Neoadjuvant Chemotherapy, Endocrine Therapy, and Targeted Therapy for Breast Cancer: ASCO Guideline

Real-world perioperative treatment patterns and economic burden of recurrence in early-stage HER2-negative breast cancer: a SEER-Medicare study

AIM

This study aimed to describe treatment patterns and quantify the economic impact of recurrence in early-stage human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC).

MATERIALS & METHODS

Medicare beneficiaries with stages I-III HER2-negative BC and lumpectomy or partial/total mastectomy were identified from SEER-Medicare data (2010-2019). Perioperative therapies were reported in the neoadjuvant and adjuvant setting. Locoregional recurrence and distant metastasis were identified using a claims-based algorithm developed with clinical input and consisting of a diagnosis-based and treatment-based indicator. All-cause and BC-related healthcare resource utilization (HRU) per-patient-month and monthly healthcare costs were estimated from the recurrence date for patients with recurrence and from an imputed index date for patients without recurrence using frequency matching. HRU and costs were compared between groups stratified by hormone receptor-positive (HR+) or triple negative BC (TNBC) using multivariable regression models.

RESULTS

Of 28,655 patients, 8.5% experienced recurrence, 90.4% had HR+ disease, and 5.6% received neoadjuvant therapy. Relative to patients without recurrence, patients with recurrence had more advanced disease (stage II/III: 73.7% vs. 34.0%) and higher-grade tumors (Grade 3/4: 40.6% vs. 18.0%) at diagnosis. Recurrence in HR+/HER2-negative BC and TNBC was associated with higher rates of all-cause hospitalizations (incidence rate ratio [IRR]: 2.84 and 3.65), emergency department (ED) visits (IRR: 1.75 and 2.00), and outpatient visits (IRR: 1.46 and 1.55; all p < 0.001). Similarly, recurrence was associated with higher rates of BC-related HRU, particularly for ED visits in HR+/HER2-negative BC (IRR: 4.24; p < 0.001) and hospitalizations in TNBC (IRR: 11.71; p < 0.001). Patients with HR+/HER2-negative BC and TNBC recurrence incurred higher monthly all-cause (cost difference [CD]: $3988 and $4651) and BC-related healthcare costs (CD: $3743 and $5819).

CONCLUSIONS

Our findings highlight the considerable economic burden of recurrence in early-stage HER2-negative BC and underscore the unmet need for optimization of therapies that reduce recurrence in this population.

Predicting progression in triple-negative breast cancer patients undergoing neoadjuvant chemotherapy: Insights from peritumoral radiomics

OBJECTIVE

To investigate whether radiomic features obtained from the intratumoral and peritumoral regions of pretreatment magnetic resonance imaging (MRI) can predict progression in patients with triple-negative breast cancer (TNBC) undergoing neoadjuvant chemotherapy (NAC) in comparison with the previously determined clinical score.

METHODS

This single-center retrospective study evaluated 224 women with TNBC who underwent NAC between 2010 and 2019. Women were randomly allocated to the training set (n = 169) for model development and the test set (n = 55) for model validation. The clinical score consisted of the histologic type, Ki-67 index, and degree of edema on T2-weighted imaging. Intratumoral and peritumoral radiomic features were extracted from T2-weighted images and the first- and last-phase images of dynamic contrast-enhanced MRI. The radiomics model was built using only radiomic features, whereas the combined model incorporated the clinical score along with radiomic features. The area under the receiver operating characteristic curve (AUC) was used to assess performance.

RESULTS

Progression occurred in 18 and five patients in the training and test sets, respectively. The radiomics model selected three radiomic features (two peritumoral and one intratumoral), while the combined model selected the clinical score and five radiomic features (four peritumoral and one intratumoral). Among the total radiomic features, Inverse Difference Normalized of the peritumoral region of the T2-weighted images, reflective of peritumoral heterogeneity, demonstrated the highest level of association with tumor progression. In the test set, the AUC values of the radiomics-only model, the combined model, and the clinical score were 0.592, 0.764, and 0.720, respectively. Compared to the clinical score, the radiomics-only model (0.720 vs. 0.592, p = 0.468) and the combined model (0.720 vs. 0.764, p = 0.553) did not show superior performance.

CONCLUSION

The radiomics features were not superior in predicting the progression of TNBC compared to the clinical score, although the peritumoral heterogeneity on T2-weighted images showed a potential.

Personalized multifactorial risk assessment in neoadjuvant-treated breast carcinoma

PURPOSE

Due to biological heterogeneity of breast carcinoma, predicting the individual response to neoadjuvant treatment (NAT) is complex. Consequently, there are no comprehensive, generally accepted practices to guide post-treatment follow-up. We present clinical and histopathological criteria to advance the prediction of disease outcome in NA-treated breast cancer.

METHODS

A retrospective consecutive cohort of 257 NA-treated Finnish breast cancer patients with up to 13-year follow-up and the corresponding tissue samples of pre- and post-NAT breast and metastatic specimen were evaluated for prognostic impacts. All relevant clinical and biomarker characteristics potentially correlated with tumor response to NAT, course of disease, or outcome of breast cancer were included in the statistical analyses.

RESULTS

The results highlight the intensified characterization of distinguished prognostic factors and previously overlooked histological features, e.g., mitotic and apoptotic activity. Particularly, decreased PR indicated 3.8-fold (CI 1.9-7.4, p = 0.0001) mortality risk, and a > 10.5-year shorter survival for the majority, > 75% of patients (Q1). Clinically applicable prognostic factors both preceding and following NAT were identified and compiled into heat maps to quantify mortality and recurrence risks. Combinations of risk factors for aggressive disease were exemplified as an interactive tool (bcnatreccalc.utu.fi) to illustrate the spectrum of disease outcomes.

CONCLUSION

The results emphasize the value of comprehensive evaluation of conventional patient and biomarker characteristics, especially concerning re-assessment of biomarkers, risk-adapted surveillance, and personalized treatment strategies. Future personalized NA-treatment strategies might benefit from models combining risk-adapted surveillance data and post-NAT re-assessed biomarkers.

Dynamic ultrasound-based modeling predictive of response to neoadjuvant chemotherapy in patients with early breast cancer

Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment of early breast cancer (EBC). Therefore, this study aims to noninvasively and early predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, to create a nomogram and construct a machine learning model. This retrospective study included 304 EBC patients recruited from multiple centers. All enrollees had completed NACT regimens, and underwent US examinations at baseline and at each NACT cycle. We subsequently determined that percentage reduction of tumor maximum diameter from baseline to third cycle of NACT serves to independent predictor for pCR, enabling creation of a nomogram ([Formula: see text]). Our predictive accuracy further improved ([Formula: see text]) by combining dynamic US data and clinicopathological features in a machine learning model. Such models may offer a means of accurately predicting NACT responses in this setting, helping to individualize patient therapy. Our study may provide additional insights into the US-based response prediction by focusing on the dynamic changes of the tumor in the early and full NACT cycle.

Apoptotic and Molecular Mechanisms of Carthamidin in Breast Cancer Therapy: An Integrated In Vitro and In Silico Study

The current study examines the anticancer properties of the chemical carthamidin in breast cancer through in-vitro and in silico analysis. This study's results demonstrated that carthamidin strongly inhibited the proliferation of MCF 7 cells in vitro, as evidenced by an IC50 value of 128.65 µg/mL at 24 h, determined using the MTT test. Laser confocal microscopy utilizing AO/EB labeling validated apoptotic effects through upregulating pro-apoptotic cell markers. At the same time, the ROS assay demonstrated elevated ROS production in the treated cells. LDH leakage was corroborated by leakage analysis, revealing high LDH levels at 100 µg/mL. The cellular growth parameters were subsequently examined via flow cytometry, showing that the cell cycle was halted in the G0/G1 phase, with 82.9% of the cells residing there. The molecular docking research demonstrated that carthamidin displayed a significant binding affinity with Notch receptors - NOTCH 1-4 and p53, with binding scores ranging from - 5.027 to - 7.402 kcal/mol. The results suggest that carthamidin has therapeutic potential in inducing apoptosis and impairing cancer cells, warranting further investigation in breast cancer treatments.

Establishment and clinical application of a prognostic index for inflammatory status in triple-negative breast cancer patients undergoing neoadjuvant therapy using machine learning

OBJECTIVE

This study aims to establish a new prognostic index using machine learning models to predict the clinical outcomes of triple-negative breast cancer (TNBC) patients receiving neoadjuvant therapy.

METHODS

In this study, we collected data from the electronic medical records system of Harbin Medical University Cancer Hospital to establish a training set of 501 breast cancer patients who received neoadjuvant therapy from January 2017 to December 2021. Additionally, we collected data from Harbin Medical University Affiliated Cancer Hospital, Harbin Medical University Affiliated Second Hospital, and Harbin Medical University Affiliated Sixth Hospital to establish a validation set of 1533 patients during the same period. All patients underwent blood tests, and the following inflammatory and immune indices were calculated for each patient: neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), systemic inflammatory response index (SIRI), and advanced lung cancer inflammation index (ALI). The observed outcomes included Disease-free survival (DFS) and overall survival (OS). Survival analysis was performed using Kaplan‒Meier survival curves, Cox survival analysis, propensity score matching analysis (PSM), and a nomogram to comprehensively investigate the impact of inflammatory status on patient survival.

