Association of Event-Free and Distant Recurrence-Free Survival With Individual-Level Pathologic Complete Response in Neoadjuvant Treatment of Stages 2 and 3 Breast Cancer: Three-Year Follow-up Analysis for the I-SPY2 Adaptively Randomized Clinical Trial

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.

DCE-MRI radiomics of primary breast lesions combined with ipsilateral axillary lymph nodes for predicting efficacy of NAT

BACKGROUND

This study aimed to assess the predictive value of radiomic analysis derived from primary lesions and ipsilateral axillary suspicious lymph nodes (SLN) on dynamic contrast-enhanced MRI (DCE-MRI) for evaluating the response to neoadjuvant therapy (NAT) in early high-risk and advanced breast cancer (BC) patients.

METHODS

A retrospective analysis was conducted on 222 BC patients (192 from Center I and 30 from Center II) who underwent NAT. Radiomic features were extracted from the primary lesion (intra- and peritumoral regions) and ipsilateral axillary SLN to develop radiomic signatures (RS-primary, RS-SLN). An integrated signature (RS-Com) combined features from both regions. Feature selection was performed using correlation analysis, the Mann-Whitney U test, and least absolute shrinkage and selection operator (LASSO) regression. A diagnostic nomogram was constructed by integrating RS-Com with key clinical factors. Model performance was evaluated using receiver operating characteristic (ROC) and decision curve analysis (DCA).

RESULTS

RS-Com demonstrated superior predictive performance compared to RS-primary and RS-SLN alone. The DeLong test confirmed that axillary SLNs provide supplementary information to the primary lesion. Among clinical factors, N staging and HER2 status were significant contributors. The nomogram, integrating RS-Com, N staging, and HER2 status, achieved the highest performance in the training (AUC: 0.926), validation (AUC: 0.868), and test (AUC: 0.839) cohorts, outperforming both the clinical models and RS-Com alone.

CONCLUSION

Radiomic features from axillary SLNs offer valuable supplementary information for predicting NAT response in BC patients. The proposed nomogram, incorporating radiomics and clinical factors, provides a robust tool for individualized treatment planning.

Screening and exploration of neoadjuvant "de-escalation" therapy for early breast cancer

Background

Neoadjuvant therapy for breast cancer improves the prognosis of high-risk patients. However, whether pathological completed response (pCR) can be used as a surrogate endpoint for de-escalation therapy in patients who are relatively sensitive to treatment remains to be elucidated.

Methods

We retrospectively reviewed 143 breast cancer patients, with clinical stage (cStage) II-IIIA who received neoadjuvant chemotherapy and achieved pCR in a short time (within 16 weeks) from 2012 to 2022. The prognosis of patients was analysed using the Kaplan-Meier method, Cox proportional hazards regression models to identify independent clinicopathologic factors affecting prognosis.

Results

The median follow-up period was 47 months, the overall 4-year disease-free survival (DFS) and overall survival (OS) were 95.3% and 96.9%, respectively, in 143 patients with pCR after neoadjuvant chemotherapy. The 4-year DFS between the postoperative adjuvant chemotherapy and no adjuvant chemotherapy groups was 76.4% and 95.2%, with a significant statistical difference between both groups (P < 0.05). For HER2-positive (HER2+) and Triple negative breast cancer (TNBC), the addition of targeted therapy or platinum-based drugs had no impact on prognosis. Univariate and multivariate analyses of prognosis showed that only postoperative adjuvant chemotherapy significantly affected prognosis.

Conclusion

Patients with operable cStage II-IIIA breast cancer who achieved pCR after a short period of neoadjuvant chemotherapy have a satisfactory prognosis and may be suitable for chemotherapy "de-escalation." This approach is also a dominant application of neoadjuvant "tailoring therapy."

Dynamic ctDNA tracking stratifies relapse risk for triple negative breast cancer patients receiving neoadjuvant chemotherapy

Early Triple negative breast cancer (eTNBC) is the subtype with the worst outcome. Circulating tumor DNA (ctDNA) is shown to predict the prognosis of breast cancer, but its utility in eTNBC remains unclear. 130 stage II-III female eTNBC patients receiving neoadjuvant chemotherapy (NAC) have been enrolled prospectively and subjected to ctDNA analysis. ctDNA at post-NAC (pre-surgery) and post-surgery, but not at baseline, is associated with worse prognosis. A threshold of 1.1% maximum variant allele frequency at baseline stratifies patients with different relapse risk, which is validated internally and externally. A systemic tumor burden model integrating baseline and post-surgery ctDNA is independently prognostic (p = 0.022). Combining systemic tumor burden with pathologic response identifies a highly curable subgroup and a subgroup of high-risk eTNBC patients. ctDNA surveillance during follow-up identifies patients with high relapse risk. In conclusion, systemic ctDNA analysis demonstrates the utility of a systemic tumor burden model of ctDNA in risk stratification of eTNBC patients, which may guide future treatment escalation or de-escalation trials.

Deep Learning Models Based on Pretreatment MRI and Clinicopathological Data to Predict Responses to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer

PURPOSE

To develop deep learning models for predicting the pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in patients with triple-negative breast cancer (TNBC) based on pretreatment multiparametric breast MRI and clinicopathological data.

METHODS

The prospective institutional review board-approved study [NCT02276443] included 282 patients with stage I-III TNBC who had multiparametric breast MRI at baseline and underwent NAST and surgery during 2016-2021. Dynamic contrast-enhanced MRI (DCE), diffusion-weighted imaging (DWI), and clinicopathological data were used for the model development and internal testing. Data from the I-SPY 2 trial (2010-2016) were used for external testing. Four variables with a potential impact on model performance were systematically investigated: 3D model frameworks, tumor volume preprocessing, tumor ROI selection, and data inputs.

RESULTS

Forty-eight models with different variable combinations were investigated. The best-performing model in the internal testing dataset used DCE, DWI, and clinicopathological data with the originally contoured tumor volume, the tight bounding box of the tumor mask, and ResNeXt50, and achieved an area under the receiver operating characteristic curve (AUC) of 0.76 (95% CI: 0.60-0.88). The best-performing models in the external testing dataset achieved an AUC of 0.72 (95% CI: 0.57-0.84) using only DCE images (originally contoured tumor volume, enlarged bounding box of tumor mask, and ResNeXt50) and an AUC of 0.72 (95% CI: 0.56-0.86) using only DWI images (originally contoured tumor volume, enlarged bounding box of tumor mask, and ResNet18).

CONCLUSIONS

We developed 3D deep learning models based on pretreatment data that could predict pCR to NAST in TNBC patients.

Prognostic role of STMN1 expression and neoadjuvant therapy efficacy in breast cancer

PURPOSE

breast cancer is common and highly malignant, currently, STMN1 was found to be associated with several human malignancies. The purpose of this study is to investigate STMN1 expression in breast cancer and explore its role in disease progression and its interaction with neoadjuvant therapy efficacy.

METHODS

we analyzed the tissue STMN1 mRNA expression in BC tissue samples from 105 patients received with neoadjuvant therapy using qPCR between 2019 and 2022.

RESULTS

Statistical analysis showed that a high expression of STMN1 before neoadjuvant chemotherapy (NACT) was a trend positively related to non-pCR in the ITT (Intention to Treat) population, while in patients with paclitaxel or docetaxel regimens, before-NACT STMN1 expression was obviously higher in non-pCR (failure to achieve pathologically complete response) patients. Additionally, compared to pCR, high expression of STMN1 after NACT was obviously related to non-pCR. Interestingly, Kaplan-Meier analysis demonstrated that patients with mid-high STMN1 expression before and post-NACT had a poorer PFS to compared to those with low expression.

CONCLUSIONS

STMN1 is the potential biomarker of NACT and prognosis for breast cancer.

Cellular interactions within the immune microenvironment underpins resistance to cell cycle inhibition in breast cancers

Immune evasion by cancer cells involves reshaping the tumor microenvironment (TME) via communication with non-malignant cells. However, resistance-promoting interactions during treatment remain lesser known. Here we examine the composition, communication, and phenotypes of tumor-associated cells in serial biopsies from stage II and III high-risk estrogen receptor positive (ER+ ) breast cancers of patients receiving endocrine therapy (letrozole) as single agent or in combination with ribociclib, a CDK4/6-targeting cell cycle inhibitor. Single-cell RNA sequencing analyses on longitudinally collected samples show that in tumors overcoming the growth suppressive effects of ribociclib, first cancer cells upregulate cytokines and growth factors that stimulate immune-suppressive myeloid differentiation, resulting in reduced myeloid cell- CD8 + T-cell crosstalk via IL-15/18 signaling. Subsequently, tumors growing during treatment show diminished T-cell activation and recruitment. In vitro, ribociclib does not only inhibit cancer cell growth but also T cell proliferation and activation upon co-culturing. Exogenous IL-15 improves CDK4/6 inhibitor efficacy by augmenting T-cell proliferation and cancer cell killing by T cells. In summary, response to ribociclib in stage II and III high-risk ER +  breast cancer depends on the composition, activation phenotypes and communication network of immune cells.

Comparative analysis of machine learning models for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer: An MRI radiomics approach

PURPOSE

The aim of this work is to compare different machine learning models for predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer using radiomics features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

METHOD

The study included 55 patients with breast cancer, among whom 18 achieved pCR and 37 did not respond completely to NAC (non-pCR). After some pre-processing steps, 1446 features were extracted and corrected for batch effects using ComBat. Five machine learning algorithms, namely random forest (RF), decision tree (DT), logistic regression (LR), k-nearest neighbors (k-NN), and extreme gradient boosting (XGB), were evaluated using area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score as classification metrics. A Leave-Group-Out cross validation (LGOCV) was applied in the outer loop.

RESULTS

RF and DT models exhibited the highest performances compared to the other algorithms. DT achieved an accuracy of 0.96 ± 0.07, and RF achieved 0.95 ± 0.05. The AUC values for RF and DT were 0.98 ± 0.06 and 0.94 ± 0.07, respectively. LR and k-NN demonstrated lower performance across all metrics, while XGB showed competitive results but slightly lower than RF and DT.

