Distant Metastatic Breast Cancer Research Articles

Novel models by machine learning to predict prognosis of breast cancer brain metastases

BackgroundBreast cancer brain metastases (BCBM) are the most fatal, with limited survival in all breast cancer distant metastases. These patients are deemed to be incurable. Thus, survival time is their foremost concern. However, there is a lack of accurate prediction models in the clinic. What’s more, primary surgery for BCBM patients is still controversial.MethodsThe data used for analysis in this study was obtained from the SEER database (2010–2019). We made a COX regression analysis to identify prognostic factors of BCBM patients. Through cross-validation, we constructed XGBoost models to predict survival in patients with BCBM. Meanwhile, a BCBM cohort from our hospital was used to validate our models. We also investigated the prognosis of patients treated with surgery or not, using propensity score matching and K–M survival analysis. Our results were further validated by subgroup COX analysis in patients with different molecular subtypes.ResultsThe XGBoost models we created had high precision and correctness, and they were the most accurate models to predict the survival of BCBM patients (6-month AUC = 0.824, 1-year AUC = 0.813, 2-year AUC = 0.800 and 3-year survival AUC = 0.803). Moreover, the models still exhibited good performance in an externally independent dataset (6-month: AUC = 0.820; 1-year: AUC = 0.732; 2-year: AUC = 0.795; 3-year: AUC = 0.936). Then we used Shiny-Web tool to make our models be easily used from website. Interestingly, we found that the BCBM patients with an annual income of over USD$70,000 had better BCSS (HR = 0.523, 95%CI 0.273–0.999, P < 0.05) than those with less than USD$40,000. The results showed that in all distant metastasis sites, only lung metastasis was an independent poor prognostic factor for patients with BCBM (OS: HR = 1.606, 95%CI 1.157–2.230, P < 0.01; BCSS: HR = 1.698, 95%CI 1.219–2.365, P < 0.01), while bone, liver, distant lymph nodes and other metastases were not. We also found that surgical treatment significantly improved both OS and BCSS in BCBM patients with the HER2 + molecular subtypes and was beneficial to OS of the HR−/HER2− subtype. In contrast, surgery could not help BCBM patients with HR + /HER2− subtype improve their prognosis (OS: HR = 0.887, 95%CI 0.608–1.293, P = 0.510; BCSS: HR = 0.909, 95%CI 0.604–1.368, P = 0.630).ConclusionWe analyzed the clinical features of BCBM patients and constructed 4 machine-learning prognostic models to predict their survival. Our validation results indicate that these models should be highly reproducible in patients with BCBM. We also identified potential prognostic factors for BCBM patients and suggested that primary surgery might improve the survival of BCBM patients with HER2 + and triple-negative subtypes.

Exosomal miRNA-223-3p derived from tumor associated macrophages promotes pulmonary metastasis of breast cancer 4T1 cells

Research about the effect of exosomes derived from tumor associated macrophages (TAM-exos) in the distant organ metastasis of breast cancer is limited. In this study, we found that TAM-exos could promote the migration of 4T1 cells. Through comparing the expression of microRNAs in 4T1 cells, TAM-exos, and exosomes from bone marrow derived macrophages (BMDM-exos) by sequencing, miR-223-3p and miR-379-5p were screened out as two noteworthy differentially expressed microRNAs. Furthermore, miR-223-3p was confirmed to be the reason for the improved migration and metastasis of 4T1 cells. The expression of miR-223-3p was also increased in 4T1 cells isolated from the lung of tumor-bearing mice. Cbx5, which has been reported to be closely related with metastasis of breast cancer, was identified to be the target of miR-223-3p. Based on the information of breast cancer patients from online databases, miR-223-3p had a negative correlation with the overall survival rate of breast cancer patients within a three-year follow-up, while Cbx5 showed an opposite relationship. Taken together, miR-223-3p in TAM-exos can be delivered into 4T1 cells and exosomal miR-223-3p promotes pulmonary metastasis of 4T1 cells by targeting Cbx5.

