Distinct ER and PR expression patterns significantly affect the clinical outcomes of early HER2-positive breast cancer: A real-world analysis of 871 patients treated with neoadjuvant therapy.

INTRODUCTION: The impact of distinct estrogen receptor (ER) and progesterone receptor (PR) expression patterns on tumor behavior and treatment outcomes within HER2-positive breast cancer is not fully explored. This study aimed to comprehensively examine the clinical differences among patients with HER2-positive breast cancer harboring distinct ER and PR expression patterns in the neoadjuvant setting. METHODS: This retrospective analysis included 871 HER2-positive breast patients treated with neoadjuvant therapy at our hospital between 2011 and 2022. Comparisons were performed across the three hormone receptor (HR)-specific subtypes, namely the ER-negative/PR-negative/HER2-positive (ER-/PR-/HER2+), the single HR-positive (HR+)/HER2+, and the triple-positive breast cancer (TPBC) subtypes. RESULTS: Of 871 patients, 21.0% had ER-/PR-/HER2+ tumors, 33.6% had single HR+/HER2+ disease, and 45.4% had TPBC. Individuals with single HR+/HER2+ tumors and TPBC cases demonstrated significantly lower pathological complete response (pCR) rates compared to those with ER-/PR-/HER2+ tumors (36.9% vs. 24.3% vs. 49.2%, p < 0.001). Multivariate analysis confirmed TPBC as significantly associated with decreased pCR likelihood (OR = 0.42, 95%CI 0.28-0.63, p < 0.001). Survival outcomes, including disease-free survival (DFS) and overall survival (OS), showed no significant differences across HR-specific subtypes in the overall patient population. However, within patients without anti-HER2 therapy, TPBC was linked to improved DFS and a trend towards better OS. CONCLUSIONS: HER2-positive breast cancer exhibited three distinct HR-specific subtypes with varying clinical manifestations and treatment responses. These findings suggest personalized treatment strategies considering ER and PR expression patterns, emphasizing the need for further investigations to unravel molecular traits underlying HER2-positive breast cancer with distinct HR expression patterns.

Machine learning radiomics of magnetic resonance imaging predicts recurrence-free survival after surgery and correlation of LncRNAs in patients with breast cancer: a multicenter cohort study.

BACKGROUND: Several studies have indicated that magnetic resonance imaging radiomics can predict survival in patients with breast cancer, but the potential biological underpinning remains indistinct. Herein, we aim to develop an interpretable deep-learning-based network for classifying recurrence risk and revealing the potential biological mechanisms. METHODS: In this multicenter study, 1113 nonmetastatic invasive breast cancer patients were included, and were divided into the training cohort (n = 698), the validation cohort (n = 171), and the testing cohort (n = 244). The Radiomic DeepSurv Net (RDeepNet) model was constructed using the Cox proportional hazards deep neural network DeepSurv for predicting individual recurrence risk. RNA-sequencing was performed to explore the association between radiomics and tumor microenvironment. Correlation and variance analyses were conducted to examine changes of radiomics among patients with different therapeutic responses and after neoadjuvant chemotherapy. The association and quantitative relation of radiomics and epigenetic molecular characteristics were further analyzed to reveal the mechanisms of radiomics. RESULTS: The RDeepNet model showed a significant association with recurrence-free survival (RFS) (HR 0.03, 95% CI 0.02-0.06, P < 0.001) and achieved AUCs of 0.98, 0.94, and 0.92 for 1-, 2-, and 3-year RFS, respectively. In the validation and testing cohorts, the RDeepNet model could also clarify patients into high- and low-risk groups, and demonstrated AUCs of 0.91 and 0.94 for 3-year RFS, respectively. Radiomic features displayed differential expression between the two risk groups. Furthermore, the generalizability of RDeepNet model was confirmed across different molecular subtypes and patient populations with different therapy regimens (All P < 0.001). The study also identified variations in radiomic features among patients with diverse therapeutic responses and after neoadjuvant chemotherapy. Importantly, a significant correlation between radiomics and long non-coding RNAs (lncRNAs) was discovered. A key lncRNA was found to be noninvasively quantified by a deep learning-based radiomics prediction model with AUCs of 0.79 in the training cohort and 0.77 in the testing cohort. CONCLUSIONS: This study demonstrates that machine learning radiomics of MRI can effectively predict RFS after surgery in patients with breast cancer, and highlights the feasibility of non-invasive quantification of lncRNAs using radiomics, which indicates the potential of radiomics in guiding treatment decisions.

Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.

BACKGROUND: in current clinical practice, the standard evaluation for axillary lymph node (ALN) status in breast cancer has a low efficiency and is based on an invasive procedure that causes operative-associated complications in many patients. Therefore, we aimed to use machine learning techniques to develop an efficient preoperative magnetic resonance imaging (MRI) radiomics evaluation approach of ALN status and explore the association between radiomics and the tumor microenvironment in patients with early-stage invasive breast cancer. METHODS: in this retrospective multicenter study, three independent cohorts of patients with breast cancer (n = 1,088) were used to develop and validate signatures predictive of ALN status. After applying the machine learning random forest algorithm to select the key preoperative MRI radiomic features, we used ALN and tumor radiomic features to develop the ALN-tumor radiomic signature for ALN status prediction by the support vector machine algorithm in 803 patients with breast cancer from Sun Yat-sen Memorial Hospital and Sun Yat-sen University Cancer Center (training cohort). By combining ALN and tumor radiomic features with corresponding clinicopathologic information, the multiomic signature was constructed in the training cohort. Next, the external validation cohort (n = 179) of patients from Shunde Hospital of Southern Medical University and Tungwah Hospital of Sun Yat-Sen University, and the prospective-retrospective validation cohort (n = 106) of patients treated with neoadjuvant chemotherapy in prospective phase 3 trials [NCT01503905], were included to evaluate the predictive value of the two signatures, and their predictive performance was assessed by the area under operating characteristic curve (AUC). This study was registered with ClinicalTrials.gov, number NCT04003558. FINDINGS: the ALN-tumor radiomic signature for ALN status prediction comprising ALN and tumor radiomic features showed a high prediction quality with AUC of 0·88 in the training cohort, 0·87 in the external validation cohort, and 0·87 in the prospective-retrospective validation cohort. The multiomic signature incorporating tumor and lymph node MRI radiomics, clinical and pathologic characteristics, and molecular subtypes achieved better performance for ALN status prediction with AUCs of 0·90, 0·91, and 0·93 in the training cohort, the external validation cohort, and the prospective-retrospective validation cohort, respectively. Among patients who underwent neoadjuvant chemotherapy in the prospective-retrospective validation cohort, there were significant differences in the key radiomic features before and after neoadjuvant chemotherapy, especially in the gray-level dependence matrix features. Furthermore, there was an association between MRI radiomics and tumor microenvironment features including immune cells, long non-coding RNAs, and types of methylated sites. Interpretation this study presented a multiomic signature that could be preoperatively and conveniently used for identifying patients with ALN metastasis in early-stage invasive breast cancer. The multiomic signature exhibited powerful predictive ability and showed the prospect of extended application to tailor surgical management. Besides, significant changes in key radiomic features after neoadjuvant chemotherapy may be explained by changes in the tumor microenvironment, and the association between MRI radiomic features and tumor microenvironment features may reveal the potential biological underpinning of MRI radiomics. FUNDING: No funding.

Neoadjuvant everolimus plus letrozole versus fluorouracil, epirubicin and cyclophosphamide for ER-positive, HER2-negative breast cancer: a randomized pilot trial.