RESULTS

The training set comprised 501 patients with a mean age of 48.63 (9.41) years, while the validation set comprised 1533 patients with a mean age of 49.01 (9.51) years. The formula for ANLR established through Lasso regression analysis on the training set is: ANLR index = NLR - 0.04 × ALB (g/L). In both the training and validation sets, ANLR was significantly associated with patient DFS and OS (all P < 0.05). Additionally, ANLR was found to be an independent prognostic factor in this study. PSM analysis further confirmed its significant correlation with patient DFS and OS (76 cases vs. 76 cases, χ2 = 2.179, P = 0.001 and χ2 = 2.063, P = 0.002). The nomogram containing ANLR also demonstrated high prognostic value. The C-index for the nomogram in the training set was 0.742 (0.619-0.886) for DFS and 0.758 (0.607-0.821) for OS, while in the validation set, the C-index was 0.733 (0.655-0.791) for DFS and 0.714 (0.634-0.800) for OS.

CONCLUSION

ANLR was associated with the prognosis of TNBC patients receiving neoadjuvant therapy and could identify high-risk postoperative patients.

Does T1c-2N0-1M0 triple negative breast cancer derive a benefit from neoadjuvant chemotherapy?

OBJECTIVES

Although neoadjuvant chemotherapy (NCT) is a standard approach for operable triple negative breast cancer (TNBC), the potential risks brought by it should also be noticed. Is the expanding indication of NCT to T1cN0M0 population appropriate? We conducted an investigation to compare the long-term survival of small tumor TNBC between NCT and adjuvant chemotherapy (ACT).

METHODS

For this propensity-matched analysis, we used data from Surveillance, Epidemiology, and End Results (SEER) database. We enrolled 1183 cases with NCT and 2550 cases with ACT who are AJCC clinical T1c-T2 N0-N1, diagnosed with invasive triple-negative breast cancer, from 2016 to 2017. The propensity score matching was utilized to minimize baseline characteristics bias. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated by the Cox proportional hazard regression model.

RESULTS

Compared with patients receiving ACT, patients with NCT in this study presented a higher proportion of younger age, T2 stage, N1 stage, and underwent more mastectomy. Multivariate analysis in matched patients showed that NCT had no significant survival benefit compared with ACT in T1c-2N0-1M0 TNBC patients. Stratified analyses by T stage and N stage demonstrated NCT mainly presented a survival advantage in patients with N1 stage. Further investigation found that NCT didn't improve BCSS (HR, 0.472; 95% CI 0.135-1.647; P = 0.239) and OS (HR, 0.392; 95% CI 0.147-1.047; P = 0.062) for patients with T1cN0M0 TNBC; however, it was associated with improved OS (HR, 1.951; 95% CI 1.003-3.797; P = 0.049) only for patients with T2N1M0 TNBC.

CONCLUSIONS

In this study, we did not find any profit brought by NCT in the stage I and stage IIa cohorts, but even more unfavorable outcomes appeared in the T1cN0M0 cohort. Therefore, whether the candidates of NCT should be extended to T1cN0M0 still need to be cautious.

Comprehensive review of drug resistance in mammalian cancer stem cells: implications for cancer therapy

Cancer remains a significant global challenge, and despite the numerous strategies developed to advance cancer therapy, an effective cure for metastatic cancer remains elusive. A major hurdle in treatment success is the ability of cancer cells, particularly cancer stem cells (CSCs), to resist therapy. These CSCs possess unique abilities, including self-renewal, differentiation, and repair, which drive tumor progression and chemotherapy resistance. The resilience of CSCs is linked to certain signaling pathways. Tumors with pathway-dependent CSCs often develop genetic resistance, whereas those with pathway-independent CSCs undergo epigenetic changes that affect gene regulation. CSCs can evade cytotoxic drugs, radiation, and apoptosis by increasing drug efflux transporter activity and activating survival mechanisms. Future research should prioritize the identification of new biomarkers and signaling molecules to better understand drug resistance. The use of cutting-edge approaches, such as bioinformatics, genomics, proteomics, and nanotechnology, offers potential solutions to this challenge. Key strategies include developing targeted therapies, employing nanocarriers for precise drug delivery, and focusing on CSC-targeted pathways such as the Wnt, Notch, and Hedgehog pathways. Additionally, investigating multitarget inhibitors, immunotherapy, and nanodrug delivery systems is critical for overcoming drug resistance in cancer cells.

Radiomics of multimodal ultrasound for early prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer

RATIONALE AND OBJECTIVES

To construct and validate a clinical-radiomics model based on radiomics features extracted from two-stage multimodal ultrasound and clinicopathologic information for early predicting pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients treated with NAC.

MATERIALS AND METHODS

Consecutive women with biopsy-proven breast cancer undergoing multimodal US pretreatment and after two cycles of NAC and followed by surgery between January 2014 and November 2023 were retrospectively collected for clinical-radiomics model construction (n = 274) and retrospective test (n = 134). The predictive performance of it was further tested in a subsequent prospective internal test set recruited between January 2024 to July 2024 (n = 76). Finally, a total of 484 patients were enrolled. The clinical-radiomics model predictive performance was compared with radiomics model, clinical model and radiologists' visual assessment by area under the receiver operating characteristic curve (AUC) analysis and DeLong test.

RESULTS

The proposed clinical-radiomics model obtained the AUC values of 0.92 (95%CI: 0.88, 0.94) and 0.85 (95%CI: 0.79, 0.89) in retrospective and prospective test sets, respectively, which were significantly higher than that those of the radiomics model (AUCs: 0.75-0.85), clinical model (AUCs: 0.68-0.72) and radiologists' visual assessments (AUCs:0.59-0.68) (all p < 0.05). In addition, the predictive efficacy of the radiologists was improved under the assistance of the clinical-radiomics model significantly.

CONCLUSION

The clinical-radiomics model developed in this study, which integrated clinicopathologic information and two-stage multimodal ultrasound features, was able to early predict pCR to NAC in breast cancer patients with favorable predictive effectiveness.

Contemporary trends in utilization of metastasectomy in the era of targeted and immunotherapies

BACKGROUND

Metastasectomy is a useful adjunct in the management of metastatic cancer. Widespread adoption of novel targeted and immunotherapies has improved the survival profiles of multiple malignancies, which has potentially altered the role of metastasectomy. This study aimed to characterize trends in metastasectomy across five primary cancers eligible for these therapies.

METHODS

The National Inpatient Sample was used to identify patients who underwent metastasectomy in the United States (2016-2021). Patients with procedure codes for resection of the lung, liver, adrenal gland, brain, or small bowel and concurrent diagnosis codes for secondary malignant neoplasm of that site were included. Subjects were subcategorized by primary malignancy: colorectal cancer, lung cancer, breast cancer, melanoma, or renal cancer. Sample weights were used to produce national estimates, which were incidence adjusted by primary malignancy. Trends in utilization were calculated with average annual percent change (AAPC) and linear regression coefficients.

RESULTS

Colorectal cancer was the most frequent indication for metastasectomy (n = 57,644 cases), followed by lung cancer (n = 55,090 cases), breast cancer (n = 12,616 cases), renal cancer (n = 8427 cases), and melanoma (n = 5658 cases). Utilization of metastasectomy increased over the study period for breast cancer (AAPC, +10.6%; p = .013) and melanoma (AAPC, +8.3%; p = .040) but did not change for lung cancer (AAPC, -1.6%; p = .26), colorectal cancer (AAPC, +0.3%; p = .83), or renal cancer (AAPC, +2.3%; p = .36).

CONCLUSIONS

Between 2016 and 2021, utilization of metastasectomy increased significantly for melanoma and breast cancer. The role of metastasectomy will likely continue to develop as new treatment protocols improve survival profiles for patients with metastatic disease.

Factors associated with malignant biopsy results for newly detected lesions within one year after breast cancer surgery

RATIONALE AND OBJECTIVES

This study aimed to identify the factors associated with malignant biopsy results for new lesions within one year after breast cancer surgery.

MATERIALS AND METHODS

This retrospective study included 192 lesions from 186 patients who underwent biopsy for newly developed breast lesions within one year of breast cancer surgery. All patients underwent breast ultrasound (US) at 6 months and breast US with mammography one year after surgery. We analyzed the biopsy results, patient age, characteristics of previous cancers (histologic type, stage, molecular subtype, histologic and nuclear grade, Ki-67 index, extensive intraductal component, lymphovascular invasion (LVI)), history of neoadjuvant chemotherapy (NAC), adjuvant therapy, and characteristics of biopsied lesions (location, mode of detection, imaging features, and Breast Imaging Reporting and Data System category). Multivariate logistic regression was performed to predict malignant results after a biopsy of the new lesion in the early postoperative period.

RESULTS

The mean patient age was 49.0 (range, 28-82) years. During follow-up, 137 lesions developed in the ipsilateral remnant breast or mastectomy bed, and 55 lesions developed in the contralateral breast. In total, 37 (19.3%) of the biopsied lesions were malignant, and the following conditions were associated with malignant results in the newly detected lesions: irregularly shaped hypoechoic mass with increased vascularity, presence of previous LVI, history of NAC, and no history of adjuvant radiotherapy or hormone therapy in the indicated patients.

CONCLUSION

Active biopsy may be warranted for new lesions with suspicious imaging findings in the breast or operation bed of patients with LVI, a history of NAC, and no history of adjuvant radiotherapy or hormone therapy, even within one year of breast cancer surgery.

