incidence of overdiagnosis due to screening mammography for breast cancer among women aged 40 years and older was 12.6%. There was high heterogeneity among the study articles (I2 = 99.993), and the pooled event rate was 0.126 (95% CI: 15 0.101–0.156). Despite the random-effects meta-analysis showing a high degree of heterogeneity among the articles, the screening tests have to allow for a certain degree of overdiagnosis (12.6%) due to screening mammography for breast cancer among women aged 40 years and older. Furthermore, efforts should be directed toward controlling and minimizing the harmful consequences associated with breast cancer screening.

Virtual Biopsy by Using Artificial Intelligence-based Multimodal Modeling of Binational Mammography Data

Background Computational models based on artificial intelligence (AI) are increasingly used to diagnose malignant breast lesions. However, assessment from radiologic images of the specific pathologic lesion subtypes, as detailed in the results of biopsy procedures, remains a challenge. Purpose To develop an AI-based model to identify breast lesion subtypes with mammograms and linked electronic health records labeled with histopathologic information. Materials and Methods In this retrospective study, 26 569 images were collected in 9234 women who underwent digital mammography to pretrain the algorithms. The training data included individuals who had at least 1 year of clinical and imaging history followed by biopsy-based histopathologic diagnosis from March 2013 to November 2018. A model that combined convolutional neural networks with supervised learning algorithms was independently trained to make breast lesion predictions with data from 2120 women in Israel and 1642 women in the United States. Results were reported using the area under the receiver operating characteristic curve (AUC) with the 95% DeLong approach to estimate CIs. Significance was tested with bootstrapping. Results The Israeli model was validated in 456 women and tested in 441 women (mean age, 51 years ± 11 [SD]). The U.S. model was validated in 350 women and tested in 344 women (mean age, 60 years ± 12). For predicting malignancy in the test sets (consisting of 220 Israeli patient examinations and 126 U.S. patient examinations with ductal carcinoma in situ or invasive cancer), the algorithms obtained an AUC of 0.88 (95% CI: 0.85, 0.91) and 0.80 (95% CI: 0.74, 0.85) for Israeli and U.S. patients, respectively (P = .006). These results may not hold for other cohorts of patients, and generalizability across populations should be further investigated. Conclusion The results offer supporting evidence that artificial intelligence applied to clinical and mammographic images can identify breast lesion subtypes when the data are sufficiently large, which may help assess diagnostic workflow and reduce biopsy sampling errors. Published under a CC BY 4.0 license. Online supplemental material is available for this article.

AMACR Expression is a Potential Diagnostic Marker in Apocrine Lesions of Breast, and is Associated with High Histologic Grade and Lymph Node Metastases in Some Invasive Apocrine Breast Cancers

BACKGROUND

Carcinoma with apocrine differentiation (AC) is a subtype of breast carcinoma with apocrine features in >90% of the tumor. Molecular studies demonstrate AC has high expression of androgen receptor (AR) mRNA. Pure AC lack estrogen receptor (ER), progesterone receptor (PR), and express AR, with variable human epidermal growth factor 2 (HER2) status. Currently, in triple negative AC, no targetable therapies or specific diagnostic markers exist.

MATERIALS AND METHODS

α-Methylacyl CoA racemase (AMACR) expression was investigated as a marker of apocrine differentiation using a single-plex immunoperoxidase stain, and a novel AMACR/p63 dual stain in a subset of cases, across 1) benign apocrine lesions (apocrine metaplasia, adenosis) 2) apocrine DCIS (ADCIS), 3) AC/ invasive ductal carcinoma (IDC) with apocrine features, 4) non-apocrine triple negative breast cancer (TNBC) and 5) IDC, no special type. A sub-set of cases were evaluated by tissue microarray.

