Comparison of patterns and prognosis among distant metastatic breast cancer patients by age groups: a SEER population-based analysis. Sci Rep. 2017;7:9254. [PMID: 28835702 PMCID: PMC5569011 DOI: 10.1038/s41598-017-10166-8]

Oral and intestinal flora translocation and tumor development

ABSTRACT

Cancer metastasis is the leading cause of death in patients. In recent years, there has been a growing recognition of the role of tumor-associated microflora in tumor metastasis. The connection between oral and gut microflora and the tumor microenvironment has also been extensively studied. The migration of oral and gut microflora is closely associated with tumor development. Although there is awareness regarding the significant impact of microbial communities on human health, the focus on their relationship with host organisms, particularly those related to tumor-associated microflora, remains inadequate. As an integral part of the body, the host microflora is crucial for regulating the cancer risk and preventing tumor recurrence. The oral-gut axis plays an indispensable role in human immunity, and many types of cancers, such as colorectal, pancreatic, and breast, are significantly influenced by their internal microbial communities. However, further exploration into the mechanisms underlying the role of the intratumoral microflora in cancer is necessary to achieve a comprehensive understanding. We have summarized and analyzed related articles in PubMed. This article reviews the impact of the oral-gut axis on the human immune system, explores the relationship between the translocation of the oral and intestinal flora and the tumor microenvironment, analyzes the specific mechanisms involved in the translocation of the oral and intestinal microflora during the evolution and progression of tumors, and elaborates on the correlations between the occurrence and development of tumors and the changes in the microflora. Finally, a summary of these abovementioned points is provided.

Peritoneal cytology predicting distant metastasis in uterine carcinosarcoma: machine learning model development and validation

OBJECTIVE

This study develops and validates a machine learning model using peritoneal cytology to predict distant metastasis in uterine carcinosarcoma, aiding clinical decision-making.

METHODS

This study utilized detailed clinical data and peritoneal cytology findings from uterine carcinosarcoma patients in the SEER database. Eight machine learning algorithms-Logistic Regression, SVM, GBM, Neural Network, RandomForest, KNN, AdaBoost, and LightGBM-were applied to predict distant metastasis. Model performance was assessed using AUC, calibration curves, DCA, confusion matrices, sensitivity, and specificity. The Logistic Regression model was visualized with a nomogram, and its results were analyzed. SHAP values were used to interpret the best-performing machine learning model.

RESULTS

Peritoneal cytology, T stage, age, and tumor size were key factors influencing distant metastasis in uterine carcinosarcoma patients. Peritoneal cytology had significant weight in the prediction models. The logistic regression model demonstrated excellent predictive performance with an AUC of 0.882 in the training set and 0.881 in the internal test set. The model was visualized and interpreted using a nomogram. In comprehensive evaluations, GBM was identified as the best-performing model and was explained using SHAP values. Additionally, calibration and DCA curves indicated that both models have significant potential clinical utility.

CONCLUSION

This study introduces the first effective tool for predicting distant metastasis in uterine carcinosarcoma patients by integrating peritoneal cytology features into model construction. It aids in early identification of high-risk patients, enhancing follow-up and monitoring during tumor development, and supports the optimization of personalized treatment strategies.

Evolutionary paths towards metastasis

The evolution of metastasis in humans is considerably less well understood than the biology of early carcinogenesis. For over a century, clinicians and scientists have been debating whether metastatic potential is the intrinsic property of a cancer, pre-determined by the molecular characteristics of the tumour founder cell, or whether metastatic capacity evolves in a stepwise fashion as the tumour grows, akin to the multistage accumulation of oncogenic alterations that give rise to the first cancer cell. In this Perspective, I examine how genetic analyses of primary tumours and matched metastases can distinguish between these two competing metastasis evolution models, with particular emphasis on the utility of metastatic randomness - a quantitative measure that reflects whether metastases arise from a random selection of primary tumour subclones or whether they are enriched for descendants of privileged lineages that have acquired pro-metastatic traits. Probable metastasis evolution trajectories in tumours with high and low baseline metastatic capacity are discussed, along with the role of seeding rates and selection at different metastatic host sites. Finally, I argue that trailblazing insights into human metastasis biology are immediately possible if we make a concerted effort to apply existing experimental and theoretical tools to the right patient cohorts.

Tumour cell-induced platelet aggregation in breast cancer: Scope of metal nanoparticles

Breast cancer is a major cause of cancer-related mortality among the female population worldwide. Among the various factors promoting breast cancer metastasis, the role of cancer-cell platelet interactions leading to tumour cell-induced platelet aggregation (TCIPA) has garnered significant attention recently. Our state-of-the-art literature review verifies the implications of metal nanoparticles in breast cancer research and TCIPA-specific breast cancer metastasis. We have evaluated in vitro and in vivo research data as well as clinical investigations within the scope of this topic presented in the last ten years. Nanoparticle-based drug delivery platforms in cancer therapy can combat the growing concerns of multi-drug resistance, the alarming rates of chemotherapy-induced toxicities and cancer progression. Metal nanoparticles conjugated with chemotherapeutics can outperform their free drug counterparts in achieving targeted drug delivery and desired drug concentration inside the tumour tissue with minimal toxic effects. Existing data highlights the potential of metal nanoparticles as a promising tool for targeting the platelet-specific interactions associated with breast cancer metastasis including TCIPA.

Nomogram for predicting the risk and prognosis of lung metastasis of four subtypes of breast cancer: A population-based study from SEER

Background

Breast cancer (BC) is the most diagnosed cancer worldwide, and patients' survival decreases with metastasis. We conducted a retrospective study using data derived from the Surveillance, Epidemiology, and End Results (SEER) database and clinicopathological data to construct a clinical predictive model to predict the risk and prognosis of lung metastasis (LM) in patients with different subtypes of BC and validate its performance.

Methods

A total of 1650 patients from the SEER database between 2011 and 2015 were enrolled in this study. Cox regression analysis was performed to identify prognostic factors for breast cancer lung metastasis (BCLM). A nomogram was constructed using the independent prognostic factors. The concordance index (C-index), area under the curve (AUC) value, calibration curve, and decision curve analysis (DCA) were used to test the prediction accuracy of the nomogram. External validation (n = 112) was performed using clinical data from the Affiliated Hospital of Qinghai University and the General Hospital of Ningxia Medical University.

Results

Multivariate Cox regression analyses suggested that age, grade, surgery, chemotherapy, subtype, and liver, bone, and brain metastases were independent prognostic factors for overall survival (OS). Kaplan-Meier survival analysis showed that the median survival times of patients with human epidermal growth factor receptor 2 (HER2)-positive, luminal A, luminal B, and triple-negative BC were 25 (95% confidence interval [CI], 20-37), 27 (95% CI, 23-29), 35 (95% CI, 30-44), and 12 (95% CI, 11-14), respectively. The C-indexes of the nomogram for predicting OS of the SEER training, SEER validation, and clinical validation cohorts were 0.7, 0.6, and 0.6, respectively, and the calculated AUCs at 3 years were 0.765, 0.794, and 0.799, respectively. The calibration curve indicates that the nomogram possessed a high level of accuracy.

Conclusions

Our nomogram demonstrates significant predictive value, indicating that molecular subtypes, brain metastasis, and liver metastasis are closely associated with the prognosis of patients with LM. This information can guide clinical practice.

Examination of Gallbladders at Military Treatment Facilities: Is Histologic Analysis Necessary?

INTRODUCTION

Gallbladder specimens from cholecystectomy procedures are a common specimen evaluated by military pathologists. These are often removed for inflammatory causes. Previous studies show that the incidence of gallbladder carcinoma (GBC) is around 3%. Incidentally identified GBC is even less common at 0.36%. Incidentally found GBCs are of little clinical consequence as most are treated by cholecystectomy alone. We hypothesize that a selective approach to histologic evaluation of gallbladders could save time for pathologists to focus on more complex cancer cases and save money for the Defense Health Agency. We propose that for patients under 50 years of age with no clinical or macroscopic concern for neoplasia, histologic evaluation may be omitted with negligible risk of missing a clinically relevant diagnosis.

MATERIALS AND METHODS

This protocol was determined to be institutional review board exempt. All pathology reports from cholecystectomies from January 1, 1998, to August 11, 2023 were pulled. Key data from these reports were extracted. These data include age, gender, and if there was a clinical or macroscopic concern for neoplasia, macroscopic findings, and histologic findings. Additionally, the patient's active duty status was pulled from Military Health Systems Genesis and the Joint Longitudinal Viewer and included for demographic data.

