Factors that predict recurrence later than 5 years after initial treatment in operable breast cancer

New Therapeutic Scenarios in the Context of Adjuvant Treatment for HR+/HER2-Breast Cancer: The Possible Role of Ribociclib in Treatment Algorithms for Stage II and III

Early breast cancer (EBC) treatment has evolved from radical surgery to a multidisciplinary approach, integrating radiotherapy, chemotherapy, targeted therapy, and hormone therapy with surgery to ensure the best possible outcome. Despite these advancements, hormone receptor-positive (HR+)/Human Epidermal Growth Factor Receptor 2-Negative (HER2-) EBC still faces high recurrence rates after endocrine therapy. A panel of oncologists from Central-Southern Italy discussed the profile of ribociclib as an adjuvant therapy, based on the results of the NATALEE study, focusing on efficacy, safety, patient profiles, and regional challenges in treatment access. The experts identified ribociclib as suitable adjuvant treatment for stage II and III HR+/HER2- EBC patients, including those without lymph node involvement but with biologically aggressive disease. In their view, ribociclib could be an interesting option for patients not eligible for chemotherapy due to contraindications. Key challenges in translating the evidence on ribociclib in EBC into clinical practice include treatment duration, patient follow-up, and adverse events management. Strategies to address these challenges range from telemedicine and support from local clinics to tailored communication to improve adherence. Ribociclib is expected to significantly impact adjuvant treatment for HR+/HER2- EBC by addressing broader patient needs and potentially improving long-term outcomes through enhanced adherence and personalized management strategies.

A Deep Reinforcement Learning-Based Feature Selection Method for Invasive Disease Event Prediction Using Imbalanced Follow-Up Data

The machine learning-based model is a promising paradigm for predicting invasive disease events (iDEs) in breast cancer. Feature selection (FS) is an essential preprocessing technique employed to identify the pertinent features for the prediction model. However, conventional FS methods often fail with imbalanced clinical data due to the bias towards the majority class. In this paper, a novel FS framework based on reinforcement learning (RLFS) is developed to identify the optimal feature subset for the imbalanced data. The RLFS employs an iterative methodology, wherein data resampling technique generates a balanced dataset before each iteration. A decision network is trained using a deep RL algorithm to identify the relevant features for the dataset in the current iteration. With such an iterative training strategy, numerous constructed datasets gradually boost the FS capacity of the decision network, resulting in a robust performance for imbalanced data. Finally, a weighted model is proposed to determine the most suitable FS solution. The RLFS is employed to predict breast cancer iDEs using real follow-up data. The comparison results demonstrated that RLFS effectively reduces the number of features while outperforming several state-of-the-art FS algorithms.

Is it really over when it is over? physical, mental and emotional health status of long-term breast cancer survivors compared to healthy matched controls

PURPOSE

This study aimed to assess pain, fitness condition, physical activity (PA) level, comorbidities, cancer-related fatigue (CRF), mood state and health-related quality of life (HRQoL) in long-term breast cancer survivors (LTBCS) compared to women without cancer history, matched by age, weight, height, and educational level.

METHODS

A cross-sectional study conducted in Granada between April 2018 and July 2023 involved 80 LTBCS and 80 matched controls. Pain, fitness condition, PA level, comorbidities, CRF, mood state, and HRQoL were evaluated ≥ 5 years post-diagnosis using validated instruments.

RESULTS

LTBCS, compared to the controls, reported significantly higher levels of "pain intensity and interference", CRF (in all domains and > 40% exhibited moderate-to-severe fatigue levels), "sadness-depression", "anxiety", "anger/hostility", and "symptom scales" (All: P = .000 to .027). Moreover, 66.25% of LTBCS not only did not reach recommended PA levels (P = .035), but also presented significantly lower levels of "general physical fitness", "muscular strength", "happiness", "functioning scales" (except "emotional functioning"), and "global health status" (All: P = .000 to .048).

CONCLUSION

LTBCS still suffer from physical (pain, fitness condition, and CRF), both mental and emotional (sadness-depression, anxiety and anger/hostility) long-term side effects as well as multiple HRQoL issues (including lower levels of physical functioning and higher levels of symptoms). These findings highlight the chronic nature of this disease and the importance of continuing long- term follow-up care for survivors many years after the diagnosis of breast cancer.

Real-world treatment patterns and outcomes in patients with HR+/HER2- metastatic breast cancer treated with chemotherapy in the United States

BACKGROUND

Until recently, treatment options for patients with hormone receptor-positive/human epidermal growth factor 2-negative (HR+/HER2-) metastatic breast cancer (mBC) and resistance to endocrine therapy were limited to chemotherapy. This real-world study describes treatment patterns and outcomes in patients treated with chemotherapy in the United States before approval of antibody-drug conjugates.

PATIENTS AND METHODS

This retrospective, observational study included adults with HR+/HER2- mBC from the ConcertAI Patient360™ Breast Cancer dataset who initiated their first chemotherapy in the metastatic setting between January 2011 and June 2021. Treatment patterns were described; real-world overall survival, time to next treatment or death, and real-world progression-free survival were evaluated for all eligible patients and patients treated with subsequent chemotherapy. Index dates were the start date of each chemotherapy treatment.

RESULTS

Among 1545 eligible patients, 76% were white, 12% had Eastern Cooperative Oncology Group performance status ≥2, 38% had de novo mBC, and median age was 61 years (range, 52-69 years). Within the index period, capecitabine was used the most as the first chemotherapy agent and decreased in later treatments, while the use of eribulin increased between first and fourth chemotherapies. Median (95% confidence interval) real-world overall survival was 23.3 months (21.3-25.4 months) from start of first chemotherapy, time to next treatment or death was 6.5 months (5.9-7.1 months), and real-world progression-free survival was 6.9 months (6.4-7.6 months); median times from second, third, and fourth chemotherapies decreased with each additional chemotherapy treatment.

CONCLUSIONS

This real-world study demonstrates that for patients with HR+/HER2- mBC, chemotherapy provides relatively limited survival benefit which decreases with each additional chemotherapy line, and highlights the need for improved treatment options.

Recurrent invasive ductal carcinoma of the breast with metastasis to the uterine cervix: A case report

This article presents a case of cervical metastasis from recurrence of invasive ductal carcinoma of the breast >20 years after initial diagnosis. The diagnosis was made after the patient presented with three months of intermittent post-menopausal vaginal spotting. She underwent palliative radiotherapy combined with chemotherapy and was disease free at the time of writing. Cervical metastasis of a primary breast cancer is extremely rare and can present with a variety of symptoms. This case report highlights the importance of life-long gynecologic care and surveillance in patients with a history of breast cancer.

Explainable 3D CNN based on baseline breast DCE-MRI to give an early prediction of pathological complete response to neoadjuvant chemotherapy

BACKGROUND

So far, baseline Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has played a key role for the application of sophisticated artificial intelligence-based models using Convolutional Neural Networks (CNNs) to extract quantitative imaging information as earlier indicators of pathological Complete Response (pCR) achievement in breast cancer patients treated with neoadjuvant chemotherapy (NAC). However, these models did not exploit the DCE-MRI exams in their full geometry as 3D volume but analysed only few individual slices independently, thus neglecting the depth information.

METHOD

This study aimed to develop an explainable 3D CNN, which fulfilled the task of pCR prediction before the beginning of NAC, by leveraging the 3D information of post-contrast baseline breast DCE-MRI exams. Specifically, for each patient, the network took in input a 3D sequence containing the tumor region, which was previously automatically identified along the DCE-MRI exam. A visual explanation of the decision-making process of the network was also provided.

RESULTS

To the best of our knowledge, our proposal is competitive than other models in the field, which made use of imaging data alone, reaching a median AUC value of 81.8%, 95%CI [75.3%; 88.3%], a median accuracy value of 78.7%, 95%CI [74.8%; 82.5%], a median sensitivity value of 69.8%, 95%CI [59.6%; 79.9%] and a median specificity value of 83.3%, 95%CI [82.6%; 84.0%], respectively. The median and CIs were computed according to a 10-fold cross-validation scheme for 5 rounds.