BACKGROUND: Here we evaluated the feasibility, efficacy, tolerability, and treatment-mediated immune modulation of neoadjuvant everolimus plus letrozole versus chemotherapy in treating postmenopausal patients with ER-positive, HER2-negative breast cancer. METHODS: Postmenopausal women with ER-positive, HER2-negative breast cancer who had a primary tumor > 2 cm or positive axillary lymph node(s) proofed by biopsy were randomly (1,1) enrolled to receive neoadjuvant everolimus plus letrozole for 18 weeks or fluorouracil, epirubicin plus cyclophosphamide (FEC) for 6 cycles before surgery. Primary outcome was feasibility of the trial. Secondary outcome included ultrasound response rate, pathological complete response rate, breast-conserving surgery rate, toxicities, treatment-mediated immune modulation and biomarkers. RESULTS: Forty patients were randomized. Completion rate was 90.0% in the neoadjuvant endocrine therapy (NET) arm but 70.0% in the neoadjuvant chemotherapy (NAC) arm. The ultrasound response rate was 65.0% in NET arm and 40.0% in FEC arm, respectively. In terms of the adverse events, clearly favored NET arm. Everolimus plus letrozole increased the ratio of peripheral Tregs to CD4+ T cells and tumor PD-L1 expression, and decreased Ki67 index and tumor-infiltrating Tregs, and patients with a greater increase of tumor-specific CTLs showed more sensitive to NET. CONCLUSION: This pilot trial showed that neoadjuvant everolimus plus letrozole might achieve a favorable ultrasound response rate with low toxicities in treating postmenopausal ER-positive, HER2-negative breast cancer patients. Everolimus plus letrozole might have positive antitumoral immunity effects. Further large randomized controlled trials are needed to confirm our findings. TRAIL REGISTRATION: A Trial of Neoadjuvant Everolimus Plus Letrozole Versus FEC in Women With ER-positive, HER2-negative Breast Cancer, registered on 07/04/2016 and first posted on 18/04/2016, NCT02742051 .

Targeting regulator of G protein signaling 1 in tumor-specific T cells enhances their trafficking to breast cancer.

Reduced infiltration of anti-tumor lymphocytes remains a major cause of tumor immune evasion and is correlated with poor cancer survival. Here, we found that upregulation of regulator of G protein signaling (RGS)1 in helper TH1 cells and cytotoxic T lymphocytes (CTLs) reduced their trafficking to and survival in tumors and was associated with shorter survival of patients with breast and lung cancer. RGS1 was upregulated by type II interferon (IFN)-signal transducer and activator of transcription (STAT)1 signaling and impaired trafficking of circulating T cells to tumors by inhibiting calcium influx and suppressing activation of the kinases ERK and AKT. RGS1 knockdown in adoptively transferred tumor-specific CTLs significantly increased their infiltration and survival in breast and lung tumor grafts and effectively inhibited tumor growth in vivo, which was further improved when combined with programmed death ligand (PD-L)1 checkpoint inhibition. Our findings reveal RGS1 is important for tumor immune evasion and suggest that targeting RGS1 may provide a new strategy for tumor immunotherapy.

Male breast cancer with ureteral metastasis: a case report.

Breast cancer is rare in men and there is no report of male breast cancer (MBC) with ureteral metastasis. In this study, we report the first case of MBC with ureteral metastasis. A 60-year-old man was diagnosed with triple negative breast cancer (TNBC) with local lymph nodes metastasis (TNM stage: T4N3M0). After surgery, chemotherapy and radiotherapy he was diagnosed with ureter metastasis because of hematuria. This patient took a Precitype gene test (immune index and PAM50) after several lines of treatment and the result indicated that this was a Luminal A subtype case as well as HER-2 mRNA positive, which was quite different from his immunohistochemical staining. Because of his poor condition and he could not tolerate chemotherapy, we adjusted his therapeutic regimen with endocrine therapy and anti-HER-2 therapy according to the gene expression analysis with the informed consent of the patient and his families. However, it seemed that there was no obvious efficacy and he passed away five months later. In our opinion, MBC patients with urinary symptoms should be considered for the possibility of metastasis although urinary metastasis in breast cancer is rare. We still need more research about gene expression analysis and more evidence of treatment recommendations for MBC.

Risk factors associated with loss to follow-up of breast cancer patients: A retrospective analysis.

