Digital analysis of distant and cancer-associated mammary adipocytes

Adipocyte heterogeneity and tumor infiltration of adipose tissue in patients with metastatic breast cancer

BACKGROUND

The adipose tissue may serve as a source of energy supporting cancer growth and metastasis. Our understanding of the adipocytes which compose the adipose tissue in different anatomical locations of the body as well as potential microscopic tumor infiltration in patients with metastatic breast cancer remains limited. This study therefore investigates regional variations in adipocyte size and adipose tissue tumor infiltration in patients with metastatic breast cancer.

METHODS

Within the UPTIDER rapid autopsy program, (NCT04531696), 94 adipose tissue samples from subcutaneous, visceral, retroperitoneal, and mammary depots of 22 patients with metastatic breast cancer were collected and analyzed. Distant adipocyte size was quantified using digital pathology, and tumor infiltration was assessed histologically. Linear mixed quantile regression analyzed the associations between adipocyte size, fat depot type and major histological subtypes.

RESULTS

Distant adipocyte size did not significantly differ across fat depots. A trend towards smaller adipocytes in mammary fat at autopsy versus diagnosis was observed, suggesting potential age and/or treatment effects. Adipocyte size correlated positively with BMI at death, especially in subcutaneous and visceral fat. Visceral fat exhibited higher tumor infiltration, notably in patients with invasive lobular carcinoma (ILC).

CONCLUSION

This study highlights the relatively uniform adipocyte size across fat depots in patients with metastatic breast cancer, with potential changes in mammary adipocytes over the disease course. The microscopic tumor cell infiltration observed in the visceral fat, mainly for ILC, underscores the need to undertake additional research to understanding the contribution of the adipose tissue in breast cancer metastasis.

Effects of the subtypes of apolipoprotein E on immune inhibition and prognosis in patients with Hepatocellular Carcinoma

PURPOSE

To investigate whether prognosis of patients with hepatocellular carcinoma (HCC) is affected by the abundance and subgroups of myeloid-derived suppressor cells (MDSCs) as well as subtypes and expression of apolipoprotein E (apoE).

METHODS

31 HCC patients were divided into three groups according to blood total apoE level for detecting the abundance of immunoregulatory cells by flow cytometry. Tumour tissue microarrays from 360 HCC patients were evaluated about the abundance and subgroups of MDSCs and the expression of apoE2, apoE3, apoE4 by immunofluorescence staining and immunohistochemistry staining. Survival analysis by means of univariate, multivariate COX regression and Kaplan-Meier methods of the 360 patients was performed based on clinical and pathological examinations along with 10 years' follow-up data.

RESULTS

The lower apoE group presented higher abundance of MDSCs in the peripheral blood of HCC patients than higher apoE group. The abundance of monocyte-like MDSCs (M-MDSCs) was higher in the apoE low level group than high level group (p = 0.0399). Lower H-score of apoE2 (HR = 6.140, p = 0.00005) and higher H-score of apoE4 (HR = 7.001, p = 0.009) in tumour tissue were significantly associated with shorter overall survival (OS). The higher infiltration of polymorphonuclear granulocyte-like MDSCs (PMN-MDSCs, HR = 3.762, p = 0.000009) and smaller proportion of M-MDSCs of total cells (HR = 0.454, p = 0.006) in tumour tissue were independent risk factors for shorter recurrence-free survival (RFS).

CONCLUSION

The abundance of MDSCs in HCC patients' plasma negatively correlates with the level of apoE. The expression of apoE4 in HCC tissue indicated a poor prognosis while apoE2 might be a potential protective factor.

Reporting on patient's body mass index (BMI) in recent clinical trials for patients with breast cancer: a systematic review

BACKGROUND

The proportion of patients with breast cancer and obesity is increasing. While the therapeutic landscape of breast cancer has been expanding, we lack knowledge about the potential differential efficacy of most drugs according to the body mass index (BMI). Here, we conducted a systematic review on recent clinical drug trials to document the dosing regimen of recent drugs, the reporting of BMI and the possible exclusion of patients according to BMI, other adiposity measurements and/or diabetes (leading comorbidity of obesity). We further explored whether treatment efficacy was evaluated according to BMI.

METHODS

A search of Pubmed and ClinicalTrials.gov was performed to identify phase I-IV trials investigating novel systemic breast cancer treatments. Dosing regimens and exclusion based on BMI, adiposity measurements or diabetes, documentation of BMI and subgroup analyses according to BMI were assessed.