CONCLUSION

Finally, this proposal holds high potential to support clinicians on non-invasively early pursuing or changing patient-centric NAC pathways.

FBXO8 is a novel prognostic biomarker in different molecular subtypes of breast cancer and suppresses breast cancer progression by targeting c-MYC

F-box only protein 8 (FBXO8) is a recently identified member of the F-box proteins, showcasing its novelty in this protein family. Extensive research has established FBXO8's role as a tumor suppressor in various cancers, including hepatocellular carcinoma, and colorectal cancer, Nevertheless, its functional, mechanistic, and prognostic roles in primary and metastatic breast cancer, particularly in different molecular subtypes of breast cancer, various stages, as well as its potential implications in immunotherapy, tumor microenvironment, and prognostic survival among breast cancer patients, remain unexplored. In this article, we employed a multi-dimensional investigation leveraging TCGA, TIMER, TISIDB, STRING, MEXPRESS, UALCAN, and cBioPortal databases to explore the underlying suppression mechanism of FBXO8 in breast cancer. FBXO8 negatively correlates with MYC, NOTCH, WNT and inflammatory signaling pathways in breast tumor microenvironment. Furthermore we conducted RT-PCR, western blot, cell proliferation, cell migration, and mRNA target gene RT-PCR analyses to elucidate the role of FBXO8 in breast cancer progression. Mechanistically, PTEN and FBXW7 expression were down-regulated and MYC, IL10, IL6, NOTCH1, WNT6 mRNA expressions were up-regulated in FBXO8 knockdown cell lines. c-MYC silenced cells showed an increase in FBXO8 protein level, which suggests a negative feedback loop between FBXO8 and c-MYC to control breast cancer metastasis. These findings illuminate the novel role of FBXO8 as a prognostic and therapeutic target across different molecular subtypes of breast cancer. Finally, through the utilization of virtual screening and Molecular Dynamics simulations, we successfully identified two FDA-approved medications, Ledipasvir and Paritaprevir, that demonstrated robust binding capabilities and interactions with FBXO8.

Prognostic influences of B-cell lymphoma 2-positive expression on late recurrence in breast cancer

Purpose

B-cell lymphoma 2 (BCL2) has an antiapoptotic role, however, has resulted in it being a powerful favorable prognostic factor in breast cancer. Several studies revealed BCL2 is strongly associated with a lower rate of early recurrence after initial treatment in breast cancer patients, but study of a prolonged effect after 5 years is lacking. We investigated BCL2 as a prognostic factor in breast cancer in comparison to early and late recurrence.

Methods

We retrieved data from 2,198 patients with primary breast cancer who underwent surgical treatment and adjuvant treatment at the breast cancer center between 2005 and 2015. Each molecular subtype was classified, and Ki-67 and BCL2 were also assessed by immunohistochemistry. BCL2 and the association between molecular subtypes were assessed in early and late recurrences, respectively. Five-year postrecurrence survival and BCL2 were also assessed.

Results

The BCL2-positive group was associated with favorable clinicopathologic characteristics. The time to recurrence was significantly longer in the BCL2-positive group (P = 0.035). Late recurrence after 5 years was higher in the BCL2-positive group (P = 0.029). In multivariate survival analysis, tumor size and BCL2-positive expression were the only independent prognostic factors for late recurrence (P = 0.004). In the patients with recurrence, 5-year postrecurrence survival was significantly higher in the BCL2-positive group (P < 0.001).

Conclusion

Our result showed that prognosis was better in BCL2-positive patients compared to BCL2-negative patients at late recurrence. We suggested that BCL2 expression could be used as a marker to help determine additional adjuvant therapy or extended hormone therapy in hormone-dependent breast cancer.

Rationale and trial design of NATALEE: a Phase III trial of adjuvant ribociclib + endocrine therapy versus endocrine therapy alone in patients with HR+/HER2- early breast cancer

Background

Ribociclib has demonstrated a statistically significant overall survival benefit in pre- and postmenopausal patients with hormone receptor positive/human epidermal growth factor receptor 2 negative (HR+/HER2-) advanced breast cancer. New Adjuvant Trial with Ribociclib [LEE011] (NATALEE) is a trial evaluating the efficacy and safety of adjuvant ribociclib plus endocrine therapy (ET) versus ET alone in patients with HR+/HER2- early nonmetastatic breast cancer (EBC).

Methods/design

NATALEE is a multicenter, randomized, open-label, Phase III trial in patients with HR+/HER2- EBC. Eligible patients include women, regardless of menopausal status, and men aged ⩾18 years. Select patients with stage IIA, stage IIB, or stage III disease (per the anatomic classification in the AJCC Cancer Staging Manual, 8th edition) with an initial diagnosis ⩽18 months prior to randomization are eligible. Patients receiving standard (neo)adjuvant ET are eligible if treatment was initiated ⩽12 months before randomization. Patients undergo 1:1 randomization to ribociclib 400 mg/day (3 weeks on/1 week off) +ET (letrozole 2.5 mg/day or anastrozole 1 mg/day [investigator's discretion] plus goserelin [men or premenopausal women]) or ET alone. Ribociclib treatment duration is 36 months; ET treatment duration is ⩾60 months. The primary end point is invasive disease-free survival.

Discussion

The 36-month treatment duration of ribociclib in NATALEE is extended compared with that in other adjuvant cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitor trials and is intended to maximize efficacy due to longer duration of CDK4/6 inhibition. Compared with the 600-mg/day dose used in advanced breast cancer, the reduced ribociclib dose used in NATALEE may improve tolerability while maintaining efficacy. NATALEE includes the broadest population of patients with HR+/HER2- EBC of any Phase III trial currently evaluating adjuvant CDK4/6 inhibitor treatment.

Trial registration

ClinicalTrials.gov identifier: NCT03701334 (https://clinicaltrials.gov/ct2/show/NCT03701334).

Towards dual function of autophagy in breast cancer: A potent regulator of tumor progression and therapy response

As a devastating disease, breast cancer has been responsible for decrease in life expectancy of females and its morbidity and mortality are high. Breast cancer is the most common tumor in females and its treatment has been based on employment of surgical resection, chemotherapy and radiotherapy. The changes in biological behavior of breast tumor relies on genomic and epigenetic mutations and depletions as well as dysregulation of molecular mechanisms that autophagy is among them. Autophagy function can be oncogenic in increasing tumorigenesis, and when it has pro-death function, it causes reduction in viability of tumor cells. The carcinogenic function of autophagy in breast tumor is an impediment towards effective therapy of patients, as it can cause drug resistance and radio-resistance. The important hallmarks of breast tumor such as glucose metabolism, proliferation, apoptosis and metastasis can be regulated by autophagy. Oncogenic autophagy can inhibit apoptosis, while it promotes stemness of breast tumor. Moreover, autophagy demonstrates interaction with tumor microenvironment components such as macrophages and its level can be regulated by anti-tumor compounds in breast tumor therapy. The reasons of considering autophagy in breast cancer therapy is its pleiotropic function, dual role (pro-survival and pro-death) and crosstalk with important molecular mechanisms such as apoptosis. Moreover, current review provides a pre-clinical and clinical evaluation of autophagy in breast tumor.

The genomic regulation of metastatic dormancy

The genomics and pathways governing metastatic dormancy are critically important drivers of long-term patient survival given the considerable portion of cancers that recur aggressively months to years after initial treatments. Our understanding of dormancy has expanded greatly in the last two decades, with studies elucidating that the dormant state is regulated by multiple genes, microenvironmental (ME) interactions, and immune components. These forces are exerted through mechanisms that are intrinsic to the tumor cell, manifested through cross-talk between tumor and ME cells including those from the immune system, and regulated by angiogenic processes in the nascent micrometastatic niche. The development of new in vivo and 3D ME models, as well as enhancements to decades-old tumor cell pedigree models that span the development of metastatic dormancy to aggressive growth, has helped fuel what arguably is one of the least understood areas of cancer biology that nonetheless contributes immensely to patient mortality. The current review focuses on the genes and molecular pathways that regulate dormancy via tumor-intrinsic and ME cells, and how groups have envisioned harnessing these therapeutically to benefit patient survival.