ASO Author Reflections: Breast-Conserving Surgery After Neoadjuvant Systemic Therapy for Early-Stage Breast Cancer: Quantitative Biomarkers and Disparities in the Precision-Medicine Era

In this era of precision medicine, incorporating quantitative measures of estrogen receptor (ER)/progesterone receptor (PR)/Ki-67 expressions and genomic assays could more precisely identify neoadjuvant systemic therapy with the highest likelihood of response and tumor downstaging. In our recent study, we quantified the likelihood of achieving breast-conserving surgery (BCS vs. mastectomy) after neoadjuvant chemotherapy or endocrine therapy as a function of demographics, quantitative ER/PR/Ki-67 expressions, 21-gene recurrence scores, or 70-gene risk scores in early-stage, hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative breast cancer. Using the 2010-2020 National Cancer Database, we found that the BCS rate after neoadjuvant chemotherapy was higher among patients with high 21-gene recurrence scores, lower ER/PR expression, or higher Ki-67 expression. Most patients who received neoadjuvant endocrine therapy underwent BCS, which was mostly dependent on ER expression. Asian women were less likely than white women to undergo BCS after neoadjuvant treatments. Lack of health insurance was associated with lower odds of BCS in both neoadjuvant settings. Although our study provides insight into the associations of BCS with quantitative biomarkers at a single time point, several questions remain unanswered. With the evolving landscape of neoadjuvant therapies in development for HR-positive/HER2-negative breast cancer, ongoing work using quantitative biomarkers and genomic assay scores is needed to select the right neoadjuvant systemic therapy for the right patient. Given the increasing amount of data available at the time of breast cancer diagnosis, novel computational approaches are needed to integrate patient demographic and tumor-specific factors to predict the optimal treatment strategy and likelihood of BCS.

Colorectal Leiomyosarcoma: Demographics Patterns, Treatment Characteristics, and Survival Analysis in the U.S. Population

BACKGROUND

Colorectal leiomyosarcoma (CR-LMS) is a rare neoplasm arising from smooth muscle cells. It accounts for less than 0.1% of all colorectal malignancies. In this population-based study, we aim to understand the demographics, treatment characteristics, and pathologic factors associated with survival in CR-LMS.

METHODS

Data from the SEER Program (2000-2018) were analyzed using SEER*Stat and SPSS. Statistical methods included descriptive analysis, Kaplan-Meier survival curves, log-rank tests, and Cox proportional hazards regression to assess the impact of various factors on disease-specific and overall survival.

RESULTS

A total of 191 cases of CR-LMS were identified. Most patients were 60-69 years of age (median: 64 years) and Caucasian (78%). There was nearly the same distribution in sex (M:F ratio; 1:1.2). The overall 5-year observed survival was 50.3% (95% C.I., 46.3-54.2). The 5-year disease-specific survival (DSS) was 66.1% (95% C.I., 62.0-70.1). The 5-year overall survival after resection was 60.8% (95% C.I., 56.3-65.3). Multivariable analysis identified grades III and IV (p = 0.028) as negative predictors of overall survival. Regional spread and distant stage are negative predictors of overall survival (p < 0.01).

CONCLUSION

Our data reveals that colorectal leiomyosarcoma (CR-LMS) often presents in patients around 64 years old with advanced stages and poor differentiation. Key adverse prognostic factors include older age, high tumor grade, large tumor size, and distant metastases, with surgical resection showing the best survival outcomes. To improve outcomes, further research and consolidation of data are essential for developing targeted therapies and comprehensive guidelines.

Dehydrocurvularin-loaded mPEG-PLGA nanoparticles for targeted breast cancer drug delivery: preparation, characterization, in vitro, and in vivo evaluation

Dehydrocurvularin (DCV) is a promising lead compound for anti-cancer therapy. Unfortunately, the development of DCV-based drugs has been hampered by its poor solubility and bioavailability. Herein, we prepared a DCV-loaded mPEG-PLGA nanoparticles (DCV-NPs) with improved drug properties and therapeutic efficacy. The spherical and discrete particles of DCV-NPs had a uniform diameter of 101.8 ± 0.45 nm and negative zeta potential of -22.5 ± 1.12 mV (pH = 7.4), and its entrapment efficiency (EE) and drug loading (DL) were ∼53.28 ± 1.12 and 10.23 ± 0.30%, respectively. In vitro the release of DCV-NPs lasted for more than 120 h in a sustained-release pattern, its antiproliferation efficacy towards breast cancer cell lines (MCF-7, MDA-MB-231, and 4T1) was better than that of starting drug DCV, and it could be efficiently and rapidly internalised by breast cancer cells. In vivo DCV-NPs were gradually accumulated in tumour areas of mice and significantly suppressed tumour growth. In summary, loading water-insoluble DCV onto nanoparticles has the potential to be an effective agent for breast cancer therapy with injectable property and tumour targeting capacity.

Machine Learning to Predict the Individual Risk of Treatment-Relevant Toxicity for Patients With Breast Cancer Undergoing Neoadjuvant Systemic Treatment

PURPOSE

Toxicity to systemic cancer treatment represents a major anxiety for patients and a challenge to treatment plans. We aimed to develop machine learning algorithms for the upfront prediction of an individual's risk of experiencing treatment-relevant toxicity during the course of treatment.

METHODS

Clinical records were retrieved from a single-center, consecutive cohort of patients who underwent neoadjuvant treatment for early breast cancer. We developed and validated machine learning algorithms to predict grade 3 or 4 toxicity (anemia, neutropenia, deviation of liver enzymes, nephrotoxicity, thrombopenia, electrolyte disturbance, or neuropathy). We used 10-fold cross-validation to develop two algorithms (logistic regression with elastic net penalty [GLM] and support vector machines [SVMs]). Algorithm predictions were compared with documented toxicity events and diagnostic performance was evaluated via area under the curve (AUROC).

RESULTS

A total of 590 patients were identified, 432 in the development set and 158 in the validation set. The median age was 51 years, and 55.8% (329 of 590) experienced grade 3 or 4 toxicity. The performance improved significantly when adding referenced treatment information (referenced regimen, referenced summation dose intensity product) in addition to patient and tumor variables: GLM AUROC 0.59 versus 0.75, P = .02; SVM AUROC 0.64 versus 0.75, P = .01.

CONCLUSION

The individual risk of treatment-relevant toxicity can be predicted using machine learning algorithms. We demonstrate a promising way to improve efficacy and facilitate proactive toxicity management of systemic cancer treatment.

Knockdown of PAIP1 Inhibits Breast Cancer Cell Proliferation by Regulating Cyclin E2 mRNA Stability

Polyadenylate-binding protein-interacting protein 1 (PAIP1) is a protein that modulates translation initiation in eukaryotic cells. Studies have shown that PAIP1 was overexpressed in various type of cancers, and drives cancer progression by promoting cancer cell proliferation, invasion, and migration. In our previous study, we identified that PAIP1 was overexpressed in breast cancer, and the expression was correlated with poor prognosis. However, the biological function of PAIP1 in breast cancer has not been clearly understood. In this study, we constructed PAIP1 specifically silenced breast cancer cells. Then, cell proliferation, cell cycle distribution, and apoptosis were detected in PAIP1 knockdown cells. RNA-seq analysis was performed to predict the downstream target of PAIP1, and the molecular mechanism was explored. As a results, we found that knockdown of PAIP1 repressed cell proliferation, induced cell cycle arrest, and triggers apoptosis. Xenograft mouse model showed that knockdown of PAIP1 inhibits cell growth in vivo. RNA-seq predicted that CCNE2 mRNA was one of the downstream targets of PAIP1. In addition, we identified that knockdown of PAIP1-inhibited cell proliferation through modulating cyclin E2 expression. Mechanically, knockdown of PAIP1 reduces the expression of cyclin E2 by regulating the mRNA stability of cyclin E2. Moreover, in breast cancer tissues, we found that the expression of PAIP1 was positively correlated with cyclin E2. Taken together, our findings establish the role and mechanism of PAIP1 in breast cancer progression, indicating that PAIP1 would be a new therapeutic target for breast cancer treatment.

Multifaceted role of phytoconstituents based nano drug delivery systems in combating TNBC: A paradigm shift from chemical to natural

Triple negative breast cancer is considered to be a malignancy of grave concern with limited routes of treatment due to the absence of specific breast cancer markers and ambiguity of other potential drug targets. Poor prognosis and inadequate survival rates have prompted further research into the understanding of the molecular pathophysiology and targeting of the disease. To overcome the recurrence and resistance mechanisms of the TNBC cells, various approaches have been devised, and are being continuously evaluated to enhance their efficacy and safety. Chemo-Adjuvant therapy is one such treatment modality being employed to improve the efficiency of standard chemotherapy. Combining chemo-adjuvant therapy with other upcoming approaches of cancer therapeutics such as phytoconstituents and nanotechnology has yielded promising results in the direction of improving the prognosis of TNBC. Numerous nanoformulations have been proven to substantially enhance the specificity and cellular uptake of drugs by cancer cells, thus reducing the possibility of unintended systemic side effects within cancer patients. While phytoconstituents offer a wide variety of beneficial active constituents useful in cancer therapeutics, most favorable outcomes have been observed within the scope of polyphenols, isoquinoline alkaloids and isothiocyanates. With an enhanced understanding of the molecular mechanisms of TNBC and the advent of newer targeting technologies and novel phytochemicals of medicinal importance, a new era of cancer theranostic treatments can be explored. This review hopes to instantiate the current body of research regarding the role of certain phytoconstituents and their potential nanoformulations in targeting specific TNBC pathways for treatment and diagnostic purposes.

Nodal Response and Survival After Neoadjuvant Endocrine Therapy in Hormone Receptor-Positive Breast Cancer: 20-Year Experience from a Single Institution

INTRODUCTION

Axillary response to neoadjuvant endocrine therapy (NET) for the treatment of hormone receptor-positive breast cancer (HR+ BC) is not well-described. This study was designed to characterize nodal response after NET.