RESULTS

AMACR expression was increased in both AC and ADCIS, with minimal expression in benign breast tissue, TNBC and IDC, NST cases. In invasive cases, those with positive AMACR (>5% positivity) were significantly associated with higher histologic grade (P = .006), initial N stage (chi squared 0.044), and lack of ER or PR expression (both P < .001), with no correlation with overall survival. Analysis of TCGA breast cancer datasets revealed AMACR expression was significantly higher in molecularly defined apocrine carcinomas relative to basal and luminal subtypes. Moreover, high AMACR expression predicted worse relapse-free and distant-metastasis free survival, among both ER-/PR-/Her2- and ER-/PR-/Her2+ breast cancer cohorts (log-rank P = .081 and .00011, respectively).

CONCLUSION

AMACR represents a promising diagnostic and prognostic marker in apocrine breast lesions. Further study is needed to determine the biologic and clinical significance of this protein in AC.

Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer

Background

Triple-negative breast cancer (TNBC) patients who recur at different times are associated with distinct biological characteristics and prognoses. Research on rapid-relapse TNBC (RR-TNBC) is sparse. In this study, we aimed to describe the characteristics of recurrence, predictors for relapse, and prognosis in rrTNBC patients.

Methods

Clinicopathological data of 1584 TNBC patients from 2014 to 2016 were retrospectively reviewed. The characteristics of recurrence were compared between patients with RR-TNBC and slow relapse TNBC(SR-TNBC). All TNBC patients were randomly divided into a training set and a validation set to find predictors for rapid relapse. The multivariate logistic regression model was used to analyze the data of the training set. C-index and brier score analysis for predicting rapid relapse in the validation set was used to evaluate the discrimination and accuracy of the multivariate logistic model. Prognostic measurements were analyzed in all TNBC patients.

Results

Compared with SR-TNBC patients, RR-TNBC patients tended to have a higher T staging, N staging, TNM staging, and low expression of stromal tumor-infiltrating lymphocytes (sTILs). The recurring characteristics were prone to appear as distant metastasis at the first relapse. The first metastatic site was apt to visceral metastasis and less likely to have chest wall or regional lymph node metastasis. Six predictors (postmenopausal status, metaplastic breast cancer,≥pT3 staging,≥pN1 staging, sTIL intermediate/high expression, and Her2 [1+]) were used to construct the predictive model of rapid relapse in TNBC patients. The C-index and brier score in the validation set was 0.861 and 0.095, respectively. This suggested that the predictive model had high discrimination and accuracy. The prognostic data for all TNBC patients showed that RR-TNBC patients had the worst prognosis, followed by SR-TNBC patients.

Conclusion

RR-TNBC patients were associated with unique biological characteristics and worse outcomes compared to non-RR-TNBC patients.

Metaplastic breast cancers and triple-negative breast cancers of no special type: are they prognostically different? A systematic review and meta-analysis

BACKGROUND AND AIMS

Metaplastic breast cancer (MBC) and triple-negative (TN) BC of no special type are often confounded with each other in terms of survival and prognosis. In this systematic study and meta-analysis, we evaluated the prognosis of each of these two different diagnoses.

METHODS

We conducted a systematic literature search and review using the MOOSE guidelines, through PUBMED database, the Ovid MEDLINE database, and the ISI Web of Science Citation Index Expanded (SCI Expanded). Overall survival (OS) and disease-free survival (DFS) were the main outcomes considered.

RESULTS

Our review eventually selected six independent studies, with a total of more than 59 519 patients. MBC was found to associate with worse OS compared to TNBC of no special type, with a significant 40% increased risk of death [summary hazard ratio (SHR) = 1.40, 95% confidence interval (CI): 1.30-1.50]. We found neither heterogeneity ( I2 = 0%) nor evidence of publication bias ( P = 0.82 and P = 0.49 by Begg's and Egger's test, respectively) between studies. No statistically significant difference was found between MBC and TNBC of no special type in terms of DFS (SHR = 1.17, 95% CI: 0.80-1.71).

CONCLUSION

This study demonstrates that TNBC of no special type and MBC have comparable DFS, although the latter presents a significantly worse prognosis in terms of OS. Despite DFS being similar in both subtypes, this did not result in significant OS benefits, with MBC score being the worse of the two diseases.