The prediction of distant metastasis risk for male breast cancer patients based on an interpretable machine learning model

ObjectivesThis research was designed to compare the ability of different machine learning (ML) models and nomogram to predict distant metastasis in male breast cancer (MBC) patients and to interpret the optimal ML model by SHapley Additive exPlanations (SHAP) framework.MethodsFour powerful ML models were developed using data from male breast cancer (MBC) patients in the SEER database between 2010 and 2015 and MBC patients from our hospital between 2010 and 2020. The area under curve (AUC) and Brier score were used to assess the capacity of different models. The Delong test was applied to compare the performance of the models. Univariable and multivariable analysis were conducted using logistic regression.ResultsOf 2351 patients were analyzed; 168 (7.1%) had distant metastasis (M1); 117 (5.0%) had bone metastasis, and 71 (3.0%) had lung metastasis. The median age at diagnosis is 68.0 years old. Most patients did not receive radiotherapy (1723, 73.3%) or chemotherapy (1447, 61.5%). The XGB model was the best ML model for predicting M1 in MBC patients. It showed the largest AUC value in the tenfold cross validation (AUC:0.884; SD:0.02), training (AUC:0.907; 95% CI: 0.899—0.917), testing (AUC:0.827; 95% CI: 0.802—0.857) and external validation (AUC:0.754; 95% CI: 0.739—0.771) sets. It also showed powerful ability in the prediction of bone metastasis (AUC: 0.880, 95% CI: 0.856—0.903 in the training set; AUC: 0.823, 95% CI:0.790—0.848 in the test set; AUC: 0.747, 95% CI: 0.727—0.764 in the external validation set) and lung metastasis (AUC: 0.906, 95% CI: 0.877—0.928 in training set; AUC: 0.859, 95% CI: 0.816—0.891 in the test set; AUC: 0.756, 95% CI: 0.732—0.777 in the external validation set). The AUC value of the XGB model was larger than that of nomogram in the training (0.907 vs 0.802) and external validation (0.754 vs 0.706) sets.ConclusionsThe XGB model is a better predictor of distant metastasis among MBC patients than other ML models and nomogram; furthermore, the XGB model is a powerful model for predicting bone and lung metastasis. Combining with SHAP values, it could help doctors intuitively understand the impact of each variable on outcome.

Sequential targeting of PARP with carboplatin inhibits primary tumour growth and distant metastasis in triple-negative breast cancer

BackgroundPatients with triple-negative breast cancer (TNBC) develop early recurrence. While PARP inhibitors (PARPi) have demonstrated potential in BRCA1/2-mutant (BRCAMUT) TNBC, durable responses will likely be achieved if PARPi are used in combination. It is plausible that sequential administration of a potent PARPi like talazoparib in combination with carboplatin can enhance primary tumour and metastasis inhibition in BRCAMUT and BRCA1/2 wild-type (BRCAWT) TNBCs, and decrease toxicity.MethodsWe evaluated the impact of the concurrent combination of talazoparib and carboplatin on cell survival in 13 TNBC cell lines. We compared the concurrent and sequential combination upon fork replication, migration and invasion. We also used three orthotopic xenograft models to evaluate primary tumour growth, distant metastasis, and toxicity.ResultsConcurrent talazoparib and carboplatin was synergistic in 92.3% of TNBC cell lines, independent of BRCA1/2-mutation status. The sequential combination decreased fork speed in normal cells, but not in TNBC cells. The talazoparib-first sequential combination resulted in a strong reduction in migration (70.4%, P < 0.0001), invasion (56.9%, P < 0.0001), lung micrometastasis (56.4%, P < 0.0001), and less toxicity in a BRCAWT model.ConclusionThe sequential combination of talazoparib and carboplatin is an effective approach to inhibit micrometastatic disease, providing rationale for the use of this combination in early TNBC patients.

Clinicomics-guided distant metastasis prediction in breast cancer via artificial intelligence

BackgroundBreast cancer has become the most common malignant tumour worldwide. Distant metastasis is one of the leading causes of breast cancer-related death. To verify the performance of clinicomics-guided distant metastasis risk prediction for breast cancer via artificial intelligence and to investigate the accuracy of the created prediction models for metachronous distant metastasis, bone metastasis and visceral metastasis.MethodsWe retrospectively enrolled 6703 breast cancer patients from 2011 to 2016 in our hospital. The figures of magnetic resonance imaging scanning and ultrasound were collected, and the figures features of distant metastasis in breast cancer were detected. Clinicomics-guided nomogram was proven to be with significant better ability on distant metastasis prediction than the nomogram constructed by only clinical or radiographic data.ResultsThree clinicomics-guided prediction nomograms on distant metastasis, bone metastasis and visceral metastasis were created and validated. These models can potentially guide metachronous distant metastasis screening and lead to the implementation of individualized prophylactic therapy for breast cancer patients.ConclusionOur study is the first study to make cliniomics a reality. Such cliniomics strategy possesses the development potential in artificial intelligence medicine.