METHODS

Patients receiving NET followed by curative intent surgery at a comprehensive cancer center from 1998 to 2022 in a prospectively collected registry were included. Patients with distant metastasis were excluded. Primary outcome was nodal pathologic complete response (pCR). Downstaging was defined as post-NET decrease in category.

RESULTS

We included 123 patients; the majority were cT2 (n = 59) or cT3 (n = 35), and cN0 (n = 81). Median age was 70.0 years (interquartile range 62.1-76.0). Forty-two patients (34.1%) were clinically node-positive. After NET, 73 (59.8%) underwent breast-conserving surgery. All patients underwent sentinel lymph node biopsy, and 12 (9.8%) underwent completion axillary lymph node dissection. In-breast downstaging was achieved in 51 (41.5%) patients, 1 (0.8%) had breast pCR, and 14 (11.4%) had breast upstaging. Axillary downstaging was achieved in 10 (23.8%), 6 patients (14.3%) had nodal pCR, and 14 (33.3%) had axillary upstaging. At 10-year follow-up, local recurrence was 1% and distant recurrence was 14%, while disease-free survival was 82%. After adjusting for demographic and clinical factors, age was the only characteristic associated with mortality (hazard ratio 1.07, 95% confidence interval 1.01-1.13).

CONCLUSIONS

In HR+ BC treated with NET, long-term disease-free survival is good, although nodal pCR is uncommon for cN+ patients. Future studies are needed to elucidate optimal neoadjuvant systemic therapy and to delineate oncologically safe strategies to deescalate axillary management for residual microscopic disease.

Quantitative Biomarkers, Genomic Assays, and Demographics Associated with Breast-Conserving Surgery Following Neoadjuvant Therapy in Early-Stage, Hormone Receptor-Positive, HER-Negative Breast Cancer

BACKGROUND

Given increased neoadjuvant therapy use in early-stage, hormone receptor (HR)-positive/HER2-negative breast cancer, we sought to quantify likelihood of breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NACT) or endocrine therapy (NET) as a function of ER%/PR%/Ki-67%, 21-gene recurrence scores (RS), or 70-gene risk groups.

METHODS

We analyzed the 2010-2020 National Cancer Database. Surgery was categorized as "mastectomy/BCS." Logistic regression was performed. Adjusted odds ratios (AOR) were per 10-unit increase in ER%/PR%/Ki-67%.

RESULTS

Overall, 42.3% underwent BCS after NACT, whereas 64.0% did after NET. Increasing ER% (AOR = 0.96, 95% confidence interval [CI] 0.94-0.97) or PR% (AOR=0.98, 95% CI 0.96-0.99) was associated with lower odds of BCS after NACT. Increasing Ki-67% was associated with greater odds of BCS (AOR = 1.07, 95% CI 1.04-1.10). Breast-conserving surgery rates increased by ~20 percentage points, with Ki-67% ≥15 or RS >20. Patients with a low (43.0%, AOR = 0.50, 95% CI 0.29-0.88) or intermediate (46.4%, AOR = 0.58, 95% CI 0.41-0.81) RS were less likely than patients with a high RS (65.0%) to undergo BCS after NACT. Increasing ER% was associated with higher odds of BCS after NET (AOR = 1.09, 95% CI 1.01-1.17). Breast-conserving surgery rates increased by ~20 percentage points between ER <50% and >80%. In both cohorts, the odds of BCS were similar between 70-gene low-risk and high-risk groups. Asian or uninsured patients had lower odds of BCS.

CONCLUSIONS

Neoadjuvant chemotherapy is unlikely to downstage tumors with a low-intermediate RS, higher ER%/PR%, or lower Ki-67%. Breast-conserving surgery after NET was most dependent on ER%. Findings could facilitate treatment decision-making based on tumor biology and racial/socioeconomic disparities and improve patient counseling on the likelihood of successful BCS.

Chemotherapy Combined With Endocrine Therapy: Old Wine in a New Bottle?

Both chemotherapy (CT) and endocrine therapy (ET) play important roles in the systemic treatment of breast cancer (BC). However, previous studies have shown an antagonistic effect when CT and ET are administered simultaneously. Therefore, sequential administration is more effective than combined administration. The current guidelines and consensus recommend a sequential schedule of CT and ET for patients with hormone receptor-positive (HR+) BC. However, with the continuous introduction of new endocrine drugs, the question of whether the simultaneous administration of CT and ET is superior to sequential therapy has surfaced again as a hot topic of clinical concern. Recent studies have shown that the combination of certain chemotherapeutic agents with endocrine drugs has a synergistic effect. This review aims to summarize the new advances achieved in recent years on the old topic of CT combined with ET in the treatment of BC.

The Value of Whole-Volume Radiomics Machine Learning Model Based on Multiparametric MRI in Predicting Triple-Negative Breast Cancer

OBJECTIVE

This study aimed to investigate the value of radiomics analysis in the precise diagnosis of triple-negative breast cancer (TNBC) based on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coefficient (ADC) maps.

METHODS

This retrospective study included 326 patients with pathologically proven breast cancer (TNBC: 129, non-TNBC: 197). The lesions were segmented using the ITK-SNAP software, and whole-volume radiomics features were extracted using a radiomics platform. Radiomics features were obtained from DCE-MRI and ADC maps. The least absolute shrinkage and selection operator regression method was employed for feature selection. Three prediction models were constructed using a support vector machine classifier: Model A (based on the selected features of the ADC maps), Model B (based on the selected features of DCE-MRI), and Model C (based on the selected features of both combined). Receiver operating characteristic curves were used to evaluate the diagnostic performance of the conventional MR image model and the 3 radiomics models in predicting TNBC.

RESULTS

In the training dataset, the AUCs for the conventional MR image model and the 3 radiomics models were 0.749, 0.801, 0.847, and 0.896. The AUCs for the conventional MR image model and 3 radiomics models in the validation dataset were 0.693, 0.742, 0.793, and 0.876, respectively.

CONCLUSIONS

Radiomics based on the combination of whole volume DCE-MRI and ADC maps is a promising tool for distinguishing between TNBC and non-TNBC.

Assessment of quality of life, pain, depression, and body-image in breast cancer patients in neoadjuvant therapy

Breast cancer is the leading cancer type among women globally, and its chemotherapy often results in multiple side effects, compromising the patient's quality of life. Our study aimed to analyze the impact of neoadjuvant chemotherapy on the quality of life in Brazilian women with breast cancer within the public health system. This research was a one-year, observational, longitudinal study, conducted at a charitable health facility, examining the effect of neoadjuvant chemotherapy on these women's quality of life. Sociodemographic and clinical data were extracted from medical records. Quality of life parameters were gauged using Portuguese-validated questionnaires: EORTC.QLQ - C30 version 3.0, EORTC.BR-23, Body Image Scale (BIS), BPI-SF pain scale, and Beck Depression Inventory (BDI). These tools were utilized at three intervals: before the start of systemic treatment, after three months (before initiating paclitaxel), and upon concluding neoadjuvant therapy. Qualitative variables were tested for normality using the Kolmogorov-Smirnov test. As the continuous variables referring to the questionnaires did not show normal distribution, non-parametric tests were used: Friedman tests for paired pairs, and Wilcoxon and Mann-Whitney tests for multiple comparisons. In all tests, the significance level adopted was 5%. The software used for the analysis was SPSS. Our findings revealed a decline in quality of life, observing deterioration in the role, social, and cognitive functioning domains. Additionally, symptoms like fatigue, hyporexia, constipation, and diarrhea became more pronounced during the treatment. The presence of minimal depressive symptoms, associated with systemic therapy side effects also contributed to this worsening. Notably, there were no improvements in any quality of life-related parameters, and no discernible differences were observed in pain levels or body image across the evaluated periods.

Optimizing Neoadjuvant Treatment Response Prediction for Triple-Negative Breast Cancer Using Clinical Trial Data and Deep Auxiliary Learning

Motivation

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options and poor prognosis. Developing predictive models for TNBC treatment responses is crucial but challenging due to data scarcity and the reliance on cell line data, which limits clinical translational value. Leveraging omics data from clinical trials, particularly through auxiliary learning, offers a potential solution to enhance predictive accuracy and reduce data requirements.

Results

In this study, we propose a new approach utilizing deep auxiliary task reweighting learning methods to automatically reweight auxiliary tasks, thereby optimizing the performance of the primary task of predicting TNBC treatment responses. We benchmark various auxiliary learning methods, including ARML, AdaLoss, GradNorm, and OL AUX, against traditional supervised machine learning algorithms and single-task learning baselines. Our results characterize the performance of auxiliary learning across various contexts, including utilizing parallel treatment arms within a multi-arm clinical trial, leveraging treatment arms from different clinical trials, and integrating multiple arms with the same treatment regimens across separate clinical trials. The last scenario also provides an opportunity for validating prediction models on an independent dataset, demonstrating the superior performance of the auxiliary learning models in predicting pathological complete response (pCR) in TNBC patients treated with standardized combinational chemotherapy with Taxane, Anthracycline, and Cyclophosphamide (TAC).

Availability and Implementation

Source code and additional resources can be accessed at https://github.com/moonchangin/DeepAux TxPred TNBC.

Systemic chemotherapy improves outcome of hepatocellular carcinoma patients treated with transarterial chemoembolization

BACKGROUND

Transarterial chemoembolization (TACE) based neoadjuvant therapy was proven effective in hepatocellular carcinoma (HCC). Recently, tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) also showed promise in HCC treatment. However, the prognostic benefits associated with these treatments remain uncertain. This study aimed to explore the relationship between pathologic response and prognostic features in HCC patients who received neoadjuvant therapy.

