Novel multi-target angiogenesis inhibitors as potential anticancer agents: Design, synthesis and preliminary activity evaluation.

Based on the crucial role of histone deacetylase (HDAC) and receptor tyrosine kinase in angiogenesis, in situ assembly, skeletal transition, molecular hybridization, and pharmacophore fusion were employed to yield seventy-six multi-target angiogenesis inhibitors. Biological evaluation indicated that most of the compounds exhibited potent proliferation inhibitory activity on MCF-7 cells, with the TH series having the highest inhibitory activity on MCF-7 cells. In addition, the IC50 values of TA11 and TH3 against HT-29 cellswere 0.078 µmol/L and 0.068 µmol/L, respectively. The cytotoxicity evaluation indicated that TC9, TA11, TM4, and TH3 displayed good safety against HEK293T cells. TH2 and TH3 could induce apoptosis of MCF-7 cells. Molecular modeling and ADMET prediction results indicated that most of target compounds showed promising medicinal properties, which was consistent with the experimental results. Our findings provided new lead compounds for the structural optimization of multi-target angiogenesis inhibitors.

Transmembrane modification of tumor vascular targeting peptide A7R as molecular cargo delivery tool.

In recent years, targeting tumor angiogenesis has emerged as a prominent research focus in the treatment and prevention of tumor expansion. A7R (ATWLPPR) exhibits high affinity and specificity for VEGFR-2, which is overexpressed in various tumors. To enhance the tumor tissue and cell penetration capabilities of A7R, we substituted its non-critical amino acid with Arginine (R) and Glutamic acid (E), cyclized the mutant peptide, and linked it to the membrane permeation sequence using coordination principles. We designed and synthesized fifteen novel penetrating peptides that target tumor blood vessels and cells, followed by conducting various biological evaluations and cell imaging experiments. The results demonstrated that Cyclo-A7R-RRR and A7R-RLLRLLR exhibited excellent permeability towards tumor cells, with Cyclo-A7R-RRR showing superior serum stability compared to A7R. Furthermore, the modified peptides showed no toxicity towards HeLa cells, U251 cells, HuH-7 cells, and HEK293 cells under 10 µmol/L. Utilizing Cyclo-A7R-RRR or A7R-RLLRLLR for transmembrane delivery of drug molecules could significantly improve their efficacy. Our findings broaden the potential application scenarios of A7R in targeted tumor angiogenesis.

Baicalein enhances immune response in TNBC by inhibiting leptin expression of adipocytes.

Triple-negative breast cancer (TNBC) is a special pathological type of breast cancer (BC) with poor prognosis. Obesity is shown to be involved in TNBC tumor progression. The interaction between obesity and BC has generated great attention in recent years, however, the mechanism is still unclear. Here, we showed that leptin secreted by adipocytes upregulated PD-L1 expression in TNBC through the p-STAT3 signaling pathway and that baicalein inhibited PD-L1 expression in tumor microenvironment by suppressing leptin transcription of adipocytes. Collectively, our findings suggest that leptin may be the key factor participating in obesity-related tumor progression and that baicalein can break through the dilemma to boost the anti-tumor immune response.

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

BACKGROUND: Breast 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. METHODS: The 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. RESULTS: The 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). CONCLUSION: We 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.

Lactoferrin-Modified Gambogic Acid Liposomes for Colorectal Cancer Treatment.

Colorectal cancer (CRC) therapy is a big challenge, and seeking an effective and safe drug is a pressing clinical need. Gambogic acid is a potent antineoplastic agent without the drawback of bone marrow suppression. To improve its druggability (e.g., poor water solubility and tumor delivery), a lactoferrin-modified gambogic acid liposomal delivery system (LF-lipo) was developed to enhance the treatment efficacy of CRC. The LF-lipo can specifically bind LRP-1 expressed on colorectal cancer cells to enhance drug delivery to the tumor cells and yield enhanced therapeutic efficacy. The LF-lipo promoted tumor cell apoptosis and autophagy, reduced reactive oxygen species (ROS) levels in tumor cells, and inhibited angiogenesis; moreover, it could also repolarize tumor-associated macrophages from the M2 to M1 phenotype and induce ICD to activate T cells, exhibiting the capability of remodeling the tumor immune microenvironment. The liposomal formulation yielded an efficient and safe treatment outcome and has potential for clinical translation.