CONCLUSIONS

This study demonstrates the potential of radiomics and machine learning for predicting pCR to NAC in breast cancer. RF and DT models proved to be the most effective in capturing underlying patterns in radiomics data. Further research is required to validate and strengthen the proposed approach and explore its applicability in diverse radiomics datasets and clinical scenarios.

The times they are AI-changing: AI-powered advances in the application of extracellular vesicles to liquid biopsy in breast cancer

Artificial intelligence (AI) is revolutionizing scientific research by facilitating a paradigm shift in data analysis and discovery. This transformation is characterized by a fundamental change in scientific methods and concepts due to AI's ability to process vast datasets with unprecedented speed and accuracy. In breast cancer research, AI aids in early detection, prognosis, and personalized treatment strategies. Liquid biopsy, a noninvasive tool for detecting circulating tumor traits, could ideally benefit from AI's analytical capabilities, enhancing the detection of minimal residual disease and improving treatment monitoring. Extracellular vesicles (EVs), which are key elements in cell communication and cancer progression, could be analyzed with AI to identify disease-specific biomarkers. AI combined with EV analysis promises an enhancement in diagnosis precision, aiding in early detection and treatment monitoring. Studies show that AI can differentiate cancer types and predict drug efficacy, exemplifying its potential in personalized medicine. Overall, the integration of AI in biomedical research and clinical practice promises significant changes and advancements in diagnostics, personalized medicine-based approaches, and our understanding of complex diseases like cancer.

A pooled analysis evaluating prognostic significance of Residual Cancer Burden in invasive lobular breast cancer

Residual Cancer Burden (RCB) after neoadjuvant chemotherapy (NAC) is validated to predict event-free survival (EFS) in breast cancer but has not been studied for invasive lobular carcinoma (ILC). We studied patient-level data from a pooled cohort across 12 institutions. Associations between RCB index, class, and EFS were assessed in ILC and non-ILC with mixed effect Cox models and multivariable analyses. Recursive partitioning was used in an exploratory model to stratify prognosis by RCB components. Of 5106 patients, the diagnosis was ILC in 216 and non-ILC in 4890. Increased RCB index was associated with worse EFS in both ILC and non-ILC (p = 0.002 and p < 0.001, respectively) and remained prognostic when stratified by receptor subtype and adjusted for age, grade, T category, and nodal status. Recursive partitioning demonstrated residual invasive cancer cellularity as most prognostic in ILC. These results underscore the utility of RCB for evaluating NAC response in those with ILC.

Comparison of 10-Year Survival Between Patients With Axillary Pathologic Complete Response After Neoadjuvant Chemotherapy and Patients With Initially Negative Nodes in Breast Cancer

PURPOSE

We aimed to determine whether patients with cytologically proven node-positive disease who achieved axillary pathologic complete response (ypN0) after neoadjuvant chemotherapy (NAC) have similar survival outcomes to those with initially pathologically negative lymph nodes (pN0).

METHODS

Patients with cytologically proven node-positive breast cancer who achieved ypN0 after NAC and those with pN0 between June 2005 and March 2012 in a large cancer hospital were reviewed. The relapse-free survival (RFS), distant-disease-free survival (DDFS) and overall survival (OS) of the 2 groups were calculated and compared.

RESULTS

A total of 2285 patients, including 183 patients with ypN0 and 2102 patients with pN0, were included in this study. The median follow-up time for patients was 121 (range 2-182) months. The 10-year cumulative RFS was 79.7% for ypN0 patients and 90.2% for pN0 patients (log-rank P < .001). The 10-year cumulative DDFS was 81.4% for ypN0 patients and 92.2% for pN0 patients (log-rank P < .001). The 10-year cumulative OS was 86.3% for ypN0 patients and 94.0% for pN0 patients (log-rank P < .001). The multivariable Cox proportional hazards models showed that compared with pN0 patients, ypN0 patients had a 2.00-fold increase in the risk of recurrence (HR = 2.00, 95% CI, 1.33-3.01, P = .001), a 2.34-fold increase in the risk of distant recurrence (HR = 2.34, 95% CI, 1.52-3.62, P < .001) and a 2.10-fold increase in the risk of death (HR = 2.10, 95% CI, 1.25-3.53, P = .005).

CONCLUSION

Patients with axillary pCR showed inferior RFS, DDFS and OS to patients with pN0.

Neoadjuvant nivolumab and chemotherapy in early estrogen receptor-positive breast cancer: a randomized phase 3 trial

Patients with estrogen receptor-positive (ER+), human epidermal growth factor receptor 2-negative (HER2-) primary breast cancer (BC) have low pathological complete response (pCR) rates with neoadjuvant chemotherapy. A subset of ER+/HER2- BC contains dense lymphocytic infiltration. We hypothesized that addition of an anti-programmed death 1 agent may increase pCR rates in this BC subtype. We conducted a randomized, multicenter, double-blind phase 3 trial to investigate the benefit of adding nivolumab to neoadjuvant chemotherapy in patients with newly diagnosed, high-risk, grade 3 or 2 (ER 1 to ≤10%) ER+/HER2- primary BC. In total, 510 patients were randomized to receive anthracycline and taxane-based chemotherapy with either intravenous nivolumab or placebo. The primary endpoint of pCR was significantly higher in the nivolumab arm compared with placebo (24.5% versus 13.8%; P = 0.0021), with greater benefit observed in patients with programmed death ligand 1-positive tumors (VENTANA SP142 ≥1%: 44.3% versus 20.2% respectively). There were no new safety signals identified. Of the five deaths that occurred in the nivolumab arm, two were related to study drug toxicity; no deaths occurred in the placebo arm. Adding nivolumab to neoadjuvant chemotherapy significantly increased pCR rates in high-risk, early-stage ER+/HER2- BC, particularly among patients with higher stromal tumor-infiltrating lymphocyte levels or programmed death ligand 1 expression, suggesting a new treatment paradigm that emphasizes the role of immunotherapy and T cell immunosurveillance in luminal disease. Clinical trials.gov identifier: NCT04109066.

Real-World Outcomes with the KEYNOTE-522 Regimen in Early-Stage Triple-Negative Breast Cancer

BACKGROUND

This study aimed to determine if the neoadjuvant (NAT) KEYNOTE-522 regimen was associated with higher rates of pathologic complete response (pCR), corresponding to higher rates of breast conservation therapy (BCT) in early-stage triple-negative breast cancer (TNBC) patients.

PATIENTS AND METHODS

Stage II-III TNBC patients diagnosed between 2019 and 2022 who underwent NAT were analyzed retrospectively. NAT with KEYNOTE-522 versus control NAT were compared for rates of BCT, axillary node dissection (ALND), pCR, and survival outcomes. The prevalence of immune-related adverse events (irAE) from chemoimmunotherapy was recorded.

RESULTS

Of 240 patients identified: 86 received KEYNOTE-522 and 154 received control. The frequency of pCR was significantly higher in KEYNOTE versus the control cohort, 59.3% and 33.1%, respectively (p = 0.001). There was no significant difference in the rate of BCT between the control (33.1%) and the KEYNOTE-522 (32.1%) groups (p = 0.47). Rates of ALND were significantly lower with KEYNOTE-522 (25.6%) as compared with control (39.6%); p = 0.03. The rate of development of grade 2 or higher irAEs was 34.9%. At a median follow-up of 2.4 years, there was no difference in survival outcomes. BRCA1 patients had high rates of pCR regardless of treatment group, KEYNOTE-522: 80.0% (4/5) and control: 75% (9/12), (p = 1).

CONCLUSION

This real-world evidence supports the use of the KEYNOTE-522 regimen in patients with early-stage TNBC given the higher pCR rate and corresponding decrease in the rate of ALND. The majority of patients in both NAT cohorts became BCT eligible, but the rate of BCT did not differ between the two groups.

Lobectomy vs Total Thyroidectomy With Ipsilateral Lateral Neck Dissection for N1b Intermediate-Risk Papillary Thyroid Carcinoma

Importance

The management of papillary thyroid carcinoma (PTC), particularly in cases with clinically apparent lateral neck lymph node metastasis (cN1b), remains an area of debate. The surgical options for PTC, including total thyroidectomy and lobectomy, have distinct impacts on patients' outcomes and quality of life.

Objective

To compare survival and recurrence outcomes between patients who underwent a lobectomy plus ipsilateral lateral neck dissection (LND) and those who underwent a total thyroidectomy plus ipsilateral LND for intermediate-risk cN1b PTC with both primary tumors and lymph node metastases in the ipsilateral neck region.

Design, Setting, and Participants

This retrospective cohort study was conducted at Ito Hospital, Tokyo, Japan. Patients who underwent surgery for PTC between January 2005 and December 2012 were included, and those with high-risk PTCs and concurrent other thyroid cancers were excluded. Data were analyzed from April to August 2024.

Exposures

Lobectomy plus LND vs total thyroidectomy plus LND.

Main Outcomes and Measures

An inverse probability of treatment weighting (IPTW)-adjusted Kaplan-Meier analysis and a Cox proportional hazards regression analysis were performed to compare the patients' overall survival, recurrence-free survival (RFS), and modified RFS (which considered the potential need for a future contralateral lobectomy).

Results

Of 401 included patients, 317 (79.1%) were female, and the median (IQR) age was 47 (36-59) years. A total of 157 patients underwent lobectomy plus ipsilateral LND and 244 underwent total thyroidectomy plus ipsilateral LND. The median (IQR) follow-up time was 13.0 (11.2-15.0) years. The IPTW-adjusted overall survival rates at 5, 10, and 15 years were 98.0% (95% CI, 93.9-99.3), 97.5% (95% CI, 93.2-99.1), and 96.8% (95% CI, 92.2-98.7), respectively, for the lobectomy group vs 99.4% (95% CI, 97.0-99.9), 97.4% (95% CI, 94.4-98.8), and 96.9% (95% CI, 93.3-98.5), respectively, for the total thyroidectomy group (hazard ratio [HR], 1.10; 95% CI, 0.35-3.47). The IPTW-adjusted RFS rates at 5, 10, and 15 years were 93.8% (95% CI, 88.5-96.7), 88.4% (95% CI, 82.0-92.6), and 84.1% (95% CI, 76.8-89.3), respectively, for the lobectomy group vs 95.4% (95% CI, 91.8-97.4), 92.9% (95% CI, 88.8-95.5), and 87.8% (95% CI, 80.8-92.4), respectively, for the total thyroidectomy group (HR, 1.41; 95% CI, 0.79-2.54). The IPTW-adjusted modified RFS rates at 5, 10, and 15 years were 96.7% (95% CI, 92.2-98.6), 93.8% (95% CI, 88.5-96.7), and 88.9% (95% CI, 82.4-93.1), respectively, for the lobectomy group vs 95.4% (95% CI, 91.8-97.4), 92.9% (95% CI, 88.8-95.5), and 87.8% (95% CI, 80.8-92.4), respectively, for the total thyroidectomy group (HR, 0.93; 95% CI, 0.49-1.76).