RESULTS

Of 9,774 cases pulled, 2,063 of these reports underwent data extraction. In total, 63 cases were excluded, and 2,000 cases were sent to the 59th Medical Wing biostatistics department for analysis. In this dataset, there were 8 instances of malignancy, 5 of which were GBC (1 of these 5 arose from an intracholecystic papillary neoplasm), 2 of which were metastatic disease, and 1 a neuroendocrine tumor. The incidence of GBC in our dataset is 0.20%, lower than that of other studies. The sensitivity of a clinical/macroscopic concern to identify malignancy in a patient aged under 50 years is 66.67%. In the 187 cases from the active duty population, there were zero instances of dysplasia or malignancy.

CONCLUSIONS

The sensitivity of a clinical/macroscopic concern for neoplasia in a patient aged under 50 years is low, identifying only 2 of 3 malignancies in our dataset. However, the case that would have been missed under our proposed guidelines was from metastatic disease of a previously known metastatic malignancy. We consider that if a selective histologic evaluation is established, a history of malignancy should be a qualifier for evaluation regardless of any other factors. A selective approach to histologic evaluation of gallbladders could save our institution $4,716 to $5,240 annually. Additional studies, incorporating prior malignancy as a qualifier, are warranted to further evaluate the potential for harm in patients aged under 50 years and a number needed to harm should be established prior to any changes in practice.

Low-Grade Chronic Inflammation: a Shared Mechanism for Chronic Diseases

Inflammation is an important physiological response of the organism to restore homeostasis upon pathogenic or damaging stimuli. However, the persistence of the harmful trigger or a deficient resolution of the process can evolve into a state of low-grade, chronic inflammation. This condition is strongly associated with the development of several increasingly prevalent and serious chronic conditions, such as obesity, cancer, and cardiovascular diseases, elevating overall morbidity and mortality worldwide. The current pandemic of chronic diseases underscores the need to address chronic inflammation, its pathogenic mechanisms, and potential preventive measures to limit its current widespread impact. The present review discusses the current knowledge and research gaps regarding the association between low-grade chronic inflammation and chronic diseases, focusing on obesity, cardiovascular diseases, digestive diseases, and cancer. We examine the state of the art in selected aspects of the topic and propose future directions and approaches for the field.

Intratumoral injection of two dosage forms of paclitaxel nanoparticles combined with photothermal therapy for breast cancer

Objective

In order to enhance the efficacy of anti-breast cancer, paclitaxel nanoparticles (PTX NPs) and polypyrrole nanoparticles (PPy NPs) were combined with photothermal therapy and chemotherapy. At the same time, the two dosage forms of PTX NPs and PTX NPs gel were compared.

Methods

PTX NPs were prepared by self-assembly method, and then the cytotoxicity in vitro was investigated by Methyl thiazolyl tetrazolium (MTT) and other methods, and the efficacy and side effects in vivo were further investigated.

Results

The average hydrated diameter, PDI and electric potential of PTX NPs were (210.20 ± 1.57) nm, (0.081 ± 0.003) mV and (15.80 ± 0.35) mV, respectively. MTT results showed that the IC50 value of PTX NPs on 4 T1 cells was 0.490 μg/mL, while that of PTX injection was 1.737 μg/mL. The cell inhibitory effect of PTX NPs was about 3.5 times higher than that of PTX injection. The tumor inhibition rates of PTX NPs and gel were 48.64% and 56.79%, respectively. Together with local photothermal stimulation, the tumor inhibition rate of the PTX NPs reached 91.05%, surpassing that of the gel under the same conditions (48.98%), moreover, the organ index and H&E staining results of PTX NPs showed a decrease in toxicity.

Conclusion

This combination therapy can significantly enhance the effect of anti-breast cancer, and the synergistic effect of chemotherapy and light and heat provides a feasible and effective strategy for the treatment of tumor.

Patterns of breast cancer locoregional relapse, metastasis, and subtypes in Ghana

BACKGROUND

Significant advances have been made in targeted therapeutics and systemic therapy regimens for breast cancer (BC) treatment over the past decade. Tumour cells can however remain in the body, leading to locoregional relapse and/or metastasis. Subtypes of BC have distinct prognostic effects and have been linked to varying risks of early locoregional relapse and metastases, response to treatment, and overall survival. Most Low- and middle-income countries (LMICs) have no registries of BC locoregional relapse and metastasis.

METHODS

This study comprehensively reviewed, a 3-year retrospective single-centre data of female BC visiting the Komfo Anokye Teaching Hospital (KATH), Ghana to determine the prevalence of locoregional relapse and metastasis across our patient population. Prevalence of metastasis among the various BC subtypes was also determined.

RESULTS

Prevalence of BC locoregional relapse and metastasis were 3.4% and 47.6% respectively. For BC patients with documented locoregional relapse (N = 36), 27.8% (CI = 15.8 - 44.0%) had relapse to the contralateral breast, 41.7% (CI = 27.1 - 57.8%) had relapse to the ipsilateral breast, and 30.6% (CI = 18.0 - 46.9%) had relapse to regional lymph nodes. For BC patients with documented metastasis (N = 503), 151 (30%) had multiple organs involvement, 141 (28%) had lung metastases, 80 (16%) had bone metastases, 45 (9%) had liver metastases, 16 (3%) had brain metastases and 70 (14%) had other metastases (ovary, uterus, spleen, peritoneum, or distant lymph nodes). Basal subtype was the most common subtype (n = 82, 41%), followed by Luminal A (n = 69, 34.5%), HER2+ (n = 37, 18.5%) and Luminal B (n = 12, 6%). Basal subtypes had the most metastasis (35%), with multiple metastasis being the most prevalent (13%).

CONCLUSION

Close to half of the patients (46%) presented with metastatic BC. BC subtypes could influence the specific metastatic site. The most common BC subtype was the Basal subtype and had the most metastases (35%), with multiple metastasis being the most prevalent (13%). These findings should serve as a guide in the management of patients to enhance early prediction and detection of locoregional relapse and metastasis for improved overall treatment outcomes.

Case report: Advanced breast cancer with scalp metastases: a report of two cases

Background

Breast cancer, identified as the most prevalent cancer worldwide, presents considerable difficulties in advanced stages, especially when involving metastatic spread. Scalp metastasis from breast cancer represents a rare and insufficiently explored occurrence. This paper seeks to illuminate this uncommon manifestation by presenting two cases of scalp metastatic breast cancer in Chinese women.

Case report

Case 1: A 45-year-old Chinese woman with a history of invasive ductal carcinoma presented with a scalp lesion indicative of recurrence. Concurrently, she was diagnosed with bone metastases and recurrence at the original site. Despite undergoing various treatments, including chemotherapy and hormonal therapy, her condition worsened, ultimately leading to her passing. Case 2: A 40-year-old Chinese woman was initially diagnosed with bilateral breast invasive mucinous carcinoma presenting with bilateral breast masses and a scalp lesion. She also had multiple bone metastases. Following chemotherapy and hormonal therapy, her disease stabilized.

Conclusion

These cases of scalp metastatic breast cancer underscore the complexities involved in managing advanced stages of the disease, especially with rare metastatic manifestations. They highlight the importance of comprehensive diagnostic methods, encompassing full-body skin evaluations, and draw attention to the socioeconomic challenges faced in cancer treatment. These findings point to the necessity for more targeted research on uncommon metastatic forms in breast cancer aiming to enhance patient outcomes and refine management approaches.

Tumor-induced endothelial RhoA activation mediates tumor cell transendothelial migration and metastasis

The endothelial barrier plays an active role in transendothelial tumor cell migration during metastasis, however, the endothelial regulatory elements of this step remain obscure. Here we show that endothelial RhoA activation is a determining factor during this process. Breast tumor cell-induced endothelial RhoA activation is the combined outcome of paracrine IL-8-dependent and cell-to-cell contact β 1 integrin-mediated mechanisms, with elements of this pathway correlating with clinical data. Endothelial-specific RhoA blockade or in vivo deficiency inhibited the transendothelial migration and metastatic potential of human breast tumor and three murine syngeneic tumor cell lines, similar to the pharmacological blockade of the downstream RhoA pathway. These findings highlight endothelial RhoA as a potent, universal target in the tumor microenvironment for anti-metastatic treatment of solid tumors.

Radiotherapy is recommended for hormone receptor-negative older breast cancer patients after breast conserving surgery

In this study, the necessity of radiotherapy (RT) for hormone receptor-negative older breast cancer patients after breast-conserving surgery (BCS) was investigated. The data of hormone receptor-negative invasive breast cancer patients who underwent BCS were extracted from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. All patients were separated into two groups, namely, the RT group and the no radiotherapy (No RT) group. The 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) rates were compared between the No RT and RT groups after propensity score matching (PSM). The nomograms for predicting the survival of patients were constructed from variables identified by univariate or multivariate Cox regression analysis. A total of 2504 patients were enrolled in the training cohort, and 630 patients were included in the validation cohort. After PSM, 738 patients were enrolled in the No RT group and RT group. We noted that RT can improve survival in hormone receptor-negative older breast cancer patients who undergo BCS. Based on the results of multivariate Cox analysis, age, race, tumour grade, receipt of RT and chemotherapy, pathological T stage, N status, M status and HER2 status were linked to OS and CSS for these patients, and nomograms for predicting OS and CSS were constructed and validated. Moreover, RT improved OS and CSS in hormone receptor-negative older breast cancer patients who underwent BCS. In addition, the proposed nomograms more accurately predicted OS and CSS for hormone receptor-negative older breast cancer patients after BCS.