Bioinformatic analysis of the clinicopathological and prognostic significance of oocyte-arresting BTG4 mRNA expression in gynecological cancers

BTG4 arrests the cell cycle and suppresses oocyte and embryonic development. We performed a bioinformatic analysis of BTG4 expression. BTG4 expression was downregulated in breast cancer compared with normal tissues (p < .05), but the opposite was observed in cervical, endometrial and ovarian cancers (p < .05). BTG4 methylation was negatively correlated with its mRNA expression in breast, cervical and endometrial cancers (p < .05). BTG4 mRNA expression was negatively correlated with T staging and distant metastasis of breast cancer; and with tumor invasion, clinical stage, low weight and BMI, low histological grade and no diabetes in endometrial cancer but positively with T stage and non-keratinizing squamous carcinoma in endometrial cancer. BTG4 expression was negatively correlated with the survival of ovarian cancer patients (p < .05), but positively for breast, cervical and endometrial cancers (p < .05). BTG4 expression is thus a potential marker reflecting the carcinogenesis, aggressiveness and prognosis in gynecological cancers. Impact Statement What is already known on this subject? Previous studies have revealed the structure and location of BTG4. BTG4 inhibit cell proliferative, promote apoptosis, induce G1 cell cycle arrest. BTG4 promotes the development of mouse embryos from cell stage 1 to 2. The methylation and biological function of BTG4 were clarified in gastric and/or colorectal cancer cells. What do the results of this study add? BTG4 is found to closely link to reflect the carcinogenesis, histogenesis, aggressive behaviors and prognosis of gynecological cancers, and involved in ligand-receptor interaction, microtubule motor activity, dynein light chain binding, cilium organization, assembly, and movement in endometrial and ovarian cancers. What are the implications of these finding for clinical practice and/or further research? Aberrant BTG4 mRNA expression can be employed as a marker of the tumorigenesis, histogenesis, aggressiveness and prognosis of gynecological cancers in the future practice and guide the investigation of BTG4-related signal pathways.

Abstract P1-05-33: RNA in Extracellular vesicles used for the prediction of distant metastasis of breast cancer and the function of TGM2 in promoting breast cancer development