BACKGROUND: Loss to follow-up (LTFU) during post-operative surveillance of breast cancer patients is detrimental. The pattern of LTFU and its risk factors in Chinese breast cancer patients remains unknown. METHOD: Eligible non-metastatic breast cancer patients who underwent surgery at our institution between 2009 and 2012 were included. The clinicopathological features, as well as the LTFU status, were retrieved from the REDCap database. LTFU was defined as the absence of patients for at least 12 months since her last contact. 5-year LTFU was defined as the LTFU status of each patients at 5 years after surgery. The incidence and potential risk factors of LTFU were analyzed. A LTFU-risk score was developed to quantify the risk of LTFU. RESULTS: A total of 1536 patients with breast cancer were included, and 411(26.8%) patients were 5-year LTFU. 198 patients were LTFU in the first year. Univariate and multivariate analysis revealed that age (younger and older), a lack of medical insurance, longer distance from residence to the hospital, pathology (DCIS/Paget's/Phyllodes), lymph node metastasis, the absence of endocrine therapy and fewer than five contact numbers were significantly and independently associated with the risk of LTFU. A LTFU-risk score was developed and was predictive of LTFU. CONCLUSIONS: A series of risk factors were significantly associated with post-operative LTFU of breast cancer patients. Patients with different risks of LTFU could possibly be identified, and surveillance plans could be individualized for different patients, so as to effectively reduce the overall LTFU rate, and optimize the allocation of medical resources.

Development and Validation of a Preoperative Magnetic Resonance Imaging Radiomics-Based Signature to Predict Axillary Lymph Node Metastasis and Disease-Free Survival in Patients With Early-Stage Breast Cancer.

Importance: Axillary lymph node metastasis (ALNM) status, typically estimated using an invasive procedure with a high false-negative rate, strongly affects the prognosis of recurrence in breast cancer. However, preoperative noninvasive tools to accurately predict ALNM status and disease-free survival (DFS) are lacking. Objective: To develop and validate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomic signatures for preoperative identification of ALNM and to assess individual DFS in patients with early-stage breast cancer. Design, Setting, and Participants: This retrospective prognostic study included patients with histologically confirmed early-stage breast cancer diagnosed at 4 hospitals in China from July 3, 2007, to September 21, 2019, randomly divided (7:3) into development and vaidation cohorts. All patients underwent preoperative MRI scans, were treated with surgery and sentinel lymph node biopsy or ALN dissection, and were pathologically examined to determine the ALNM status. Data analysis was conducted from February 15, 2019, to March 20, 2020. Exposure: Clinical and DCE-MRI radiomic signatures. Main Outcomes and Measures: The primary end points were ALNM and DFS. Results: This study included 1214 women (median [IQR] age, 47 [42-55] years), split into development (849 [69.9%]) and validation (365 [30.1%]) cohorts. The radiomic signature identified ALNM in the development and validation cohorts with areas under the curve (AUCs) of 0.88 and 0.85, respectively, and the clinical-radiomic nomogram accurately predicted ALNM in the development and validation cohorts (AUC, 0.92 and 0.90, respectively) based on a least absolute shrinkage and selection operator (LASSO)-logistic regression model. The radiomic signature predicted 3-year DFS in the development and validation cohorts (AUC, 0.81 and 0.73, respectively), and the clinical-radiomic nomogram could discriminate high-risk from low-risk patients in the development cohort (hazard ratio [HR], 0.04; 95% CI, 0.01-0.11; P < .001) and the validation cohort (HR, 0.04; 95% CI, 0.004-0.32; P < .001) based on a random forest-Cox regression model. The clinical-radiomic nomogram was associated with 3-year DFS in the development and validation cohorts (AUC, 0.89 and 0.90, respectively). The decision curve analysis demonstrated that the clinical-radiomic nomogram displayed better clinical predictive usefulness than the clinical or radiomic signature alone. Conclusions and Relevance: This study described the application of MRI-based machine learning in patients with breast cancer, presenting novel individualized clinical decision nomograms that could be used to predict ALNM status and DFS. The clinical-radiomic nomograms were useful in clinical decision-making associated with personalized selection of surgical interventions and therapeutic regimens for patients with early-stage breast cancer.

Multicentre, randomised, open-label, non-inferiority trial comparing the effectiveness and safety of ductal lavage versus oral corticosteroids for idiopathic granulomatous mastitis: a study protocol.