Conclusions and Relevance

In this study, for these selected intermediate-risk cN1b PTC cases, total thyroidectomy and lobectomy provided comparable outcomes in terms of prognosis and recurrence. These data may help inform future guideline revisions and support joint decision-making between patients and their clinicians.

Pathologic complete response (pCR) rates for patients with HR+/HER2- high-risk, early-stage breast cancer (EBC) by clinical and molecular features in the phase II I-SPY2 clinical trial

BACKGROUND

Hormone receptor-positive (HR+), human epidermal growth factor receptor 2 (HER2)-negative early-stage breast cancer (EBC) is a heterogenous disease. Identification of better clinical and molecular biomarkers is essential to guide optimal therapy for each patient.

PATIENTS AND METHODS

We analyzed rates of pathologic complete response (pCR) and distant recurrence-free survival (DRFS) for patients with HR+/HER2-negative EBC in eight neoadjuvant arms in the I-SPY2 trial by clinical/molecular features: age, stage, histology, percentage estrogen receptor (ER) positivity, ER/progesterone receptor status, MammaPrint (MP)-High1 (0 to -0.57) versus MP-High2 (<-0.57), BluePrint (BP)-Luminal-type versus BP-Basal-type, and ImPrint immune signature. We quantified the clinical/molecular heterogeneity, assessed overlap among these biomarkers, and evaluated associations with pCR and DRFS.

RESULTS

Three hundred and seventy-nine patients with HR+/HER2-negative EBC were included in this analysis, with an observed pCR rate of 17% across treatment arms. pCR rates were higher in patients with stage II versus III disease (21% versus 9%, P = 0.0013), ductal versus lobular histology (19% versus 11%, P = 0.049), lower %ER positivity (≤66% versus >66%) (35% versus 9%, P = 3.4E-09), MP-High2 versus MP-High1 disease (31% versus 11%, P = 1.1E-05), BP-Basal-type versus BP-Luminal-type disease (34% versus 10%, P = 1.62E-07), and ImPrint-positive versus -negative disease (38% versus 10%, P = 1.64E-09). Patients with lower %ER were more likely to have MP-High2 and BP-Basal-type disease. At a median follow-up of 4.8 years, patients who achieved pCR had excellent outcomes irrespective of clinical/molecular features. Among patients who did not achieve pCR, DRFS events were more frequent in patients with MP-High2 and BP-Basal-type disease than those with MP-High1 and BP-Luminal-type disease.

CONCLUSIONS

Among patients with high molecular-risk HR+/HER2-negative EBC, the MP-High2, BP-Basal-type, and ImPrint-positive signatures identified a partially overlapping subset of patients who were more likely to achieve pCR in response to neoadjuvant chemotherapy ± targeted agents or immunotherapy compared to patients with MP-High1, BP-Luminal-type, and ImPrint-negative disease. I-SPY2.2 is incorporating the use of these biomarkers to molecularly define specific patient populations and optimize treatment selection.

Multiple time points for detecting circulating tumor DNA to monitor the response to neoadjuvant therapy in breast cancer: a meta-analysis

BACKGROUND

Not all breast cancer (BC) patients can benefit from neoadjuvant therapy (NAT). A poor response may result in patients missing the best opportunity for treatment, ultimately leading to a poor prognosis. Thus, to identify an effective predictor that can assess and predict patient response at early time points, we focused on circulating tumor DNA (ctDNA), which is a vital noninvasive liquid biopsy biomarker. We performed a meta-analysis to explore the predictive value of response by monitoring ctDNA at four time points of NAT using pathologic complete response (pCR) and residual cancer burden (RCB).

METHODS

By searching Embase, PubMed, the Cochrane Library, and the Web of Science until December 24, 2023, we selected studies concerning the relationship between ctDNA and response or prognosis. We analysed the results at the following various time points: baseline (T0), first cycle of NAT (T1), mid-treatment (MT), and end of NAT (EOT). pCR and RCB were used to evaluate the response as the primary endpoint. The secondary endpoint was to investigate the relationship between ctDNA and prognosis. Odds ratios (ORs) and hazard ratios (HRs) were used as effect indicators.

RESULTS

Thirteen reports from twelve studies were eligible for inclusion in this meta-analysis. The results demonstrated that ctDNA negativity was associated with pCR at T1 (OR = 0.34; 95% CI: 0.21-0.57), MT (OR = 0.35; 95% CI: 0.20-0.60), and EOT (OR = 0.38; 95% CI: 0.22-0.66). When RCB was used to evaluate responses, ctDNA negativity was associated with RCB-0/I at the MT (OR = 0.34; 95% CI: 0.21-0.55) and EOT (OR = 0.26; 95% CI: 0.15-0.46). Furthermore, ctDNA positivity at T1 predicted a worse prognosis for patients (HR = 2.73; 95% CI: 1.29-5.75). We also performed a subgroup analysis to more accurately assess the predictive value of ctDNA for triple-negative breast cancer.

CONCLUSIONS

Our meta-analysis suggested that the ctDNA status at the early stage of NAT can predict patient response, which provides evidence for adjusting personalized treatment strategies and improving patient survival.

PROSPERO REGISTRATION NUMBER

CRD42024496465.

Hormone Receptor-Positive HER2-Negative/MammaPrint High-2 Breast Cancers Closely Resemble Triple-Negative Breast Cancers

PURPOSE

The MammaPrint (MP) prognostic assay categorizes breast cancers into high- and low-risk subgroups, and the high-risk group can be further subdivided into high-1 (MP-H1), and very high-risk high-2 (MP-H2). The aim of this analysis was to assess clinical and molecular differences between the hormone receptor-positive (HR+)/HER2-negative MP-H1, -H2, and triple-negative (TN) MP-H1 and -H2 cancers.

EXPERIMENTAL DESIGN

Pretreatment gene expression data from 742 HER2-negative breast cancers enrolled in the I-SPY2 neoadjuvant trial were used. Prognostic risk categories were assigned using the MP assay. Transcriptional similarities across the four receptor and prognostic groups were assessed using principal component analyses and by identifying differentially expressed genes. We also examined pathologic complete response rates and event-free survivals by risk group.

RESULTS

Principal component analysis showed that HR+/MP-H2 tumors clustered with TN/MP-H2 cancers. Only 125 genes showed differential expression between the HR+/MP-H2 and TN/MP-H2 cancers, whereas 1,465 genes were differentially expressed between HR+/MP-H2 and -H1. Gene set analysis revealed similarly high expression of cell cycle, DNA repair, and immune infiltration-related pathways in HR+/MP-H2 and TN/MP-H2 cancers. HR+/MP-H2 cancers also showed low estrogen receptor-related gene expression. Pathologic complete response rates were similarly high in TN/MP-H2 and HR+/MP-H2 cancers (42% vs. 30.5%; P = 0.11), and MP-H2 cancers with residual cancer had similarly poor event-free survival regardless of estrogen receptor status.

CONCLUSIONS

In conclusion, HR+/MP-H2 cancers closely resemble TN breast cancers in transcriptional and clinical features and benefit from similar treatment strategies.

Datopotamab-deruxtecan plus durvalumab in early-stage breast cancer: the sequential multiple assignment randomized I-SPY2.2 phase 2 trial

Sequential adaptive trial designs can help accomplish the goals of personalized medicine, optimizing outcomes and avoiding unnecessary toxicity. Here we describe the results of incorporating a promising antibody-drug conjugate, datopotamab-deruxtecan (Dato-DXd) in combination with programmed cell death-ligand 1 inhibitor, durvalumab, as the first sequence of therapy in the I-SPY2.2 phase 2 neoadjuvant sequential multiple assignment randomization trial for high-risk stage 2/3 breast cancer. The trial includes three blocks of treatment, with initial randomization to different experimental agent(s) (block A), followed by a taxane-based regimen tailored to tumor subtype (block B), followed by doxorubicin-cyclophosphamide (block C). Subtype-specific algorithms based on magnetic resonance imaging volume change and core biopsy guide treatment redirection after each block, including the option of early surgical resection in patients predicted to have a high likelihood of pathologic complete response, which is the primary endpoint assessed when resection occurs. There are two primary efficacy analyses: after block A and across all blocks for six prespecified HER2-negative subtypes (defined by hormone receptor status and/or response-predictive subtypes). In total, 106 patients were treated with Dato-DXd/durvalumab in block A. In the immune-positive subtype, Dato-DXd/durvalumab exceeded the prespecified threshold for success (graduated) after block A; and across all blocks, pathologic complete response rates were equivalent to the rate expected for the standard of care (79%), but 54% achieved that result after Dato-DXd/durvalumab alone (block A) and 92% without doxorubicin-cyclophosphamide (after blocks A + B). The treatment strategy across all blocks graduated in the hormone-negative/immune-negative subtype. No new toxicities were observed. Stomatitis was the most common side effect in block A. No patients receiving block A treatment alone had adrenal insufficiency. Dato-DXd/durvalumab is a promising therapy combination that can eliminate standard chemotherapy in many patients, particularly the immune-positive subtype.ClinicalTrials.gov registration: NCT01042379 .

Prediction of pathological complete response to chemotherapy for breast cancer using deep neural network with uncertainty quantification

BACKGROUND

The I-SPY 2 trial is a national-wide, multi-institutional clinical trial designed to evaluate multiple new therapeutic drugs for high-risk breast cancer. Previous studies suggest that pathological complete response (pCR) is a viable indicator of long-term outcomes of neoadjuvant chemotherapy for high-risk breast cancer. While pCR can be assessed during surgery after the chemotherapy, early prediction of pCR before the completion of the chemotherapy may facilitate personalized treatment management to achieve an improved outcome. Notably, the acquisition of dynamic contrast-enhanced magnetic resonance (DCEMR) images at multiple time points during the I-SPY 2 trial opens up the possibility of achieving early pCR prediction.