Analyzing breast cancer invasive disease event classification through explainable artificial intelligence

Introduction

Recently, accurate machine learning and deep learning approaches have been dedicated to the investigation of breast cancer invasive disease events (IDEs), such as recurrence, contralateral and second cancers. However, such approaches are poorly interpretable.

Methods

Thus, we designed an Explainable Artificial Intelligence (XAI) framework to investigate IDEs within a cohort of 486 breast cancer patients enrolled at IRCCS Istituto Tumori "Giovanni Paolo II" in Bari, Italy. Using Shapley values, we determined the IDE driving features according to two periods, often adopted in clinical practice, of 5 and 10 years from the first tumor diagnosis.

Results

Age, tumor diameter, surgery type, and multiplicity are predominant within the 5-year frame, while therapy-related features, including hormone, chemotherapy schemes and lymphovascular invasion, dominate the 10-year IDE prediction. Estrogen Receptor (ER), proliferation marker Ki67 and metastatic lymph nodes affect both frames.

Discussion

Thus, our framework aims at shortening the distance between AI and clinical practice.

A machine learning ensemble approach for 5- and 10-year breast cancer invasive disease event classification

Designing targeted treatments for breast cancer patients after primary tumor removal is necessary to prevent the occurrence of invasive disease events (IDEs), such as recurrence, metastasis, contralateral and second tumors, over time. However, due to the molecular heterogeneity of this disease, predicting the outcome and efficacy of the adjuvant therapy is challenging. A novel ensemble machine learning classification approach was developed to address the task of producing prognostic predictions of the occurrence of breast cancer IDEs at both 5- and 10-years. The method is based on the concept of voting among multiple models to give a final prediction for each individual patient. Promising results were achieved on a cohort of 529 patients, whose data, related to primary breast cancer, were provided by Istituto Tumori "Giovanni Paolo II" in Bari, Italy. Our proposal greatly improves the performances returned by the baseline original model, i.e., without voting, finally reaching a median AUC value of 77.1% and 76.3% for the IDE prediction at 5-and 10-years, respectively. Finally, the proposed approach allows to promote more intelligible decisions and then a greater acceptability in clinical practice since it returns an explanation of the IDE prediction for each individual patient through the voting procedure.

SINGLE-CENTER ONCOLOGIC OUTCOME OF FAT TRANSFER FOR BREAST RECONSTRUCTION FOLLOWING MASTECTOMY IN 1000 CANCER CASES - A MATCHED CASE-CONTROL STUDY

BACKGROUND

Autologous fat transfer (AFT) has an important role in breast reconstructive surgery. Nevertheless, Some concerns remain with regards to its oncological safety. We present a single center case-matching study analysing the impact of AFT in cumulative incidence of local recurrences (LR).

MATERIALS AND METHODS

From a prospectively maintained database, we identified 902 patients who underwent 1025 breast reconstructions from 2005 to 2017. Data regarding demographics, tumor characteristics, surgery details and follow-up were collected. Exclusion criteria were patients with distant metastases at diagnosis, recurrent tumor or incomplete data regarding primary tumor, patients who underwent prophylactic mastectomies and breast-conserving surgeries. Statistical analysis was done to evaluate the impact of the variables on the incidence of LR. A p-value < 0.05 was considered statistically significant.

RESULTS

After 1:n case-matching, we selected 919 breasts, out of which 425 (46.2%) patients received at least one AFT session vs 494 (53.8%) control cases. LR had an overall rate of 6.8% and we found LR in 14 (3.0%) AFT cases and 54 (9.6%) controls. Statistical analysis showed that AFT did not increase risk of LR: HR 0.337 (CI 0.173-0.658), p=0.00007. Multivariate analysis identified IDC subtype and lymph node metastases to have an increased risk of local recurrences (HR > 1). Conversely, positive hormonal receptor status was associated with a reduced risk of events (HR < 1).

CONCLUSIONS

AFT was not associated with a higher probability of locoregional recurrence in patients undergoing breast reconstruction therefore it can be safely used for total breast reconstruction or aesthetic refinements.LEVEL OF EVIDENCE: 3.

The current staging and classification systems of breast cancer and their pitfalls: Is it possible to integrate the complexity of this neoplasm into a unified staging system?

Breast cancer is one of the leading causes of cancer death in women worldwide due to its variable aggressiveness and high propensity to develop distant metastases. The staging can be performed clinically or pathologically, generating the stage stratification by the TNM (T - tumor size; N- lymph node metastasis; M - distant organ metastasis) system. However, cancers with virtually identical TNM characteristics can present highly contrasting behaviors due to the divergence of molecular profiles. This review focuses on the histopathological nuances and molecular understanding of breast cancer through the profiling of gene and protein expression, culminating in improvements promoted by the integration of this information into the traditional staging system. As a culminating point, it will highlight predictive statistical tools for genomic risks and decision algorithms as a possible solution to integrate the various systems because they have the potential to reduce the indications for such tests, serving as a funnel in association with staging and previous classification.

In Vitro Growth Inhibition, Caspase-Dependent Apoptosis, and S and G2/M Phase Arrest in Breast Cancer Cells Induced by Fluorine-Incorporated Gold I Compound, Ph3PAu[SC(OMe)=NC6H4F-3]

Gold-based anticancer compounds have been attracting increasing research interest due to their ability to kill cancer cells resistant to platinum-based compounds. Gold I- and gold III-based complexes have shown satisfactory anticancer activities. In this study, two new fluorine-incorporated gold (I) compounds such as Ph3PAu[SC(OMe)=NC6H4F-3] and DPPFeAu2[(SC(OMe)=NC6H4F-3)]2 were evaluated for their in vitro activities against human breast cancer cell lines, primary breast cancer cells, and breast cancer stem cells (parental breast cancer stem cells, BCSC-P, and breast cancer stem cells, BCSC). Assays for growth inhibition and cytotoxicity, including real-time cell analysis, were carried out to screen effective antibreast cancer compounds. In addition, further in vitro assays such as apoptosis, caspase 3/7 activity, and cell cycle analysis were performed to observe the action and mechanism of killing breast cancer cells by the selected gold I compound, Ph3PAu[SC(OMe)=NC6H4F-3]. The gold (I) compound, Ph3PAu[SC(OMe)=NC6H4F-3], showed low toxicity to H9c2 normal cells and significant growth inhibition in MDA-MB-231 and MCF-7 cells, primary breast cancer cells, and breast cancer stem cells (BCSC-P and BCSC). The IC50 doses of the gold (I) compound Ph3PAu[SC(OMe)=NC6H4F-3] against the breast cancer cell lines MDA-MB-231 and MCF-7 were approximately 6-fold lower than that of cisplatin (cis-diamineplatinum (II) dichloride, CDDP). Moreover, the compound Ph3PAu[SC(OMe)=NC6H4F-3] induced caspase 3/7-dependent apoptosis and cell cycle arrest at S and G2/M phases. Ph3PAu[SC(OMe)=NC6H4F-3], a gold (I) compound incorporated with fluorine, is a potential candidate for the treatment of breast cancer.

Mortality After Late Breast Cancer Recurrence in Denmark

PURPOSE

Late breast cancer (BC) recurrence (ie, ≥ 10 years after primary diagnosis) may have a more favorable prognosis than earlier recurrence. We investigated the risk of BC death after late recurrence, identified prognostic factors, and compared survival after early and late recurrence.

METHODS

Using the Danish Breast Cancer Group and other nationwide databases, we identified women with early or late BC recurrence during 2004-2018, who were alive 6 months after recurrence. We followed them until BC death, death from other causes, emigration, 10 years, or December 31, 2018, whichever came first. We calculated mortality rates (MRs) per 1,000 person-years (PY) and cumulative BC mortality, for early versus late recurrence, and by characteristics of the primary tumor and the late recurrence. Using Cox regression, we calculated adjusted hazard ratios (HRs) for BC death, accounting for death from other causes as competing risks.