INTRODUCTION: The ideal treatment for idiopathic granulomatous mastitis (IGM) remains unclear. In a prospective, single-centre, pilot study, we reported that ductal lavage treatment for non-lactational mastitis patients had a 1-year clinical complete response (cCR) rate of >90%, without any significant adverse events. Thus, in this multicentre, randomised, open-label, non-inferiority trial, we will aim to compare the effectiveness and safety of ductal lavage vs oral corticosteroids as the first-line treatment for patients with IGM. METHODS AND ANALYSIS: The trial will be conducted at the Breast Tumor Center of Sun Yat-sen Memorial Hospital in China and at least at one participating regional centre. We plan to recruit 140 eligible IGM patients who will be randomised into the ductal lavage group or oral corticosteroid group with a 1:1 ratio. The patients in the oral corticosteroid group will receive meprednisone or prednisone for 6 months. The patients in the ductal lavage group will receive ductal lavage and breast massage, as previously reported. All the participants will be followed up at the clinic for 1 year post randomisation. The primary endpoint of this trial will be the 1-year cCR rate, and the secondary endpoints will include the time to cCR, treatment failure rate, relapse rate and protocol compliance rate. The trial was designed to determine whether ductal lavage is non-inferior to oral corticosteroids (1-year cCR rate assumed to be 90%), with a non-inferiority margin of 15%. ETHICS AND DISSEMINATION: The ethics committee of Sun Yat-sen Memorial Hospital at Sun Yat-sen University approved the study (2018-Lun-Shen-Yan-No. 30). The results of the trial will be communicated to the participating primary care practices, published in international journals and presented at international clinical and scientific conferences. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT03724903); Pre-results.

Identification of SOCS family members with prognostic values in human ovarian cancer.

BACKGROUND: Suppressor of cytokine signaling (SOCS) family proteins regulate cytokine responses through inhibition of multiple signaling pathways. The expression profiles and prognostic significance of SOCS members in ovarian cancer (OC) patients still remains unclear. Here, we aimed to provide a comprehensive understanding of the prognostic values of SOCS family members in OC and to discover promising therapeutic targets for OC. METHODS: We firstly analyzed the KEGG pathway enrichment to reveal the possible pathways associated with SOCS family. Next, we used public databases including cBioPortal, Human Protein Atlas and Oncomine to investigate genetic alterations and mRNA expression of SOCS family in OC patients. More importantly, we explored the prognostic value of each individual SOCS members in OC patients using Kaplan Meier plotter database. RESULTS: SOCS family was markedly enriched in JAK-STAT signaling pathway. A high mutation rate in SOCSs was observed in patients with ovarian serous cancer (OSC). An increased mRNA expression of SOCS1 indicated a favorable overall survival (OS) in both OC and OSC patients, while increased SOCS5 and SOCS7 expressions were significantly associated with poorer OS. We also explored the diverse roles of SOCS members in OC patients with different clinicopathological features including grades, stages and therapies employed. CONCLUSION: SOCS1, SOCS5 and SOCS7 may serve as prognostic biomarkers for OC patients. SOCS5 and SOCS7 may be potential therapeutic targets for OC treatment. Our results render novel insights into the association between SOCS family genes and OC development, and may highlight promising molecular targets for therapeutic interventions in OC patients.

Efficacy and safety of camrelizumab combined with apatinib in advanced triple-negative breast cancer: an open-label phase II trial.