A nomogram based on inflammation and nutritional biomarkers for predicting the survival of breast cancer patients

Background

We aim to develop a new prognostic model that incorporates inflammation, nutritional parameters and clinical-pathological features to predict overall survival (OS) and disease free survival (DFS) of breast cancer (BC) patients.

Methods

The study included clinicopathological and follow-up data from a total of 2857 BC patients between 2013 and 2021. Data were randomly divided into two cohorts: training (n=2001) and validation (n=856) cohorts. A nomogram was established based on the results of a multivariate Cox regression analysis from the training cohorts. The predictive accuracy and discriminative ability of the nomogram were evaluated by the concordance index (C-index) and calibration curve. Furthermore, decision curve analysis (DCA) was performed to assess the clinical value of the nomogram.

Results

A nomogram was developed for BC, incorporating lymphocyte, platelet count, hemoglobin levels, albumin-to-globulin ratio, prealbumin level and other key variables: subtype and TNM staging. In the prediction of OS and DFS, the concordance index (C-index) of the nomogram is statistically greater than the C-index values obtained using TNM staging alone. Moreover, the time-dependent AUC, exceeding the threshold of 0.7, demonstrated the nomogram's satisfactory discriminative performance over different periods. DCA revealed that the nomogram offered a greater overall net benefit than the TNM staging system.

Conclusion

The nomogram incorporating inflammation, nutritional and clinicopathological variables exhibited excellent discrimination. This nomogram is a promising instrument for predicting outcomes and defining personalized treatment strategies for patients with BC.

6th and 7th International consensus guidelines for the management of advanced breast cancer (ABC guidelines 6 and 7)

This manuscript describes the Advanced Breast Cancer (ABC) international consensus guidelines updated at the last two ABC international consensus conferences (ABC 6 in 2021, virtual, and ABC 7 in 2023, in Lisbon, Portugal), organized by the ABC Global Alliance. It provides the main recommendations on how to best manage patients with advanced breast cancer (inoperable locally advanced or metastatic), of all breast cancer subtypes, as well as palliative and supportive care. These guidelines are based on available evidence or on expert opinion when a higher level of evidence is lacking. Each guideline is accompanied by the level of evidence (LoE), grade of recommendation (GoR) and percentage of consensus reached at the consensus conferences. Updated diagnostic and treatment algorithms are also provided. The guidelines represent the best management options for patients living with ABC globally, assuming accessibility to all available therapies. Their adaptation (i.e. resource-stratified guidelines) is often needed in settings where access to care is limited.

Construction of a prognostic score model for breast cancer based on multi-omics analysis of study on bone metastasis

Background

Breast cancer (BRCA) is the most common type of cancer and the second leading cause of cancer-related death in women all over the world. Metastasis to bone is an indicator of poor prognosis in BRCA patients. This study aimed to develop a prognostic score model for predicting bone metastasis in patients with BRCA.

Methods

BRCA-related RNA sequencing datasets and corresponding clinical information were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) were screened using Limma package of R software. A risk score based predictive model was constructed based on the key genes identified through univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression. The gene expression profiles in BRCA patients were analyzed by gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). Random survival forest (RSF) analysis of BRCA patients with bone metastasis was conducted to identify the key DEGs.

Results

Based on DEG analysis, a total of 677 genes were identified as genes related to bone metastasis in BRCA. By univariate Cox regression and LASSO regression, 28 DEGs were identified as signature genes to develop the prognostic model. A risk score for each patient was created by incorporating the expression values of each specific gene and weighting them with the corresponding estimated regression coefficients. Patients were divided into a low-risk and a high-risk group based on the median risk score. Overall survival (OS) was significantly lower in the high-risk group. The receiver operating characteristic (ROC) curve and multi-omics analysis indicated that the model had high training/testing accuracy and a good clinical predictive value. We used extra data from GEO database to verify the robustness of the prognostic model, and the lower OS in high-risk group and area under the curve (AUC) value indicated the model had strong predictive efficacy for prognosis of BRCA.

Conclusions

A prognostic prediction model was constructed based on 28 key DEGs identified through multi-omics analysis of studies on bone metastasis. The model may provide a promising method for distinguishing the high-risk BRCA patients and help on decision making in addition to prognosis prediction for BRCA patients.

KDM5 family as therapeutic targets in breast cancer: Pathogenesis and therapeutic opportunities and challenges

Breast cancer (BC) is the most frequent malignant cancer diagnosis and is a primary factor for cancer deaths in women. The clinical subtypes of BC include estrogen receptor (ER) positive, progesterone receptor (PR) positive, human epidermal growth factor receptor 2 (HER2) positive, and triple-negative BC (TNBC). Based on the stages and subtypes of BC, various treatment methods are available with variations in the rates of progression-free disease and overall survival of patients. However, the treatment of BC still faces challenges, particularly in terms of drug resistance and recurrence. The study of epigenetics has provided new ideas for treating BC. Targeting aberrant epigenetic factors with inhibitors represents a promising anticancer strategy. The KDM5 family includes four members, KDM5A, KDM5B, KDM5C, and KDMD, all of which are Jumonji C domain-containing histone H3K4me2/3 demethylases. KDM5 proteins have been extensively studied in BC, where they are involved in suppressing or promoting BC depending on their specific upstream and downstream pathways. Several KDM5 inhibitors have shown potent BC inhibitory activity in vitro and in vivo, but challenges still exist in developing KDM5 inhibitors. In this review, we introduce the subtypes of BC and their current therapeutic options, summarize KDM5 family context-specific functions in the pathobiology of BC, and discuss the outlook and pitfalls of KDM5 inhibitors in this disease.

Forget Me Not: Incidental Findings on Breast MRI

With the growing utilization and expanding role of breast MRI, breast imaging radiologists may encounter an increasing number of incidental findings beyond the breast and axilla. Breast MRI encompasses a large area of anatomic coverage extending from the lower neck to the upper abdomen. While most incidental findings on breast MRI are benign, identifying metastatic disease can have a substantial impact on staging, prognosis, and treatment. Breast imaging radiologists should be familiar with common sites, MRI features, and breast cancer subtypes associated with metastatic disease to assist in differentiating malignant from benign findings. Furthermore, detection of malignancies of nonbreast origin as well as nonmalignant, but clinically relevant, incidental findings can significantly impact clinical management and patient outcomes. Breast imaging radiologists should consistently follow a comprehensive search pattern and employ techniques to improve the detection of these important incidental findings.

Patterns of distant metastasis and survival outcomes in de novo metastatic breast cancer according to age groups

Background

Is de novo metastatic breast cancer (dnMBC) the same disease in the elderly as in younger breast cancer remains unclear. This study aimed to determine the metastatic patterns and survival outcomes in dnMBC according to age groups.

Methods

We included patients from the Surveillance Epidemiology and End Results program. Chi-square test, multivariate logistic regression analyses, and multivariate Cox regression models were used for statistical analyses.

Results

A total of 17719 patients were included. There were 3.6% (n=638), 18.6% (n=3290), 38.0% (n=6725), and 39.9% (n=7066) of patients aged <35, 35-49, 50-64, and ≥65 years, respectively. Older patients had a significantly higher risk of lung metastasis and a significantly lower risk of liver metastasis. There were 19.1%, 25.6%, 30.9%, and 35.7% of patients with lung metastasis in those aged <35, 35-49, 50-64, and ≥65 years, respectively. Moreover, the proportion of liver metastasis was 37.6%, 29.5%, 26.3%, and 19.2%, respectively. Age was the independent prognostic factor associated with breast cancer-specific survival (BCSS) and overall survival (OS). Those aged 50-64 years had significantly inferior BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. Patients aged ≥65 years also had significantly lower BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. However, similar outcomes were found between those aged 35-49 and <35 years.

Conclusion

Our study suggests that different age groups may affect the metastatic patterns among patients with dnMBC and the survival of younger patients is more favorable than those of older patients.

Dysregulation of deubiquitination in breast cancer

Breast cancer (BC) is a highly frequent malignant tumor that poses a serious threat to women's health and has different molecular subtypes, histological subtypes, and biological features, which act by activating oncogenic factors and suppressing cancer inhibitors. The ubiquitin-proteasome system (UPS) is the main process contributing to protein degradation, and deubiquitinases (DUBs) are reverse enzymes that counteract this process. There is growing evidence that dysregulation of DUBs is involved in the occurrence of BC. Herein, we review recent research findings in BC-associated DUBs, describe their nature, classification, and functions, and discuss the potential mechanisms of DUB-related dysregulation in BC. Furthermore, we present the successful treatment of malignant cancer with DUB inhibitors, as well as analyzing the status of targeting aberrant DUBs in BC.