A Novel Combined Nomogram Model for Predicting the Pathological Complete Response to Neoadjuvant Chemotherapy in Invasive Breast Carcinoma of No Specific Type: Real-World Study

Objective

To explore the value of a predictive model combining the multiparametric magnetic resonance imaging (mpMRI) radiomics score (RAD-score), clinicopathologic features, and morphologic features for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in invasive breast carcinoma of no specific type (IBC-NST).

Methods

We enrolled, retrospectively and consecutively, 206 women with IBC-NST who underwent surgery after NAC and obtained pathological results from August 2018 to October 2021. Four RAD-scores were constructed for predicting the pCR based on fat-suppression T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), contrast-enhanced T1-weighted imaging (T1WI+C) and their combination, which was called mpMRI. The best RAD-score was combined with clinicopathologic and morphologic features to establish a nomogram model through binary logistic regression. The predictive performance of the nomogram was evaluated using the area under receiver operator characteristic (ROC) curve (AUC) and calibration curve. The clinical net benefit of the model was evaluated using decision curve analysis (DCA).

Results

The mpMRI RAD-score had the highest diagnostic performance, with AUC of 0.848 among the four RAD-scores. T stage, human epidermal growth factor receptor-2 (HER2) status, RAD-score, and roundness were independent factors for predicting the pCR (P < 0.05 for all). The combined nomogram model based on these factors achieved AUCs of 0.930 and 0.895 in the training cohort and validation cohort, respectively, higher than other models (P < 0.05 for all). The calibration curve showed that the predicted probabilities of the nomogram were in good agreement with the actual probabilities, and DCA indicated that it provided more net benefit than the treat-none or treat-all scheme by decision curve analysis in both training and validation datasets.

Conclusion

The combined nomogram model based on the mpMRI RAD-score combined with clinicopathologic and morphologic features may improve the predictive performance for the pCR of NAC in patients with IBC-NST.

Biomarker profile of invasive lobular carcinoma: pleomorphic versus classic subtypes, clinicopathological characteristics and prognosis analyses

PURPOSE

To compare the clinicopathologic features and prognosis of pleomorphic invasive lobular carcinoma (P-ILC) and classic ILC (C-ILC) according to the biomarker profile.

METHODS

A total of 667 C-ILCs and 133 P-ILCs between 2011 and 2021 were included. Clinicopathologic features and stromal tumor-infiltrating lymphocytes (sTILs) status were evaluated. P-ILCs were divided into subtypes based on ER/PR and HER2 expression. The overall survival and disease-free survival (DFS) of patients were compared among matched P-ILCs, C-ILCs, and invasive ductal carcinomas (IDCs) with biomarker subtypes.

RESULTS

Compared to C-ILCs, P-ILCs had greater tumor sizes and stages, fewer ER-positive, more HER2-positive, triple negative (TN), and Ki-67 > 20% tumors (P < 0.05). P-ILCs were subdivided into ER+ (63.1%), HER2+ (21.1%) and TN (15.8%). ER+ P-ILCs were mainly showed trabecular and solid growth patterns. Apocrine and solid features were more strongly associated with HER2+ P-ILCs and TN-P-ILCs, respectively. The prognosis of each biomarker group (ER+, HER2+ and TN) differed by subtype. The P-ILC biomarker subtypes had worse prognosis than the same subtypes in the IDC group, while there was no difference between the P-ILC and the C-ILC counterparts. Solid variants of P-ILC had the worst prognosis. Bone was the most common metastatic site in ER+ P-ILCs and TN-P-ILCs. HER2+ P-ILCs tended to metastasize to the brain and liver. DFS of HER2+ P-ILCs and TN-P-ILCs were worse than that of ER+ P-ILCs. Lacking lobular carcinoma in situ and sTILs ≤ 10% were associated with worse survival of ER+ P-ILCs and TN-P-ILCs, respectively. For HER2+ P-ILCs, Ki-67 > 20% and sTILs ≤ 10% were significant factors for lower DFS.