METHODS

HCC patients who received TACE either with or without TKIs/ICIs as neoadjuvant therapy before liver resection were retrospectively collected from the First Affiliated Hospital, Zhejiang University School of Medicine in China. Pathologic response was determined by calculating the proportion of non-viable area within the tumor. Major pathologic response (MPR) was defined as the presence of non-viable tumor cells reaching a minimum of 90 %. Complete pathologic response (CPR) was characterized by the absence of viable cells observed in the tumor.

RESULTS

A total of 481 patients meeting the inclusion criteria were enrolled, with 76 patients (15.8 %) achieving CPR and 179 (37.2 %) reaching MPR. The median recurrence-free survival (mRFS) in the CPR + MPR group was significantly higher than the non-MPR group (31.3 vs. 25.1 months). The difference in 3-year overall survival (OS) rate was not significant (90.2 % vs. 87.6 %). Multivariate Cox regression analysis identified failure to achieve MPR (hazard ratio = 1.548, 95 % confidence interval: 1.122-2.134; P = 0.008), HBsAg positivity (HR = 1.818, 95 % CI: 1.062-3.115, P = 0.030), multiple lesions (HR = 2.278, 95 % CI: 1.621-3.195, P < 0.001), and baseline tumor size > 5 cm (HR = 1.712, 95 % CI: 1.031-2.849, P = 0.038) were independent risk factors for RFS. Subgroup analysis showed that 67 of 93 (72.0 %) patients who received the combination of TACE, TKIs, and ICIs achieved MPR + CPR.

CONCLUSIONS

In individuals who received TACE-based neoadjuvant therapy for HCC, failure to achieve MPR emerges as an independent risk factor for RFS. Notably, the combination of TACE, TKIs, and ICIs demonstrated the highest rate of MPR.

Assessing the Prognostic Value of Cytoplasmic and Stromal Caveolin-1 in Early Triple-Negative Breast Cancer Undergoing Neoadjuvant Chemotherapy

Triple-negative breast cancer (TNBC) is a highly aggressive subtype with limited therapeutic options, leading to higher relapse rates and mortality. Identifying prognostic biomarkers like caveolin-1 (CAV1) is crucial for personalized treatment. CAV1 influences tumor progression and chemotherapy response, particularly through its interaction with the tumor microenvironment (TME) and cancer metabolism. Understanding the prognostic value of CAV1 in different cellular compartments is essential for its clinical application in TNBC. In the methods section CAV1 gene expression in TNBC was evaluated using in silico analysis, followed by the immunohistochemical staining of tumor cytoplasm (cCAV1) and stromal cells (sCAV1) in 58 early-stage TNBC patients. Statistical analyses were performed to correlate CAV1 expression with clinicopathological features and survival. In the results section, in silico analysis revealed higher CAV1 expression in TNBC, correlating with shorter overall survival. In the patient samples, cCAV1 was observed in 10.3% of cases, and was associated with larger tumors, higher grades, and poorer prognoses. sCAV1 was detected in 42% of cases, associated with less proliferative and less aggressive tumors, but did not significantly impact prognoses. In conclusion, cCAV1 expression is a significant prognostic marker in early-stage TNBC, highlighting the importance of assessing CAV1 in different cellular compartments. Further research is needed to explore the mechanisms and clinical implications of cCAV1.

Association between mammographic breast density and outcome in patients with unilateral invasive breast cancer receiving neoadjuvant chemotherapy

PURPOSE

To analyze the relationship between mammographic breast density and tumor response and outcome at follow-up, in terms of overall survival (OS) and disease-free survival (DFS), in patients with unilateral invasive breast cancer receiving neoadjuvant chemotherapy (NACT).

METHODS

A total of 228 women (mean age, 47.6 years ± 10 [SD]; range: 24-74 years) with invasive breast cancer who underwent NACT were included in this observational retrospective study. Clinical, radiological and histopatological data were retrieved. Categorization of breast density was performed by two radiologists in consensus on mammography acquired at the time of diagnosis according to BI-RADS categories. Association between density categories and tumor response was analyzed in the overall population and in subgroups defined by menopausal status, tumor phenotype and stage at diagnosis. Kaplan-Meier (KM) curves were used to estimate the OS and DFS probabilities. Subgroup analyses based on menopausal status and tumor phenotype were performed.

RESULTS

A total of 30 patients (13.2%) achieved pathological complete response (pCR). No association between density categories and pCR was found (P = 0.973), even at subgroups analysis. The median follow-up time was 92 months. Patients with dense breast showed the longest DFS (P = 0.0094), results confirmed in premenopausal patients (P = 0.0024) and in triple negative breast cancers (P = 0.0292). Density category did not show a statistically significant association with OS.

CONCLUSION

Breast cancer patients receiving NACT with extremely dense breasts showed better DFS. No evidence of breast density as a predictive marker for complete pathological response or as a prognostic factor in terms of OS was found.

Axillary Surgery for Patients With Residual Isolated Tumor Cells (ypN0i+) After Neoadjuvant Systemic Therapy for Early Breast Cancer

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology, to patients seen in their own clinical practice.

Harnessing curcumin and nanotechnology for enhanced treatment of breast cancer bone metastasis

Breast cancer (BC) bone metastasis poses a significant clinical challenge due to its impact on patient prognosis and quality of life. Curcumin (CUR), a natural polyphenol compound found in turmeric, has shown potential in cancer therapy due to its anti-inflammatory, antioxidant, and anticancer properties. However, its metabolic instability and hydrophobicity have hindered its clinical applications, leading to a short plasma half-life, poor absorption, and low bioavailability. To enhance the drug-like properties of CUR, nanotechnology-based delivery strategies have been employed, utilizing polymeric, lipidic, and inorganic nanoparticles (NPs). These approaches have effectively overcome CUR's inherent limitations by enhancing its stability and cellular bioavailability both in vitro and in vivo. Moreover, targeting molecules with high selectivity towards bone metastasized breast cancer cells can be used for site specific delivery of curcumin. Alendronate (ALN), a bone-seeking bisphosphonate, is one such moiety with high selectivity towards bone and thus can be effectively used for targeted delivery of curcumin loaded nanocarriers. This review will detail the process of bone metastasis in BC, elucidate the mechanism of action of CUR, and assess the efficacy of nanotechnology-based strategies for CUR delivery. Specifically, it will focus on how these strategies enhance CUR's stability and improve targeted delivery approaches in the treatment of BC bone metastasis.

Long-term trends in the burden of breast cancer in China over three decades: a joinpoint regression and age-period-cohort analysis based on Global Burden of Disease 2021

We analyzed the trends in breast cancer (BC) morbidity, prevalence, and mortality among Chinese residents from 1990 to 2021. We then used joinpoint regression to further assess BC morbidity and mortality. We screened the morbidity, mortality, and prevalence of BC in Chinese residents (1990-2021) from the Global Burden of Disease. We used age-period-cohort (APC) modeling to assess the effects of age, period, and cohort on BC morbidity and mortality separately. We also used the joinpoint model to characterize trends in BC morbidity and mortality in China. From 1990 to 2021, age-standardized rates of morbidity have risen significantly, whereas mortality has declined. We discovered that the risk of morbidity and death rose with age by using the APC model. We also found that mortality and morbidity roughly continued to increase over time, and finally, we found that the later the birth cohort, the lower the mortality and the higher the morbidity. From 1990 to 2021, the burden of BC disease in China will continue to rise, and the situation of BC prevention and control will remain severe. Therefore, regular imaging and palpation examinations should be performed in the regular population over 40 years of age. When treating patients with BC, healthcare workers should develop individualized treatment plans to further reduce mortality.

Chronic Aromatase Inhibition Attenuates Synaptic Plasticity in Ovariectomized Mice

Brain-derived estrogen (17β-estradiol, E2) is a neuromodulator that plays important roles in neural plasticity and network excitability. Chronic inhibition of estrogen synthesis is used in adjuvant breast cancer therapy for estrogen receptor-positive tumors and may have been associated with cognitive and affective side effects. Here, we have developed a model of adjuvant therapy in female ovariectomized mice in which the E2 biosynthetic enzyme aromatase is inhibited by letrozole (1 mg/kg/day, i.p., for up to 3 weeks), Using two-photon longitudinal in vivo imaging in Thy1-GFP-M mice, we found that spine density in the apical dendrites of neocortical layer 5 pyramidal cells was unaffected by letrozole treatment but spine turnover was reduced. LTP in layer 4 to layer 2/3 synapses in the somatosensory cortex was also reduced in slices from letrozole-treated mice, showing deficits in structural and functional plasticity resulting from aromatase inhibition. Ovariectomized mice performed worse than intact control mice in the novel object recognition test but, surprisingly, letrozole treatment rescued this deficit.

Correlation of preoperative sonographic staging and postoperative histopathologic staging in patients with invasive breast cancer

PURPOSE

To assess the accuracy of preoperative sonographic staging in patients with primary invasive breast cancer.

METHODS

We retrospectively analyzed a prospectively kept service database of patients with newly diagnosed, unifocal, cT1-3, invasive breast cancer. All patients were diagnosed at a single center institution between January 2013 and December 2021. Clinical T stage was assessed preoperatively by ultrasound and correlated with the definite postoperative pathologic T stage. Demographics, clinical and pathological characteristics were collected. Factors influencing accuracy, over- and underdiagnosis of sonographic staging were analyzed with multivariable regression analysis.