Cancer-associated fibroblast infiltration in gastric cancer: the discrepancy in subtypes pathways and immunosuppression.

BACKGROUND: General role of cancer-associated fibroblast (CAF) and its infiltration characteristics in gastric cancer remains to be unknown. METHODS: We estimate CAF infiltration in bulk tumor tissue with RNA-seq data and analyzed its relationship with gastric cancer subtype, survival and immune microenvironment. RESULTS: We revealed CAF intend to have higher infiltration in diffuse, genomically stable, and advanced gastric cancer. CAF is associated with immunosuppressive microenvironment. Wide transcriptomics alterations occur in high CAF infiltrated gastric cancer, PI3K/AKT, TGFB and Hedgehog pathway are remarkable in this procedure. We utilized receptor tyrosine kinases and TGFB pathway ligands to construct risk score system that can predict survival. CONCLUSION: Thus, CAF is associated with aggressive phenotype of gastric cancer and risk score based on RTK and TGFB pathway ligands expression is a promising tool for assessment of gastric cancer survival.

Survival analysis for male ductal and lobular breast cancer patients with different stages.

AIM: We aimed to investigate risk factors and current treatment effects in male breast cancer patients. METHODS: Kaplan-Meier plot, log-rank test, COX model, nomograms and propensity score matching were used. RESULTS: Among stage I-III patients, surgery was associated with better prognosis. In subgroup analysis, performing surgery and no radiation or chemotherapy led to worse prognosis in research group. Among stage IV patients, chemotherapy correlated with better prognosis and radiation led to better breast cancer-specific survival. In addition, brain and liver metastasis correlated with worse prognosis; and lung correlated with worse breast cancer-specific survival. CONCLUSION: For stage I-III patients, surgery and chemotherapy were recommended. And not applying radiation or chemotherapy could be carefully considered for ER(+) HER-2(-) patients. For stage IV patients, chemotherapy and radiation were commended.

NPR-A: A Therapeutic Target in Inflammation and Cancer.

Natriuretic peptide receptor A (NPR-A) is the receptor for atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP). NPR-A plays critical physiological and pathophysiological roles in several target cell and tissue system processes, such as cell growth, apoptosis, proliferation, and inflammation. Accumulating data demonstrate that NPR-A is involved in immune and inflammatory reactions and is a potential target in inflammation treatment. It is expressed in various cancer cells and is important for tumor growth. A recent study indicated that NPR-A signaling can regulate stem cell recruitment and angiogenesis. This signaling can serve as a model for studying the linkage between inflammation and tumorigenesis. In this review we highlight the mechanisms by which NPR-A affects signaling pathways involved in inflammation and cancer, and we discuss its potential as a novel target in inflammation, cancer, and cancer-related inflammation.

High dose Vitamin C inhibits PD-L1 by ROS-pSTAT3 signal pathway and enhances T cell function in TNBC.

Vitamin C (VitC) presents excellent anti-tumor effect for long time. Recently, high dose VitC achieved by intravenous administration manifests superior anti-tumor effect. However, the functions and detailed mechanisms of high dose VitC's role in cancer immunity are not fully understood. This study investigates the effect of high dose VitC on PD-L1 expression in triple negative breast cancer (TNBC) and the potential mechanism. Results showed VitC inhibited PD-L1 expression in breast cancer cell lines and enhanced anti-tumor effects of T cells. Furthermore, we found VitC inhibited PD-L1 transcription through ROS-pSTAT3 signal pathways. Consistent with in vitro results, in vivo study showed VitC suppressed tumor growth in immunocompetent mice and enhanced CD8+ T cells infiltration and function in tumor microenvironment. Our findings identify the effects of high dose VitC on PD-L1 expression and provide a rationale for the use of high dose VitC as immunomodulator for cancer therapy.

Rotational gland dissection for refractory granulomatous mastitis: A single-center retrospective study.