PURPOSE

In this study, we investigated the feasibility of the early prediction of pCR to neoadjuvant chemotherapy using multi-time point DCEMR images and clinical data acquired in the I-SPY2 trial. The prediction uncertainty was also quantified to allow physicians to make patient-specific decisions on treatment plans based on the level of associated uncertainty.

METHODS

The dataset used in our study included 624 patients with DCEMR images acquired at 3 time points before the completion of the chemotherapy: pretreatment (T0), after 3 cycles of treatment (T1), and after 12 cycles of treatment (T2). A convolutional long short-term memory (LSTM) network-based deep learning model, which integrated multi-time point deep image representations with clinical data, including tumor subtypes, was developed to predict pCR. The performance of the model was evaluated via the method of nested 5-fold cross validation. Moreover, we also quantified prediction uncertainty for each patient through test-time augmentation. To investigate the relationship between predictive performance and uncertainty, the area under the receiver operating characteristic curve (AUROC) was assessed on subgroups of patients stratified by the uncertainty score.

RESULTS

By integrating clinical data and DCEMR images obtained at three-time points before treatment completion, the AUROC reached 0.833 with a sensitivity of 0.723 and specificity of 0.800. This performance was significantly superior (p < 0.01) to models using only images (AUROC = 0.706) or only clinical data (AUROC = 0.746). After stratifying the patients into eight subgroups based on the uncertainty score, we found that group #1, with the lowest uncertainty, had a superior AUROC of 0.873. The AUROC decreased to 0.637 for group #8, which had the highest uncertainty.

CONCLUSIONS

The results indicate that our convolutional LSTM network-based deep learning model can be used to predict pCR earlier before the completion of chemotherapy. By combining clinical data and multi-time point deep image representations, our model outperforms models built solely on clinical or image data. Estimating prediction uncertainty may enable physicians to prioritize or disregard predictions based on their associated uncertainties. This approach could potentially enhance the personalization of breast cancer therapy.

In-Breast Tumor Progression During Neoadjuvant Chemotherapy: Impact on and Factors Influencing Distant Recurrence-Free Survival

BACKGROUND

Most patients with breast cancer treated with neoadjuvant chemotherapy (NAC) experience clinical benefit, however, a small proportion progress. We aimed to characterize factors predicting in-breast tumor progression and impact on distant recurrence.

PATIENTS AND METHODS

We reviewed all patients with clinical stage I-III breast cancer treated with NAC in 2006-2021 at our institution. We compared in-breast progressive disease (PD), defined as ≥ 20% increase in tumor size, with stable disease (SD) or response. Distant recurrence-free survival (DRFS) was analyzed using the Kaplan-Meier method and Cox proportional hazards regression.

RESULTS

Of 1403 patients, 70 (5%) experienced in-breast PD, 243 (17%) SD, 560 (40%) partial response (PR), and 530 (38%) breast pathologic complete response (breast pCR, ypT0/Tis). The rate of PD varied by tumor subtype (8% in HR+/HER2-, 5% TNBC, 2% HER2+, p < 0.001). With median 48 months follow-up, the rates of DRFS were significantly different according to clinical breast response as follows: PD 56%, SD 68%, PR 82%, or breast pCR 93%, p < 0.001. In patients with PD on multivariable analysis, post-NAC grade (adjusted HR 2.9, p = 0.002) and ypT3-4 category (adjusted HR 2.4, p = 0.03) were the strongest predictors of DRFS. Combining these factors, 23% had neither, 44% had one, and 33% had both, which stratified outcome in PD with 3-year DRFS of 100%, 77%, and 30%, respectively (p < 0.001).

CONCLUSIONS

While in-breast PD during NAC is uncommon (5%), it predicts poor survival. Among patients with in-breast PD, post-NAC tumor grade and T category predict outcomes and may be useful to guide treatment escalation.

Datopotamab-deruxtecan in early-stage breast cancer: the sequential multiple assignment randomized I-SPY2.2 phase 2 trial

Among the goals of patient-centric care are the advancement of effective personalized treatment, while minimizing toxicity. The phase 2 I-SPY2.2 trial uses a neoadjuvant sequential therapy approach in breast cancer to further these goals, testing promising new agents while optimizing individual outcomes. Here we tested datopotamab-deruxtecan (Dato-DXd) in the I-SPY2.2 trial for patients with high-risk stage 2/3 breast cancer. I-SPY2.2 uses a sequential multiple assignment randomization trial design that includes three sequential blocks of biologically targeted neoadjuvant treatment: the experimental agent(s) (block A), a taxane-based regimen tailored to the tumor subtype (block B) and doxorubicin-cyclophosphamide (block C). Patients are randomized into arms consisting of different investigational block A treatments. Algorithms based on magnetic resonance imaging and core biopsy guide treatment redirection after each block, including the option of early surgical resection in patients predicted to have a high likelihood of pathological complete response, the primary endpoint. There are two primary efficacy analyses: after block A and across all blocks for the six prespecified breast cancer subtypes (defined by clinical hormone receptor/human epidermal growth factor receptor 2 (HER2) status and/or the response-predictive subtypes). We report results of 103 patients treated with Dato-DXd. While Dato-DXd did not meet the prespecified threshold for success (graduation) after block A in any subtype, the treatment strategy across all blocks graduated in the hormone receptor-negative HER2-Immune-DNA repair deficiency- subtype with an estimated pathological complete response rate of 41%. No new toxicities were observed, with stomatitis and ocular events occurring at low grades. Dato-DXd was particularly active in the hormone receptor-negative/HER2-Immune-DNA repair deficiency- signature, warranting further investigation, and was safe in other subtypes in patients who followed the treatment strategy. ClinicalTrials.gov registration: NCT01042379 .

High C-reactive protein is associated with the efficacy of neoadjuvant chemotherapy for hormone receptor-positive breast cancer

C-reactive protein (CRP) is a nonspecific biomarker for systemic inflammatory response and is linked to the prognosis of breast cancer (BC); however, few studies have investigated the correlation between CRP and the effectiveness of neoadjuvant chemotherapy treatment for BC. We recruited 177 patients with BC who underwent neoadjuvant chemotherapy in our clinical trial. the median CRP level (0.24 mg/L), patients were categorized into high and low groups. We examined the relationship between CRP levels and various clinicopathological factors, including pathological complete response (pCR), using the chi-square test or Fisher exact test. Furthermore, we evaluated the predictive capacity of CRP for different molecular subtypes by constructing receiver operating characteristic curves. To identify the independent variables associated with pCR, we conducted logistic regression multivariate analysis. No association was found between C-reactive levels at baseline and pCR rates. CRP level was significantly associated with higher body mass index, and the high CRP group had more overweight patients (47.06% vs. 16.30%, P < .001). In hormone receptor-positive patients, the high CRP group demonstrated a significantly higher pCR rate (OR = 4.115, 95% CI: 1.481-11.36, P = .009). The areas under the curve was 0.670 (95% CI: 0.550-0.792, P < .001). Multivariate logistic analysis showed that the CRP level was a significant independent predictor of pCR (OR = 5.882, 95% CI: 1.470-28.57, P = .017). High CRP levels were found to be associated with a higher pCR rate, indicating their independent predictive value in determining the efficacy of neoadjuvant chemotherapy in hormone receptor-positive BC patients.

Tumor Morphology for Prediction of Poor Responses Early in Neoadjuvant Chemotherapy for Breast Cancer: A Multicenter Retrospective Study

BACKGROUND

This multicenter and retrospective study investigated the additive value of tumor morphologic features derived from the functional tumor volume (FTV) tumor mask at pre-treatment (T0) and the early treatment time point (T1) in the prediction of pathologic outcomes for breast cancer patients undergoing neoadjuvant chemotherapy.

METHODS

A total of 910 patients enrolled in the multicenter I-SPY 2 trial were included. FTV and tumor morphologic features were calculated from the dynamic contrast-enhanced (DCE) MRI. A poor response was defined as a residual cancer burden (RCB) class III (RCB-III) at surgical excision. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive performance. The analysis was performed in the full cohort and in individual sub-cohorts stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status.

RESULTS

In the full cohort, the AUCs for the use of the FTV ratio and clinicopathologic data were 0.64 ± 0.03 (mean ± SD [standard deviation]). With morphologic features, the AUC increased significantly to 0.76 ± 0.04 (p < 0.001). The ratio of the surface area to volume ratio between T0 and T1 was found to be the most contributing feature. All top contributing features were from T1. An improvement was also observed in the HR+/HER2- and triple-negative sub-cohorts. The AUC increased significantly from 0.56 ± 0.05 to 0.70 ± 0.06 (p < 0.001) and from 0.65 ± 0.06 to 0.73 ± 0.06 (p < 0.001), respectively, when adding morphologic features.

CONCLUSION

Tumor morphologic features can improve the prediction of RCB-III compared to using FTV only at the early treatment time point.

Predictive and Prognostic Value of Inflammatory and Nutritional Indexes in Patients with Breast Cancer Receiving Neoadjuvant Chemotherapy

Background and Objectives: Neoadjuvant chemotherapy (NAC) improves survival by increasing pathologic complete response (pCR). Blood-based indexes have been studied in breast cancer for predicting pCR and prognosis, but the results are conflicting. We aimed to assess the impact of inflammatory and nutritional indexes on pCR and survival. Materials and Methods: We retrospectively analyzed 304 patients. Pre-NAC laboratory data were used to calculate their neutrophil-to-lymphocyte ratios (NLR), pan-immune inflammation values (PIV), lactate dehydrogenase-albumin ratios (LAR), and prognostic nutritional indexes. The optimal cut-off values were determined through an analysis of the receiver operating characteristic curve. Survival analyses were performed using the Kaplan-Meier method. Multivariate regression analyses were performed to reveal the factors predicting pCR. Univariate and multivariate survival analyses were conducted to identify prognostic factors predicting survival. Results: The median follow-up was 38.5 months. pCR was achieved in 41.4% of the patients. In the univariate analyses, the NLR (p = 0.032) and PIV (p = 0.002) were indexes associated with pCR. In the multivariate analysis, the PIV (p = 0.008) was the only index significantly correlated with pCR. According to the multivariate Cox regression analyses, clinical stage 3 (p = 0.032), a pathologic response other than pCR (p = 0.021), and a high LAR (≥4.72) (p = 0.002) were correlated with increased recurrence risk. The univariate Cox regression analyses revealed that failure to achieve pCR (p = 0.037) and the presence of a high LAR (p = 0.044) were significant predictors of overall survival. However, the multivariate analyses failed to identify any significant predictors of death. Conclusions: We found that the PIV was more effective than the other indexes in predicting pCR. To our knowledge, this study is the first to determine an association between the LAR and disease-free survival in patients with breast cancer receiving NAC. We concluded that a high LAR was a poor prognostic factor, especially in patients without a pCR. Therefore, close postoperative monitoring and the intensification of adjuvant treatment should be considered for these patients. However, further studies are needed to confirm our findings.

