Neoadjuvant Chemotherapy In Breast Cancer Research Articles

Prediction of response to neoadjuvant chemotherapy in breast cancer with recurrent neural networks and raw ultrasound signals

Objective. Prediction of the response to neoadjuvant chemotherapy (NAC) in breast cancer is important for patient outcomes. In this work, we propose a deep learning based approach to NAC response prediction in ultrasound (US) imaging. Approach. We develop recurrent neural networks that can process serial US imaging data to predict chemotherapy outcomes. We present models that can process either raw radio-frequency (RF) US data or regular US images. The proposed approach is evaluated based on 204 sequences of US data from 51 breast cancers. Each sequence included US data collected before the chemotherapy and after each subsequent dose, up to the 4th course. We investigate three pre-trained convolutional neural networks (CNNs) as back-bone feature extractors for the recurrent network. The CNNs were pre-trained using raw US RF data, US b-mode images and RGB images from the ImageNet dataset. The first two networks were developed using US data collected from malignant and benign breast masses. Main results. For the pre-treatment data, the better performing network, with back-bone CNN pre-trained on US images, achieved area under the receiver operating curve (AUC) of 0.81 (±0.04). Performance of the recurrent networks improved with each course of the chemotherapy. For the 4th course, the better performing model, based on the CNN pre-trained with RGB images, achieved AUC value of 0.93 (±0.03). Statistical analysis based on the DeLong test presented that there were no significant differences in AUC values between the pre-trained networks at each stage of the chemotherapy (p-values > 0.05). Significance. Our study demonstrates the feasibility of using recurrent neural networks for the NAC response prediction in breast cancer US.

Association of Residual Ductal Carcinoma In Situ With Breast Cancer Recurrence in the Neoadjuvant I-SPY2 Trial

Pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer strongly correlates with overall survival and has become the standard end point in neoadjuvant trials. However, there is controversy regarding whether the definition of pCR should exclude or permit the presence of residual ductal carcinoma in situ (DCIS). To examine the association of residual DCIS in surgical specimens after neoadjuvant chemotherapy for breast cancer with survival end points to inform standards for the assessment of pathologic complete response. The study team analyzed the association of residual DCIS after NAC with 3-year event-free survival (EFS), distant recurrence-free survival (DRFS), and local-regional recurrence (LRR) in the I-SPY2 trial, an adaptive neoadjuvant platform trial for patients with breast cancer at high risk of recurrence. This is a retrospective analysis of clinical specimens and data from the ongoing I-SPY2 adaptive platform trial of novel therapeutics on a background of standard of care for early breast cancer. I-SPY2 participants are adult women diagnosed with stage II/III breast cancer at high risk of recurrence. Participants were randomized to receive taxane and anthracycline-based neoadjuvant therapy with or without 1 of 10 investigational agents, followed by definitive surgery. The presence of DCIS and EFS, DRFS, and LRR. The study team identified 933 I-SPY2 participants (aged 24 to 77 years) with complete pathology and follow-up data. Median follow-up time was 3.9 years; 337 participants (36%) had no residual invasive disease (residual cancer burden 0, or pCR). Of the 337 participants with pCR, 70 (21%) had residual DCIS, which varied significantly by tumor-receptor subtype; residual DCIS was present in 8.5% of triple negative tumors, 15.6% of hormone-receptor positive tumors, and 36.6% of ERBB2-positive tumors. Among those participants with pCR, there was no significant difference in EFS, DRFS, or LRR based on presence or absence of residual DCIS. The analysis supports the definition of pCR as the absence of invasive disease after NAC regardless of the presence or absence of DCIS. ClinicalTrials.gov Identifier NCT01042379.