Evidence for microtubule nucleation at the Golgi in breast cancer cells

Golgi-derived microtubule (MT) arrays are essential to directionally persistent cell migration and vesicle transport. In this study, we have examined MT nucleation sites in two breast cancer cell lines, MDA-MB-231 and MCF-7, with the hypothesis that only the migratory invasive MDA-MB-231 cells exhibit MTs originating from the Golgi. MTs were disassembled and allowed to slightly regrow so individual nucleation sites could then be observed via fluorescently tagged antibodies (α-tubulin, cis-Golgi marker GM130, and EB1-a MT plus-end binding protein) and confocal microscopy. To determine if MT nucleation at the Golgi is more apparent during active migration compared to when cells are stationary, cells were treated with the chemoattractant epidermal growth factor (EGF) and examined for colocalizations between the Golgi, α-tubulin, and γ-tubulin. Images were analyzed qualitatively for color overlap, and quantitatively using Manders Colocalization Coefficients. Differences between groups were tested for significance using one-way analysis of variances and Tukey's post hoc test. Significantly higher colocalization values (coloc) in the highly invasive MDA-MB-231 cells (α-tubulin coloc GM130 = 0.39, GM130 coloc α-tubulin = 0.82, GM130 coloc EB1 = 0.24, and EB1 coloc GM130 = 0.38) compared to the weakly invasive MCF-7 cells (0.15, 0.08, 0.02, and 0.16, respectively) were observed. EGF-treated cells exhibited higher colocalization values than control cells for three of the four protein combinations tested, but EGF-treated MDA-MB-231 cells exhibited significantly higher values (α-tubulin coloc GM130 = 0.20, GM130 coloc α-tubulin = 0.89, and γ-tubulin coloc GM130 = 0.47) than both control groups as well as the EGF-treated MCF-7 cells. Results support the hypothesis that MT nucleation at the Golgi occurs more frequently in the invasive MDA-MB-231 cell line compared to the weakly invasive MCF-7 cells. The presence or absence of Golgi-derived MTs may help to explain the difference in migratory potential commonly exhibited by these two cell lines.

A Web-based Prediction Model for Early Death in Patients With Metastatic Triple-negative Breast Cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by the absence of expression of estrogen receptor, progesterone receptor, or human epidermal growth factor receptor 2. This subtype of breast cancer is known for its high aggressiveness, high metastatic potential, tendency for recurrence, and poor prognosis. Patients with metastatic TNBC (mTNBC) have a poorer prognosis and a higher likelihood of early death (survival time ≤3 months). Therefore, the development of effective individualized survival prediction tools, such as prediction nomograms and web-based survival calculators, is of great importance for predicting the probability of early death in patients with metastatic TNBC.

METHODS

Patients diagnosed with mTNBC in the Surveillance, Epidemiology, and End Results database between 2010 and 2015 were included in the model construction. Univariate and multivariate logistic regression analysis was performed to identify risk factors associated with early death in patients with mTNBC and predictive prognostic nomograms were constructed. The accuracy of the nomograms was verified using receiver operating characteristic curves, and GiViTi Calibration belt plots were used to evaluate the model consistency. The clinical applicability of the nomograms was evaluated using decision curve analysis. On the basis of the predictive prognostic nomograms, a network survival rate calculator was developed for individualized survival prediction in patients with mTNBC.

RESULTS

A total of 2230 patients diagnosed with mTNBC were included in the Surveillance, Epidemiology, and End Results database for this study. After strict exclusion criteria, 1428 patients were found to be eligible for the study. All the patients were randomly divided into a training cohort and a validation cohort in a ratio of 7:3. Independent risk factors for mTNBC, including age, tumor size, brain metastasis, liver metastasis, surgery, and chemotherapy, were identified and integrated to construct the prediction nomogram and survival calculator. Results of receiver operating characteristic curves, calibration curves, and decision curve analysis curves from the training and validation cohort confirmed that the developed nomogram and web-based survival calculator in this study could accurately predict the probability of early death in patients with mTNBC.

CONCLUSIONS

In this study, we developed a reliable prediction nomogram and web-based survival calculator for predicting the probability of early death in patients with mTNBC. These tools can assist clinical physicians in identifying high-risk patients and developing personalized treatment plans as early as possible.

Machine learning-based prediction model for distant metastasis of breast cancer

BACKGROUND

Breast cancer is the most prevalent malignancy in women. Advanced breast cancer can develop distant metastases, posing a severe threat to the life of patients. Because the clinical warning signs of distant metastasis are manifested in the late stage of the disease, there is a need for better methods of predicting metastasis.

METHODS

First, we screened breast cancer distant metastasis target genes by performing difference analysis and weighted gene co-expression network analysis (WGCNA) on the selected datasets, and performed analyses such as GO enrichment analysis on these target genes. Secondly, we screened breast cancer distant metastasis target genes by LASSO regression analysis and performed correlation analysis and other analyses on these biomarkers. Finally, we constructed several breast cancer distant metastasis prediction models based on Logistic Regression (LR) model, Random Forest (RF) model, Support Vector Machine (SVM) model, Gradient Boosting Decision Tree (GBDT) model and eXtreme Gradient Boosting (XGBoost) model, and selected the optimal model from them.

RESULTS

Several 21-gene breast cancer distant metastasis prediction models were constructed, with the best performance of the model constructed based on the random forest model. This model accurately predicted the emergence of distant metastases from breast cancer, with an accuracy of 93.6 %, an F1-score of 88.9 % and an AUC value of 91.3 % on the validation set.

CONCLUSION

Our findings have the potential to be translated into a point-of-care prognostic analysis to reduce breast cancer mortality.

The Utility of Ultrasound-guided Tru-cut Biopsy in the Diagnosis of Occult Breast Carcinoma Presenting as Ovarian Malignancy with Multiple Metastases: A Case of Unknown Primary

This paper documents the utility of ultrasound-guided tru-cut biopsy in the diagnosis and subsequent management of a case of occult breast carcinoma presenting with multiple distant metastases in the absence of a primary breast lesion. She was initially diagnosed as primary ovarian malignancy with metastatic disease and subsequently underwent transvaginal ultrasound-guided tru-cut biopsy of the right ovarian mass. Histologic and immunohistochemical studies were consistent with a metastatic adenocarcinoma of breast origin. The patient underwent chemotherapy for primary breast carcinoma and has responded well.

Metastasis, characteristic, and treatment of breast cancer in young women and older women: A study from the Surveillance, Epidemiology, and End Results registration database

BACKGROUND

Younger age is an independent risk factor for breast cancer (BC) prognosis, and BC in young women is often considered more aggressive. BC patients with different age and molecular subtypes have different metastasis patterns and survival. Herein, we aim to explore the metastasis patterns, characteristics and treatment methods of young patients with BC, and to compare them with older patients.

METHODS

Data of young patients (aged ≤40 years old) and older patients (aged >40 years old) with BC were extracted from the Surveillance, Epidemiology, and End Results (SEER) registration database in 2010-2019 in this retrospective cohort study. Univariate and multivariate competing risk models and proportional hazard models were used to explore the association between different metastasis patterns and treatments and BC prognoses in young and older patients. Kaplan-Meier (KM) curves were drawn to reflect the survival probability of patients with BC who have different metastasis patterns. Also, we performed subgroup analysis of different metastasis patterns to explore the association between different treatments and overall survival (OS)/cancer specific survival (CSS) in patients with BC. The evaluation index was hazard ratios (HRs) with 95% confidence intervals (CIs).

RESULTS

Totally, 5,984 patients died, and 92.56% of them died from BC. There were respectively 1,089 young patients and 9,105 older patients, and we found some differences of characteristics and metastasis patterns between them. After adjusting for covariates, young patients who had brain metastasis and multiple sites metastasis seemed to have high risk of both lower OS and CSS. Among older patients with BC, brain metastasis, liver metastasis, and multiple sites metastasis were all positively associated with both lower OS and CSS. In young and older patients, those who not receive radiotherapy or surgery, or received non-surgery combined with radiotherapy seemed to have high risk of both lower OS and CSS. Breast-conserving surgery (BCS) and surgery combined with radiotherapy were associated with higher OS and CSS in young patients, while only older patients received surgery combined with radiotherapy had higher OS and CSS. Results of subgroup analysis indicated that for patients with different metastasis patterns, developing a personalized treatment plan is necessary.

CONCLUSIONS

Characteristics of BC between young patients and older patients were different. Clinicians should focus on different metastasis sites and choose appropriate treatments in patients with different ages, which may improve the prognoses.