Comparison of proportions and prognostic impact of pathological complete response between evaluations of representative specimen and total specimen in primary breast cancer after neoadjuvant chemoradiotherapy: an ancillary study of JCOG0306

BACKGROUND

In JCOG0306 trial, a phase II study to examine the efficacy of neoadjuvant chemotherapy followed by radiation therapy (NAC-RT) to primary breast cancer, pathological complete response (pCR) was evaluated from specimens of the representative cross-section including the tumor center that had been accurately marked [representative specimen (RS) method]. In this ancillary study, we examined if the RS method was comparable to the conventional total specimen (TS) method, which is widely employed in Japan, to identify the pCR group showing excellent prognosis.

METHODS

We obtained long-term follow-up data of 103 patients enrolled in JCOG0306 trial. As histological therapeutic effect, pCR (ypT0 and ypT0/is) and quasi-pCR [QpCR, ypT0/is plus Grade 2b (only a few remaining invasive cancer cells)] were evaluated with RS and TS methods. Concordance of pCR between these two methods and associations of the pCR with prognosis were examined.

RESULTS

ypT0, ypT0/is, and QpCR were observed in 28 (27.2%), 39 (37.9%), and 45 (43.7%) patients with RS method, whereas these were 20 (19.4%), 25 (24.3%) and 40 (38.9%) with TS method, respectively. Between RS and TS methods, concordance proportions of ypT0 and ypTis were 92.2% and 86.4%, respectively. Risk of recurrence of ypT0/is group was lower than that of non-ypT0/is group (HR 0.408, 95% CI [0.175-0.946], P = 0.037) and risk of death of ypT0/is group was lower than that of non-ypT0/is group (HR 0.251, 95% CI [0.073-0.857], P = 0.027). The ypT0 and ypT0/is groups with RS method showed excellent prognosis similarly with those with TS method, and RS method was able to differentiate the OS and RFS between pCR and non-pCR than TS method significantly even if pCR was classified ypT0 or ypT0/is. With TS method, QpCR criteria stratified patients into the better and worse prognosis groupsmore clearly than pCR criteria of ypT0 or ypT0/is.

CONCLUSIONS

RS method was comparable to TS method for the evaluation of pCR in the patients who received NAC-RT to primary breast cancer provided the tumor center was accurately marked. As pCR criteria with RS method, ypT0/is appeared more appropriate than ypT0.

Molecular and modular intricacies of precision oncology

Precision medicine is revolutionizing the world in combating different disease modalities, including cancer. The concept of personalized treatments is not new, but modeling it into a reality has faced various limitations. The last decade has seen significant improvements in incorporating several novel tools, scientific innovations and governmental support in precision oncology. However, the socio-economic factors and risk-benefit analyses are important considerations. This mini review includes a summary of some commendable milestones, which are not just a series of successes, but also a cautious outlook to the challenges and practical implications of the advancing techno-medical era.

Targeting IGF-IR improves neoadjuvant chemotherapy efficacy in breast cancers with low IGFBP7 expression

There has been a long-standing interest in targeting the type 1 insulin-like growth factor receptor (IGF-1R) signaling system in breast cancer due to its key role in neoplastic proliferation and survival. However, no IGF-1R targeting agent has shown substantial clinical benefit in controlled phase 3 trials, and no biomarker has been shown to have clinical utility in the prediction of benefit from an IGF-1R targeting agent. IGFBP7 is an atypical insulin-like growth factor binding protein as it has a higher affinity for the IGF-1R than IGF ligands. We report that low IGFBP7 gene expression identifies a subset of breast cancers for which the addition of ganitumab, an anti-IGF-1R monoclonal antibody, to neoadjuvant chemotherapy, substantially improved the pathological complete response rate compared to neoadjuvant chemotherapy alone. The pCR rate in the chemotherapy plus ganitumab arm was 46.9% in patients in the lowest quartile of IGFBP7 expression, in contrast to only 5.6% in the highest quartile. Furthermore, high IGFBP7 expression predicted increased distant metastasis risk. If our findings are confirmed, decisions to halt the development of IGF-1R targeting drugs, which were based on disappointing results of prior trials that did not use predictive biomarkers, should be reviewed.

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.

Precision Oncology Clinical Trials: A Systematic Review of Phase II Clinical Trials with Biomarker-Driven, Adaptive Design

Novel clinical trial designs are conducted in the precision medicine era. This study aimed to evaluate biomarker-driven, adaptive phase II trials in precision oncology, focusing on infrastructure, efficacy, and safety. We systematically reviewed and analyzed the target studies. EMBASE and PubMed searches from 2015 to 2023 generated 29 eligible trials. Data extraction included infrastructure, biomarker screening methodologies, efficacy, and safety profiles. Government agencies, cancer hospitals, and academic societies with accumulated experiences led investigator-initiated precision oncology clinical trials (IIPOCTs), which later guided sponsor-initiated precision oncology clinical trials (SIPOCTs). Most SIPOCTs were international studies with basket design. IIPOCTs primarily used the central laboratory for biomarker screening, but SIPOCTs used both central and local laboratories. Most of the studies adapted next-generation sequencing and/or immunohistochemistry for biomarker screening. Fifteen studies included an independent central review committee for outcome investigation. Efficacy assessments predominantly featured objective response rate as the primary endpoint, with varying results. Nine eligible studies contributed to the United States Food and Drug Administration's marketing authorization. Safety monitoring was rigorous, but reporting formats lacked uniformity. Health-related quality of life and patient-reported outcomes were described in some protocols but rarely reported. Our results reveal that precision oncology trials with adaptive design rapidly and efficiently evaluate anticancer drugs' efficacy and safety, particularly in specified biomarker-driven cohorts. The evolution from IIPOCT to SIPOCT has facilitated fast regulatory approval, providing valuable insights into the precision oncology landscape.

A clinicopathological-imaging nomogram for the prediction of pathological complete response in breast cancer cases administered neoadjuvant therapy

OBJECTIVE

To construct a user-friendly nomogram with MRI and clinicopathological parameters for the prediction of pathological complete response (pCR) after neoadjuvant therapy (NAT) in patients with breast cancer (BC).

METHODS

We retrospectively enrolled consecutive female patients pathologically confirmed with breast cancer who received NAT followed by surgery between January 2018 and December 2022 as the development cohort. Additionally, we prospectively collected eligible candidates between January 2023 and December 2023 as an external validation group at our institution. Pretreatment MRI features and clinicopathological variables were collected, and the pre- and post-treatment background parenchymal enhancement (BPE) and the changes in BPE on two MRIs were compared between patients who achieved pCR and those who did not. Multivariable logistic regression analysis was used to identify independent variables associated with pCR in the development cohort. These independent variables were combined into a predictive nomogram for which performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration plot, decision curve analysis, and external validation.

RESULTS

In the development cohort, there were a total of 276 female patients with a mean age of 48.3 ± 8.7 years, while in the validation cohort, there were 87 female patients with a mean age of 49.0 ± 9.5 years. Independent prognostic factors of pCR included small tumor size, HER2(+), high Ki-67 index,high signal enhancement ratio (SER), low minimum value of apparent diffusion coefficient (ADCmin), and significantly decreased BPE after NAT(change of BPE). The nomogram, which incorporates the above parameters, demonstrated excellent predictive performance in both the development and external validation cohorts, with AUC values of 0.900 and 0.850, respectively. Additionally, the nomogram showed excellent calibration capacities, as indicated by Hosmer-Lemeshow test p values of 0.508 and 0.423 in the two cohorts. Furthermore, the nomogram provided greater net benefits compared to the default simple schemes in both cohorts.

CONCLUSION

A nomogram constructed using tumor size, HER2 status, Ki-67 index, SER, ADCmin, and changes in pre- and post-NAT BPE demonstrated strong predictive performance, calibration ability, and greater net benefits for predicting pCR in patients with BC after NAT. This suggests that the user-friendly nomogram could be a valuable imaging biomarker for identifying suitable candidates for NAT.

Major pathologic response and long-term clinical benefit in hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer after neoadjuvant chemotherapy

BACKGROUND

The majority of HR+/HER2-breast cancer patients can also achieve long-term survival despite not attaining pCR, indicating limited prognostic value of pCR in this population. This study aimed to identify novel pathologic end points for predicting long-term outcomes in HR+/HER2-breast cancer after neoadjuvant chemotherapy.

METHODS

We analyzed HR+/HER2-breast cancer patients with stage II-III tumors who underwent curative surgery after neoadjuvant chemotherapy from three hospitals. Major pathologic response (MPR), defined as the presence of Miller-Payne grades 3-5 and positive lymph node ratio of ≤10 %, was used as a pathological evaluation indicator. We assessed the association between MPR and event-free survival (EFS) and performed Multivariable Cox regression to identify independent factors associated with EFS.

RESULTS

From January 2010 to December 2020, 386 patients were included in the final analysis. 28 patients (7.3 %) achieved pCR and 118 patients (30.6 %) achieved MPR. The median duration of follow-up was 54.4 months,5-year EFS was 87 % in the MPR group vs. 68 % in the non-MPR group. Multivariate analysis showed that low PR expression, high clinical stage, lower Miller-Payne grades and Positive lymph node ratio were independent poor prognostic factors for EFS (all P values < 0.05). The prognostic effect of MPR remained in multivariable models (hazard ratio (HR), 0.45; 95 % confidence interval (CI), 0.26-0.76; P = 0.008), In non-pCR patients, those who achieved MPR exhibited a similar EFS compared with pCR patients (HR, 2.25; 95 % CI, 0.51-9.84; P = 0.28).