RESULTS

Among 2,004 patients with late recurrence, 721 died of BC with a median survival time of 10 years (MR = 84.8 per 1,000 PY; 10-year cumulative mortality = 50%). Among 1,528 patients with early recurrence, 1,092 BC deaths occurred with a median survival time of 4 years (MR = 173.9 per 1,000 PY; 10-year cumulative mortality = 72%). We observed a lower hazard of BC-specific death among patients who developed late compared with early recurrence (hazard ratio = 0.72; 95% CI, 0.62 to 0.85). Advanced stage at primary diagnosis, distant metastases, adjuvant treatment for locoregional recurrence, and systemic treatment for distant recurrence were associated with increased mortality after late recurrence. Breast-conserving surgery at primary diagnosis, locoregional recurrence, and surgery for recurrence were associated with lower mortality after late recurrence.

CONCLUSION

Patients with late recurrence had more favorable prognosis than patients with early recurrence. The localization of recurrent disease was the main prognostic factor for BC death.

Comparison of Clinical and Pathological Factors Affecting Early and Late Recurrences in Patients with Operable Breast Cancer

In this study, we aimed to assess clinicopathological factors affecting early and late recurrences in patients with operable breast cancer. Patients with early (≤5 years) and late (>5 years) recurrences were assessed. Prognostic factors for disease-free survival (DFS) were also evaluated in patients with recurrence. A total of 854 patients were included. There were 432 and 205 patients in the early and late recurrence groups, respectively. In multivariate analyses, HER2+ disease, lymph node metastasis, lymphovascular invasion (LVI), and high tumor grade were associated with increased risk of early recurrence, while HER2+ disease and LVI were associated with decreased risk of late recurrence. In multivariate analyses, presence of HER2+ disease and triple-negative breast cancer (TNBC) were poor prognostic factors for DFS in patients with early recurrence. Presence of LVI and perineural invasion (PNI) were poor prognostic factors for DFS in patients with late recurrence. Molecular subtypes and LVI were effective on the early and late recurrences. However, lymph node positivity and grade were only associated with the early recurrence. After 5 years, LVI and PNI were the prognostic factors for DFS.

LINC00355 regulates p27KIP expression by binding to MENIN to induce proliferation in late-stage relapse breast cancer

Late-stage relapse (LSR) in patients with breast cancer (BC) occurs more than five years and up to 10 years after initial treatment and has less than 30% 5-year relative survival rate. Long non-coding RNAs (lncRNAs) play important roles in BC yet have not been studied in LSR BC. Here, we identify 1127 lncRNAs differentially expressed in LSR BC via transcriptome sequencing and analysis of 72 early-stage and 24 LSR BC patient tumors. Decreasing expression of the most up-regulated lncRNA, LINC00355, in BC and MCF7 long-term estrogen deprived cell lines decreases cellular invasion and proliferation. Subsequent mechanistic studies show that LINC00355 binds to MENIN and changes occupancy at the CDKN1B promoter to decrease p27Kip. In summary, this is a key study discovering lncRNAs in LSR BC and LINC00355 association with epigenetic regulation and proliferation in BC.

Machine Learning to Discern Interactive Clusters of Risk Factors for Late Recurrence of Metastatic Breast Cancer

Simple Summary

Breast cancer is the most frequently diagnosed cancer and second leading cause of cancer-related death among women worldwide. After initial tumor resection, breast cancer may recur locally and/or in distant organs within several months to years or even decades. Multiple methods exist to prognosticate disease progression in the early months and years after diagnosis. However, further efforts are needed to identify risk factors that relate to recurrence beyond the initial 5-year window. In this study, we applied machine learning to retrieve single and interactive clinical and pathological risk factors of 5-, 10- and 15-year metastases.

Abstract

Background: Risk of metastatic recurrence of breast cancer after initial diagnosis and treatment depends on the presence of a number of risk factors. Although most univariate risk factors have been identified using classical methods, machine-learning methods are also being used to tease out non-obvious contributors to a patient’s individual risk of developing late distant metastasis. Bayesian-network algorithms can identify not only risk factors but also interactions among these risks, which consequently may increase the risk of developing metastatic breast cancer. We proposed to apply a previously developed machine-learning method to discern risk factors of 5-, 10- and 15-year metastases. Methods: We applied a previously validated algorithm named the Markov Blanket and Interactive Risk Factor Learner (MBIL) to the electronic health record (EHR)-based Lynn Sage Database (LSDB) from the Lynn Sage Comprehensive Breast Center at Northwestern Memorial Hospital. This algorithm provided an output of both single and interactive risk factors of 5-, 10-, and 15-year metastases from the LSDB. We individually examined and interpreted the clinical relevance of these interactions based on years to metastasis and reliance on interactivity between risk factors. Results: We found that, with lower alpha values (low interactivity score), the prevalence of variables with an independent influence on long-term metastasis was higher (i.e., HER2, TNEG). As the value of alpha increased to 480, stronger interactions were needed to define clusters of factors that increased the risk of metastasis (i.e., ER, smoking, race, alcohol usage). Conclusion: MBIL identified single and interacting risk factors of metastatic breast cancer, many of which were supported by clinical evidence. These results strongly recommend the development of further large data studies with different databases to validate the degree to which some of these variables impact metastatic breast cancer in the long term.

Circulating Tumor Cells as a Tool to Untangle the Breast Cancer Heterogeneity Issue

Breast cancer (BC) is a disease characterized by high degrees of heterogeneity at morphologic, genomic, and genetic levels, even within the same tumor mass or among patients. As a consequence, different subpopulations coexist and less represented clones may have a selective advantage, significantly influencing the outcome of BC patients. Circulating tumor cells (CTCs) represent a rare population of cells with a crucial role in metastatic cascade, and in recent years have represented a fascinating alternative to overcome the heterogeneity issue as a “liquid biopsy”. However, besides the raw enumeration of these cells in advanced epithelial tumors, there are no CTC-based assays applied in the clinical practice to improve personalized medicine. In this review, we report the latest findings in the field of CTCs for intra-tumoral heterogeneity unmasking in BC, supporting the need to deepen their analysis to investigate their role in metastatic process and include the molecular characterization in the clinical practice. In the future, CTCs will be helpful in monitoring patients during treatment, as well as to better address therapeutic strategies.

Risk of recurrence among patients with HR-positive, HER2-negative, early breast cancer receiving adjuvant endocrine therapy: A systematic review and meta-analysis

BACKGROUND

A systematic review and meta-analysis was conducted to assess breast cancer (BC) outcomes among patients with early-stage hormone receptor positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) BC, receiving adjuvant endocrine therapy.

METHODS

Randomized controlled trials (RCTs) and real-world evidence (RWE) studies were identified using Ovid MEDLINE®, Embase, and Evidence-Based Medicine Reviews. Clinical and methodological similarities including alignment of outcome definitions with standardized definitions for efficacy endpoints criteria were assessed to evaluate feasibility of conducting a meta-analysis. Where feasible, 5-year probabilities of BC recurrence or death were estimated using a Bayesian hierarchical arm-based model.

RESULTS

Of 21 included studies, 8 RCTs and 4 RWE studies reported outcome data of interest. There was heterogeneity in outcome reporting, as well as variation in recurrence risk amongst studies with aligned reporting. Of the 12 studies, 10 were considered for inclusion in a meta-analysis of BC recurrence or death. Only a subgroup analysis of node-positive patients (3 studies; n = 7307) was deemed feasible. The 5-year probability of BC recurrence or death was 17.2% (95% credible interval: 14.6%-20.3%).

CONCLUSION

Although studies reporting recurrence outcomes were limited, there remains a high risk of BC recurrence, especially among node-positive patients. Approximately 1 in 6 women with node-positive HR+/HER2- early-stage BC receiving endocrine therapy experience recurrence or death within 5-years of initiating treatment, suggesting a need for novel treatments for this population.