The Ratio of Key Metabolic Transcripts Is a Predictive Biomarker of Breast Cancer Metastasis to the Lung

Understanding the rewired metabolism underlying organ-specific metastasis in breast cancer could help identify strategies to improve the treatment and prevention of metastatic disease. Here, we used a systems biology approach to compare metabolic fluxes used by parental breast cancer cells and their brain- and lung-homing derivatives. Divergent lineages had distinct, heritable metabolic fluxes. Lung-homing cells maintained high glycolytic flux despite low levels of glycolytic intermediates, constitutively activating a pathway sink into lactate. This strong Warburg effect was associated with a high ratio of lactate dehydrogenase (LDH) to pyruvate dehydrogenase (PDH) expression, which correlated with lung metastasis in patients with breast cancer. Although feature classification models trained on clinical characteristics alone were unable to predict tropism, the LDH/PDH ratio was a significant predictor of metastasis to the lung but not to other organs, independent of other transcriptomic signatures. High lactate efflux was also a trait in lung-homing metastatic pancreatic cancer cells, suggesting that lactate production may be a convergent phenotype in lung metastasis. Together, these analyses highlight the essential role that metabolism plays in organ-specific cancer metastasis and identify a putative biomarker for predicting lung metastasis in patients with breast cancer.

SIGNIFICANCE

Lung-homing metastatic breast cancer cells express an elevated ratio of lactate dehydrogenase to pyruvate dehydrogenase, indicating that ratios of specific metabolic gene transcripts have potential as metabolic biomarkers for predicting organ-specific metastasis.

Evaluation Factors Affecting on Recurrence, Metastasis, and Survival of Breast Cancer in Iranian Women by Multi-State Model Approach

Background

We used the multistate model to investigate how prognostic factors of breast cancer are seen to affect the disease process.

Methods

This cohort study was conducted at Motamed Cancer Institute of Tehran, Iran on 2363 breast cancer patients admitted from 1978 to 2017, and they were followed up until 2018. We applied the multistate models, including four states: diagnosis, recurrence, metastasis, and final absorbing mortality state.

Results

Age over 50 years, positive lymph nodes and tumor size intensified the hazard of transition from diagnosis to metastasis (P=0.002, P<0.001 and P=0.001 respectively) and they also intensified the hazard of transition from diagnosis to mortality (P=0.010, P<0.001 and P<0.001 respectively). At the same time, the educational level decreased the hazard of mentioned transitions (P<0.001). Positive estrogen receptors reduced the hazard of transition from diagnosis to metastasis (P=0.007) and positive lymph nodes also intensified the hazard of transition from metastasis to mortality (P=0.040). Tumor size had an increasing role in the transitions from diagnosis to recurrence, recurrence to metastasis, and metastasis to mortality (P=0.014, P=0.018 and P=0.002 respectively).

Conclusion

Multistate model presented the detailed effects of prognostic factors on progression of breast cancer. Implementing early diagnosis strategies and providing informational programs, especially in younger ages and lower educational level patients may be helpful in reducing the hazard of transition to higher states of breast cancer and increasing the survival of Iranian women with breast cancer by controlling tumor size growth, lymph nodes involvements and estrogen receptor status.

Deep Learning-Based Computational Cytopathologic Diagnosis of Metastatic Breast Carcinoma in Pleural Fluid

A Pleural effusion cytology is vital for treating metastatic breast cancer; however, concerns have arisen regarding the low accuracy and inter-observer variability in cytologic diagnosis. Although artificial intelligence-based image analysis has shown promise in cytopathology research, its application in diagnosing breast cancer in pleural fluid remains unexplored. To overcome these limitations, we evaluate the diagnostic accuracy of an artificial intelligence-based model using a large collection of cytopathological slides, to detect the malignant pleural effusion cytology associated with breast cancer. This study includes a total of 569 cytological slides of malignant pleural effusion of metastatic breast cancer from various institutions. We extracted 34,221 augmented image patches from whole-slide images and trained and validated a deep convolutional neural network model (DCNN) (Inception-ResNet-V2) with the images. Using this model, we classified 845 randomly selected patches, which were reviewed by three pathologists to compare their accuracy. The DCNN model outperforms the pathologists by demonstrating higher accuracy, sensitivity, and specificity compared to the pathologists (81.1% vs. 68.7%, 95.0% vs. 72.5%, and 98.6% vs. 88.9%, respectively). The pathologists reviewed the discordant cases of DCNN. After re-examination, the average accuracy, sensitivity, and specificity of the pathologists improved to 87.9, 80.2, and 95.7%, respectively. This study shows that DCNN can accurately diagnose malignant pleural effusion cytology in breast cancer and has the potential to support pathologists.

Optimal surgical procedure for treating early-stage adenoid cystic carcinoma of the breast

To explore the superiority of breast conservation surgery (BCS) to mastectomy in treating early-stage adenoid cystic carcinoma of the breast (BACC). Patients with surgically treated stage I/II BACC were enrolled between 2000 and 2019 in the SEER database; they were divided into the BCS and mastectomy groups. Overall survival (OS) and disease-specific survival (DSS) were compared between the two groups, and Cox hazard regression models were used to determine the independent predictors. Of the 583 patients in the study, 386 were included in the BCS group. The 10-year OS rates for the BCS and mastectomy groups were 78% (95% CI: 74-82%) and 76% (95% CI: 70-82%), respectively, but the difference was not statistically significant (p = 0.968). The 10-year DSS rates for the BCS and mastectomy groups were 95% (95% CI: 93-97%) and 89% (95% CI: 85-93%), respectively, and the difference was statistically significant (p = 0.002). Pathological examination of regional lymph nodes and adjuvant treatment were not associated with improved OS or DSS, but age, disease grade, and lymph node metastasis were independent prognostic factors. For stage I/II BACC, BCS can achieve more satisfactory 10-year OS and DSS than mastectomy.

Upregulation of the Oct3/4 Network in Basal Breast Cancer Is Associated with Its Metastatic Potential and Shows Tissue Dependent Variability

Adaptive plasticity of Breast Cancer stem cells (BCSCs) is strongly correlated with cancer progression and resistance, leading to a poor prognosis. In this study, we report the expression profile of several pioneer transcription factors of the Oct3/4 network associated with tumor initiation and metastasis. In the triple negative breast cancer cell line (MDA-MB-231) stably transfected with human Oct3/4-GFP, differentially expressed genes (DEGs) were identified using qPCR and microarray, and the resistance to paclitaxel was assessed using an MTS assay. The tumor-seeding potential in immunocompromised (NOD-SCID) mice and DEGs in the tumors were also assessed along with the intra-tumor (CD44+/CD24-) expression using flow cytometry. Unlike 2-D cultures, the Oct3/4-GFP expression was homogenous and stable in 3-D mammospheres developed from BCSCs. A total of 25 DEGs including Gata6, FoxA2, Sall4, Zic2, H2afJ, Stc1 and Bmi1 were identified in Oct3/4 activated cells coupled with a significantly increased resistance to paclitaxel. In mice, the higher Oct3/4 expression in tumors correlated with enhanced tumorigenic potential and aggressive growth, with metastatic lesions showing a >5-fold upregulation of DEGs compared to orthotopic tumors and variability in different tissues with the highest modulation in the brain. Serially re-implanting tumors in mice as a model of recurrence and metastasis highlighted the sustained upregulation of Sall4, c-Myc, Mmp1, Mmp9 and Dkk1 genes in metastatic lesions with a 2-fold higher expression of stem cell markers (CD44+/CD24-). Thus, Oct3/4 transcriptome may drive the differentiation and maintenance of BCSCs, promoting their tumorigenic potential, metastasis and resistance to drugs such as paclitaxel with tissue-specific heterogeneity.

β-Catenin signaling in alveolar macrophages enhances lung metastasis through a TNF-dependent mechanism

The main cause of malignancy-related mortality is metastasis. Although metastatic progression is driven by diverse tumor-intrinsic mechanisms, there is a growing appreciation for the contribution of tumor-extrinsic elements of the tumor microenvironment, especially macrophages, which correlate with poor clinical outcomes. Macrophages consist of bone marrow-derived and tissue-resident populations. In contrast to bone marrow-derived macrophages, the transcriptional pathways that govern the pro-metastatic activities of tissue-resident macrophages (TRMs) remain less clear. Alveolar macrophages (AMs) are a TRM population with critical roles in tissue homeostasis and metastasis. Wnt/β-catenin signaling is a hallmark of cancer and has been identified as a pathologic regulator of AMs in infection. We tested the hypothesis that β-catenin expression in AMs enhances metastasis in solid tumor models. Using a genetic β-catenin gain-of-function approach, we demonstrated that (a) enhanced β-catenin in AMs heightened lung metastasis; (b) β-catenin activity in AMs drove a dysregulated inflammatory program strongly associated with Tnf expression; and (c) localized TNF-α blockade abrogated this metastatic outcome. Last, β-catenin gene CTNNB1 and TNF expression levels were positively correlated in AMs of patients with lung cancer. Overall, our findings revealed a Wnt/β-catenin/TNF-α pro-metastatic axis in AMs with potential therapeutic implications against tumors refractory to the antineoplastic actions of TNF-α.