CONCLUSION

MPR may be a novel pathologic end point in HR+/HER2-breast cancer after neoadjuvant chemotherapy, holding greater applicability in the prognosis evaluation than pCR.

Long-term outcomes of neoadjuvant trastuzumab emtansine + pertuzumab (T-DM1 + P) and docetaxel + carboplatin + trastuzumab + pertuzumab (TCbHP) for HER2-positive primary breast cancer: results of the randomized phase 2 JBCRG20 study (Neo-peaks)

PURPOSE

The randomized phase 2 Neo-peaks study examined usefulness of neoadjuvant trastuzumab emtansine + pertuzumab (T-DM1 + P) following docetaxel + carboplatin + trastuzumab + pertuzumab (TCbHP) as compared with the standard TCbHP regimen. We previously reported that pCR rate after neoadjuvant therapy tended to be higher with TCbHP followed by T-DM1 + P. We conducted an exploratory analysis of prognosis 5 years after surgery.

METHODS

Neoadjuvant treatment with TCbHP (6 cycles; group A), TCbHP (4 cycles) followed by T-DM1 + P (4 cycles; group B), and T-DM1 + P (4 cycles; group C, + 2 cycles in responders) were compared. Group C non-responders after 4 cycles were switched to an anthracycline-based regimen. We evaluated 5-year disease-free survival (DFS), distant DFS (DDFS), and overall survival (OS).

RESULTS

Data from 203 patients (50, 52, and 101 in groups A-C, respectively) were analyzed. No significant intergroup differences were found for DFS, DDFS, or OS. The 5-year DFS rates (95% CI) were 91.8% (79.6-96.8%), 92.3% (80.8-97.0%), and 88.0% (79.9-93.0%) in groups A-C, respectively. TCbHP followed by T-DM1 + P and T-DM1 + P with response-guided addition of anthracycline therapy resulted in similar long-term prognosis to that of TCbHP.

CONCLUSIONS

In patients who achieved pCR after neoadjuvant therapy with T-DM1 + P, omission of adjuvant anthracycline may be considered, whereas treatment should be adjusted for non-pCR patients with residual disease. T-DM1 + P with response-guided treatment adjustment may be useful for minimizing toxicity.

TRIAL REGISTRATION NUMBER AND DATE OF REGISTRATION

UMIN-CTR, UMIN000014649, prospectively registered July 25, 2014. Some of the study results were presented as a Mini Oral session at the ESMO Breast Cancer 2023 (Berlin, Germany, 11-13 May 2023).

Tailoring Neoadjuvant Therapy in Human Epidermal Growth Factor Receptor 2-Positive Early Breast Cancer: Recent Advances and Strategies

Neoadjuvant HER2 Therapy: Beyond one-size-fits-all.

Concurrent epirubicin and trastuzumab use increases complete pathological response rate without additional cardiotoxicity in patients with human epidermal growth factor receptor 2-positive early breast cancer: A meta-regression analysis

BACKGROUND

Due to cardiotoxicity concerns, the concurrent use of epirubicin and trastuzumab has not been fully studied. This study aimed to examine the cardiotoxicity and pathological complete response (pCR) rate associated with the concurrent regimens in patients with human epidermal growth factor receptor 2 (HER2)-positive early breast cancer (EBC).

METHODS

We conducted a systematic search for relevant literature in the NCBI/PubMed, the Cochrane database, and international conference abstracts for phase II or III randomized controlled trials between January 1, 2000, and February 28, 2021, focusing on the concurrent regimens in patients with HER2-positive EBC. To compare the risk of cardiotoxicity and the odds of the pCR rate, we performed linear meta-regression analyses to investigate the effects of multiple covariates.

RESULTS

We analyzed 7 neoadjuvant trials involving the concurrent use of epirubicin and trastuzumab with 1797 patients. The median cumulative dose of epirubicin used was 300 mg/m2, with a total of 96 reported adverse cardiac events. The concurrent regimens did not result in a significant increase in cardiotoxicity compared to nonconcurrent regimens (risk ratio [RR] = 1.18, 95% confidence interval [CI] = 0.68-2.05). Compared with nonconcurrent or non-anthracycline-containing regimens, concurrent regimens were associated with a significant increase in the pCR rate (odds ratio = 1.48, 95% CI = 1.04-2.12). The linear fixed-effects meta-regression analysis indicated that in trials including more patients with hormone receptor-positive EBC, the RR of cardiotoxicity significantly increased with concurrent regimens, and the pCR rate became less significant.

CONCLUSIONS

The combination of trastuzumab and a low dose of epirubicin positively impacted the pCR rate without a significant increase in cardiotoxicity. We recommend exploring concurrent regimens for HR-negative, HER2-positive tumors to enhance pCR rates, with caution advised for HR-positive tumors due to potential cardiotoxicity.

Taxane combined with lobaplatin or anthracycline for neoadjuvant chemotherapy of triple-negative breast cancer: a randomized, controlled, phase II study

BACKGROUND

Previous studies have shown that the addition of platinum to neoadjuvant chemotherapy (NAC) improved outcomes for patients with triple-negative breast cancer (TNBC). However, no studies have assessed the efficacy and safety of the combination of taxane and lobaplatin. In this study, we conducted a randomized controlled phase II clinical study to compare the efficacy and safety of taxane combined with lobaplatin or anthracycline.

METHODS

We randomly allocated patients with stage I-III TNBC into Arm A and Arm B. Arm A received six cycles of taxane combined with lobaplatin (TL). Arm B received six cycles of taxane combined with anthracycline and cyclophosphamide (TEC) or eight cycles of anthracycline combined with cyclophosphamide and sequential use of taxane (EC-T). Both Arms underwent surgery after NAC. The primary endpoint was the pathologic complete response (pCR). Secondary endpoints were event-free survival (EFS), overall survival (OS), and safety.

RESULTS

A total of 103 patients (51 in Arm A and 52 in Arm B) were assessed. The pCR rate of Arm A was significantly higher than that of Arm B (41.2% vs. 21.2%, P = 0.028). Patients with positive lymph nodes and low neutrophil-to-lymphocyte ratio (NLR) benefited significantly more from Arm A than those with negative lymph nodes and high NLR (Pinteraction = 0.001, Pinteraction = 0.012, respectively). There was no significant difference in EFS (P = 0.895) or OS (P = 0.633) between the two arms. The prevalence of grade-3/4 anemia was higher in Arm A (P = 0.015), and the prevalence of grade-3/4 neutropenia was higher in Arm B (P = 0.044).

CONCLUSIONS

Neoadjuvant taxane plus lobaplatin has shown better efficacy than taxane plus anthracycline, and both regimens have similar toxicity profiles. This trial may provide a reference for a better combination strategy of immunotherapy in NAC for TNBC in the future.

Cell-free DNA Concentration as a Biomarker of Response and Recurrence in HER2-Negative Breast Cancer Receiving Neoadjuvant Chemotherapy

PURPOSE

We previously demonstrated the clinical significance of circulating tumor DNA (ctDNA) in patients with HER2-negative breast cancer receiving neoadjuvant chemotherapy (NAC). Here, we compared its predictive and prognostic value with cell-free DNA (cfDNA) concentration measured in the same samples from the same patients.

EXPERIMENTAL DESIGN

145 patients with hormone receptor (HR)-positive/HER2-negative and 138 triple-negative breast cancer (TNBC) with ctDNA data from a previous study were included in the analysis. Associations of serial cfDNA concentration with residual cancer burden (RCB) and distant recurrence-free survival (DRFS) were examined.

RESULTS

In TNBC, we observed a modest negative correlation between cfDNA concentration 3 weeks after treatment initiation and RCB, but none of the other timepoints showed significant correlation. In contrast, ctDNA was significantly positively correlated with RCB at all timepoints (all R > 0.3 and P < 0.05). In the HR-positive/HER2-negative group, cfDNA concentration did not associate with response to NAC, but survival analysis showed that high cfDNA shedders at pretreatment had a significantly worse DRFS than low shedders (hazard ratio, 2.12; P = 0.037). In TNBC, the difference in survival between high versus low cfDNA shedders at all timepoints was not statistically significant. In contrast, as previously reported, ctDNA at all timepoints was significantly correlated with DRFS in both subtypes.

CONCLUSIONS

In TNBC, cfDNA concentrations during therapy were not strongly correlated with response or prognosis. In the HR-positive/HER2-negative group, pretreatment cfDNA concentration was prognostic for DRFS. Overall, the predictive and prognostic value of cfDNA concentration was more limited than that of ctDNA.

Pathological and clinical outcomes following neoadjuvant dual HER2 therapy for early-stage breast cancer: An Australian institutional real-world experience

AIM

There has been significant progress made in developing novel targeted therapies in the neoadjuvant setting for non-metastatic HER2-positive breast cancer, which may be used in combination with conventional chemotherapy to optimise pathological responses at surgery. However, these therapies, particularly the chemotherapeutic components, may portend significant and long-lasting toxicity. Hence, de-escalation of treatment intensity has been an area of interest and was evaluated in the phase II NeoSphere study. Herein, we report the real-world pathological and survival outcomes from neoadjuvant taxane and dual HER2 blockade recorded at our centre.

METHODS

This was a retrospective cohort study of patients receiving neoadjuvant pertuzumab, trastuzumab and taxane chemotherapy for non-metastatic HER2-positive breast cancer at a single centre in Sydney, Australia. We collected data pertaining to baseline demographic characteristics, pathological response rates, post-surgical prescribing patterns and also undertook survival analyses for invasive disease-free survival (iDFS) as well as exploratory analyses for correlations between pre-specified clinicopathologic factors and pathological response at surgery.

RESULTS

Our population was largely similar at baseline to the NeoSphere study. 71 patients were included in the final analysis. 61% achieved a pathological complete response (pCR). Three patients received conventional chemotherapy in the adjuvant setting. 92% of included patients were alive and disease-free at 3 years of follow-up. Only 3 events of recurrence or death were recorded at a median follow-up of 32 months. No significant difference in iDFS was noted between patients achieving pCR and those with residual disease at surgery.