CONCLUSION

P-ILCs is an aggressive subtype of ILCs. Analyzing the prognostic factors of P-ILCs with heterogeneous morphological and biomarker characteristics is helpful for creating an individualized treatment.

HER2-positive apocrine carcinoma of the breast: a population-based analysis of treatment and outcome

PURPOSE

Apocrine carcinoma of the breast (APO) expresses HER2 in 30-50% of cases. This study explored the clinicopathological features and outcome of HER2+/APO and matched HER2+/NST cohort.

METHODS

We used the SEER database to explore the cohorts. Univariate and multivariate analyses were used to assess the survival. Based on ER and PR [steroid receptors/SR/] and HER2 status, we divided the cohorts to match the intrinsic molecular subtypes for comparisons.

RESULTS

We retrieved 259 cases of HER2+/APO. Most HER2+/APO were SR negative (65%). HER2+/APO were more prevalent in the 80+ age group (24.7% vs. 15.7%, p < 0.001). HER2+/SR-/APO had a significantly lower histological grade than the HER2+/SR-/NST (p < 0.001). Breast cancer-related deaths were more prevalent in HER2+/NST (7.8% vs. 3.9%, p = 0.019). This was particularly evident between SR- subgroups (10.4% in HER2+/SR-/NST vs. 4.2% in HER2+/SR-/APO, p = 0.008) and was reaffirmed in breast cancer-specific survival in univariate analysis (p = 0.03). Other than race and SR status, HER2+/APO subgroups did not differ in clinicopathological parameters.

CONCLUSIONS

Our study confirms the rarity of the APO and reveals that SR status in APO does not affect these patients' prognosis. HER2+/APO tumors tend to have a less aggressive phenotype and a more favorable outcome despite a markedly lower ER/PR positivity.

Multi-omics analyses provide novel biological insights to distinguish lobular ductal types of invasive breast cancers

BACKGROUND

Invasive lobular carcinoma (ILC) treatment is similar to invasive ductal carcinoma (IDC; now invasive carcinoma-no special type, IBC-NST), based on its intrinsic subtype. However, further investigation is required for an integrative understanding of differentially perturbed molecular patterns and pathways in these histotypes.

METHODS

A dataset of 780 IDC and 201 ILC samples from the TCGA-BRCA project for cross-platform multi-omics was analyzed. We leveraged a consensus approach integrating different bioinformatic algorithms to analyze mutations, CNAs, mRNA, miRNA abundance, methylation, and protein abundance to understand the complex crosstalks that distinguish ILC and IDC samples. A histotype-matched comparison was performed. We performed Cox survival analyses for prognosis based on our identified 53 histotype-specific and four discordant genes.

RESULTS

Approximately 90% of ILC cases were of the luminal subtype. Somatic mutations in CDH1 were higher in ILC than in IDC (FDR-adjusted p < 0.01). Fifty-three significant oncogenic or tumor-suppressive DEGs were identified in a single histotype. PPAR signaling and lipolysis regulation in adipocytes were significantly enriched in ILC tumors. CDH1 protein had the highest differential abundance (AUC: 0.85). Moreover, BTG2, GSTA2, GPR37L1, and PGBD5 amplification was associated with poorer OS in ILC compared with no alteration. RIMS2, NACA4P, MYC, ZFPM2, and POU5F1B amplification showed a lower overall survival in patients with IDC. miR-195 showed an IDC-specific downregulation, causing overexpression of CCNE1. Integrative multi-omics supervised analysis identified 296 differentially expressed genes that successfully distinguished IDC and ILC histotypes.

CONCLUSIONS

Our findings identify novel molecular candidates that potentially drive and modify the disease differentially among these histotypes.