Autologous Fat Grafting Does Not Increase Risk of Oncologic Recurrence in the Reconstructed Breast

INTRODUCTION

Autologous fat grafting (AFG) is a popular and effective method of breast reconstruction after mastectomy; however, the oncological safety of AFG remains in question. The aim of this study was to determine whether AFG increases the risk of cancer recurrence in the reconstructed breast.

METHODS

A matched, case-control study was conducted from 2000 to 2017 at the senior author's institution. Inclusion was limited to female patients who underwent mastectomy and breast reconstruction with or without AFG. Data were further subdivided at the breast level. χ analyses were used to test the association between AFG status and oncologic recurrence. A Cox proportional-hazards model was constructed to assess for possible differences in time to oncologic recurrence. The probability of recurrence was determined by Kaplan-Meier analyses and confirmed with log-rank testing.

RESULTS

Overall, 428 breasts met study criteria. Of those, 116 breasts (27.1%) received AFG, whereas 312 (72.9%) did not. No differences in the rates of oncologic recurrence were found between the groups (8.2% vs 9.0%, P < 1.000). Unadjusted (hazard ratio = 1.03, confidence interval = 0.41-2.60, P < 0.957) and adjusted hazard models showed no statistically significant increase in time to oncologic recurrence when comparing AFG to non-AFG. In addition, no statistical differences in disease-free survival were found (P = 0.96 by log rank test).

CONCLUSION

Autologous fat grafting for breast reconstruction is oncologically safe and does not increase the likelihood of oncologic recurrence. Larger studies (eg, meta analyses) with longer follow-up are needed to further elucidate the long-term safety of AFG as a reconstructive adjunct.

A Clinicogenetic Prognostic Classifier for Prediction of Recurrence and Survival in Asian Breast Cancer Patients

Background

Several prognostic factors affect the recurrence of breast cancer in patients who undergo mastectomy. Assays of the expression profiles of multiple genes increase the probability of overexpression of certain genes and thus can potentially characterize the risk of metastasis.

Methods

We propose a 20-gene classifier for predicting patients with high/low risk of recurrence within 5 years. Gene expression levels from a quantitative PCR assay were used to screen 473 luminal breast cancer patients treated at Taiwan Hospital (positive for estrogen and progesterone receptors, negative for human epidermal growth factor receptor 2). Gene expression scores, along with clinical information (age, tumor stage, and nodal stage), were evaluated for risk prediction. The classifier could correctly predict patients with and without relapse (logistic regression, P<0.05).

Results

A Cox proportional hazards regression analysis showed that the 20-gene panel was prognostic with hazard ratios of 5.63 (95% confidence interval 2.77-11.5, univariate) and 5.56 (2.62-11.8, multivariate) for the “genetic” model, and of 8.02 (3.52-18.3, univariate) and 19.8 (5.96-65.87, multivariate) for the “clinicogenetic” model during a 5-year follow-up.

Conclusions

The proposed 20-gene classifier can successfully separate the patients into two risk groups, and the two risk group had significantly different relapse rate and prognosis. This 20-gene classifier can provide better estimation of prognosis, which can help physicians to make better personalized treatment plans.

Outcomes After Accelerated Partial Breast Irradiation in Women With Triple Negative Subtype and Other "High Risk" Variables Categorized as Cautionary in The ASTRO Guidelines

PURPOSE

To report a primary objective clinical outcome of ipsilateral breast recurrence following accelerated partial breast irradiation (APBI) in women with triple negative and other high risk breast cancer (as described in 2017 ASTRO guidelines) (i.e., age 40-49, size 2.1-3.0 cm, estrogen receptor negative and invasive lobular breast cancer). Secondary objectives of axillary and regional failure as well as overall survival are also reported.

METHODS AND MATERIAL

Patients from two clinical trials (NCT01185145, NCT01185132) were treated with 38.5 Gy IMRT or 3D-CRT APBI w/3.85 Gy fraction/BID fractionation for 10 fractions. Triple negative and other high risk patients (n=269) were compared to a total of 478 low risk patients which ASTRO defined as "suitable" for APBI. High risk patients, for the purpose of this study, were defined as those who possess one or more high risk criteria: triple negative (n=30), tumor size >2 cm <3 cm (n=50), HER 2+ (n=54), age range 40-50 years (n=120), ER- (n=43), and ILC histology (n=52).

RESULTS

Median follow up was 4.0 years for all patients. No significant difference was found for this high-risk cohort at 5 years for ipsilateral breast, or regional recurrences. Axillary recurrence was significantly adversely impacted by triple negative and ER- statuses (p=0.01, p=0.04). There were significant correlations between triple negative type and axillary recurrence on multivariate analysis (p=0.03). Overall survival for all patients was unaffected by any of the high-risk categories.

CONCLUSION

The data from this study suggests that women possessing high risk features are at no more meaningful risk for recurrence than other patients considered to be acceptable for APBI treatment. However, the finding of axillary recurrence in patients with triple negative breast cancer does warrant a degree of caution in proceeding with accelerated partial breast irradiation technique in this patient group.

A Clinical Decision Support System for Predicting Invasive Breast Cancer Recurrence: Preliminary Results

The mortality associated to breast cancer is in many cases related to metastasization and recurrence. Personalized treatment strategies are critical for the outcomes improvement of BC patients and the Clinical Decision Support Systems can have an important role in medical practice. In this paper, we present the preliminary results of a prediction model of the Breast Cancer Recurrence (BCR) within five and ten years after diagnosis. The main breast cancer-related and treatment-related features of 256 patients referred to Istituto Tumori “Giovanni Paolo II” of Bari (Italy) were used to train machine learning algorithms at the-state-of-the-art. Firstly, we implemented several feature importance techniques and then we evaluated the prediction performances of BCR within 5 and 10 years after the first diagnosis by means different classifiers. By using a small number of features, the models reached highly performing results both with reference to the BCR within 5 years and within 10 years with an accuracy of 77.50% and 80.39% and a sensitivity of 92.31% and 95.83% respectively, in the hold-out sample test. Despite validation studies are needed on larger samples, our results are promising for the development of a reliable prognostic supporting tool for clinicians in the definition of personalized treatment plans.

Predictors and outcomes in breast cancer patients who did or did not pursue fertility preservation

PURPOSE

Breast cancer is the most common cancer in reproductive age women, and treatment can affect fertility; however, there is often concern regarding the safety of increased estradiol (E₂) levels and potential delays in treatment with ovarian stimulation for fertility preservation (FP). The aim of this study was to compare recurrence and survival in breast cancer patients who pursued FP without concurrent letrozole to those who did not (non-FP).

METHODS

We reviewed charts of women with breast cancer who contacted the FP patient navigator (PN) at Northwestern University from 01/2005-01/2018. Oncology and fertility outcome data were collected. Data were analyzed by Chi-square test or regression, as appropriate. Kaplan-Meier curves were used to examine breast cancer recurrence and survival. Statistical analyses were performed with SPSS IBM Statistics 26.0 for Windows.

RESULTS

332 patients were included, of which 157 (47.3%) underwent FP. Median days to treatment after consulting the PN was 35 in the FP group and 21 in non-FP (p < 0.05). Cancer recurrence was noted in 7 (4.7%) FP patients and 13 (7.9%) non-FP patients (NS), and mortality in 5 (3.2%) FP patients and 7 (4.2%) non-FP patients (NS). Within the FP group, no significant differences were found in recurrence or mortality based on ER status, age, BMI, peak E₂ level or total gonadotropin dose. Likelihood of pursuing FP was primarily a function of age and parity, and was not affected by breast cancer stage. To date, 21 have used cryopreserved specimens, and 13 (62%) had a live birth.

CONCLUSIONS

FP is safe and effective in breast cancer patients, regardless of receptor status; E₂ elevations and the 2-week delay in treatment start are unlikely to be clinically significant. These findings are unique in that our institution does not use concomitant letrozole during stimulation to minimize E₂ elevations in breast cancer patients.