RESULTS

A total of 2478 patients were included in the analysis. Median patients' age was 65 years. 1577 patients (63.6%) had clinical T1 stage, 864 (34.9%) T2 and 37 (1.5%) T3 stage. The overall accuracy of sonography and histology was 76.5% (n = 1896), overestimation was observed in 9.1% (n = 225) of all cases, while underestimation occurred in 14.4% (n = 357) of all cases. Accuracy increased when clinical tumor stage cT was higher (OR 1.23; 95% CI 1.10-1.38, p ≤ 0.001). The highest accuracy was seen for patients with T2 stage (82.8%). The accuracy was lower in Luminal B tumors compared to Luminal A tumors (OR 0.71; 95% CI 0.59-0.87, p ≤ 0.001). We could not find any association between sonographic accuracy in HER2 positive patients, and demographic characteristics, or tumor-related factors.

CONCLUSION

Our unicentric study showed a high accuracy of sonography in predicting T stage, especially for tumors with clinical T2 stage. Tumor stage and biological tumor factors do affect the accuracy of sonographic staging.

Effectiveness and safety of neoadjuvant therapy in triple-negative breast cancer in a real-world population

OBJECTIVE

Triple-negative breast cancer is a subtype of aggressive breast cancer. Our aim is to evaluate the effectiveness and safety of neoadjuvant treatment in early-stage triple-negative breast cancer and to identify predictors of pathological complete response.

METHODS

This is a single-center, retrospective study involving 79 patients with triple-negative breast cancer who initiated neoadjuvant treatment between January 2017 and October 2022. Descriptive analyses were performed as appropriate. Statistical analysis utilized bivariate logistic regression to explore the presence of factors related to pathological complete response, and the Kaplan-Meier method was employed for survival analysis.

RESULTS

In the overall population, 27 patients (n=78; 34.6%) achieved pathological complete response in the breast and axillary lymph nodes, and 31 (n=73; 42.5%) achieved a grade 5 pathological complete response in the breast, according to the Miller and Payne classification. The addition of platinum to standard therapy improved both breast and axillary lymph node pathological complete response rates. Age less than 40 years was identified as a predictor of pathological complete response in our study population through bivariate analysis, while Ki67 levels lower than 70% were associated with a lower pathological complete response rate. Adverse events were reported in 72 patients (91.1%), with grade 3-5 adverse events observed in 33 (41.8%). There was a particularly notable increase in gastrointestinal and hematological adverse events when platinum was added.

CONCLUSIONS

In this population, we observed moderate rates of pathological complete response with acceptable chemotherapy tolerance. Platinum-based chemotherapy appears to enhance the likelihood of achieving pathological complete response, albeit with a less favorable safety profile. Therefore, evaluating the benefit-risk balance is crucial when selecting the optimal chemotherapy regimen for individual patients.

Deep learning Radiomics Based on Two-Dimensional Ultrasound for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer

We investigate the predictive value of a comprehensive model based on preoperative ultrasound radiomics, deep learning, and clinical features for pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for the breast cancer. We enrolled 155 patients with pathologically confirmed breast cancer who underwent NAC. The patients were randomly divided into the training set and the validation set in the ratio of 7:3. The deep learning and radiomics features of pre-treatment ultrasound images were extracted, and the random forest recursive elimination algorithm and the least absolute shrinkage and selection operator were used for feature screening and DL-Score and Rad-Score construction. According to multifactorial logistic regression, independent clinical predictors, DL-Score, and Rad-Score were selected to construct the comprehensive prediction model DLRC. The performance of the model was evaluated in terms of its predictive effect, and clinical practicability. Compared to the clinical, radiomics (Rad-Score), and deep learning (DL-Score) models, the DLRC accurately predicted the pCR status, with an area under the curve (AUC) of 0.937 (95%CI: 0.895-0.970) in the training set and 0.914 (95%CI: 0.838-0.973) in the validation set. Moreover, decision curve analysis confirmed that the DLRC had the highest clinical value among all models. The comprehensive model DLRC based on ultrasound radiomics, deep learning, and clinical features can effectively and accurately predict the pCR status of breast cancer after NAC, which is conducive to assisting clinical personalized diagnosis and treatment plan.

The Role of the NOLUS Score in Predicting pCR and iDFS in HR-positive HER2-negative Early Breast Cancer Patients who Received Neoadjuvant Chemotherapy

Background/Aim

Breast cancer remains a significant health challenge, with neoadjuvant chemotherapy (NACT) improving clinical outcomes in certain subtypes. However, the role of NACT in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer is unclear due to various outcomes and generally low rates of pathologic complete response (pCR). This study introduces the Non-Luminal Disease Score (NOLUS) as a potential predictive tool for assessing the response to NACT in these cases.

Patients and Methods

We retrospectively assessed patients diagnosed with locally advanced HR+/HER2- breast cancer who received NACT at our institution from 2009 to 2023. The study explored the association between NOLUS and pCR rates. NOLUS was calculated as positive or negative based on the percentage of estrogen receptor, progesterone receptor, and Ki-67 in tumor cells. We also investigated the correlation between pCR and invasive disease-free survival (iDFS), and examined NOLUS positivity across different age groups.

Results

A total of 149 patients met the inclusion criteria. NOLUS-positive patients exhibited a significantly higher pCR rate of 33.33% compared to 10.4% in NOLUS-negative patients (p=0.0031). With a median follow-up of 2.47 years, NOLUS-positive patients who achieved pCR had a 100% iDFS rate, mirroring the pCR versus residual disease patterns seen in triple-negative patients. NOLUS positivity was observed in 20.43% of patients aged 22-50, compared to 8.93% in those over 50, though this difference was not statistically significant.

Conclusion

NOLUS exhibits potential in predicting pCR in HR+/HER2- breast cancer, serving as a cost-effective substitute for genomic tests.

Chaperonin-containing TCP1 subunit 6A inhibition via TRIM21-mediated K48-linked ubiquitination suppresses triple-negative breast cancer progression through the AKT signalling pathway

BACKGROUND

Triple-negative breast cancer (TNBC) is distinguished by a significant likelihood of distant recurrence and an unfavourable prognosis. However, the underlying molecules and mechanisms have not been fully elucidated.

METHODS

We investigated the expression profile and clinical relevance of chaperonin-containing TCP1 subunit 6A (CCT6A) in TNBC. We performed cell function assays on TNBC cells with CCT6A knockdown or overexpression. To further explore the mechanism of action of CCT6A, RNA sequencing and co-immunoprecipitation-mass spectrometry analyses were utilized. Rescue and ubiquitination assays evaluated the impact of TRIM21-mediated CCT6A ubiquitination and degradation on TNBC progression in vitro and in vivo. Finally, we studied the potential of Ipatasertib, a pharmacological AKT inhibitor, and/or anti-PD1 therapy in inhibiting TNBC progression.

RESULTS

Elevated CCT6A expression in TNBC patients was associated with an adverse prognosis and lymph node metastasis. Mechanistically, CCT6A facilitated cell migration, invasion, epithelial-mesenchymal transition and proliferation by activating the phosphatidylinositol 3-kinase (PI3K)/AKT pathway. The TRIM21 RING domain is an E3 ligase, facilitating the K48-linked ubiquitination-mediated degradation of CCT6A, thereby impeding TNBC progression. Moreover, in the tumour tissues of the CCT6A-overexpressing mice, the quantity of CD8+ T cells and the concentration of secreted interferon-gamma were decreased, whereas in the group double-overexpression of CCT6A and TRIM21, they were elevated; the opposite was observed in the knockdown and double-knockdown groups. Ipatasertib demonstrated enhanced efficacy in inhibiting cell proliferation, invasion and migration in TNBC cells ectopically expressing CCT6A. When Ipatasertib and anti-PD1 therapies were combined, both the tumour volume and mass exhibited a notable reduction, while the expression of CD45+CD8+ T cells increased, and that of CD45+CD4+CTLA4+ and CD45+CD4+PD1+ T cells decreased.

CONCLUSIONS

Our findings indicate that TRIM21 inhibits TNBC progression by facilitating the K48-linked ubiquitination-mediated degradation of CCT6A via the PI3K/AKT signalling pathway. This highlights the potential of Ipatasertib and/or anti-PD1 as therapeutic strategies, particularly for TNBC patients overexpressing CCT6A.

KEY POINTS

Chaperonin TCP1 subunit 6A (CCT6A) plays an oncogenic role in triple-negative breast cancer (TNBC) through the AKT signaling pathway. TRIM21 facilitated K48-linked ubiquitination-mediated degradation of CCT6A, thereby impeding TNBC progression. Our study collectively underscores the potential of Ipatasertib in conjunction with anti-PD1 therapy as a promising strategy to counteract CCT6A/AKT hyperactivity-driven TNBC progression.

Applying whole-genome and whole-exome sequencing in breast cancer: a review of the landscape

Whole-genome sequencing (WGS) and whole-exome sequencing (WES) are crucial within the context of breast cancer (BC) research. They play a role in the detection of predisposed genes, risk stratification, and identification of rare single nucleotide polymorphisms (SNPs). These technologies aid in the discovery of associations between various syndromes and BC, understanding the tumour microenvironment (TME), and even identifying unknown mutations that could be useful in future for personalised treatments. Genetic analysis can find the associated risk of BC and can be used in early screening, diagnosis, specific treatment plans, and prevention in patients who are at high risk of tumour formation. This article focuses on the application of WES and WGS, and how uncovering novel candidate genes associated with BC can aid in treating and preventing BC.