Micropapillary Breast Carcinoma: From Molecular Pathogenesis to Prognosis

Invasive micropapillary carcinoma (IMPC) of the breast is an infrequent type of breast cancer often discussed for its potency for lymphovascular invasion and difficulty in accurate imaging estimation. Micropapillary carcinomas are noted to be present as larger tumors, of higher histological grade and a notably higher percentage of disease-positive lymph nodes. Hormonal and HER-2 positivity in IMPC is also commoner when compared to other NST carcinomas. IMPC occurs either as a pure form or more often as a component of mixed Non-Specific Type (NST) carcinoma. The latest data suggest that despite having comparable survival rates to other histological subtypes of breast carcinoma, effective surgical treatment often requires extended surgical margins and vigilant preoperative axillary staging due to an increased incidence of lymph node invasion, and locoregional recurrence. Moreover, the presence of micropapillary in situ components within tumors also seems to alter tumor aggression and influence the nodal disease stage. In this review, we present an overview of the current literature of micropapillary carcinoma of the breast from biology to prognosis, focusing on biological differences and treatment.

An Update on the Molecular and Clinical Characteristics of Apocrine Carcinoma of the Breast

Apocrine carcinoma of the breast is a rare malignancy. According to 2019 WHO classification, apocrine cellular features and a characteristic steroid receptor profile (Estrogen receptor (ER)-negative and androgen receptor (AR)-positive) define apocrine carcinoma. Her-2/neu protein expression is reported in ∼30-50% of apocrine carcinomas, while NGS analysis showed frequent PIK3CA/PTEN/AKT and TP53 mutations Followed by deregulation in the mitogen-activated protein kinase pathway components (mutations of KRAS, NRAS, BRAF). A recent miRNA study indicates various miRNAs (downregulated hsa-miR-145-5p and upregulated 14 miRNAs such as hsa-miR-182-5p, hsa-miR-3135b, and hsa-miR-4417) may target the commonly altered pathways in apocrine carcinomas such as ERBB2/HER2 and mitogen-activated protein kinase signaling pathway. Although AR expression is a hallmark of apocrine carcinoma, little is known regarding the efficacy/resistance to antiandrogens. Success of bicalutamide, a non-steroidal anti-androgen, was reported in a case of Her2-negative apocrine carcinoma. Two recent studies, however, described presence of anti-androgen resistance biomarkers (a splice variant ARv7 and AR/NCOA2 co-amplification) in a subset of AR+ apocrine carcinomas, cautioning the use of anti-androgens in AR+ triple-negative breast carcinomas. Apocrine carcinomas rarely show biomarkers predictive of response to immune checkpoint inhibitors (PD-L1 expression, MSI-H status, and TMB-high). Therefore, a comprehensive cancer profiling of apocrine carcinomas is necessary to identify potential therapeutic targets for a truly individualized treatment approach.

Lobular Breast Cancer: Histomorphology and Different Concepts of a Special Spectrum of Tumors

Simple Summary

Invasive lobular breast cancer (ILC) is a special type of breast cancer (BC) that was first described in 1941. The diagnosis of ILC is made by microscopy of tumor specimens, which reveals a distinct morphology. This review recapitulates the developments in the microscopic assessment of ILC from 1941 until today. We discuss different concepts of ILC, provide an overview on ILC variants, and highlight advances which have contributed to a better understanding of ILC as a special histologic spectrum of tumors.