Incidence and Predictors of Recurrence among Breast Cancer Patients in Black Lion Specialized Hospital Adult Oncology Unit, Addis Ababa, Ethiopia: Retrospective Follow-up Study with Survival Analysis

Currently, breast cancer is becoming a major public health problem for developing countries. In Ethiopia, breast cancer is the most prevalent cancer among women, and constitutes a major public health concern. Hence, this study was aimed to determine the incidence and predictor of recurrence among breast cancer clients at Black Lion Specialized Hospital, Ethiopia, in 2018. We analyzed 513 patients out of 835 women breast cancer patients treated at Black Lion Specialized Hospital. Recurrent-free survival was determined using the Kaplan-Meier method, with comparisons between groups through the log-rank test. The Cox proportional hazards model was used to identify predictors of recurrence among breast cancer clients. The incidence rate of recurrence among breast cancer was 6.5% per (95% CI = 6.49-12.47) follow-up. The median recurrent-free survival time was 60.33 months (95% CI = 54.46-62.30). Predictors of recurrence were negative estrogen receptor (hazard ratio [HR] = 1.8, 95% CI = 1.53-7.62), high histologic grade (HR = 2.8, 95% CI = 1.14-10.31), positive lymph node status (HR = 2.6, 95% CI = 1.14-10.31), clinical staging III (HR = 2.5, 95% CI = 1.26-9.42), and involved deep surgical margin (HR = 3.6, 95% CI = 2.14-8.61). This research showed that incidence of recurrence was high. Advanced clinical stage, positive nodal status, high histologic grade, negative estrogen receptor, and involved deep surgical margin were associated with higher recurrence rates. In contrast, hormonal therapy has a great role in decreasing the development of recurrence.

Breast cancer: insights in disease and influence of drug methotrexate

According to the World Health Organization, cancer is one of the leading causes of morbidity and mortality worldwide. The previously estimated 14 million new cases in the year of 2012 are expected to rise, yearly, over the following 2 decades. Among women, breast cancer is the most common one. In 2012, almost 1.7 million people were diagnosed worldwide and half a million died from the disease. Despite having several treatments available, from surgery to chemotherapy, most of these treatments have severe adverse effects. Chemotherapy has a narrow therapeutic window and requires high dosage treatment in patients with advanced-stage cancers and further need innovative treatment strategies. Although methotrexate (MTX) is not a first line drug used against breast cancer, however, it might be valuable to fight the disease. MTX is an effective and cheap drug that might impair malignant growth without irreversible damage to normal tissues. Nevertheless, while MTX does present some disadvantages including poor solubility and low permeability, several strategies are being used to discover and provide novel and effective targeted treatment against breast cancer. In this review, we analyze the chemotherapy of breast cancer and its relationship with drug MTX.

DGM-CM6: A New Model to Predict Distant Recurrence Risk in Operable Endocrine-Responsive Breast Cancer

To investigate the prognostic value of DGM-CM6 (Distant Genetic Model-Clinical variable Model 6) for endocrine-responsive breast cancer (ERBC) patients, we analyzed 752 operable breast cancer patients treated in a Taiwan cancer center from 2005 to 2014. Among them, 490 ERBC patients (identified by the PAM50 or immunohistochemistry method) were classified by DGM-CM6 into low- and high-risk groups (cutoff <33 and ≥33, respectively). Significant differences were observed between the DGM-CM6 low- and high-risk groups for 10-year distant recurrence-free survival (DRFS) in both lymph node (LN)- (P < 0.05) and LN+ patients (P < 0.05). Multivariate analysis confirmed the independent strength of DGM-CM6 for the prediction of high- vs. low- risk groups for DRFS (P < 0.0001, HR: 6.76, 95% CI, 1.8–25.42) and overall survival (P = 0.01, HR: 6.06, 95% CI:1.55–23.47), respectively. In summary, DGM-CM6 may be used to classify low- and high-risk groups for 10-year distant recurrence in both LN- and LN+ ERBC patients in the Asian population. A large scale clinical trial is warranted.

Risk factors for breast cancer brain metastases: a systematic review

Background: Brain metastasis (BM) is an increasingly common and devastating complication of breast cancer (BC).

Methods: A systematic literature search of EMBASE and MEDLINE was conducted to elucidate the current state of knowledge on known and novel prognostic factors associated with 1) the risk for BCBM and 2) the time to brain metastases (TTBM).

Results: A total of 96 studies involving institutional records from 28 countries were identified. Of these, 69 studies reported risk factors of BCBM, 46 factors associated with the TTBM and twenty studies examined variables for both outcomes. Young age, estrogen receptor negativity (ER-), overexpression of human epidermal factor (HER2+), and higher presenting stage, histological grade, tumor size, Ki67 labeling index and nodal involvement were consistently found to be independent risk factors of BCBM. Of these, triple-negative BC (TNBC) subtype, ER-, higher presenting histological grade, tumor size, and nodal involvement were also reported to associate with shorter TTBM. In contrast, young age, hormone receptor negative (HR-) status, higher presenting stage, nodal involvement and development of liver metastasis were the most important risk factors for BM in HER2-positive patients.

Conclusions: The study provides a comprehensive and individual evaluation of the risk factors that could support the design of screening tools and interventional trials for early detection of BCBM.

Metabolic consequences of perioperative oral carbohydrates in breast cancer patients - an explorative study

Background

The metabolic consequences of preoperative carbohydrate load in breast cancer patients are not known. The present explorative study investigated the systemic and tumor metabolic changes after preoperative per-oral carbohydrate load and their influence on tumor characteristics and survival.

Methods

The study setting was on university hospital level with primary and secondary care functions in south-west Norway. Serum and tumor tissue were sampled from a population-based cohort of 60 patients with operable breast cancer who were randomized to either per-oral carbohydrate load (preOp™; n = 25) or standard pre-operative fasting (n = 35) before surgery. Magnetic resonance (MR) metabolomics was performed on serum samples from all patients and high-resolution magic angle spinning (HR-MAS) MR analysis on 13 tumor samples available from the fasting group and 16 tumor samples from the carbohydrate group.

Results

Fourteen of 28 metabolites were differently expressed between fasting and carbohydrate groups. Partial least squares discriminant analysis showed a significant difference in the metabolic profile between the fasting and carbohydrate groups, compatible with the endocrine effects of insulin (i.e., increased serum-lactate and pyruvate and decreased ketone bodies and amino acids in the carbohydrate group). Among ER-positive tumors (n = 18), glutathione was significantly elevated in the carbohydrate group compared to the fasting group (p = 0.002), with a positive correlation between preoperative S-insulin levels and the glutathione content in tumors (r = 0.680; p = 0.002). In all tumors (n = 29), glutamate was increased in tumors with high proliferation (t-test; p = 0.009), independent of intervention group. Moreover, there was a positive correlation between tumor size and proliferation markers in the carbohydrate group only. Patients with ER-positive / T2 tumors and high tumor glutathione (≥1.09), high S-lactate (≥56.9), and high S-pyruvate (≥12.5) had inferior clinical outcomes regarding relapse-free survival, breast cancer-specific survival, and overall survival. Moreover, Integrated Pathway Analysis (IPA) in serum revealed activation of five major anabolic metabolic networks contributing to proliferation and growth.

Conclusions

Preoperative carbohydrate load increases systemic levels of lactate and pyruvate and tumor levels of glutathione and glutamate in ER-positive patients. These biological changes may contribute to the inferior clinical outcomes observed in luminal T2 breast cancer patients.

Trial of registration

ClinicalTrials.gov; NCT03886389. Retrospectively registered March 22, 2019.

Pertuzumab and Trastuzumab Emtansine for Human Epidermal Growth Factor Receptor-2-Positive Metastatic Breast Cancer: Contemporary Population-Based Outcomes

Background

Real-world outcomes for patients with human epidermal growth factor receptor-2 (HER2)-positive metastatic breast cancer (MBC) treated with pertuzumab in combination with taxane chemotherapy plus trastuzumab (TaxTP) in the first line setting and trastuzumab emtansine (TE) in any line of treatment are lacking.