CONCLUSION

This study demonstrates that de-escalated adjuvant treatment for HER2-positive early breast cancer achieved favourable pathological and long-term outcomes comparable to large trials, some utilising more intensive chemotherapeutic components.

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

INTRODUCTION

The impact of distinct estrogen receptor (ER) and progesterone receptor (PR) expression patterns on tumor behavior and treatment outcomes within HER2-positive breast cancer is not fully explored. This study aimed to comprehensively examine the clinical differences among patients with HER2-positive breast cancer harboring distinct ER and PR expression patterns in the neoadjuvant setting.

METHODS

This retrospective analysis included 871 HER2-positive breast patients treated with neoadjuvant therapy at our hospital between 2011 and 2022. Comparisons were performed across the three hormone receptor (HR)-specific subtypes, namely the ER-negative/PR-negative/HER2-positive (ER-/PR-/HER2+), the single HR-positive (HR+)/HER2+, and the triple-positive breast cancer (TPBC) subtypes.

RESULTS

Of 871 patients, 21.0% had ER-/PR-/HER2+ tumors, 33.6% had single HR+/HER2+ disease, and 45.4% had TPBC. Individuals with single HR+/HER2+ tumors and TPBC cases demonstrated significantly lower pathological complete response (pCR) rates compared to those with ER-/PR-/HER2+ tumors (36.9% vs. 24.3% vs. 49.2%, p < 0.001). Multivariate analysis confirmed TPBC as significantly associated with decreased pCR likelihood (OR = 0.42, 95%CI 0.28-0.63, p < 0.001). Survival outcomes, including disease-free survival (DFS) and overall survival (OS), showed no significant differences across HR-specific subtypes in the overall patient population. However, within patients without anti-HER2 therapy, TPBC was linked to improved DFS and a trend towards better OS.

CONCLUSIONS

HER2-positive breast cancer exhibited three distinct HR-specific subtypes with varying clinical manifestations and treatment responses. These findings suggest personalized treatment strategies considering ER and PR expression patterns, emphasizing the need for further investigations to unravel molecular traits underlying HER2-positive breast cancer with distinct HR expression patterns.

Omics-based molecular classifications empowering in precision oncology

BACKGROUND

In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.

CONCLUSION

This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

Tumor-Infiltrating Lymphocytes Refine Outcomes in Triple-Negative Breast Cancer Treated with Anthracycline-Free Neoadjuvant Chemotherapy

PURPOSE

Stromal tumor-infiltrating lymphocytes (sTIL) are associated with pathologic complete response (pCR) and long-term outcomes for triple-negative breast cancer (TNBC) in the setting of anthracycline-based chemotherapy. The impact of sTILs on refining outcomes beyond prognostic information provided by pCR in anthracycline-free neoadjuvant chemotherapy (NAC) is not known.

EXPERIMENTAL DESIGN

This is a pooled analysis of two studies where patients with stage I (T>1 cm)-III TNBC received carboplatin (AUC 6) plus docetaxel (75 mg/m2; CbD) NAC. sTILs were evaluated centrally on pre-treatment hematoxylin and eosin slides using standard criteria. Cox regression analysis was used to examine the effect of variables on event-free survival (EFS) and overall survival (OS).

RESULTS

Among 474 patients, 44% had node-positive disease. Median sTILs were 5% (range, 1%-95%), and 32% of patients had ≥30% sTILs. pCR rate was 51%. On multivariable analysis, T stage (OR, 2.08; P = 0.007), nodal status (OR, 1.64; P = 0.035), and sTILs (OR, 1.10; P = 0.011) were associated with pCR. On multivariate analysis, nodal status (HR, 0.46; P = 0.008), pCR (HR, 0.20; P < 0.001), and sTILs (HR, 0.95; P = 0.049) were associated with OS. At 30% cut-point, sTILs stratified outcomes in stage III disease, with 5-year OS 86% versus 57% in ≥30% versus <30% sTILs (HR, 0.29; P = 0.014), and numeric trend in stage II, with 5-year OS 93% versus 89% in ≥30% versus <30% sTILs (HR, 0.55; P = 0.179). Among stage II-III patients with pCR, EFS was better in those with ≥30% sTILs (HR, 0.16; P, 0.047).

CONCLUSIONS

sTILs density was an independent predictor of OS beyond clinicopathologic features and pathologic response in patients with TNBC treated with anthracycline-free CbD chemotherapy. Notably, sTILs density stratified outcomes beyond tumor-node-metastasis (TNM) stage and pathologic response. These findings highlight the role of sTILs in patient selection and stratification for neo/adjuvant escalation and de-escalation strategies.

Integrating Imaging and Circulating Tumor DNA Features for Predicting Patient Outcomes

Biomarkers for evaluating tumor response to therapy and estimating the risk of disease relapse represent tremendous areas of clinical need. To evaluate treatment efficacy, tumor response is routinely assessed using different imaging modalities like positron emission tomography/computed tomography or magnetic resonance imaging. More recently, the development of circulating tumor DNA detection assays has provided a minimally invasive approach to evaluate tumor response and prognosis through a blood test (liquid biopsy). Integrating imaging- and circulating tumor DNA-based biomarkers may lead to improvements in the prediction of patient outcomes. For this mini-review, we searched the scientific literature to find original articles that combined quantitative imaging and circulating tumor DNA biomarkers to build prediction models. Seven studies reported building prognostic models to predict distant recurrence-free, progression-free, or overall survival. Three discussed building models to predict treatment response using tumor volume, pathologic complete response, or objective response as endpoints. The limited number of articles and the modest cohort sizes reported in these studies attest to the infancy of this field of study. Nonetheless, these studies demonstrate the feasibility of developing multivariable response-predictive and prognostic models using regression and machine learning approaches. Larger studies are warranted to facilitate the building of highly accurate response-predictive and prognostic models that are generalizable to other datasets and clinical settings.

Precision Oncology in Breast Cancer Surgery

Outcomes for patients with breast cancer have improved over time due to increased screening and the availability of more effective therapies. It is important to recognize that breast cancer is a heterogeneous disease that requires treatment based on molecular characteristics. Early endpoints such as pathologic complete response correlate with event-free survival, allowing the opportunity to consider de-escalation of certain cancer treatments to avoid overtreatment. This article discusses clinical trials of tailoring treatment (eg, I-SPY2) and screening (eg, WISDOM) to individual patients based on their unique risk features.

Long-term overall survival of patients who undergo breast-conserving therapy or mastectomy for early operable HER2-Positive breast cancer after preoperative systemic therapy: an observational cohort study

Background

Understanding the survival outcomes associated with breast-conserving therapy (BCT) and mastectomy after preoperative systemic therapy (PST) enables clinicians to provide more personalized treatment recommendations. However, lack of firm survival benefit data limits the breast surgery choices of human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients who receive PST. We sought to determine whether BCT or mastectomy after PST for early operable HER2-positive breast cancer is associated with better long-term survival outcomes and determine the degree to which PST response affects this association.

Methods

In this observational cohort study, we compared the long-term survival outcomes of BCT and mastectomy after PST for HER2-positive breast cancer and evaluated the impact of PST response on the relationship between breast surgery performed and survival outcomes. Our cohort included 625 patients with early operable HER2-positive breast cancer who received PST followed by BCT or mastectomy between January 1998 and October 2009. These patients also received standard postoperative radiation, trastuzumab, and endocrine therapy as indicated clinically. We used propensity score matching to assemble mastectomy and BCT cohorts with similar baseline characteristics and used Kaplan-Meier plots and Cox proportional hazards regression to detect associations between surgery types and outcomes. Furthermore, in this study, we analyzed the original data of 625 patients using the inverse probability of treatment weighting (IPTW) method to enhance the reliability of the comparison between the mastectomy and BCT cohorts by addressing potential confounding variables.

Findings

Propensity score matching yielded cohorts of 221 patients who received BCT and 221 patients who underwent mastectomy. At the median follow-up time of 9.9 years, compared with BCT, mastectomy was associated with worse overall survival (hazard ratio, 1.66; 95% confidence interval [CI]: 1.08-2.57; P = 0.02). In patients who had axillary lymph node pathological complete response, mastectomy was associated with worse overall survival before matching (hazard ratio, 2.17; 95% CI: 1.22-3.86; P < 0.01) and after matching (hazard ratio, 2.12; 95% CI: 1.15-3.89; P = 0.02). Among patients with pathological complete response in the breast, the survival results did not differ significantly between BCT and mastectomy patients. IPTW method validated that BCT offers better overall survival in patients who had axillary lymph node pathological complete response.

Interpretation

People with HER2-positive breast cancer who have already had PST are more likely to survive after BCT, especially if they get a pathological complete response in the axillary lymph nodes. These findings underscore the necessity for further investigation into how responses to PST can inform the choice of surgical intervention and the potential impact on overall survival. Such insights could lead to the development of innovative tools that support personalized surgical strategies in the management of breast cancer.

Funding

This work was supported by grants from the Nantong Science and Technology Project (JCZ2022079), Nantong Health Commission Project (QA2021031, MSZ2023040) and National Natural Science Foundation of China (No. 82394430).

Impact of body mass index on pathological response after neoadjuvant chemotherapy: results from the I-SPY 2 trial

PURPOSE

Increased body mass index (BMI) has been associated with poor outcomes in women with breast cancer. We evaluated the association between BMI and pathological complete response (pCR) in the I-SPY 2 trial.

METHODS

978 patients enrolled in the I-SPY 2 trial 3/2010-11/2016 and had a recorded baseline BMI prior to treatment were included in the analysis. Tumor subtypes were defined by hormone receptor and HER2 status. Pretreatment BMI was categorized as obese (BMI ≥ 30 kg/m2), overweight (25 ≤ BMI < 30 kg/m2), and normal/underweight (< 25 kg/m2). pCR was defined as elimination of detectable invasive cancer in the breast and lymph nodes (ypT0/Tis and ypN0) at the time of surgery. Logistic regression analysis was used to determine associations between BMI and pCR. Event-free survival (EFS) and overall survival (OS) between different BMI categories were examined using Cox proportional hazards regression.