The intratumoral microbiota: friend or foe?

The intratumoral microbiota has been recently identified as important in cancer evasion strategies. It can induce DNA damage, favor the epithelial-mesenchymal transition, inactivate drugs, polarize the immune system toward a protumorigenic profile, induce vascular reshaping and favor metastasis formation, and protect tumor cells from fluid shear stress during cell migration. However, recently also some positive effects of the intratumoral microbiota have been highlighted such as the activation of bacterial antigen-specific responses that could be harnessed to broaden not only the immune response to tumor antigens, but also the polarization of antitumorigenic responses. As in the gut, it is likely that the ratio between symbionts and pathobionts affects the outcome. More research is needed in this field to better understand this dual role.

Molecular subtypes predict the preferential site of distant metastasis in advanced breast cancer: a nationwide retrospective study

Objective

This study aimed to explore possible associations between molecular subtypes and site of distant metastasis in advanced breast cancer (ABC).

Methods

3577 ABC patients were selected from 21 hospitals of seven geographic regions in China from 2012-2014. A questionnaire was designed to collect medical information regarding demographic characteristics, risk factors, molecular subtype, recurrence/metastasis information, and disease-free survival (DFS). The cancers were classified into Luminal A, Luminal B, HER2-enriched and Triple Negative subtypes. Chi-square test and multivariate Cox proportional hazard models were performed to explore the associations between molecular subtypes and distant metastasis sites.

Results

A total of 2393 cases with molecular subtypes information were finally examined. Patients with Luminal A (51.1%) and Luminal B (44.7%) were most prone to bone metastasis, whereas liver metastasis was more frequently observed in HER2-enriched ABC patients (29.1%).The cumulative recurrence and metastasis rates of ABC patients at 36 months of DFS were the most significant within molecular types, of which Triple Negative was the highest (82.7%), while that of Luminal A was the lowest (58.4%). In the adjusted Cox regression analysis, Luminal B, HER2-enriched and Triple Negative subtypes increased the risk of visceral metastasis by 23%, 46% and 87% respectively. In addition, Triple Negative patients had a higher probability of brain metastasis (HR 3.07, 95% CI: 1.04-9.07).

Conclusion

Molecular subtypes can predict the preferential sites of distant metastasis, emphasizing that these associations were of great help in choices for surveillance, developing appropriate screening and cancer management strategies for follow-up and personalized therapy in ABC patients.

Dual Magnetic Particle Imaging and Akaluc Bioluminescence Imaging for Tracking Cancer Cell Metastasis

Magnetic particle imaging (MPI) provides hotspot tracking and direct quantification of superparamagnetic iron oxide nanoparticle (SPIO)-labelled cells. Bioluminescence imaging (BLI) with the luciferase reporter gene Akaluc can provide complementary information on cell viability. Thus, we explored combining these technologies to provide a more holistic view of cancer cell fate in mice. Akaluc-expressing 4T1Br5 cells were labelled with the SPIO Synomag-D and injected into the mammary fat pads (MFP) of four nude mice. BLI was performed on days 0, 6 and 13, and MPI was performed on days 1, 8 and 14. Ex vivo histology and fluorescence microscopy of MFP and a potential metastatic site was conducted. The BLI signal in the MFP increased significantly from day 0 to day 13 (p < 0.05), mirroring tumor growth. The MPI signal significantly decreased from day 1 to day 14 (p < 0.05) due to SPIO dilution in proliferating cells. Both modalities detected secondary metastases; however, they were visualized in different anatomical regions. Akaluc BLI complemented MPI cell tracking, allowing for longitudinal measures of cell viability and sensitive detection of distant metastases at different locations. We predict this multimodal imaging approach will help to evaluate novel therapeutics and give a better understanding of metastatic mechanisms.

Evaluation of machine learning algorithms for the prognosis of breast cancer from the Surveillance, Epidemiology, and End Results database

INTRODUCTION

Many researchers used machine learning (ML) to predict the prognosis of breast cancer (BC) patients and noticed that the ML model had good individualized prediction performance.

OBJECTIVE

The cohort study was intended to establish a reliable data analysis model by comparing the performance of 10 common ML algorithms and the the traditional American Joint Committee on Cancer (AJCC) stage, and used this model in Web application development to provide a good individualized prediction for others.

METHODS

This study included 63145 BC patients from the Surveillance, Epidemiology, and End Results database.

RESULTS

Through the performance of the 10 ML algorithms and 7th AJCC stage in the optimal test set, we found that in terms of 5-year overall survival, multivariate adaptive regression splines (MARS) had the highest area under the curve (AUC) value (0.831) and F1-score (0.608), and both sensitivity (0.737) and specificity (0.772) were relatively high. Besides, MARS showed a highest AUC value (0.831, 95%confidence interval: 0.820-0.842) in comparison to the other ML algorithms and 7th AJCC stage (all P < 0.05). MARS, the best performing model, was selected for web application development (https://w12251393.shinyapps.io/app2/).

CONCLUSIONS

The comparative study of multiple forecasting models utilizing a large data noted that MARS based model achieved a much better performance compared to other ML algorithms and 7th AJCC stage in individualized estimation of survival of BC patients, which was very likely to be the next step towards precision medicine.

Invasion and Secondary Site Colonization as a Function of In Vitro Primary Tumor Matrix Stiffness: Breast to Bone Metastasis

Increased breast tissue stiffness is correlated with breast cancer risk and invasive cancer progression. However, its role in promoting bone metastasis, a major cause of mortality, is not yet understood. It is previously identified that the composition and stiffness of alginate-based hydrogels mimicking normal (1-2 kPa) and cancerous (6-10 kPa) breast tissue govern phenotype of breast cancer cells (including MDA-MB-231) in vitro. Here, to understand the causal effect of primary tumor stiffness on metastatic potential, a new breast-to-bone in vitro model is described. Together with alginate-gelatin hydrogels to mimic breast tissue, 3D printed biohybrid poly-caprolactone (PCL)-composite scaffolds, decellularized following bone-ECM deposition through Saos-2 engraftment, are used to mimic the bone tissue. It is reported that higher hydrogel stiffness results in the increased migration and invasion capacity of MDA-MB 231 cells. Interestingly, increased expression of osteolytic factors PTHrP and IL-6 is observed when MDA-MB-231 cells pre-conditioned in stiffer hydrogels (10 kPa, 3% w/v gelatin) colonize the bone/PCL scaffolds. The new breast-to-bone in vitro models herein described are designed with relevant tissue microenvironmental factors and could emerge as future non-animal technological platforms for monitoring metastatic processes and therapeutic efficacy.

Survival analysis and prognosis of patients with breast cancer with pleural metastasis

Background

Breast cancer (BC) is the most common malignant cancer. The prognosis of patients differs according to the location of distant metastasis, with pleura being a common metastatic site in BC. Nonetheless, clinical data of patients with pleural metastasis (PM) as the only distant metastatic site at initial diagnosis of metastatic BC (MBC) are limited.

Patient cohort and methods

The medical records of patients who were hospitalized in Shandong Cancer Hospital between January 1, 2012 and December 31, 2021 were reviewed, and patients eligible for the study were selected. Survival analysis was conducted using Kaplan-Meier (KM) method. Univariate and multivariate Cox proportional-hazards models were used to identify prognostic factors. Finally, based on these selected factors, a nomogram was constructed and validated.

Results

In total, 182 patients were included; 58 (group A), 81 (group B), and 43 (group C) patients presented with only PM, only lung metastasis (LM), and PM combined with LM, respectively. The KM curves revealed no significant difference in overall survival (OS) among the three groups. However, in terms of survival after distant metastasis (M-OS), the difference was significant: patients with only PM exhibited the best prognosis, whereas those with PM combined with LM exhibited the worst prognosis (median M-OS: 65.9, 40.5, and 32.4 months, respectively; P = 0.0067). For patients with LM in groups A and C, those with malignant pleural effusion (MPE) exhibited significantly worse M-OS than those without MPE. Univariate and multivariate analyses indicated that primary cancer site, T stage, N stage, location of PM, and MPE were independent prognostic factors for patients with PM without other distant metastasis. A nomogram prediction model incorporating these variables was created. According to the C-index (0.776), the AUC values of the 3-, 5-, and 8-year M-OS (0.86, 0.86, and 0.90, respectively), and calibration curves, the predicted and actual M-OS were in good agreement.

Conclusion

BC patients with PM only at the first diagnosis of MBC exhibited a better prognosis than those with LM only or PM combined with LM. We identified five independent prognostic factors associated with M-OS in this subset of patients, and a nomogram model with good predictive efficacy was established.