RESULTS

495 trials evaluating 26 different drugs were included. Most of the drugs (21/26, 81%) were given in a fixed dose independent of patient weight. BMI was an exclusion criterion in 3 out of 495 trials. Patients with diabetes, the leading comorbidity of obesity, were excluded in 67/495 trials (13.5%). Distribution of patients according to BMI was mentioned in 8% of the manuscripts, subgroup analysis was performed in 2 trials. No other measures of adiposity/body composition were mentioned in any of the trials. Retrospective analyses on the impact of BMI were performed in 6 trials.

CONCLUSIONS

Patient adiposity is hardly considered as most novel drug treatments are given in a fixed dose. BMI is generally not reported in recent trials and few secondary analyses are performed. Given the prevalence of patients with obesity and the impact obesity can have on pharmacokinetics and cancer biology, more attention should be given by investigators and study sponsors to reporting patient's BMI and evaluating its impact on treatment efficacy and toxicity.

Adipose Tissue Analysis Toolkit (ATAT) for automated analysis of adipocyte size and extracellular matrix in white adipose tissue

OBJECTIVE

The pathological expansion of white adipose tissue (WAT) in obesity involves adipocyte hypertrophy accompanied by expansion of the collagen-rich pericellular extracellular matrix (ECM) and development of crown-like structures (CLS). Traditionally, WAT morphology is assessed through immunohistochemical analysis of WAT sections. However, manual analysis of large histological sections is time-consuming, and the available digital tools for analyzing adipocyte size and pericellular ECM are limited. To address this gap, the authors developed the Adipose Tissue Analysis Toolkit (ATAT), an ImageJ plugin facilitating analysis of adipocyte size, WAT ECM, and CLS.

METHODS AND RESULTS

ATAT utilizes local and image-level differentials in pixel intensity to independently threshold image background, distinguishing adipocyte-free tissue without user input. It accurately captures adipocytes in histological sections stained with common dyes and automates the analysis of adipocyte cross-sectional area, total-field, and localized region-of-interest ECM. ATAT allows fully automated batch analysis of histological images using default or user-defined adipocyte detection parameters.

CONCLUSIONS

ATAT provides several advantages over existing WAT image analysis tools, enabling high-throughput analyses of adipocyte-specific parameters and facilitating the assessment of ECM changes associated with WAT remodeling due to weight changes and other pathophysiological alterations that affect WAT function.

Adipose Tissue Analysis Toolkit (ATAT) for Automated Analysis of Adipocyte Size and Extracellular Matrix in White Adipose Tissue

Objective

The pathological expansion of white adipose tissue (WAT) in obesity involves adipocyte hypertrophy accompanied by expansion of collagen-rich pericellular extracellular matrix (ECM) and the development of crown-like structures (CLS). Traditionally, WAT morphology is assessed through immunohistochemical analysis of WAT sections. However, manual analysis of large histological sections is time-consuming, and available digital tools for analyzing adipocyte size and pericellular ECM are limited. To address this gap, we developed the Adipose Tissue Analysis Toolkit (ATAT), an ImageJ plugin facilitating analysis of adipocyte size, WAT ECM and CLS.

Methods and Results

ATAT utilizes local and image-level differentials in pixel intensity to independently threshold background, distinguishing adipocyte-free tissue without user input. It accurately captures adipocytes in histological sections stained with common dyes and automates the analysis of adipocyte cross-sectional area, total-field, and localized region-of-interest ECM. ATAT allows fully automated batch analysis of histological images using default or user-defined adipocyte detection parameters.

Conclusions

ATAT provides several advantages over existing WAT image analysis tools, enabling high-throughput analyses of adipocyte-specific parameters and facilitating the assessment of ECM changes associated with WAT remodeling due to weight changes and other pathophysiological alterations that affect WAT function.

Study Importance Questions

What is already known about this subject?: The manual analysis of large WAT histological sections is very time-consuming, while digital tools for the analysis of WAT are limited.What are the new findings in your manuscript?: - ATAT enables fully automated analysis of batches of histological images using either default or user-defined adipocyte detection parameters- ATAT allows high-throughput analyses of adipocyte-specific parameters and pericellular extracellular matrix- ATAT enables the assessment of fibrotic changes associated with WAT remodeling and crown-like structuresHow might your results change the direction of research or the focus of clinical practice?: - ATAT is designed to work with histological sections and digital images obtained using a slide scanner or a microscope.- This tool will help basic and clinical researchers to conduct automated analyses of adipose tissue histological sections.