BACKGROUND: Refractory granulomatous mastitis (RGM) is a chronic benign breast disease that commonly occurred in women of childbearing age and is usually treated with surgery, with numerous cases suffering from unsatisfied postoperative recovery of breast shape, high rates of surgical complications, and even high recurrence. This study tries to evaluate the efficacy of an innovative surgical procedure, the rotational gland dissection for the treatment of RGM. METHODS: 129 patients with RGM who underwent surgical treatment at the Second Affiliated Hospital of Xi'an Jiaotong University between Apr. 2017 and May. 2021 were retrospectively included in this study. The article analyzed the age, local symptoms, lesion location, and size, days in hospital, recurrence rate, and satisfaction rate of the patients. RESULTS: Patients ranged in age from 19 to 58 years, with a median age of onset of 32 years. In 63 patients (48.84%), their lesions coverage exceeded two quadrants, and 52.71% of patients had lesions larger than 10 cm2. The average days in hospital of patients was 7.5 days, and 85.27% of them were satisfied with their post-surgery breast appearance. Within the median follow-up of 56 months, only 3.10% of patients experienced a recurrence of mastitis on the operation side. CONCLUSION: This novel surgical procedure we created is an effective treatment for RGM with a high success rate, high patient satisfaction, and low recurrence rate, and is significantly superior to other studies for it has the largest sample size and longest follow-up in this field.

Downregulation of circular RNA hsa_circ_0087856 sensitizes bladder cancer cells to cisplatin through targeting miR-1184/CITED2 signaling.

CircRNAs are considered as one of the potential therapeutic targets of multiple cancers. According to accumulating evidence, circRNA regulates cancer progression by acting as a miRNA sponge. In the current work, our data discovered that hsa_circ_0087856 and CITED2 expression was increased, while miR-1184 expression was decreased in BC cell lines and tissues. Hsa_circ_0087856 expression negatively correlated with miR-1184, whereas positively correlated with CITED2. Hsa_circ_0087856 silencing suppressed BC tumor growth, and contributed to the inhibition of cisplatin to tumor growth. In cellular experiments, hsa_circ_0087856 increasing promoted BC cells proliferation, migration and invasion, and inhibited the cells apoptosis. Hsa_circ_0087856 increasing partly reversed the inhibition of cisplatin to BC cell proliferation and the promotion to cell apoptosis. Oppositely, hsa_circ_0087856 silencing could increase the sensitivity of BC cells to cisplatin. Hsa_circ_0087856 promoted CITED2 expression through binding with miR-1184 and inhibiting its expression. CITED2 increasing partly reversed the promotion of hsa_circ_0087856 silencing to cisplatin-induced BC cells apoptosis promotion and proliferation suppression. Overall, our results revealed the role of hsa_circ_0087856 that downregulation its expression could enhance the BC cells sensitivity to cisplatin by facilitating CITED expression via sponging miR-1184. Moreover, our research provided a potential therapeutic target for BC.

A patent perspective of antiangiogenic agents.

INTRODUCTION: Angiogenesis plays a crucial role in the development of numerous vascular structures and is involved in a variety of physiologic and pathologic processes, including psoriasis, diabetic retinopathy, and especially cancer. By obstructing the process of angiogenesis, these therapies effectively inhibit the progression of the disease. Consequently, anti-angiogenic agents were subsequently developed. AREAS COVERED: This review provides a comprehensive summary of the anti-angiogenic inhibitors developed in the past five years in terms of chemical structure, biochemical/pharmacological activity and potential clinical applications. A literature search was conducted using utilizing the databases Web of Science, SciFinder and PubMed with the key word 'anti-angiogenic agents' and 'angiogenesis inhibitor.' EXPERT OPINION: This is despite the fact that the concept of antiangiogenesis has been proposed for more than 50 years and angiogenesis inhibitors are extensively employed in clinical practice. However, significant challenges continue to confront them. In recent years, there has been a significant increase in the number of patents focusing on angiogenesis inhibitors. These patents aim to enhance the selectivity of drugs against VEGF/VEGFR, explore new targets to overcome drug resistance, and explore potential drug combinations, thereby expanding the therapeutic possibilities in this field.

Risk, molecular subtype and prognosis of second primary breast cancer: an analysis based on first primary cancers.