Abstract Background: Extracellular vesicles (EVs) can be released by living cells during the process of tumor metastasis. Since EVs could contain various of molecular with high stability, a growing number of evidences indicated that those molecular can be utilized as biomarkers of liquid biopsy for metastatic prediction. Therefore, we aimed to identify genes and build a model that can predict the risk of metastasis in breast cancer patients with acceptable sensitivity and accuracy. Methods: Pretreatment plasma EV-RNAs of patients diagnosed at Fudan University Shanghai Cancer Center from 2017 to 2018 were extracted and analyzed by next generation sequencing (NGS) and bioinformatics, including breast cancer patients (n=114) and benign cases (n=18). Weighted correlation network analysis (WGCNA) was utilized to determine the relationship between clinical features and genes. The Kaplan-Meier was used for survival analysis in public database. By 100 times of 5 folds cross-validation, we used logistic regression analysis to set up the model. The receiver operating characteristic curve (ROC) and area under curve (AUC) were used to assess the predicted capacity of the model. QRT-PCR was conducted to further confirm the expression of genes selected by the predicting model in 175 breast cancer patients with and without metastasis, along with 5 EV-RNAs of tumor samples and paired normal adjacent breast tissues. The functions of candidate genes on cell proliferation, metastasis, and invasion were determined by a series of in vitro experiments in cancer lines. RNA sequencing and bioinformatic analysis were performed to explore the mechanism of the candidate genes. Moreover, co-immunoprecipitation (Co-IP) was used to reveal interacting proteins. Results: WGCNA screened 40 hub genes which were significantly associated with the distant metastasis in patients with breast cancer. A total of 207 upregulated genes were identified in patients with distant metastasis. After intersection, 6 genes were selected. Survival analysis suggested that high expression of IGFBP5, BCL6B, TGM2, and SH3PXD2A were correlated with poor distant metastasis-free survival (DMFS). The metastasis predicting model built based on those genes showed an AUC value of 0.923 with diagnostic accuracy of 91.2%. In the validation cohort, data showed the AUC value of each single gene were 0.835, 0.818, 0.845, 0.834, for TGM2, IGFBP5, BCL6B, and SH3PXD2A respectively. Among those four genes, TGM2 was significantly upregulated with clinical stages and correlated with poor prognosis. Moreover, TGM2 showed the highest abundance in tumor tissue EVs. Functional experiments revealed that TGM2 promoted breast cancer proliferation, metastasis, and invasion in vitro. The initially upregulated expression of TGM2 in EVs of cell lines was significantly decreased by adding the exosome release inhibitor GW4869. In addition, EVs from TGM2 overexpressed cells promoted cell migration and invasion of wild-type cells. Mechanistically, TGM2 was positively correlated with EMT, Hedgehog and IL6-JAK-STAT3 pathways. Co-IP assay found that TGM2 interacted with TMF1, which was an effector for degradation of STAT3 through the ubiquitin-proteasome pathway. Interfering the expression of TMF1 remarkably promoted the migration ability of cells and reversed by TGM2 overexpression. Conclusion: Based on the plasma EV-RNAs, we constructed a model with promising predicted capacity of distant metastasis in patients with breast cancer. TGM2, as the most effective predictor, can promote the progression and metastasis of breast cancer by targeting TMF1/STAT3. Key words Breast Cancer; Extracellular vesicles; Metastasis; Prediction model; TGM2 Citation Format: Jiong Wu, Yayun Chi. RNA in Extracellular vesicles used for the prediction of distant metastasis of breast cancer and the function of TGM2 in promoting breast cancer development [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-05-33.

Abstract P6-14-11: Exosome-mediated Circ-CRSP1 promotes tumor proliferation and metastasis through stabilizing ELAVL1 protein and suppresses anti-tumor immune response in regulating the progression of Triple-Negative Breast Cancer

Abstract Background: Triple-negative breast cancer (TNBC) is one of the most malignant subtype of breast cancer. Lacking targetable molecular drivers, chemotherapy is almost the only effective systematic treatment for TNBC. Compared with other types of breast cancer, TNBC shows a higher long-term recurrence rate and worse prognostic outcome, and its main cause of death is tumor metastasis. Therefore, there is an urgent clinical need to explore underlying molecular mechanisms and find novel targets for therapeutic intervention, as well as biomarkers for early clinical diagnosis. Materials &amp; Methods: To explore the signal pathways and target molecules related to tumor immunity by bioinformatics analysis of tissue samples [TNBC (n = 55), Her2 (n = 39), Luminal B (n = 30), Luminal A (n = 29), healthy (n = 11)]. Co-culture experiment was conducted to study the effect of TNBC-derived exosome-mediated molecules on the proliferation and migration of breast cancer. qRT-PCR assay was used to confirm the expression level of Circ-CRSP1 in tumor tissues, breast cancer cells, exosomes of breast cancer cells and serum exosomes of breast cancer patients. Overexpression and knockout experiments investigated the role of Circ-CRSP1 in promoting the proliferation and migration of TNBC cells. Protein molecular docking technique was used to predict the possible targeting binding protein ELAVL1, and molecular experiments and nude mice model were used to study the mechanism of Circ-CRSP1-ELAVL1 complex in tumor immunity. Results: TNBC-derived exosome-mediated molecular transmission promotes the proliferation and migration of breast cancer, and may promote distant metastasis of breast cancer by changing the tumor microenvironment (TME) before metastasis. Bioinformatics analysis of TNBC tumor samples confirmed that TNBC is strongly associated with tumor immune-related biological processes and signal pathways. Circ-CRSP1 is highly expressed in TNBC tumor tissues, TNBC cells, exosome derived from TNBC cells and serum exosomes of TNBC patients, and is related to the poor clinical prognosis of TNBC patients. Overexpression of Circ-CRSP1 enhanced the proliferation and migration ability of TNBC cells, and the expression levels of EMT and cell-cycle related genes altered. Circ-CRSP1 binds to protein ELAVL1 at the physical level. The target gene of Circ-CRSP1-ELAVL1 complex is involved in the immune response, and the overexpression of Circ-CRSP1 significantly down-regulates the expression level of immune-related genes. Conclusion: Exosome-mediated Circ-CRSP1 promotes the transport of ELAVL1 from nucleus to cytoplasm through targeted binding with ELAVL1, and then regulates cytoplasmic proliferation and metastasis and inhibits the stability and translation of anti-tumor immune-related gene mRNA, thus finally promotes the proliferation, invasion and metastasis of TNBC. This study can further understand the mechanism of circRNA in the growth and metastasis of TNBC from the theoretical level, further explore the feasibility of Circ-CRSP1 as a molecular target for gene therapy, and provide theoretical basis and pre-clinical data for Circ-CRSP1 in serum exosomes as a high risk screening index and prognostic marker for TNBC patients. Citation Format: Sujin Yang, Jinhai Tang. Exosome-mediated Circ-CRSP1 promotes tumor proliferation and metastasis through stabilizing ELAVL1 protein and suppresses anti-tumor immune response in regulating the progression of Triple-Negative Breast Cancer. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-14-11.