Impact of obesity and white adipose tissue inflammation on the omental microenvironment in endometrial cancer

BACKGROUND

A complex relationship between adipose tissue and malignancy, involving an inflammatory response, has been reported. The goal of this work was to assess the prevalence of white adipose tissue (WAT) inflammation in patients with endometrial cancer (EC), and the association with circulating inflammation markers. Furthermore, the aim was to characterize the pathways activated in and the cell type composition of adipose tissue in patients with EC.

METHODS

Adipose tissue and blood samples were prospectively collected from 101 patients with EC at initial surgery. WAT inflammation was determined based on adipocytes surrounded by macrophages forming crown-like structures. Circulating levels of metabolic syndrome-associated and inflammatory markers were quantified. RNA-sequencing was performed on adipose samples (n = 55); differential gene expression, pathway, and cellular decomposition analyses were performed using state-of-the-art bioinformatics methods.

RESULTS

WAT inflammation was identified in 46 (45.5%) of 101 EC patients. Dyslipidemia, hypertension, and diabetes mellitus were significantly associated with WAT inflammation (p < .05). WAT inflammation was associated with greater body mass index (p < .001) and higher circulating levels of leptin, high-sensitivity C-reactive protein, and interleukin-6, as well as lower levels of adiponectin and sex hormone-binding globulin (p < .05). Transcriptomic analysis demonstrated increased levels of proinflammatory and pro-neoplastic-related gene expression in inflamed omental adipose tissue.

CONCLUSIONS

WAT inflammation is associated with metabolic syndrome, obesity, and inflammatory markers, as well as increased expression of proinflammatory and proneoplastic genes.

The association between adiposity and anti-proliferative response to neoadjuvant endocrine therapy with letrozole in post-menopausal patients with estrogen receptor positive breast cancer

The impact of adiposity on the efficacy of endocrine treatment in patients with estrogen receptor positive breast cancer is poorly investigated. Here, we retrospectively investigated in a cohort of 56 patients whether body mass index and/or mammary adiposity are associated with anti-proliferative response in the neoadjuvant setting. Anti-proliferative response was defined as high Ki67 at baseline (Ki67_bl) and low Ki67 at surgery (Ki67_srg), using the 14% cut-off. Mammary adipocyte size was assessed on hematoxylin and eosin slides from the surgical samples using digital pathology. A higher proportion of tumors with an anti-proliferative response was observed in patients with obesity (54.5%) as compared to patients with normal weight (9.0%) and patients with overweight (40.0%) (p = 0.031), confirmed by multivariable regression analysis adjusted for baseline Ki67 (OR, obese vs normal weight: 13.76, 95%CI: 1.49–207.63, p = 0.020). Larger adipocyte diameter was identified as predictor of anti-proliferative response (OR per increase in diameter of 5 μm for adipocytes distant from the tumor: 2.24, 95%CI: 1.01–14.32, p = 0.046). This study suggests that anti-proliferative response to neoadjuvant letrozole might be more frequent in patients with increased systemic or mammary adiposity.

Tumor Glucose and Fatty Acid Metabolism in the Context of Anthracycline and Taxane-Based (Neo)Adjuvant Chemotherapy in Breast Carcinomas

Breast cancer is characterized by considerable metabolic diversity. A relatively high percentage of patients diagnosed with breast carcinoma do not respond to standard-of-care treatment, and alteration in metabolic pathways nowadays is considered one of the major mechanisms responsible for therapeutic resistance. Consequently, there is an emerging need to understand how metabolism shapes therapy response, therapy resistance and not ultimately to analyze the metabolic changes occurring after different treatment regimens. The most commonly applied neoadjuvant chemotherapy regimens in breast cancer contain an anthracycline (doxorubicin or epirubicin) in combination or sequentially administered with taxanes (paclitaxel or docetaxel). Despite several efforts, drug resistance is still frequent in many types of breast cancer, decreasing patients’ survival. Understanding how tumor cells rapidly rewire their signaling pathways to persist after neoadjuvant cancer treatment have to be analyzed in detail and in a more complex system to enable scientists to design novel treatment strategies that target different aspects of tumor cells and tumor resistance. Tumor heterogeneity, the rapidly changing environmental context, differences in nutrient use among different cell types, the cooperative or competitive relationships between cells pose additional challenges in profound analyzes of metabolic changes in different breast carcinoma subtypes and treatment protocols. Delineating the contribution of metabolic pathways to tumor differentiation, progression, and resistance to different drugs is also the focus of research. The present review discusses the changes in glucose and fatty acid pathways associated with the most frequently applied chemotherapeutic drugs in breast cancer, as well the underlying molecular mechanisms and corresponding novel therapeutic strategies.