Second primary breast cancer (SPBC) was potentially related to other cancers, which may impact its incidence, prognosis and therapeutic approaches. Nevertheless, few studies have characterized this relationship and analyzed the subtypes of SPBC. Our study intended to investigate the occurrence and prognosis of SPBC. We analyzed the patterns, clinical characteristics, standardized incidence ratio (SIR) and standardized mortality ratio (SMR) of patients with SPBC. The propensity score matching (PSM) approach was further used to balance the differences in clinical features between patients with primary breast cancer (PBC) and SPBC, then Kaplan-Meier (KM) survival analysis was used to compare their overall survival and breast cancer-specific survival. Finally, a predictive model was constructed to estimate the 3- and 5-year survival rates of SPBC patients. We found that the SIR of individuals with SPBC was significantly higher in cancer survivors than in the general population (SIR=1.16, 95% CI=1.15-1.17, P<0.05). SPBC patients with first primary lung/bronchus cancer had a much higher SMR (SMR=1.71, 95% CI=1.58-1.85, P<0.05) compared with survivors of other malignancies. Individuals with SPBC had a larger proportion of the HR-/HER2- subtype than those with PBC. Particularly among survivors of estrogen-dependent ovarian and breast cancer, the proportion of the HR-/HER2- subtype of SPBC considerably rose. After propensity score matching, we discovered that SPBC patients' overall survival remained poorer than that of PBC patients (HR=1.43, 95% CI=1.39-1.47, P<0.001). However, the prognosis of SPBC in first primary thyroid cancer survivors was better than PBC patients (HR=0.64, 95% CI=0.55-0.75, P<0.001). Also, an extreme gradient boosting (XGBoost) model was developed to evaluate the 3-year (AUC=0.817) and 5-year survival (AUC=0.825) of SPBC patients. Our data demonstrated the distinct biological performance of SPBC with various first primary cancers. Furthermore, our findings revealed an indispensable role of first primary cancer (FPC) in the development of SPBC and provided an additional theoretical basis for the clinical follow-up and identification of SPBC.

Prognostic Models Using Machine Learning Algorithms and Treatment Outcomes of Occult Breast Cancer Patients.

BACKGROUND: Occult breast cancer (OBC) is an uncommon malignant tumor and the prognosis and treatment of OBC remain controversial. Currently, there exists no accurate prognostic clinical model for OBC, and the treatment outcomes of chemotherapy and surgery in its different molecular subtypes are still unknown. METHODS: The SEER database provided the data used for this study's analysis (2010-2019). To identify the prognostic variables for patients with ODC, we conducted Cox regression analysis and constructed prognostic models using six machine learning algorithms to predict overall survival (OS) of OBC patients. A series of validation methods, including calibration curve and area under the curve (AUC value) of receiver operating characteristic curve (ROC) were employed to validate the accuracy and reliability of the logistic regression (LR) models. The effectiveness of clinical application of the predictive models was validated using decision curve analysis (DCA). We also investigated the role of chemotherapy and surgery in OBC patients with different molecular subtypes, with the help of K-M survival analysis as well as propensity score matching, and these results were further validated by subgroup Cox analysis. RESULTS: The LR models performed best, with high precision and applicability, and they were proved to predict the OS of OBC patients in the most accurate manner (test set: 1-year AUC = 0.851, 3-year AUC = 0.790 and 5-year survival AUC = 0.824). Interestingly, we found that the N1 and N2 stage OBC patients had more favorable prognosis than N0 stage patients, but the N3 stage was similar to the N0 stage (OS: N0 vs. N1, HR = 0.6602, 95%CI 0.4568-0.9542, p < 0.05; N0 vs. N2, HR = 0.4716, 95%CI 0.2351-0.9464, p < 0.05; N0 vs. N3, HR = 0.96, 95%CI 0.6176-1.5844, p = 0.96). Patients aged >80 and distant metastases were also independent prognostic factors for OBC. In terms of treatment, our multivariate Cox regression analysis discovered that surgery and radiotherapy were both independent protective variables for OBC patients, but chemotherapy was not. We also found that chemotherapy significantly improved both OS and breast cancer-specific survival (BCSS) only in the HR-/HER2+ molecular subtype (OS: HR = 0.15, 95%CI 0.037-0.57, p < 0.01; BCSS: HR = 0.027, 95%CI 0.027-0.81, p < 0.05). However, surgery could help only the HR-/HER2+ and HR+/HER2- subtypes improve prognosis. CONCLUSIONS: We analyzed the clinical features and prognostic factors of OBC patients; meanwhile, machine learning prognostic models with high precision and applicability were constructed to predict their overall survival. The treatment results in different molecular subtypes suggested that primary surgery might improve the survival of HR+/HER2- and HR-/HER2+ subtypes, however, only the HR-/HER2+ subtype could benefit from chemotherapy. The necessity of surgery and chemotherapy needs to be carefully considered for OBC patients with other subtypes.