A Novel Nanoemulsion Formula for an Improved Delivery of a Thalidomide Analogue to Triple-Negative Breast Cancer; Synthesis, Formulation, Characterization and Molecular Studies

Background

Thalidomide (THD) and its analogues were recently reported as a promising treatment for different types of solid tumors due to their antiangiogenic effect.

Methods

In this work, we synthesized a novel THD analogue (TA), and its chemistry was confirmed with different techniques such as IR, mass spectroscopy, elemental analysis as well as ¹H and ¹³C NMR. To increase solubility and anticancer efficacy, a new oil in water (O/W) nanoemulsion (NE) was used in the formulation of the analogue. The novel formula's surface charge, size, stability, FTIR, FE-TEM, in vitro drug release and physical characteristics were investigated. Furthermore, molecular docking studies were conducted to predict the possible binding modes and molecular interactions behind the inhibitory activities of the THD and TA.

Results

TA showed a significant cytotoxic activity with IC₅₀ ranging from 0.326 to 43.26 µmol/mL when evaluated against cancerous cells such as MCF-7, HepG2, Caco-2, LNCaP and RKO cell lines. The loaded analogue showed more potential cytotoxicity against MDA-MB-231 and MCF-7-ADR cell lines with IC₅₀ values of 0.0293 and 0.0208 nmol/mL, respectively. Moreover, flow cytometry of cell cycle analysis and apoptosis were performed showing a suppression in the expression levels of TGF-β, MCL-1, VEGF, TNF-α, STAT3 and IL-6 in the MDA-MB-231 cell line.

Conclusion

The novel NE formula dramatically reduced the anticancer dosage of TA from micromolar efficiency to nanomolar efficiency. This indicates that the synthesized analogue exhibited high potency in the NE formulation and proved its efficacy against triple-negative breast cancer cell line.

Breast Cancer Metastasis to the Gastrointestinal Tract With Unusual Endoscopic and Histologic Presentations

The gastrointestinal (GI) tract is an infrequent site of breast cancer metastasis, but it often poses a diagnostic challenge when it occurs. The symptoms of GI metastases are often nonspecific, and the endoscopic manifestations are variable, requiring tissue biopsies for histologic examination. We report 2 cases of breast cancer metastasizing to the GI tract: a case of human epidermal growth factor receptor 2-positive invasive ductal carcinoma that metastasized to the stomach, a rare location for this histologic subtype, and another case of invasive lobular cell carcinoma that metastasized to the colon with unusual findings of mucosal pallor and edema on colonoscopy.

Gastric Outlet Obstruction Secondary to Metastatic Breast Carcinoma 25 Years After Initial Diagnosis: A Mimic of Primary Gastric Carcinoma

Although breast cancer is the most common form of cancer in women, metastasis to the stomach is incredibly rare. Gastric metastasis of breast cancer has been described in the literature, with an estimated median of 6 years from the initial diagnosis of primary breast cancer to metastasis and multiple instances greater than 10 years. In this case, a patient presented with gastric outlet obstruction in the setting of breast cancer metastasis to the pylorus 25 years after the original diagnosis.

Deciphering functional tumor states at single-cell resolution

Within a tumor, cancer cells exist in different states that are associated with distinct tumor functions, including proliferation, differentiation, invasion, metastasis, and resistance to anti-cancer therapy. The identification of the gene regulatory networks underpinning each state is essential for better understanding functional tumor heterogeneity and revealing tumor vulnerabilities. Here, we review the different studies identifying tumor states by single-cell sequencing approaches and the mechanisms that promote and sustain these functional states and regulate their transitions. We also describe how different tumor states are spatially distributed and interact with the specific stromal cells that compose the tumor microenvironment. Finally, we discuss how the understanding of tumor plasticity and transition states can be used to develop new strategies to improve cancer therapy.

Sarcopenia using pectoralis muscle area and lymphocyte-to-monocyte ratio (LMR) are independent prognostic factors in patients for nonmetastatic breast cancer

Sarcopenia is defined as loss of skeletal muscle mass and strength. This can lead to adverse clinical outcomes in patients with advanced cancer. The lymphocyte-to-monocyte ratio (LMR), a converted inflammatory response, is associated with poor prognosis in patients with malignancies. Herein, we examined the prognostic influence of sarcopenia status assessed by pectoralis muscle area (PMA), inflammatory status calculated by LMR, and its association with disease-free survival (DFS) in a cohort of women diagnosed with nonmetastatic breast cancer. A total of 293 patients with nonmetastatic breast cancer who underwent primary mass resection and radiotherapy between January 2011 and December 2017 were enrolled. The cross-sectional area of the muscle (cm2) at PMA was measured using computed tomography before radiation therapy. Baseline monocyte and lymphocyte counts were obtained from the complete blood count to calculate the LMR. Most of the patients (248/293, 84.6%) underwent breast conservation surgery. Lymph node involvement at diagnosis (hazard ratio [HR], 5.08; P < .001), low LMR (HR, 2.79; P = .007), and low PMA (HR, 3.80; P < .001) were independent poor prognostic factors in multivariate analysis. The mean DFS of sarcopenic and nonsarcopenic patients was 89.8 months and 118.8 months, respectively (P < .001). Sarcopenic patients with low LMR showed the worst outcomes, whereas nonsarcopenic patients with high LMR showed the best outcomes. Low PMA and low LMR were independent poor prognostic factors for DFS in patients with nonmetastatic breast cancer.

Estrone, the major postmenopausal estrogen, binds ERa to induce SNAI2, epithelial-to-mesenchymal transition, and ER+ breast cancer metastasis

Recent work showed that the dominant post-menopausal estrogen, estrone, cooperates with nuclear factor κB (NF-κB) to stimulate inflammation, while pre-menopausal 17β-estradiol opposes NF-κB. Here, we show that post-menopausal estrone, but not 17β-estradiol, activates epithelial-to-mesenchymal transition (EMT) genes to stimulate breast cancer metastasis. HSD17B14, which converts 17β-estradiol to estrone, is higher in cancer than normal breast tissue and in metastatic than primary cancers and associates with earlier metastasis. Treatment with estrone, but not 17β-estradiol, and HSD17B14 overexpression both stimulate an EMT, matrigel invasion, and lung, bone, and liver metastasis in estrogen-receptor-positive (ER+) breast cancer models, while HSD17B14 knockdown reverses the EMT. Estrone:ERα recruits CBP/p300 to the SNAI2 promoter to induce SNAI2 and stimulate an EMT, while 17β-estradiol:ERα recruits co-repressors HDAC1 and NCOR1 to this site. Present work reveals novel differences in gene regulation by these estrogens and the importance of estrone to ER+ breast cancer progression. Upon loss of 17β-estradiol at menopause, estrone-liganded ERα would promote ER+ breast cancer invasion and metastasis.

Comprehensive Review of Metastatic Breast Carcinoma in Cytology Specimens

Breast carcinomas are known to metastasize to various organs of the human body. Fine needle aspiration cytology or exfoliative cytology often are the standard method for diagnosis at these metastatic sites due to ease of procurement of diagnostic material, accessibility, less complications, high sensitivity, and specificity of diagnosis and evaluation of biomarker status needed to guide future management. This comprehensive review article discusses in detail metastatic patterns, cytomorphology of metastatic breast cancer at different body sites, immunohistochemistry needed for diagnosis of breast carcinoma, sensitivity and specificity of diagnosis and breast biomarker assays in the cytology material.

STAT family of transcription factors in breast cancer: Pathogenesis and therapeutic opportunities and challenges

Breast cancer is the most commonly diagnosed cancer and second-leading cause of cancer deaths in women. Breast cancer stem cells (BCSCs) promote metastasis and therapeutic resistance contributing to tumor relapse. Through activating genes important for BCSCs, transcription factors contribute to breast cancer metastasis and therapeutic resistance, including the signal transducer and activator of transcription (STAT) family of transcription factors. The STAT family consists of six major isoforms, STAT1, STAT2, STAT3, STAT4, STAT5, and STAT6. Canonical STAT signaling is activated by the binding of an extracellular ligand to a cell-surface receptor followed by STAT phosphorylation, leading to STAT nuclear translocation and transactivation of target genes. It is important to note that STAT transcription factors exhibit diverse effects in breast cancer; some are either pro- or anti-tumorigenic while others maintain dual, context-dependent roles. Among the STAT transcription factors, STAT3 is the most widely studied STAT protein in breast cancer for its critical roles in promoting BCSCs, breast cancer cell proliferation, invasion, angiogenesis, metastasis, and immune evasion. Consequently, there have been substantial efforts in developing cancer therapeutics to target breast cancer with dysregulated STAT3 signaling. In this comprehensive review, we will summarize the diverse roles that each STAT family member plays in breast cancer pathobiology, as well as, the opportunities and challenges in pharmacologically targeting STAT proteins and their upstream activators in the context of breast cancer treatment.