Abstract P5-03-11: The impact of single nucleotide polymorphisms on return-to-work after taxane-based chemotherapy in breast cancer

Abstract Background Return-to-work (RTW) after breast cancer may be challenging for breast cancer survivors, especially those who experience adverse effects. Neuropathies are common adverse effect of taxane-based chemotherapy. Single nucleotide polymorphisms (SNPs) in genes related to taxane metabolism and transport, neural function, and neural- or DNA-repair may influence the risk of taxane-induced adverse effects, potentially impacting patient recovery and RTW. We examined the association of such SNPs with RTW in premenopausal breast cancer survivors. Methods We used Denmark’s nationwide population-based health registries to ascertain data on premenopausal women aged 18‒55 years diagnosed with non‒distant metastatic breast cancer during 2007‒2011, who were candidates for adjuvant combination chemotherapy including cyclophosphamide and docetaxel. Only women employed at diagnosis were included. We collected archived tumor tissue from nationwide pathology departments and genotyped 26 SNPs in 20 genes using TaqMan assays. For each SNP, we categorized the women as wildtype, homozygote or heterozygote. Follow-up continued from the date of primary surgery to the first of RTW (defined as 4 consecutive weeks of work), recurrence, maternity leave/childbirth, other malignancy, retirement, death, emigration or 25th September 2017. We computed the cumulative incidence of RTW and used Cox regression models to calculate unadjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of RTW. Results We included 1,963 women. Women who were homozygotes for the phase 1 metabolizer CYP3A5 rs776746 (n=15) had lower cumulative incidence of RTW than wildtypes (n=1,600) and heterozygotes (n=249), 7%, 25% and 17% at six months, 57%, 87% and 88% at two years, and 82%, 94% and 94% at end of follow-up, respectively. Compared with wildtypes, CYP3A5 rs776746 homozygotes had delayed RTW throughout follow-up (HR 0-10 years: 0.48, 95% CI: 0.26, 0.86). No other SNPs were associated with RTW. Conclusions Among 26 SNPs, CYP3A5 rs776746 was associated with delayed RTW after breast cancer among premenopausal women. Our findings may help identify women at risk of a poor clinical course, who may benefit from enhanced supportive care during treatment and follow-up. Citation Format: Cathrine Hjorth, Per Damkier, Tore B. Stage, Søren Feddersen, Stephen Hamilton-Dutoit, Bent Ejlertsen, Timothy L. Lash, Henrik Bøggild, Henrik Sørensen, Deirdre Cronin-Fenton. The impact of single nucleotide polymorphisms on return-to-work after taxane-based chemotherapy in breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-03-11.