A novel web-based prognostic nomogram and the features influencing the curative effect of chemotherapy and radiotherapy for Paget's disease with invasive ductal carcinoma.

Paget's disease (PD) of the breast is a rare underlying malignant tumor. Approximately 50% to 60% of patients with mammary PD are concurrently diagnosed with invasive ductal carcinoma (PD-IDC), a condition associated with a worse prognosis than IDC without PD. Thus far, there has been a lack of an accurate and efficient prognostic model for PD-IDC, and the factors influencing the effectiveness of chemotherapy and radiotherapy for these patients remain unknown. In this study, we developed a web-based nomogram based on the data from the Surveillance Epidemiology and End Results (SEER) database. We subjected the model to a series of validation methods, including area under the curve (AUC) values, receiver operating characteristic curve (ROC) analysis, calibration curves, and decision curve analysis (DCA). Our results demonstrated that our model exhibited high discrimination, accuracy, and clinical applicability in predicting the overall survival (OS) of patients with PD-IDC (testing set: three- and five-year AUCs, 0.831 and 0.841, respectively). To further validate our nomogram, we used external data from both our institution and sister hospitals (external data: three- and five-year AUCs, 0.892 and 0.914, respectively). Multivariable Cox regression analysis identified several independent unfavorable prognostic factors for the OS of patients with PD-IDC, including increasing age, high grade, widowed status, higher T stages, and the presence of bone metastases. Furthermore, propensity score matching (PSM)-adjusted analysis was conducted, revealing that chemotherapy did not significantly improve the survival of patients with PD-IDC across molecular subtypes, except for those in the grade III/IV group, where it improved both OS and breast cancer-specific survival (BCSS). Additionally, our findings indicated that only patients with PD-IDC with T4 and N3 stages benefited from radiotherapy, leading to improvements in both OS and BCSS. In conclusion, we have comprehensively analyzed the clinical characteristics and prognosis of patients with PD-IDC, culminating in the development of a user-friendly web-based nomogram for predicting their survival. Our predictive model is not only highly accurate but also offers simplicity, making it accessible for healthcare providers and patients. Furthermore, our stratified analysis highlights that the pathological grade, rather than the molecular subtype, plays a pivotal role in determining the efficacy of chemotherapy in improving the prognosis for patients with PD-IDC, while radiotherapy confers survival benefits to patients with PD-IDC in T4 and N3 stages.

EZH2 engages TGFß signaling to promote breast cancer bone metastasis via integrin ß1-FAK activation.

Bone metastases occur in 50-70% of patients with late-stage breast cancers and effective therapies are needed. The expression of enhancer of zeste homolog 2 (EZH2) is correlated with breast cancer metastasis, but its function in bone metastasis hasn't been well-explored. Here we report that EZH2 promotes osteolytic metastasis of breast cancer through regulating transforming growth factor beta (TGFß) signaling. EZH2 induces cancer cell proliferation and osteoclast maturation, whereas EZH2 knockdown decreases bone metastasis incidence and outgrowth in vivo. Mechanistically, EZH2 transcriptionally increases ITGB1, which encodes for integrin ß1. Integrin ß1 activates focal adhesion kinase (FAK), which phosphorylates TGFß receptor type I (TGFßRI) at tyrosine 182 to enhance its binding to TGFß receptor type II (TGFßRII), thereby activating TGFß signaling. Clinically applicable FAK inhibitors but not EZH2 methyltransferase inhibitors effectively inhibit breast cancer bone metastasis in vivo. Overall, we find that the EZH2-integrin ß1-FAK axis cooperates with the TGFß signaling pathway to promote bone metastasis of breast cancer.

Inhaled heparin polysaccharide nanodecoy against SARS-CoV-2 and variants.

The heparin polysaccharide nanoparticles block the interaction between heparan sulfate/S protein and inhibit the infection of both wild-type SARS-CoV-2 pseudovirus and the mutated strains through pulmonary delivery.Image 1.

Relationship between metastasis and second primary cancers in women with breast cancer.