Effectiveness and safety of neoadjuvant therapy in triple-negative breast cancer in a real-world population

OBJECTIVE

Triple-negative breast cancer is a subtype of aggressive breast cancer. Our aim is to evaluate the effectiveness and safety of neoadjuvant treatment in early-stage triple-negative breast cancer and to identify predictors of pathological complete response.

METHODS

This is a single-center, retrospective study involving 79 patients with triple-negative breast cancer who initiated neoadjuvant treatment between January 2017 and October 2022. Descriptive analyses were performed as appropriate. Statistical analysis utilized bivariate logistic regression to explore the presence of factors related to pathological complete response, and the Kaplan-Meier method was employed for survival analysis.

RESULTS

In the overall population, 27 patients (n = 78; 34.6%) achieved pathological complete response in the breast and axillary lymph nodes, and 31 (n = 73; 42.5%) achieved a grade 5 pathological complete response in the breast, according to the Miller and Payne classification. The addition of platinum to standard therapy improved both breast and axillary lymph node pathological complete response rates. Age less than 40 years was identified as a predictor of pathological complete response in our study population through bivariate analysis, while Ki67 levels lower than 70% were associated with a lower pathological complete response rate. Adverse events were reported in 72 patients (91.1%), with grade 3-5 adverse events observed in 33 (41.8%). There was a particularly notable increase in gastrointestinal and hematological adverse events when platinum was added.

CONCLUSIONS

In this population, we observed moderate rates of pathological complete response with acceptable chemotherapy tolerance. Platinum-based chemotherapy appears to enhance the likelihood of achieving pathological complete response, albeit with a less favorable safety profile. Therefore, evaluating the benefit-risk balance is crucial when selecting the optimal chemotherapy regimen for individual patients.

Strategies for the treatment of hormone receptor-positive HER2-low breast cancer based on clinical practice: a round table discussion

Human epidermal growth factor receptor 2 (HER2)-low breast cancer is a newly identified targetable subset of breast tumors, and its clinical characteristics and treatment strategies are controversial. The emergence of novel anti-HER2 antibody-drug conjugate (ADC) has brought promising approaches for HER2-low breast cancer treatment. Several clinical trials have validated the efficacy and safety of trastuzumab deruxtecan (T-Dxd) in HER2-low breast cancer at different treatment settings. The treatment timing, candidate identification, long-term management, and overcoming drug resistance are crucial questions to improve breast cancer patient survival. Here we present a clinical case of hormone receptor-positive (HR+) HER2-low breast cancer patient who experienced neoadjuvant chemotherapy, surgery, adjuvant, and first-line endocrine therapy with limited effectiveness. After the treatment failure of CDK4/6 inhibitors, the utilization of T-Dxd brought a long-term disease response and tolerable low toxicities. In this round table discussion, we summarized opinions and recommendations from breast cancer surgeons and oncologists on treatment strategies for this patient. The discussion mainly focused on the precise diagnosis of HER2-low breast cancer, treatment design at different disease status, regimens selection according to drug response, strategies consideration for overcoming drug resistance and the management of adverse events in long-term survival. These opinions would provide critical insights to improve HER2-low breast cancer treatment and offer valuable suggestions for clinical practice.

Predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer using a machine learning approach

BACKGROUND

For patients with breast cancer undergoing neoadjuvant chemotherapy (NACT), most of the existing prediction models of pathologic complete response (pCR) using clinicopathological features were based on standard statistical models like logistic regression, while models based on machine learning mostly utilized imaging data and/or gene expression data. This study aims to develop a robust and accessible machine learning model to predict pCR using clinicopathological features alone, which can be used to facilitate clinical decision-making in diverse settings.

METHODS

The model was developed and validated within the National Cancer Data Base (NCDB, 2018-2020) and an external cohort at the University of Chicago (2010-2020). We compared logistic regression and machine learning models, and examined whether incorporating quantitative clinicopathological features improved model performance. Decision curve analysis was conducted to assess the model's clinical utility.

RESULTS

We identified 56,209 NCDB patients receiving NACT (pCR rate: 34.0%). The machine learning model incorporating quantitative clinicopathological features showed the best discrimination performance among all the fitted models [area under the receiver operating characteristic curve (AUC): 0.785, 95% confidence interval (CI): 0.778-0.792], along with outstanding calibration performance. The model performed best among patients with hormone receptor positive/human epidermal growth factor receptor 2 negative (HR+/HER2-) breast cancer (AUC: 0.817, 95% CI: 0.802-0.832); and by adopting a 7% prediction threshold, the model achieved 90.5% sensitivity and 48.8% specificity, with decision curve analysis finding a 23.1% net reduction in chemotherapy use. In the external testing set of 584 patients (pCR rate: 33.4%), the model maintained robust performance both overall (AUC: 0.711, 95% CI: 0.668-0.753) and in the HR+/HER2- subgroup (AUC: 0.810, 95% CI: 0.742-0.878).

CONCLUSIONS

The study developed a machine learning model ( https://huolab.cri.uchicago.edu/sample-apps/pcrmodel ) to predict pCR in breast cancer patients undergoing NACT that demonstrated robust discrimination and calibration performance. The model performed particularly well among patients with HR+/HER2- breast cancer, having the potential to identify patients who are less likely to achieve pCR and can consider alternative treatment strategies over chemotherapy. The model can also serve as a robust baseline model that can be integrated with smaller datasets containing additional granular features in future research.

A Multicenter Physician Survey Evaluating the Use of Ki-67 in Breast Cancer Management in Canada

BACKGROUND

Ki-67's response to pre-operative endocrine therapy (ET) in early breast cancer is an evidence-based tool to guide adjuvant treatment decisions. Physicians across Canada were surveyed to explore current practice patterns and perceived barriers to the use of Ki-67 in practice.

METHODS

Physicians were invited to participate in an anonymous survey and were eligible if they prescribed systemic therapy for breast cancer in Canada. Respondents were asked to describe their usage of Ki-67, perceptions of the evidence surrounding Ki-67 ET response, and interest in future trials using this approach.

RESULTS

The survey received 48/163 responses (29.4%). The majority of respondents (97.6%) reported access to Ki-67 testing upon request. Treatment decisions for adjuvant Abemaciclib was the most common reason (97.6%), followed by adjuvant chemotherapy decisions (16.7%). Only 19.0% had used Ki-67's response to pre-operative ET in practice. Common barriers to this approach that were identified included a lack of awareness from other providers (54.8%), an increased resource requirement (54.8%), and a lack of timely medical oncology consultation (52.4%). The majority of physicians (85.3%) reported that they would participate in future trials using the Ki-67 endocrine response, and that rate of treatment decision change (95.2%) and cost analysis (42.3%) were important endpoints.

CONCLUSIONS

Despite the widespread availability of Ki-67 testing, few physicians in Canada currently use it to assess endocrine response, predominantly due to logistical and resource constraints. There is a high level of interest in participating in future trials using this strategy, which should focus on disease related outcomes, feasibility, and the financial impact on the public healthcare system.

Sacituzumab Govitecan in Triple Negative Breast Cancer: A Systematic Review of Clinical Trials

BACKGROUND/OBJECTIVES

Triple-negative breast cancer is difficult to treat due to the absence of hormone receptors and Her2neu. Sacituzumab govitecan is a new therapeutic approach that uses an antibody directed against the Trop-2 antigen present in solid epithelial tumors, linked to the active metabolite SN-38, similar to irinotecan, to specifically target cancer cells while minimizing damage to healthy cells. The objective of the present review was to evaluate the efficacy and safety of sacituzumab govitecan as a single treatment in patients with triple-negative breast cancer and to compare its results with the standard conventional chemotherapy regimen currently used in this disease.

METHODS

A systematic review of randomized clinical trials of sacituzumab govitecan was performed. The search was performed in Medline (PubMed), Web of Science, and Cochrane from September 2022 to January 2024.

RESULTS

Thirty-eight articles are included and evaluated according to inclusion and exclusion criteria corresponding to the two most relevant clinical trials, including specific analyses of cohorts and subgroup study arms within these trials. Data from more recent clinical trials are also reviewed.

CONCLUSIONS

The efficacy results showed a significantly greater clinical benefit with sacituzumab govitecan compared to standard chemotherapy in patients with triple-negative breast cancer. This drug will become a treatment of substantial impact in future treatment guidelines for this type of cancer.

ROS-Responsive and Self-Catalytic Nanocarriers for a Combination of Chemotherapy and Reinforced Ferroptosis against Breast Cancer

Ferroptosis is an appealing cancer therapy strategy based on the H2O2-involved Fenton reaction to produce toxic •OH for lipid peroxidation. However, intracellular H2O2 is easily consumed and results in a deficient Fenton reaction. This obstacle can be overcome by traditional chemotherapeutic drugs for H2O2 supplements. Moreover, a recent work illustrated that dihydroartemisinin (DHA) could promote ferroptosis against tumoral cells, particularly in the presence of ferrous compounds. To achieve combined chemotherapy and ferroptosis, a nanocarrier (TKNPDHA-Fc) was constructed by using thioketal (TK)-bridged paclitaxel prodrug (PEG-TK-PTX) and ferrocene (Fc)-conjugated PEG-Fc, where DHA was encapsulated by a hydrophobic-hydrophobic interaction. Upon cellular uptake, TKNPDHA-Fc could facilitate PTX release through TK breakage under an excess H2O2 microenvironment. Owing to the loss of the hydrophobic PTX component, TKNPDHA-Fc underwent a rapid dissociation for improving DHA to act as a ferroptotic inducer along with Fe supplied from Fc. Moreover, both the chemotherapy-induced reactive oxygen species and the •OH produced from reinforced ferroptosis further stimulated the TK cleavage. The "self-catalytic" loop of TKNPDHA-Fc remarkably improved the antitumor performance in vivo via combined mechanisms, and its tumor inhibition rate reached 78.3%. This work highlights the contribution of ROS-responsive and self-catalytic nanoplatforms for enhancing the potential of combined chemotherapy and ferroptosis for cancer therapy in the future.