Abstract PD16-05: Systemic staging in breast cancer patients receiving neoadjuvant chemotherapy

Abstract Introduction Per NCCN guidelines, patients with stage I-III breast cancer should only have staging work up with CT chest, abdomen, and pelvis and bone scan if there are concerning symptoms, lab abnormalities, or physical exam findings. These patients do not require staging imaging because previous studies have documented the low incidence of metastatic disease found on systemic imaging, and the use of routine staging imaging has been shown to have a high false positive rate resulting in additional imaging and further work up with a low true positive rate. Despite the NCCN guidelines, extensive imaging is often performed prior to embarking on neoadjuvant therapy to look for evidence of metastatic spread of disease prior to surgery regardless of clinical stage and lack of symptoms. Methods We performed a retrospective analysis of patients at the University of Virginia diagnosed with invasive breast cancer who were recommended for neoadjuvant therapy and underwent systemic imaging to assess for the presence of distant metastatic breast cancer between 2012 and 2019. All receptor subtypes were included. Patients with signs/symptoms of metastatic disease at time of initial consultation were excluded. We evaluated the rate of metastatic breast cancer detected on systemic imaging. We also evaluated the rate of incidental findings on systemic imaging and how often this resulted in additional imaging or biopsy. Results 328 patients met inclusion criteria and were recommended for neoadjuvant chemotherapy and underwent systemic staging. Of these, 8 patients had bilateral breast cancer at time of diagnosis. Included patients were 54.2% hormone receptor (HR) positive, 35.4% triple negative, and 23.2% HER2 positive; 74.1% were node positive (Table 1). Metastatic breast cancer was identified in 9.1% (30 patients), which included 19 HR positive, 8 HER2 positive, and 7 triple negative patients. Of the patients found to have metastatic breast cancer, 80% had anatomic stage III disease at presentation and 93.3% were node positive. Two metastatic patients that were node negative had a cT2 or cT3 primary tumor. Systemic imaging identified incidental findings in 72.6% (238) patients. Most common incidental findings were pulmonary nodules (107), bone lesion or abnormality (71), hepatic lesions (55), and gynecologic lesions (50). Of the patients with incidental findings, 40.7% (98) underwent additional imaging for further work up or monitoring and 12.2% (29) underwent a biopsy or procedure for further work up. These biopsies identified benign or non-diagnostic results in 20 cases (69.0%) and identified an alternative malignancy in 9 cases (31%). Conclusions Within this study, asymptomatic metastatic disease was most commonly found in node positive stage III breast cancer, but was never or rarely found in stage I or II breast cancer patients. This validates NCCN recommendations that asymptomatic anatomic stage I or II breast cancer patients do not benefit from systemic staging. Yet, we did find a relatively high proportion of metastatic disease in asymptomatic patients with stage III breast cancer, indicating that systemic staging may be appropriate for this population. This must be balanced against the high probability of incidental findings with frequent additional imaging or biopsy, which has implications for patient anxiety, potential harm, and cost. Table 1: Patient Characteristics Citation Format: Courtney Lattimore, Squeo Gabriella, Christiana Brenin, Shayna Showalter, Trish Millard. Systemic staging in breast cancer patients receiving neoadjuvant chemotherapy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD16-05.

Predicting the site of distant metastases in breast cancer

Background. Distant organ tumor dissemination is a major cause of breast cancer-related deaths. Breast cancer can metastasize to several organs, and the most frequent metastatic sites include the bones, lungs and liver. There is a question what factors can influence the direction of spread of tumor cells to a particular organ.Material and Methods. We summarized the data available in the world literature on methods for prediction of the localization of distant metastases in breast cancer patients.Results. We divided the factors associated with the localization of distant metastases into two main groups: clinicopathological parameters of breast cancer patients and molecular features of tumor microenvironment and tumor cells (primary tumor and circulating tumor cells) or its derivates – exosomes. From our point of view, the most powerful clinicopathological factor predicting the distant metastasis site is a molecular subtype of primary tumor. We can conclude that luminal (HR+/HER2-) tumors are often characterized by single metastases and bones are the most common metastatic site, while TNBC and HER2-enriched tumors often metastasize to multiple sites, most commonly brain and liver. However, several authors did not reveal these associations in their studies. It likely indicates the existence of other factors that significantly affect the organotropism of metastasis. Numerous studies demonstrate the association of different molecules expressed on tumor cells with organotropic metastasis. However, these data are very fragmentary and rather contradictory.Conclusion. The found associations are common to all participants of metastatic cascade, but remains unclear which factors are essential and crucial in determining the direction of metastasis.

Discordance of HER2-Low between Primary Tumors and Matched Distant Metastases in Breast Cancer.