Background: Breast cancer (BC) survivors have an increased risk of developing second primary cancers (SPCs); however, it is still unclear if metastasis is a risk factor for developing SPCs. Usually, long-term cancer survivors face an increased risk of developing SPCs; however, less attention has been paid to SPCs in patients with metastatic cancer as the survival outcomes of the patients are greatly reduced. Methods: A total of 17,077 American women diagnosed with breast cancer between 2010 and 2018 were identified from Surveillance, Epidemiology, and End Results (SEER) database and were included in the study. The clinical characteristics, standardized incidence ratio (SIR), standardized mortality ratio (SMR), and patterns of SPCs in BC patients with no metastasis, regional lymph node metastasis, and distant metastasis were investigated. Kaplan-Meier method was used to compare the prognosis of BC patients after developing SPCs with different metastatic status. XGBoost, a high-precision machine learning algorithm, was used to create a prediction model to estimate the prognosis of metastatic breast cancer (MBC) patients with SPCs. Results: The results reveal that the SIR (1.01; 95% CI, 0.99-1.03, p>0.05) of SPCs in non-metastasis breast cancer (NMBC) patients was similar to the general population. Further, patients with regional lymph node metastasis showed an 8% increased risk of SPCs (SIR=1.08, 95%CI, 1.05-1.11, p<0.05), and patients with distant metastasis had a 26% increased risk of SPCs (SIR=1.26, 95%CI, 1.16-1.37, p<0.05). The SIR of SPCs in all patients below the age of 40 was the highest, which decreased with age. Patients with poorly differentiated cancers, large tumor size, and late N stage had an increased risk of SPCs. However, an increase in SIR of SPCs was observed in distant MBC patients, even at the early T1 (SIR=1.60, 95% CI, 1.22-1.98, p<0.05) and N1 (SIR=1.27, 95% CI, 1.10-1.44, p<0.05) stage. An increase in the SIR of SPCs was observed in patients with triple-negative BC, and the SIR of SPC increased with metastasis development in BC patients with luminal A subtype. The peak of SPCs risk occurrence was earlier in MBC patients (4-6 months and 10 months) compared to NMBC patients (12 months). The effect of metastasis on the prognosis of SPCs patients was dependent on the type of SPCs. Meanwhile, the XGBoost model was created to predict the 3-year (AUC=0.873) and 5-year survival (AUC=0.918) of SPCs in MBC patients. Conclusions: Our study provides novel insight into the impact of metastasis on SPCs in BC patients. Metastasis could promote the second primary tumorigenesis which further increased cancer-related deaths. Therefore, more attention should be paid to the occurrence of SPCs in MBC patients.

Machine learning predicts the prognosis of breast cancer patients with initial bone metastases.

Background: Bone is the most common metastatic site of patients with advanced breast cancer and the survival time is their primary concern; however, we lack accurate predictive models in clinical practice. In addition to this, primary surgery for breast cancer patients with bone metastases is still controversial. Method: The data used for analysis in this study were obtained from the SEER database (2010-2019). We made a COX regression analysis to identify prognostic factors of patients with bone metastatic breast cancer (BMBC). Through cross-validation, we constructed an XGBoost model to predicting survival in patients with BMBC. We also investigated the prognosis of patients treated with neoadjuvant chemotherapy plus surgical and chemotherapy alone using propensity score matching and K-M survival analysis. Results: Our validation results showed that the model has high sensitivity, specificity, and correctness, and it is the most accurate one to predict the survival of patients with BMBC (1-year AUC = 0.818, 3-year AUC = 0.798, and 5-year survival AUC = 0.791). The sensitivity of the 1-year model was higher (0.79), while the specificity of the 5-year model was higher (0.86). Interestingly, we found that if the time from diagnosis to therapy was ≥1 month, patients with BMBC had even better survival than those who started treatment immediately (HR = 0.920, 95%CI 0.869-0.974, P < 0.01). The BMBC patients with an income of more than USD$70,000 had better OS (HR = 0.814, 95%CI 0.745-0.890, P < 0.001) and BCSS (HR = 0.808 95%CI 0.735-0.889, P < 0.001) than who with income of < USD$50,000. We also found that compared with chemotherapy alone, neoadjuvant chemotherapy plus surgical treatment significantly improved OS and BCSS in all molecular subtypes of patients with BMBC, while only the patients with bone metastases only, bone and liver metastases, bone and lung metastases could benefit from neoadjuvant chemotherapy plus surgical treatment. Conclusion: We constructed an AI model to provide a quantitative method to predict the survival of patients with BMBC, and our validation results indicate that this model should be highly reproducible in a similar patient population. We also identified potential prognostic factors for patients with BMBC and suggested that primary surgery followed by neoadjuvant chemotherapy might increase survival in a selected subgroup of patients.