RESULTS

The median age in the study population was 49 years. pCR rates were 32.8% in normal/underweight, 31.4% in overweight, and 32.5% in obese patients. In univariable analysis, there was no significant difference in pCR with BMI. In multivariable analysis adjusted for race/ethnicity, age, menopausal status, breast cancer subtype, and clinical stage, there was no significant difference in pCR after neoadjuvant chemotherapy for obese compared with normal/underweight patients (OR = 1.1, 95% CI 0.68-1.63, P = 0.83), and for overweight compared with normal/underweight (OR = 1, 95% CI 0.64-1.47, P = 0.88). We tested for potential interaction between BMI and breast cancer subtype; however, the interaction was not significant in the multivariable model (P = 0.09). Multivariate Cox regression showed there was no difference in EFS (P = 0.81) or OS (P = 0.52) between obese, overweight, and normal/underweight breast cancer patients with a median follow-up time of 3.8 years.

CONCLUSION

We found no difference in pCR rates by BMI with actual body weight-based neoadjuvant chemotherapy in this biologically high-risk breast cancer population in the I-SPY2 trial.

Neoadjuvant Trebananib plus Paclitaxel-based Chemotherapy for Stage II/III Breast Cancer in the Adaptively Randomized I-SPY2 Trial-Efficacy and Biomarker Discovery

PURPOSE

The neutralizing peptibody trebananib prevents angiopoietin-1 and angiopoietin-2 from binding with Tie2 receptors, inhibiting angiogenesis and proliferation. Trebananib was combined with paclitaxel±trastuzumab in the I-SPY2 breast cancer trial.

PATIENTS AND METHODS

I-SPY2, a phase II neoadjuvant trial, adaptively randomizes patients with high-risk, early-stage breast cancer to one of several experimental therapies or control based on receptor subtypes as defined by hormone receptor (HR) and HER2 status and MammaPrint risk (MP1, MP2). The primary endpoint is pathologic complete response (pCR). A therapy "graduates" if/when it achieves 85% Bayesian probability of success in a phase III trial within a given subtype. Patients received weekly paclitaxel (plus trastuzumab if HER2-positive) without (control) or with weekly intravenous trebananib, followed by doxorubicin/cyclophosphamide and surgery. Pathway-specific biomarkers were assessed for response prediction.

RESULTS

There were 134 participants randomized to trebananib and 133 to control. Although trebananib did not graduate in any signature [phase III probabilities: Hazard ratio (HR)-negative (78%), HR-negative/HER2-positive (74%), HR-negative/HER2-negative (77%), and MP2 (79%)], it demonstrated high probability of superior pCR rates over control (92%-99%) among these subtypes. Trebananib improved 3-year event-free survival (HR 0.67), with no significant increase in adverse events. Activation levels of the Tie2 receptor and downstream signaling partners predicted trebananib response in HER2-positive disease; high expression of a CD8 T-cell gene signature predicted response in HR-negative/HER2-negative disease.

CONCLUSIONS

The angiopoietin (Ang)/Tie2 axis inhibitor trebananib combined with standard neoadjuvant therapy increased estimated pCR rates across HR-negative and MP2 subtypes, with probabilities of superiority >90%. Further study of Ang/Tie2 receptor axis inhibitors in validated, biomarker-predicted sensitive subtypes is warranted.

MRI-based tumor shrinkage patterns after early neoadjuvant therapy in breast cancer: correlation with molecular subtypes and pathological response after therapy

BACKGROUND

MRI-based tumor shrinkage patterns (TSP) after neoadjuvant therapy (NAT) have been associated with pathological response. However, the understanding of TSP after early NAT remains limited. We aimed to analyze the relationship between TSP after early NAT and pathological response after therapy in different molecular subtypes.

METHODS

We prospectively enrolled participants with invasive ductal breast cancers who received NAT and performed pretreatment DCE-MRI from September 2020 to August 2022. Early-stage MRIs were performed after the first (1st-MRI) and/or second (2nd-MRI) cycle of NAT. Tumor shrinkage patterns were categorized into four groups: concentric shrinkage, diffuse decrease (DD), decrease of intensity only (DIO), and stable disease (SD). Logistic regression analysis was performed to identify independent variables associated with pathologic complete response (pCR), and stratified analysis according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype.

RESULTS

344 participants (mean age: 50 years, 113/345 [33%] pCR) with 345 tumors (1 bilateral) had evaluable 1st-MRI or 2nd-MRI to comprise the primary analysis cohort, of which 244 participants with 245 tumors had evaluable 1st-MRI (82/245 [33%] pCR) and 206 participants with 207 tumors had evaluable 2nd-MRI (69/207 [33%] pCR) to comprise the 1st- and 2nd-timepoint subgroup analysis cohorts, respectively. In the primary analysis, multivariate analysis showed that early DD pattern (OR = 12.08; 95% CI 3.34-43.75; p < 0.001) predicted pCR independently of the change in tumor size (OR = 1.37; 95% CI 0.94-2.01; p = 0.106) in HR+/HER2- subtype, and the change in tumor size was a strong pCR predictor in HER2+ (OR = 1.61; 95% CI 1.22-2.13; p = 0.001) and triple-negative breast cancer (TNBC, OR = 1.61; 95% CI 1.22-2.11; p = 0.001). Compared with the change in tumor size, the SD pattern achieved a higher negative predictive value in HER2+ and TNBC. The statistical significance of complete 1st-timepoint subgroup analysis was consistent with the primary analysis.

CONCLUSION

The diffuse decrease pattern in HR+/HER2- subtype and stable disease in HER2+ and TNBC after early NAT could serve as additional straightforward and comprehensible indicators of treatment response.

TRIAL REGISTRATION

Trial registration at https://www.chictr.org.cn/ .

REGISTRATION NUMBER

ChiCTR2000038578, registered September 24, 2020.

Treatment of residual disease following neoadjuvant therapy in breast cancer

Substantial advances have been made in the systemic treatment of breast cancer with residual disease following neoadjuvant therapy. We reviewed recent and ongoing studies informing the standard clinical management of residual disease by subtype: HER2+, TNBC, and HR+/HER2-, as well as strategies for BRCA+ disease. We conclude with a discussion of ongoing clinical trials and current controversies regarding the treatment of residual disease in breast cancer.

Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial

Molecular subtyping of breast cancer is based mostly on HR/HER2 and gene expression-based immune, DNA repair deficiency, and luminal signatures. We extend this description via functional protein pathway activation mapping using pre-treatment, quantitative expression data from 139 proteins/phosphoproteins from 736 patients across 8 treatment arms of the I-SPY 2 Trial (ClinicalTrials.gov: NCT01042379). We identify predictive fit-for-purpose, mechanism-of-action-based signatures and individual predictive protein biomarker candidates by evaluating associations with pathologic complete response. Elevated levels of cyclin D1, estrogen receptor alpha, and androgen receptor S650 associate with non-response and are biomarkers for global resistance. We uncover protein/phosphoprotein-based signatures that can be utilized both for molecularly rationalized therapeutic selection and for response prediction. We introduce a dichotomous HER2 activation response predictive signature for stratifying triple-negative breast cancer patients to either HER2 or immune checkpoint therapy response as a model for how protein activation signatures provide a different lens to view the molecular landscape of breast cancer and synergize with transcriptomic-defined signatures.

Construction of a risk stratification model integrating ctDNA to predict response and survival in neoadjuvant-treated breast cancer

BACKGROUND

The pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) of breast cancer is closely related to a better prognosis. However, there are no reliable indicators to accurately identify which patients will achieve pCR before surgery, and a model for predicting pCR to NAC is required.

METHODS

A total of 269 breast cancer patients in Shandong Cancer Hospital and Liaocheng People's Hospital receiving anthracycline and taxane-based NAC were prospectively enrolled. Expression profiling using a 457 cancer-related gene sequencing panel (DNA sequencing) covering genes recurrently mutated in breast cancer was carried out on 243 formalin-fixed paraffin-embedded tumor biopsies samples before NAC from 243 patients. The unique personalized panel of nine individual somatic mutation genes from the constructed model was used to detect and analyze ctDNA on 216 blood samples. Blood samples were collected at indicated time points including before chemotherapy initiation, after the 1st NAC and before the 2nd NAC cycle, during intermediate evaluation, and prior to surgery. In this study, we characterized the value of gene profile mutation and circulating tumor DNA (ctDNA) in combination with clinical characteristics in the prediction of pCR before surgery and investigated the prognostic prediction. The median follow-up time for survival analysis was 898 days.

RESULTS

Firstly, we constructed a predictive NAC response model including five single nucleotide variant (SNV) mutations (TP53, SETBP1, PIK3CA, NOTCH4 and MSH2) and four copy number variation (CNV) mutations (FOXP1-gain, EGFR-gain, IL7R-gain, and NFKB1A-gain) in the breast tumor, combined with three clinical factors (luminal A, Her2 and Ki67 status). The tumor prediction model showed good discrimination of chemotherapy sensitivity for pCR and non-pCR with an AUC of 0.871 (95% CI, 0.797-0.927) in the training set, 0.771 (95% CI, 0.649-0.883) in the test set, and 0.726 (95% CI, 0.556-0.865) in an extra test set. This tumor prediction model can also effectively predict the prognosis of disease-free survival (DFS) with an AUC of 0.749 at 1 year and 0.830 at 3 years. We further screened the genes from the tumor prediction model to establish a unique personalized panel consisting of 9 individual somatic mutation genes to detect and analyze ctDNA. It was found that ctDNA positivity decreased with the passage of time during NAC, and ctDNA status can predict NAC response and metastasis recurrence. Finally, we constructed the chemotherapy prediction model combined with the tumor prediction model and pretreatment ctDNA levels, which has a better prediction effect of pCR with the AUC value of 0.961.

CONCLUSIONS

In this study, we established a chemotherapy predictive model with a non-invasive tool that is built based on genomic features, ctDNA status, as well as clinical characteristics for predicting pCR to recognize the responders and non-responders to NAC, and also predicting prognosis for DFS in breast cancer. Adding pretreatment ctDNA levels to a model containing gene profile mutation and clinical characteristics significantly improves stratification over the clinical variables alone.