We examined differences in HER2 expression between primary tumors and distant metastases, particularly within the HER2-negative primary breast cancer cohort (HER2-low and HER2-zero). The retrospective study included 191 consecutive paired samples of primary breast cancer and distant metastases diagnosed between 1995 and 2019. HER2-negative samples were divided into HER2-zero (immunohistochemistry [IHC] score 0) and HER2-low (IHC score 1+ or 2+/in situ hybridization [ISH]-negative). The main objective was to analyze the discordance rate between matched primary and metastatic samples, focusing on the site of distant metastasis, molecular subtype, and de novo metastatic breast cancer. The relationship was determined by cross-tabulation and calculation of Cohen's Kappa coefficient. The final study cohort included 148 paired samples. The largest proportion in the HER2-negative cohort was HER2-low [primary tumor 61.4% (n = 78), metastatic samples 73.5% (n = 86)]. The discordance rate between the HER2 status of primary tumors and corresponding distant metastases was 49.6% (n = 63) (Kappa -0.003, 95%CI -0.15-0.15). Development of a HER2-low phenotype occurred most frequently (n = 52, 40.9%), mostly with a switch from HER2-zero to HER2-low (n = 34, 26.8%). Relevant HER2 discordance rates were observed between different metastatic sites and molecular subtypes. Primary metastatic breast cancer had a significantly lower HER2 discordance rate than secondary metastatic breast cancer [30.2% (Kappa 0.48, 95%CI 0.27-0.69) versus 50.5% (Kappa 0.14, 95% CI -0.03-0.32)]. This highlights the importance of evaluating potentially therapy-relevant discordance rates between a primary tumor and corresponding distant metastases.

Exploring the relationships between hormone receptor, HER2 status, and bone involvement in the first distant metastases of in Chinese breast cancer patients who lacked HER2 targeted therapy

BackgroundThis retrospective study explored the relationship between hormone receptor (HR), human epidermal growth factor receptor 2 (HER2) status, and bone involvement in the first distant metastases (DM) of Chinese breast cancer (BC) patients who lacked the HER2 targeted therapy. Such therapy was rarely received due to its lag approval or high cost in China compared with the developed countries.MethodsAll eligible women with primary unilateral stage I – III BC and first DM diagnosed in 2008—2018 at one cancer center were identified for enrollment. Based on chart records, a full or no/partial compliance status of endocrine therapy (ET) was assigned for HR-positive patients. Multivariate logistic regression was used to estimate the adjusted odd ratio (aOR), its 95%CI and p value.ResultsFour hundred eighteen patients had an average age of 50.7 years and median disease-free survival of 27.1 months at DM. Bone, lung, liver and brain metastasis rates in patients were 55.7%, 34.7%, 33.0% and 8.1%, respectively. Compared to HR-negative patients, HR-positive patients with the full and non/partial compliance of ET were significantly associated with higher risk of bone involvement with an aOR of 2.329 (1.316 – 1.741, p = 0.004) and 2.317 (1.330 – 4.036, p = 0.003), respectively. No difference of such risk was found between the two groups of ET compliance (p = 0.984) nor between HER2-negative and HER2-positive patients (aOR 0.827, p = 0.431). Stratified analyses further indicated that HR-positive was associated with bone involvement only in HER2-negative BC patients (p = 0.006—0.015).ConclusionsHR-positive tumors are significantly associated with bone involvement in HER2-negative metastatic BC patients. ET does not appear to impact this association. HER2 status per se is not associated with such risk.

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

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

ADC of Diffusion-weighted MRI and SUVmax of 18F-FDG-PET/CT: Correlation with Prognostic Factors and Distant Metastasis in Breast Cancer

ADC of Diffusion-weighted MRI and SUVmax of 18F-FDG-PET/CT: Correlation with Prognostic Factors and Distant Metastasis in Breast Cancer

Explainable Machine Learning Explores Association Between Sarcopenia and Breast Cancer Distant Metastasis

Explainable Machine Learning Explores Association Between Sarcopenia and Breast Cancer Distant Metastasis

Very late distant retroperitoneal metastasis of breast cancer diagnosed using EUS-guided tissue acquisition.

Very late distant retroperitoneal metastasis of breast cancer diagnosed using EUS-guided tissue acquisition.