BACKGROUND: Previous trials showed that antiangiogenesis or anti-programmed death protein 1/programmed death ligand 1 (PD-1/PD-L1) monotherapy only showed marginal effect in triple-negative breast cancer (TNBC). Preclinical studies demonstrated that antiangiogenic therapy could sensitize breast cancer to PD-1/PD-L1 blockade via reprogramming tumor microenvironment. Combinational treatment of checkpoint blockade and antiangiogenesis for TNBC has not been reported. METHODS: Patients with advanced TNBC with less than three lines of systemic therapy were enrolled in an open-label, non-comparative, two-arm, phase II trial at Sun Yat-sen Memorial Hospital. Camrelizumab (intravenously every 2 weeks) with apatinib orally at either continuous dosing (d1-d14) or intermittent dosing (d1-d7) was given until disease progression or unacceptable toxicities. Primary endpoint was objective response rate (ORR). RESULTS: From January 2018 to April 2019, 40 patients were enrolled, including 10 in the apatinib intermittent dosing cohort and 30 in the apatinib continuous dosing cohort. The ORR was 43.3% (13 of 30) in the continuous dosing cohort, while no objective response was observed in the intermittent dosing cohort. The disease control rate was 63.3% (19 of 30) in the apatinib continuous dosing cohort, and 40.0% (4 of 10) in the apatinib intermittent dosing cohort, respectively. The median progression-free survival (PFS) was 3.7 (95% CI 2.0 to 6.4) months and 1.9 (95% CI 1.8 to 3.7) months in the continuous dosing and intermittent dosing cohort, respectively. In the continuous dosing cohort, the median PFS of patients with partial response (8.3 months, 95% CI 5.9 to not reached) was significantly longer than that of patients with stable disease/progressive disease/not evaluable (2.0 months, 95% CI 1.7 to 3.0). The most common adverse events (AEs) included elevated aspartate aminotransferase/alanine aminotransferase and hand-foot syndrome. Overall, 26.7% and 20.0% of patients experienced grade ≥3 AEs in the continuous dosing and intermittent dosing cohort, respectively. In the continuous dosing cohort, a high percentage of baseline tumor-infiltrating lymphocytes (>10%) was associated with higher ORR and favorable PFS (p=0.029, 0.054, respectively). CONCLUSIONS: The ORR by this chemo-free regimen was dramatically higher than previously reported ORR by anti-PD-1/PD-L1 antibody or apatinib monotherapy. Camrelizumab combined with apatinib demonstrated favorable therapeutic effects and a manageable safety profile in patients with advanced TNBC. TRIAL REGISTRATION NUMBER: NCT03394287.

Incidence and survival outcomes of early male breast cancer: a population-based comparison with early female breast cancer.

BACKGROUND: Male breast cancer (MBC) is a rare malignancy. We aimed to analyze the incidence trends, clinicopathological characteristics, and survival outcomes in early MBC comparison with early female breast cancer (FBC). METHODS: We included eligible MBC and FBC patients with stage I-II disease in the Surveillance, Epidemiology, and End Results (SEER) database from 2000-2015. Joinpoint regression was used to evaluate the trends in age-adjusted incidence. A one-to-four propensity score matching (PSM) analysis was performed to reduce bias in a retrospective study. Survival outcomes were evaluated using Kaplan-Meier analyses with the log-rank test and Cox proportional hazards regression analysis. RESULTS: Trends in the age-adjusted incidence rates of early MBC were stable [2000-2015, annual percentage change (APC) =0.50, 95% confidence interval (CI): -0.1 to 1.1, P=0.102]; however, the incidence of early FBC changed significantly over the time period (2000-2015, APC = 0.30, 95% CI: 0.0 to 0.6, P=0.045). In the matched cohort, unmarried status, higher grade, larger tumor size, and advanced lymph node (LN) status were associated with a higher risk of breast cancer death and death of any causes both in early MBC and FBC patients. The hormone receptor (HR) status was as a prognostic factor in FBC patients, but not in MBC. Early MBC had worse breast cancer-specific survival (BCSS) and overall survival (OS) than early FBC in stage I, stage II and HR-positive subgroup of patients. CONCLUSIONS: The biological behavior, clinicopathological features, and clinical outcomes of early MBC are different from that of FBC. Further studies on individualized treatment approaches in MBC are needed.

Development and validation of a novel nomogram for predicting distant metastasis-free survival among breast cancer patients.

BACKGROUND: Distant metastasis (DM) from breast cancer has a poor prognosis. Our objective was to develop and validate a nomogram to predict individual distant metastasis-free survival (DMFS) and risk stratification in non-metastatic breast cancer patients. METHODS: A nomogram was based on an analysis of 1,201 breast cancer patients treated at Sun Yat-sen Memorial Hospital from 2001 to 2014. Using univariate and multivariate analyses to identify the predictors, this model was externally validated in an independent cohort of 538 patients from the Guangdong General Hospital between 2004 and 2012. The predictive discrimination and calibration ability of this nomogram were assessed using concordance index (C-index), risk group stratification, and calibration curve. RESULTS: The 5-year DMFS in the training and validation cohorts were 95.74% and 91.02%, respectively. On multivariable analysis of training cohort, the prognostic factors in the nomogram comprised age, tumor size, lymph node status, molecular subtype, and lymphovascular invasion (LVI). The C-index of our model was 0.75 [95% confidence interval (CI): 0.67-0.83] for the training cohort and 0.71 (95% CI: 0.64-0.78) for the validation cohort. The calibration curves for 5-year DMFS showed good agreement between the model prediction and actual observation. Based on the risk stratification, Kaplan-Meier curves indicated that the low-risk group had significantly better prognosis than the high-risk group (P<0.001). CONCLUSIONS: Our nomogram can provide an individual prediction of 5-year DMFS in non-metastatic breast cancer patients. This prognostic tool may help clinicians to make appropriate treatment regimens and optimal surveillance plans.