Methods

Cohorts of patients treated with (1) TaxTP and (2) TE from January 1, 2013 through December 31, 2016 were retrospectively obtained from a population-based database. Cohorts were described according to age, hormone receptor (HR) status, prior systemic therapies, event-free survival (EFS) defined as time from start of treatment to start of next line of treatment or death, and overall survival (OS).

Results

A total of 122 patients were treated with TaxTP and 104 with TE. In the TaxTP cohort, EFS was significantly longer in the trastuzumab-naïve group compared with the adjuvant trastuzumab group (median EFS = 27.0 vs 12.4 months; P = .002). In the TaxTP cohort, median OS was not reached. In the TE cohort, EFS was significantly longer in the pertuzumab-naïve group compared with pertuzumab-exposed group (median time to treatment failure [TTF] = 18.7 vs 5.5 months; P < .001). Overall survival was also significantly longer in the pertuzumab-naïve group compared with the pertuzumab-exposed group (median OS = 23.2 vs 14.1 months; P = .022). In multivariable analyses, adjuvant trastuzumab and prior pertuzumab exposure in the metastatic setting remained significant predictors of inferior EFS for patients treated with TaxTP and TE, respectively.

Conclusions

New anti-HER2 therapies appear to be clinically relevant in the real-world.

Reirradiation of recurrent breast cancer with proton beam therapy: A case report and literature review

BACKGROUND

Locoregional recurrence of breast cancer is challenging for clinicians, due to the various former treatments patients have undergone. However, treatment of the recurrence with systemic therapy and subsequent reirradiation of chest wall is accompanied by increased toxicities, particularly radiation-induced cardiovascular disease. Reirradiation by proton beam therapy (PBT) enables superior preservation of adjacent organs at risk as well as concurrent dose escalation for delivery to the gross tumor. This technology is expected to improve the overall outcome of recurrent breast cancer.

CASE SUMMARY

A 47-year-old female presented with an extensive locoregional recurrence at 10 yr after primary treatment of a luminal A breast cancer. Because of tumor progression despite having undergone bilateral ovarectomy and systemic therapy, the patient was treated with PBT BE total dose of 64.40 Gy to each gross tumor and 56.00 Gy to the upper mediastinal and retrosternal lymphatics including the entire sternum in 28 fractions. Follow-up computed tomography showed a partial remission, without evidence of newly emerging metastasis. At 19 mo after the PBT, the patient developed a radiation-induced pericardial disease and pleural effusions with clinical burden of dyspnea, which were successfully treated by drainage and corticosteroid. Cytological analysis of the puncture fluid showed no malignancy, and the subsequent computed tomography scan indicated stable disease as well as significantly decreased pericardial and pleural effusions. The patient remains free of progression to date.

CONCLUSION

PBT was a safe and effective method of reirradiation for locoregionally recurrent breast cancer in our patient.

Young Patients with Hormone Receptor-Positive Breast Cancer Have a Higher Long-Term Risk of Breast Cancer Specific Death

Purpose

Although it is widely accepted that hormone receptor (HR) status is associated with later post-diagnostic periods, a debate exists as to whether the association is independent of age. The aim of our study was to confirm the impact of HR status on later period breast cancer-specific death (LP-BCSD) and later period non-breast cancer-specific death (LP-non-BCSD) in different age subgroups.

Methods

Surveillance, Epidemiology, and End Results databases were utilized to identify 181,108 breast cancer patients with > 5 years survival. The cumulative incidence of LP-BCSD and LP-non-BCSD was calculated using the Gray method. The subdistribution hazard ratio (SHR) of variables was estimated via the Fine and Gray proportional hazard regression model. Subgroup analyses for LP-BCSD and LP-non-BCSD were performed according to the HR status.

Results

The risk of LP-BCSD was exceeded by that of LP-non-BCSD at > 5 years since the diagnosis, particularly in old women. The competing risk regression model indicated that hormone receptor-positive (HR+) was an independent factor for more LP-BCSD (hazard ratio, 1.54; 95% confidence interval, 1.44–1.54; p < 0.001). However, stratified analysis indicated that HR+ was only associated with more LP-BCSD in the young women subgroup. Although HR+ was associated with more LP-non-BCSD, the predictive value of HR+ for LP-non-BCSD was eliminated after adjusting for age.

Conclusions

HR+ was related to LP-BCSD in the premenopausal population. LP-BCSD should be an optimal endpoint in future trials designed to evaluate the role of extended adjuvant endocrine therapy.

Prognostic Factors of Local-Regional Recurrence in Patients with Operable Breast Cancer in Asia: A Meta-Analysis

BACKGROUND

Cause of recurrence of breast cancer is multifactorial. Also, the occurrence of breast cancer in Asian patients has some different factors from the recurrence of breast cancer in western countries.

AIM

This study aims to determine the prognostic factors of local-regional recurrence in patients with operable breast cancer in Asia.

METHODS

The authors conducted a meta-analysis of published research articles published in an online database of PubMed, ProQuest and EBSCO between January 2000 and July 2018. Pooled risk ratios (RR) were calculated using fixed and random-effect models. Data were processed by using Review Manager 5.3 (RevMan 5.3).

RESULTS

This study reviewed 879 articles. There were 11 studies conducted a systematic review then continued by meta-analysis of relevant data with total patients involved were 5,213 patients. The prognostic factors found of local-regional recurrence in patients with operable breast cancer were Nodal (N) stage with the highest risk ratio (RR = 6.35 [95% CI 3.78-10.67]) followed by HER2 positive (RR = 2.14 [95% CI 1.16-3.97]), stage of cancer (RR = 1.82 [95% CI 1.44-2.31]), tumor size (RR = 1.55 [95% CI 1.04-2.31]), tumor grade (RR = 1.43 [95% CI 1.23-1.65]), PR status (RR = 0.65 [95% CI 0.48-0.88]) and the least was ER status (RR = 0.60 [95% CI 0.39-0.91]). Homogeneity of variance was found in N stage, tumor size and tumor grade for recurrence of operable breast cancer.

CONCLUSION

This meta-analysis confirmed the correlation of N stage, HER2, stage of cancer, tumour size, tumour grade, ER and PR status with recurrence in patients with operable breast cancer in Asia.

A conditional model predicting the 10-year annual extra mortality risk compared to the general population: a large population-based study in Dutch breast cancer patients

Objective

Many cancer survivors are facing difficulties in getting a life insurance; raised premiums and declinatures are common. We generated a prediction model estimating the conditional extra mortality risk of breast cancer patients in the Netherlands. This model can be used by life insurers to accurately estimate the additional risk of an individual patient, conditional on the years survived.

Methodology

All women diagnosed with stage I-III breast cancer in 2005–2006, treated with surgery, were selected from the Netherlands Cancer Registry. For all stages separately, multivariable logistic regression was used to estimate annual mortality risks, conditional on the years survived, until 10 years after diagnosis, resulting in 30 models. The conditional extra mortality risk was calculated by subtracting mortality rates of the general Dutch population from the patient mortality rates, matched by age, gender and year. The final model was internally and externally validated, and tested by life insurers.

Results

We included 23,234 patients: 10,101 stage I, 9,868 stage II and 3,265 stage III. The final models included age, tumor stage, nodal stage, lateralization, location within the breast, grade, multifocality, hormonal receptor status, HER2 status, type of surgery, axillary lymph node dissection, radiotherapy, (neo)adjuvant systemic therapy and targeted therapy. All models showed good calibration and discrimination. Testing of the model by life insurers showed that insurability using the newly-developed model increased with 13%, ranging from 0%-24% among subgroups.

Conclusion

The final model provides accurate conditional extra mortality risks of breast cancer patients, which can be used by life insurers to make more reliable calculations. The model is expected to increase breast cancer patients’ insurability and transparency among life insurers.

Potential protein markers for breast cancer recurrence: a retrospective cohort study

BACKGROUND

We evaluated five key proteins involved in various cancer-related pathways and assessed their relation to breast cancer recurrence.