Real-world data of HER2-low metastatic breast cancer: A population based cohort study

BackgroundWith the introduction of investigational human epidermal growth factor receptor 2 (HER2) targeting treatments, thorough understanding of breast cancer with different HER2 expression levels is critical. The aim of this study was to compare clinicopathologic characteristics and survival of patients with metastatic breast cancer according to the level of HER2 expression. MethodsWomen with distant metastatic breast cancer during 2008–2016 were selected from PALGA, the Dutch Pathology Registry, and linked to the PHARMO Database Network. Breast cancer samples were categorised as HER2 immunohistochemistry score 0 (IHC0), HER2-low or HER2+. ResultsAmong women with hormone receptor (HR) positive metastatic breast cancer (n = 989), 373 (38%) cancers were HER2 IHC0, 472 (48%) were HER2-low and 144 (15%) were HER2+. Among HR negative patients (n = 272), the proportion of HER2 IHC0, HER2-low and HER2+ was 110 (40%), 104 (38%) and 58 (21%) respectively.Within the HR + cohort, patients with HER2 IHC0 or HER2-low cancer were significantly older compared to HER2+ patients. This age difference was not seen in the HR-cohort. The localisation of distant metastases differed significantly between HER2 IHC0 or HER2-low versus HER2+ cases. Survival rates did not differ markedly by subtypes. ConclusionSubstantial proportion of patients had a HER2-low breast cancer. No clear differences in survival were found when comparing HER2 and HR status. Getting more granular insights in the level of HER2 expression and addressing HER2-low as a separate category could help to assess the impact of emerging treatment strategies. Therefore, more detailed information on HER2 expression should be routinely reported.

Sabizabulin, a Potent Orally Bioavailable Colchicine Binding Site Agent, Suppresses HER2+ Breast Cancer and Metastasis.

HER2+ breast cancer accounts for 15% of all breast cancer cases. Current frontline therapy for HER2+ metastatic breast cancer relies on targeted antibodies, trastuzumab and pertuzumab, combined with microtubule inhibitors in the taxane class (paclitaxel or docetaxel). It is well known that the clinical efficacy of taxanes is limited by the development of chemoresistance and hematological and neurotoxicities. The colchicine-binding site inhibitors (CBSIs) are a class of promising alternative agents to taxane therapy. Sabizabulin (formerly known as VERU-111) is a potent CBSI that overcomes P-gp-mediated taxane resistance, is orally bioavailable, and inhibits tumor growth and distant metastasis in triple negative breast cancer (TNBC). Herein, we demonstrate the efficacy of sabizabulin in HER2+ breast cancer. In vitro, sabizabulin inhibits the proliferation of HER2+ breast cancer cell lines with low nanomolar IC50 values, inhibits clonogenicity, and induces apoptosis in a concentration-dependent manner. In vivo, sabizabulin inhibits breast tumor growth in the BT474 (ER+/PR+/HER2+) xenograft model and a HER2+ (ER-/PR-) metastatic patient-derived xenograft (PDX) model, HCI-12. We demonstrate that sabizabulin is a promising alternative agent to target tubulin in HER2+ breast cancer with similar anti-metastatic efficacy to paclitaxel, but with the advantage of oral bioavailability and lower toxicity than taxanes.

RNA m6A reader IGF2BP3 promotes metastasis of triple-negative breast cancer via SLIT2 repression.

Triple-negative breast cancer (TNBC) is a group of fatal malignancies characterized by high metastatic capacity, the underlying mechanisms of which remain largely elusive. We have found here that insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3) is highly expressed in TNBC and correlates clinically with distant metastasis-free survival of TNBC patients. IGF2BP3 promotes the migration and invasion capabilities of TNBC cells dependent upon cellular RNA N6-methyladenosine (m6A) modification. Mechanistically, IGF2BP3 binds to and destabilizes m6A-methylated mRNA of the extracellular matrix glycoprotein, SLIT2, impairs its downstream signaling via the cognate receptor ROBO1, and consequently triggers the activation of canonical PI3K/AKT and MEK/ERK pathways. The IGF2BP3/SLIT2 axis is critically involved in the regulation of TNBC metastasis in vivo. These findings shed light into the regulatory network of distant metastasis of breast cancer and provide rationale for targeting the m6A machinery in the treatment of TNBC.