Overall survival of individuals with metastatic cancer in Sweden: a nationwide study

Aims

Consistent improvements for overall survival (OS) have been reported for individuals with metastatic cancer. Swedish population-based registers allow national coverage and long follow-up time. The aim of this study was to estimate and explore long-term OS of individuals diagnosed with metastatic cancer using Swedish nationwide health registers.

Methods

Individuals with metastatic breast (MBC), non-small cell lung (MNSCLC), ovary (MOC) or colorectal cancer (MCRC) or metastatic malignant melanoma (MMM) were identified in the Swedish national cancer register and national patient registers. Survival was estimated and stratified by available variables. Potential cure fractions were estimated using mixture cure models.

Results

In total, approximately 69,000 individuals were identified. The most common cancers were MCRC (36.2%) and MNSCLC (29.5%). Men were more frequently diagnosed with MNSCLC, MCRC, and MMM compared to women. Except for MOC, about 50% of individuals were 70 years or older at diagnosis. Throughout the study period survival differed across cancers. The longest median OS was observed for individuals with MOC and MBC. At 10 years of follow-up, the survival curves flatten at a survival rate of approximately 10% for all cancers except MNSCLC. The youngest age groups had the longest median OS. Increased survival was also observed for individuals diagnosed in 2015 and 2018 compared to individuals diagnosed during earlier years. The estimated cure fractions were 4% for MBC, 1.5% for MNSCLC, 6.8% for MCRC, 8.6% for MOC and MMM.

Conclusions

Long-term survival has been assessed across all indications except for NSCLC.. The findings may be relevant for healthcare planning to meet the needs of future patients and potential long-term survivors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14255-w.

Metastasis patterns and prognosis in young breast cancer patients: A SEER database analysis

Background

There are few studies on young patients with metastatic breast cancer (MBC). This study aims to explore the metastasis pattern and prognosis of young patients with MBC.

Methods

A total of 6,336 MBC patients diagnosed in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015 were selected. They were divided into two age groups: the younger group (≤40 years old) and the older group (>40 years old). χ² test was used to compare clinicopathological characteristics. Survival differences were compared by Kaplan–Meier analysis. Cox regression models were used to determine the prognostic factors affecting survival. Propensity score matching (PSM) was performed to balance the effects of baseline clinicopathological differences.

Results

Finally, 494 patients (7.8%) who are ≤40 years old and 5,842 patients (92.2%) who are >40 years old were included. In the younger group, the proportion of liver metastasis was significantly higher than that in the older group; the proportion of lung metastasis was significantly lower than that of the older group. Kaplan–Meier analysis showed that the younger group had the best prognosis and the older group had the worst. Youth is an independent protective factor for overall survival (OS). In the younger group, liver metastasis had the best prognosis among all metastatic sites, and the HER2-enriched subtype had the best prognosis among all subtypes.

Conclusions

The disease in young MBC patients is more aggressive but has a better prognosis, especially in liver metastases and the HER2-enriched subtypes.

Development and validation of nomograms for predicting overall survival and cancer specific survival in locally advanced breast cancer patients: A SEER population-based study

Background

For patients with locally advanced breast cancer (LABC), conventional TNM staging is not accurate in predicting survival outcomes. The aim of this study was to develop two accurate survival prediction models to guide clinical decision making.

Methods

A retrospective analysis of 22,842 LABC patients was performed from 2010 to 2015 using the Surveillance, Epidemiology and End Results (SEER) database. An additional cohort of 200 patients from the Binzhou Medical University Hospital (BMUH) was analyzed. The least absolute shrinkage and selection operator (LASSO) regression was used to screen for variables. The identified variables were used to build a survival prediction model. The performance of the nomogram models was assessed based on the concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA).

Results

The LASSO analysis identified 9 variables in patients with LABC, including age, marital status, Grade, histological type, T-stage, N-stage, surgery, radiotherapy, and chemotherapy. In the training cohort, the C-index of the nomogram in predicting the overall survival (OS) was 0.767 [95% confidence intervals (95% CI): 0.751-0.775], cancer specific survival (CSS) was 0.765 (95% CI: 0.756-0.774). In the external validation cohort, the C-index of the nomogram in predicting the OS was 0.858 (95% CI: 0.812-0.904), the CSS was 0.866 (95% CI: 0.817-0.915). In the training cohort, the area under the receiver operator characteristics curve (AUC) values of the nomogram in prediction of the 1, 3, and 5-year OS were 0.836 (95% CI: 0.821-0.851), 0.769 (95% CI: 0.759-0.780), and 0.750 (95% CI: 0.738-0.762), respectively. The AUC values for prediction of the 1, 3, and 5-year CSS were 0.829 (95% CI: 0.811-0.847), 0.769 (95% CI: 0.757-0.780), and 0.745 (95% CI: 0.732-0.758), respectively. Results of the C-index, ROC curve, and DCA demonstrated that the nomogram was more accurate in predicting the OS and CSS of patients compared with conventional TNM staging.

Conclusion

Two prediction models were developed and validated in this study which provided more accurate prediction of the OS and CSS in LABC patients than the TNM staging. The constructed models can be used for predicting survival outcomes and guide treatment plans for LABC patients.

ATP6AP1 is a potential prognostic biomarker and is associated with iron metabolism in breast cancer

Cancer occurrence and progression may be facilitated by aberrant expression of ATPase H+ transporting accessory protein 1 (ATP6AP1). However, the clinical relevance of ATP6AP1 in breast cancer remains unclear. In this study, we investigated the association between ATP6AP1 and breast cancer. Data collected from patients with breast cancer from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were used in this study. To determine the relationship between ATP6AP1 and breast cancer survival rates, Kaplan-Meier analysis was used. To determine the prognostic value of ATP6AP1, a receiver operating characteristic (ROC) curve was constructed. To identify the major pathways involving ATP6AP1, we performed functional enrichment analysis using gene set enrichment analysis (GSEA). We analyzed the association between ATP6AP1 expression and tumor immunity using the ESTIMATE algorithm and single-sample GSEA (ssGSEA). A nomogram based on a Cox regression analysis was constructed to predict the impact of ATP6AP1 on prognosis. ATP6AP1 expression was significantly upregulated in breast cancer tissues. Moreover, patients with elevated ATP6AP1 expression had shorter total survival rates than those with lower expression levels (p = 0.032). The area under the receiver operating characteristic curve for ATP6AP1 was 0.939. Gene set enrichment analysis revealed that reaction iron uptake and transport, proteasome degradation, glutathione metabolism, and pyruvate metabolism were enriched in the ATP6AP1 high expression phenotype. The relationship between immune infiltration cells and ATP6AP1 expression, including macrophages, B cells, dendritic cells, cytotoxic cells, NK cells, and T cells, was found to be negative, suggesting that ATP6AP1 overexpression results in immunosuppression. Based on the Cox regression analyses, the calibration plot of the nomogram demonstrated effective performance in predicting breast cancer patients. ATP6AP1 may facilitate breast cancer progression by inhibiting antitumor immunity and promoting iron metabolism and may be a biomarker for breast cancer prognosis.

Diagnostic and Prognostic Nomograms for Lung Metastasis in Triple-Negative Breast Cancer

Background

The lungs are one of the common sites of metastasis of triple-negative breast cancer (TNBC). Patients with lung metastases (LM) have a shorter duration of survival. This study is aimed at determining the prognostic factors of patients with TNBC with LM and constructing two nomograms to assess the risk of LM and the prognosis of patients with TNBC with LM.

Methods

Clinicopathological and follow-up data of patients with TNBC between 2010 and 2015 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were used to screen for independent predictors of LM in patients with TNBC and identify the independent prognostic factors of patients with TNBC with LM. The two nomograms were appraised using calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

Results

A total of 27,048 patients with TNBC were included in this study. Age, tumour size, T stage, and N stage were identified as independent risk factors for LM in patients with TNBC. Histological type, marital status, prior surgery, chemotherapy, bone metastases, brain metastases, and LM were confirmed as independent prognostic factors for patients with TNBC with LM. The area under the ROC curve (AUC) of the diagnostic nomogram was 0.838 (95% confidence interval 0.817-0.860) in the training cohort and 0.894 (95% confidence interval 0.875-0.917) in the verification cohort. The AUC values of the 6-, 12-, and 18-month prognostic nomograms in the training cohort were 0.809 (95% confidence interval 0.771-0.868), 0.779 (95% confidence interval 0.737-0.834), and 0.735 (95% confidence interval 0.699-0.811), respectively, and the corresponding AUC values in the validation cohort were 0.735(95% confidence interval 0.642-0.820), 0.672 (95% confidence interval 0.575-0.758), and 0.705 (95% confidence interval 0.598-0.782), respectively. According to the calibration curves and data analysis, both nomograms exhibited good performance.

Conclusion

We successfully constructed and verified two valuable nomograms for predicting the incidence of LM and prognosis of patients TNBC with LM.