Abstract

Invasive lobular breast cancer (ILC) is the most common special histological type of breast cancer (BC). This review recapitulates developments in the histomorphologic assessment of ILC from its beginnings with the seminal work of Foote and Stewart, which was published in 1941, until today. We discuss different concepts of ILC and their implications. These concepts include (i) BC arising from mammary lobules, (ii) BC growing in dissociated cells and single files, and (iii) BC defined as a morpho-molecular spectrum of tumors with distinct histological and molecular characteristics related to impaired cell adhesion. This review also provides a comprehensive overview of ILC variants, their histomorphology, and differential diagnosis. Furthermore, this review highlights recent advances which have contributed to a better understanding of the histomorphology of ILC, such as the role of the basal lamina component laminin, the molecular specificities of triple-negative ILC, and E-cadherin to P-cadherin expression switching as the molecular determinant of tubular elements in CDH1-deficient ILC. Last but not least, we provide a detailed account of the tumor microenvironment in ILC, including tumor infiltrating lymphocyte (TIL) levels, which are comparatively low in ILC compared to other BCs, but correlate with clinical outcome. The distinct histomorphology of ILC clearly reflects a special tumor biology. In the clinic, special treatment strategies have been established for triple-negative, HER2-positive, and ER-positive BC. Treatment specialization for patients diagnosed with ILC is just in its beginnings. Accordingly, ILC deserves greater attention as a special tumor entity in BC diagnostics, patient care, and cancer research.

PSMA radioligand therapy for solid tumors other than prostate cancer: background, opportunities, challenges, and first clinical reports

In the past decade, a growing body of literature has reported promising results for prostate-specific membrane antigen (PSMA)-targeted radionuclide imaging and therapy in prostate cancer. First clinical studies evaluating the efficacy of [¹⁷⁷Lu]Lu-PSMA radioligand therapy (PSMA-RLT) demonstrated favorable results in prostate cancer patients. [¹⁷⁷Lu]Lu-PSMA is generally well tolerated due to its limited side effects. While PSMA is highly overexpressed in prostate cancer cells, varying degrees of PSMA expression have been reported in other malignancies as well, particularly in the tumor-associated neovasculature. Hence, it is anticipated that PSMA-RLT could be explored for other solid cancers. Here, we describe the current knowledge of PSMA expression in other solid cancers and define a perspective towards broader clinical implementation of PSMA-RLT. This review focuses specifically on salivary gland cancer, glioblastoma, thyroid cancer, renal cell carcinoma, hepatocellular carcinoma, lung cancer, and breast cancer. An overview of the (pre)clinical data on PSMA immunohistochemistry and PSMA PET/CT imaging is provided and summarized. Furthermore, the first clinical reports of non-prostate cancer patients treated with PSMA-RLT are described.

Breast cancer detection by dedicated breast positron emission tomography according to the World Health Organization classification of breast tumors

OBJECTIVE

Considering the difficulty in detecting primary breast cancers using whole-body positron emission tomography (WBPET) owing to its limited spatial resolution, we aimed to evaluate the detectability of breast cancer by ring-type dedicated breast PET (DbPET) on the World Health Organization (WHO) histological classification in comparison with WBPET.

METHODS

A total of 938 patients with breast cancer underwent WBPET and ring-type DbPET, and 1021 lesions were histologically assessed based on the WHO classification of tumors of the breast. The findings of WBPET and DbPET were retrospectively evaluated and compared.

RESULTS

The size-related sensitivity of DbPET was superior to that of WBPET for subcentimetric tumors (81.9% vs. 52.4%, P < 0.001). The histological distribution was as follows: 11 lobular carcinoma in situ, 158 ductal carcinoma in situ, 738 infiltrating duct carcinoma not otherwise specified (NOS), 12 lobular carcinoma NOS, 40 mucinous adenocarcinoma, 13 tubular carcinoma, 36 invasive breast carcinoma others, and 13 papillary neoplasms. WBPET had low sensitivity for lobular carcinoma in situ, ductal carcinoma in situ, lobular carcinoma NOS, mucinous adenocarcinoma, and tubular carcinoma. DbPET showed improved sensitivity for all the above except lobular and tubular carcinoma. The maximum standardized uptake values (SUVmax) of DbPET were significantly higher than those of WBPET for histological types, excluding lobular carcinoma in situ. The SUVmax of papillary neoplasms was high regardless of low-grade histology and Ki-67 labeling index.

CONCLUSIONS

DBPET was found to have high sensitivity and SUVmax values for all histologic types that showed low sensitivity of detection on WBPET, except lobular carcinoma in situ.