Deep learning-based computed tomography urography image analysis for prediction of HER2 status in bladder cancer

Purpose: Bladder cancer (BCa) is one of the most common malignant tumors in the urinary system. BCa with HER2 overexpression can benefit from more precise treatments, but HER2 testing is costly and subjective. This study aimed to detect HER2 expression using computed tomography urography (CTU) images. Method: We gathered CTU images from 97 patients with BCa during the excretion phase in Renmin Hospital of Wuhan University, manually delineated the BCa regions, extracted radiomic features using the Pyradiomics package, conducted data dimensionality reduction via principal component analysis (PCA), and trained three models (Logistic Regression [LR], Random Forest [RF] and Multilayer Perceptron [MLP]) to discern the HER2 expression status. Results: Pyradiomics package was used to extract 975 radiological features and the cumulative interpretation area under the variance curve was 90.964 by PCA. Using an MLP-based deep learning model for identifying HER2 overexpression, the area under the curve (AUC) reached 0.79 (95% confidence interval [CI] 0.74-0.86) in the training set and 0.73 (95% CI 0.66-0.77) in the validation set. LR and RF had AUC of 0.69 (95% CI 0.63-0.75) and 0.66 (95% CI 0.61-0.70) in the training set and 0.61 (95% CI 0.55-0.67) and 0.59 (95% CI 0.55-0.63) in the test set, respectively. Conclusion: The study firstly presents a non-invasive method for identifying and detecting HER2 expression in BCa CTU images. It might not only reduce the cost and subjectivity of traditional HER2 testing but also provide a new technical method for the precise treatment of BCa.

The Influence of Microbiota on Breast Cancer: A Review

Breast cancer remains one of the leading causes of death among women worldwide, and recent research highlights its growing connection to alterations in the microbiota. This review delves into the intricate relationship between microbiotas and breast cancer, exploring its presence in healthy breast tissue, its changes during cancer progression, and its considerable impact on both the tumor microenvironment (TME) and the tumor immune microenvironment (TIME). We extensively analyze how the microbiota influences cancer growth, invasion, metastasis, resistance to drugs, and the evasion of the immune system, with a special focus on its effects on the TIME. Furthermore, we investigate distinct microbial profiles associated with the four primary molecular subtypes of breast cancer, examining how the microbiota in tumor tissues compares with that in adjacent normal tissues. Emerging studies suggest that microbiotas could serve as valuable diagnostic and prognostic biomarkers, as well as targets for therapy. This review emphasizes the urgent need for further research to improve strategies for breast cancer prevention, diagnosis, and treatment. By offering a detailed examination of the microbiota's critical role in breast cancer, this review aims to foster the development of novel microbiota-based approaches for managing the disease.

The prognostic impact of Her2 status in early triple negative breast cancer: a Turkish Oncology Group (TOG) study

The studies evaluating the impact of Her2 levels in neoadjuvant setting have conflicting data. The aim of the study was to evaluate the prognostic impact of Her2 status in early triple negative breast cancer(TNBC). In the study TNBC patients who were treated with neoadjuvant chemotherapy (NAC) and surgery were analyzed retrospectively. The primary aim of the study was to analyze the impact of Her2 status(Her2-0 and Her2-low) on pathological complete response (pCR). The secondary objectives were disease free survival (DFS) and overall survival (OS). 620 female triple negative breast cancer patients were evaluated. 427 patients (68.9%) had Her2-0 and 193(31.1%) had her2-low pathology. The pCR rates were similar between Her2-0 and Her2-low patients (33.0% vs. 27.5%, p = 0.098). Although Her2-0 group has better DFS (106 vs. 50 months, p = 0.002), in multivariate analysis it had a HR of 0.74 (p = 0.06). In addition, OS was similar (131 vs. 105 months, p = 0.13) with a HR of 0.88 (p = 0.61). In multivariate analysis; presence of LVI (HR:2.2 (95% CI 1.1-3.5) p = 0.001), Clinical stage T1/T2 (HR:0.39 (95% CI 0.2-0.6) p < 0.001) and lymph node negativity (HR:0.35 (95% CI 0.1-0.9) p = 0.03) were independent factors for OS. Although there were pathological and clinical differences, the pCR, DFS and OS were similar between Her2-0 and Her2-low TNBC patients. The importance of Her2 status of TNBC in neoadjuvant setting should be further studied.

Deep-learning based discrimination of pathologic complete response using MRI in HER2-positive and triple-negative breast cancer

Distinguishing between pathologic complete response and residual cancer after neoadjuvant chemotherapy (NAC) is crucial for treatment decisions, but the current imaging methods face challenges. To address this, we developed deep-learning models using post-NAC dynamic contrast-enhanced MRI and clinical data. A total of 852 women with human epidermal growth factor receptor 2 (HER2)-positive or triple-negative breast cancer were randomly divided into a training set (n = 724) and a validation set (n = 128). A 3D convolutional neural network model was trained on the training set and validated independently. The main models were developed using cropped MRI images, but models using uncropped whole images were also explored. The delayed-phase model demonstrated superior performance compared to the early-phase model (area under the receiver operating characteristic curve [AUC] = 0.74 vs. 0.69, P = 0.013) and the combined model integrating multiple dynamic phases and clinical data (AUC = 0.74 vs. 0.70, P = 0.022). Deep-learning models using uncropped whole images exhibited inferior performance, with AUCs ranging from 0.45 to 0.54. Further refinement and external validation are necessary for enhanced accuracy.

A phenocopy signature of TP53 loss predicts response to chemotherapy

In preclinical studies, p53 loss of function impacts chemotherapy response, but this has not been consistently validated clinically. We trained a TP53-loss phenocopy gene expression signature from pan-cancer clinical samples in the TCGA. In vitro, the TP53-loss phenocopy signature predicted chemotherapy response across cancer types. In a clinical dataset of 3003 breast cancer samples treated with neoadjuvant chemotherapy, the TP53-loss phenocopy samples were 56% more likely to have a pathologic complete response (pCR), with a significant association between TP53-loss phenocopy and pCR in both ER positive and ER negative tumors. In an independent clinical validation in the I-SPY2 trial (N = 987), we confirmed the association with neoadjuvant chemotherapy pCR and found higher rates of chemoimmunotherapy response in TP53-loss phenocopy tumors compared to non-TP53-loss phenocopy tumors (64% vs. 28%). The TP53-loss phenocopy signature predicts chemotherapy response across cancer types in vitro, and in a proof-of-concept clinical validation is associated with neoadjuvant chemotherapy response across multiple clinical breast cancer cohorts.

Tailoring neoadjuvant systemic therapy in breast cancer: "The advent of a personalized approach"-The Breast-Gynecological and Immuno-Oncology International Cancer Conference (BGICC) consensus and recommendations

BACKGROUND

The management of early breast cancer (BC) has witnessed an uprise in the use of neoadjuvant therapy and a remarkable reshaping of the systemic therapy postneoadjuvant treatment in the last few years, with the evolution of many controversial clinical situations that require consensus.

METHODS

During the 14th Breast-Gynecological and Immuno-Oncology International Cancer Conference held in Egypt in 2022, a panel of 44 BC experts from 13 countries voted on statements concerning debatable challenges in the neo/adjuvant treatment setting. The recommendations were subsequently updated based on the most recent data emerging. A modified Delphi approach was used to develop this consensus. A consensus was achieved when ≥75% of voters selected an answer.

RESULTS AND CONCLUSIONS

The consensus recommendations addressed different escalation and de-escalation strategies in the setting of neoadjuvant therapy for early BC. The recommendations recapitulate the available clinical evidence and expert opinion to individualize patient management and optimize therapy outcomes. Consensus was reached in 63% of the statements (52/83), and the rationale behind each statement was clarified.

Expanded Indications for Neoadjuvant Endocrine Therapy in Early-Stage Breast Cancer During the COVID-19 Pandemic

BACKGROUND

In response to the COVID-19 pandemic, the Pandemic Breast Cancer Consortium (PBCC) published recommendations for triage of breast cancer patients. The recommendations included neoadjuvant treatment of early-stage breast cancer patients experiencing delays in surgery. This study evaluated national patterns of neoadjuvant treatment according to triage guidelines.

METHODS

Patients treated with surgery (upfront or post-neoadjuvant) in 2018-2020 were collected from the National Cancer Database. The proportions of patients treated according to the PBCC triage guidelines were calculated in 2020 and compared with similar cohorts in 2018-2019. Patient and hospital factors were evaluated for association with treatment.

RESULTS

Among cT1N0 ER+/PR+/HER2- patients, those treated in 2020 were more likely to receive neoadjuvant endocrine therapy (NET) compared with those before that time (odds ratio [OR], 3.08; range, 2.93-3.24). Among the patients with cT2N0 or cT1N1 disease, NET was more common in 2020 (OR, 1.76; range, 1.65-1.88). Academic facility, black or Asian race, more comorbidities, and the New England/Middle Atlantic region were associated with NET use.

CONCLUSIONS

During the COVID-19 pandemic, expanded utilization of neoadjuvant therapy for surgical breast cancer patients was observed. Health care system limitations during the pandemic contributed to expanded adoption of neoadjuvant therapy for early breast cancer, contrary to usual practice. Long-term outcomes for patients treated according to PBCC recommendations should be closely monitored.