METHODS

We used the Kentucky Cancer Registry to retrospectively identify primary invasive breast cancer cases (n = 475) that were diagnosed and treated at University of Kentucky Medical Center between 2000 and 2007. Breast cancer recurrence was observed in 62 cases during the 5-year follow-up after diagnosis. Protein expression or activity level was analyzed from surgery tissue using immuno-histochemical assays.

RESULTS

Compared to ER+/PR+/HER2- patients without recurrence, those with recurrence had higher TWIST expression (p = 0.049) but lower ABL1/ABL2 activity (p = 0.003) in primary tumors. We also found that triple-negative breast cancer patients with recurrence had higher SNAI1 expression compared to those without recurrence (p = 0.03). After adjusting for potential confounders, the higher ABL1/ABL2 activity in primary tumors was associated with a decreased risk of recurrence (OR 0.72, 95% CI 0.85-0.90) among ER+/PR+/HER2- patients. In addition, among patients with recurrence we observed that the activity level of ABL1/ABL2 was significantly increased in recurrent tumors compared to the matched primary tumors regardless of the subtype (p = 0.013).

CONCLUSIONS

These findings provide evidence that the expression/activity level of various proteins may be differentially associated with risk of recurrence of breast tumor subtypes.

Introducing novel and comprehensive models for predicting recurrence in breast cancer using the group LASSO approach: are estimates of early and late recurrence different?

Background

In here, we constructed personalized models for predicting breast cancer (BC) recurrence according to timing of recurrence (as early and late recurrence).

Methods

An efficient algorithm called group LASSO was used for simultaneous variable selection and risk factor prediction in a logistic regression model.

Results

For recurrence < 5 years, age (OR 0.96, 95% CI = 0.95–0.97), number of pregnancies (OR 0.94, 95% CI = 0.89–0.99), family history of other cancers (OR 0.73, 95% CI = 0.60–0.89), hormone therapy (OR 0.76, 95% CI = 0.61–0.96), dissected lymph nodes (OR 0.98, 95% CI = 0.97–0.99), right-sided BC (OR 0.87, 95% CI = 0.77–0.99), diabetes (OR 0.77, 95% CI = 0.60–0.98), history of breast operations (OR 0.38, 95% CI = 0.17–0.88), smoking (OR 5.72, 95% CI = 2.11–15.55), history of breast disease (OR 3.32, 95% CI = 1.92–5.76), in situ component (OR 1.58, 95% CI = 1.35–1.84), tumor necrosis (OR 1.87, 95% CI = 1.57–2.22), sentinel lymph node biopsy (SLNB) (OR 2.90, 95% CI = 2.05–4.11) and SLNB+axillary node dissection (OR 3.50, 95% CI = 2.26–5.42), grade 3 (OR 1.79, 95% CI = 1.46–2.21), stage 2 (OR 2.71, 95% CI = 2.18–3.35), stages 3 and 4 (OR 5.01, 95% CI = 3.52–7.13), and mastectomy+radiotherapy (OR 2.97, 95% CI = 2.39–3.68) were predictors of recurrence < 5 years. Moreover, relative to mastectomy without radiotherapy (as reference for comparison), quadrantectomy without radiotherapy had a noticeably higher odds ratio compared to quadranectomy with radiotherapy for recurrence < 5 years. (OR 17.58, 95% CI = 6.70–46.10 vs. OR: 2.50, 95% CI = 2–3.12).

Accuracy, sensitivity, and specificity of the model were 82%, 75.6%, and 74.9%, respectively.

For recurrence > 5 years, stage 2 cancer (OR 1.67, 95% CI = 1.31–2.14) and radiotherapy+mastectomy (OR 2.45, 95% CI = 1.81–3.32) were significant predictors; furthermore, relative to mastectomy without radiotherapy (as reference for comparison), quadranectomy without radiotherapy had a noticeably higher odds ratio compared to quadranectomy with radiotherapy for recurrence > 5 years (OR 7.62, 95% CI = 1.52–38.15 vs. OR 1.75, 95% CI = 1.32–2.32). Accuracy, sensitivity, and specificity of the model were 71%, 78.8%, and 55.8%, respectively.

Conclusion

For the first time, we constructed models for estimating recurrence based on timing of recurrence which are among the most applicable models with excellent accuracy (> 80%).

Electronic supplementary material

The online version of this article (10.1186/s12957-018-1489-0) contains supplementary material, which is available to authorized users.

Ten-year conditional recurrence risks and overall and relative survival for breast cancer patients in the Netherlands: Taking account of event-free years

BACKGROUND

Survival estimates from diagnosis are of limited importance for (ex-)breast cancer patients who survived several years, as it includes information on already deceased patients. This study analysed the 10-year conditional risk of recurrent breast cancer in specific prognostic subgroups. Second, we investigated 10-year conditional overall survival (OS) and relative survival (RS), adjusted for confounding.

PATIENTS AND METHODS

All women diagnosed in 2005 with operated T1-2N0-1 breast cancer were selected from the Netherlands Cancer Registry. Patients were classified into T1N0, T1N1, T2N0 and T2N1 stage. Ten-year conditional recurrence rates were calculated from diagnosis, and for patients without an event (local [LR], regional recurrence [RR], distant metastasis [DM] or death) every year following diagnosis. Ten-year conditional OS was calculated using multivariable Cox regression. RS was estimated by dividing patient survival rates by those of the general Dutch population.

RESULTS

We included 7969 patients: 52.3% had T1N0, 15.3% T1N1, 19.9% T2N0 and 12.5% T2N1 stage. For T1N0, 10-year LR rates changed from 4.6% at diagnosis to 0.5% in year 10. RR rates changed from 2.3% to 0.2%, and DM rates changed from 7.8% to 0.6%. For T2N1 stage, the LR, RR and DM rates changed from 6.2% to 0.8%, 5.2%-0.4% and 19.6%-1.5%, respectively. For the luminal A subtype, LR, RR and DM rates changed from 3.9% to 0.4%, 1.7%-0.5% and 7.3%-1.1%, while for triple negative, these rates changed from 5.6% to 0.7%, 4.9%-0.2% and 16.7%-0%, respectively. Differences between subgroups attenuated over time, and all recurrence rates became ≤1.5% in year 10. Ten-year OS and RS, adjusted for confounding, showed declining risk differences between subgroups over time.

CONCLUSION

Differences in recurrence rates, OS and RS between prognostic subgroups declined as years passed by. These results highlight the importance of taking into account disease-free years to more accurately predict (ex-)breast cancer patients' prognosis over time.

Construction of a novel multi-gene assay (42-gene classifier) for prediction of late recurrence in ER-positive breast cancer patients

PURPOSE

Prediction models for late (> 5 years) recurrence in ER-positive breast cancer need to be developed for the accurate selection of patients for extended hormonal therapy. We attempted to develop such a prediction model focusing on the differences in gene expression between breast cancers with early and late recurrence.

METHODS

For the training set, 779 ER-positive breast cancers treated with tamoxifen alone for 5 years were selected from the databases (GSE6532, GSE12093, GSE17705, and GSE26971). For the validation set, 221 ER-positive breast cancers treated with adjuvant hormonal therapy for 5 years with or without chemotherapy at our hospital were included. Gene expression was assayed by DNA microarray analysis (Affymetrix U133 plus 2.0).

RESULTS

With the 42 genes differentially expressed in early and late recurrence breast cancers in the training set, a prediction model (42GC) for late recurrence was constructed. The patients classified by 42GC into the late recurrence-like group showed a significantly (P = 0.006) higher late recurrence rate as expected but a significantly (P = 1.62 × E-13) lower rate for early recurrence than non-late recurrence-like group. These observations were confirmed for the validation set, i.e., P = 0.020 for late recurrence and P = 5.70 × E-5 for early recurrence.

CONCLUSION

We developed a unique prediction model (42GC) for late recurrence by focusing on the biological differences between breast cancers with early and late recurrence. Interestingly, patients in the late recurrence-like group by 42GC were at low risk for early recurrence.