Risk factors of catheter-related thrombosis in early-stage breast cancer patients: a single-center retrospective study.

PURPOSE: Totally implantable venous access devices (TIVADs) are widely used in cancer patients. The main purpose of our study is to observe the incidence and identified risk factors of catheter-related thrombosis (CRT) in breast cancer patients with TIVAD. PATIENTS AND METHODS: We performed a retrospective cohort study of consecutive breast cancer patients who received the ultrasound-guided TIVAD implantation for the administration of chemotherapy from 2013 to 2016. The primary outcome was CRT (both symptomatic and asymptomatic detected by ultrasound). Univariable and multivariable logistic regression analyses were used to identify the risk factors for breast cancer TIVAD-related CRT. RESULTS: A total of 209 breast cancer patients with a newly implanted TIVAD for chemotherapy were included in this study. The average time of port duration was 7 months. Of the enrolled 209 patients, 33 patients (15.8%) had CRT, 2 of the 33 cases were symptomatic (1 pulmonary embolism, 1 deep-venous thrombosis [DVT]), the other 31 cases were asymptomatic detected by routine ultrasound examination of the catheter-associated vein before TIVAD removal with all cycles of chemotherapy completed. In total, 19 (57.6%) of CRT patients underwent directly TIVAD removal without any further treatments, 14 patients received anticoagulation treatments for 3-30 days followed by TIVAD removal. No DVT event was observed within at least 1.5 years of follow-up. In the multiple-variable analysis, tumor size >2 cm (OR 2.735, 95% CI 1.042-7.177; P=0.032), positive HbsAg (OR 2.803 95% CI 1.027-7.856; P=0.047) and low-density lipoprotein (LDL) >3.6 mmol/L (OR 2.360, 95% CI 1.059-5.351; P=0.040) were the significant independent risk factors of breast cancer TIVAD-related CRT. CONCLUSION: CRT is a common complication in breast cancer patients with TIVAD for chemotherapy. Tumor size, HbsAg status and LDL level were independent predictors of breast cancer for TIVAD-related CRT. Removal of the port without anticoagulation treatments might be a feasible choice for asymptomatic TIVAD-related CRT.

Expression profile and prognostic values of STAT family members in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is a highly malignant type of cancer with a poor 5-year survival rate. The development of prognostic biomarkers and novel drug targets are required in order to improve the survival for NSCLC patients. Signal transducer and activator of transcription (STAT) proteins are cytoplasmic transcription factors known to play key roles in many cellular biological processes. However, the roles of STAT family members in the development and progression of NSCLC have not yet been apparently determined. Our study investigated the roles of STATs in the prognosis of NSCLC using cBioPortal, Human Protein Atlas, ONCOMINE, and Kaplan-Meier Plotter databases. High mutation rate of STATs existed in both lung adenocarcinoma (ADE) patients and squamous cell carcinoma (SCC) patients. High mRNA expression of STAT2 was significantly associated with shorter overall survival (OS) in NSCLC patients, while increased STAT5 and STAT6 were associated with better OS in NSCLC patients. We further found that increased mRNA expressions of STAT2 and STAT3 predicted unfavorable overall survival (OS) while high mRNA expression of STAT5B and STAT6 related to favorable OS for lung ADE patients. However, no significant correlation was identified for lung SCC patients. In stratified survival analysis, high expression of STAT2 predicted poor prognosis in stage II NSLCC patients, surgical margins negative patients and female patients. Taken together, our results illustrated that STAT5B and STAT6 could be effective prognostic biomarkers for survivals of NSCLC patients. And STAT2 might be a promising therapeutic target for the treatment of NSCLC as well as ADE.