Diagnostic Accuracy of Radioactive Iodine Seed Placement in the Axilla With Sentinel Lymph Node Biopsy After Neoadjuvant Chemotherapy in Node-Positive Breast Cancer

Several less-invasive staging procedures have been proposed to replace axillary lymph node dissection (ALND) after neoadjuvant chemotherapy (NAC) in patients with initially clinically node-positive (cN+) breast cancer, but these procedures may fail to detect residual disease. Owing to the lack of high-level evidence, it is not yet clear which procedure is most optimal to replace ALND. To determine the diagnostic accuracy of radioactive iodine seed placement in the axilla with sentinel lymph node biopsy (RISAS), a targeted axillary dissection procedure. This was a prospective, multicenter, noninferiority, diagnostic accuracy trial conducted from March 1, 2017, to December 31, 2019. Patients were included within 14 institutions (general, teaching, and academic) throughout the Netherlands. Patients with breast cancer clinical tumor categories 1 through 4 (cT1-4; tumor diameter <2 cm and up to >5 cm or extension to the chest wall or skin) and pathologically proven positive axillary lymph nodes (ie, clinical node categories cN1, metastases to movable ipsilateral level I and/or level II axillary nodes; cN2, metastases to fixed or matted ipsilateral level I and/or level II axillary nodes; cN3b, metastases to ipsilateral level I and/or level II axillary nodes with metastases to internal mammary nodes) who were treated with NAC were eligible for inclusion. Data were analyzed from July 2020 to December 2021. Pre-NAC, the marking of a pathologically confirmed positive axillary lymph node with radioactive iodine seed (MARI) procedure, was performed and after NAC, sentinel lymph node biopsy (SLNB) combined with excision of the marked lymph node (ie, RISAS procedure) was performed, followed by ALND. The identification rate, false-negative rate (FNR), and negative predictive value (NPV) were calculated for all 3 procedures: RISAS, SLNB, and MARI. The noninferiority margin of the observed FNR was 6.25% for the RISAS procedure. A total of 212 patients (median [range] age, 52 [22-77] years) who had cN+ breast cancer underwent the RISAS procedure and ALND. The identification rate of the RISAS procedure was 98.2% (223 of 227). The identification rates of SLNB and MARI were 86.4% (197 of 228) and 94.1% (224 of 238), respectively. FNR of the RISAS procedure was 3.5% (5 of 144; 90% CI, 1.38-7.16), and NPV was 92.8% (64 of 69; 90% CI, 85.37-97.10), compared with an FNR of 17.9% (22 of 123; 90% CI, 12.4%-24.5%) and NPV of 72.8% (59 of 81; 90% CI, 63.5%-80.8%) for SLNB and an FNR of 7.0% (10 of 143; 90% CI, 3.8%-11.6%) and NPV of 86.3% (63 of 73; 90% CI, 77.9%-92.4%) for the MARI procedure. In a subgroup of 174 patients in whom SLNB and the MARI procedure were successful and ALND was performed, FNR of the RISAS procedure was 2.5% (3 of 118; 90% CI, 0.7%-6.4%), compared with 18.6% (22 of 118; 90% CI, 13.0%-25.5%) for SLNB (P < .001) and 6.8% (8 of 118; 90% CI, 3.4%-11.9%) for the MARI procedure (P = .03). Results of this diagnostic study suggest that the RISAS procedure was the most feasible and accurate less-invasive procedure for axillary staging after NAC in patients with cN+ breast cancer.

MRI Images-Based Evaluation of Efficacy of Neoadjuvant Chemotherapy for Breast Cancer and Its Effect on Depression and Immune Function of Patients.

The aim of this study was to investigate the therapeutic value of neoadjuvant chemotherapy for breast cancer (BC) based on magnetic resonance imaging (MRI) and to evaluate its effect on depressive mood and immune function in patients. 70 female patients with BC who received neoadjuvant chemotherapy were selected for the experiment to comprehensively evaluate the MRI image findings, immune cell levels before and after chemotherapy, as well as the depression score and influencing factors of the patients during chemotherapy. The results showed that 49 patients (70%) responded to treatment, and MRI showed that the breast mass after chemotherapy was significantly reduced. 55 patients experienced depressive mood during chemotherapy, and the incidence of depression was 78.5%. Adverse symptoms such as pain, worry, sadness, vertigo, and nausea are important factors in the development of depression in patients. However, there were no significant changes in the levels of CD4+, CD8+, CD4+/CD8+, and killer cells before and after chemotherapy, and only B cells showed a significant decrease (9.78 ± 3.65% and 7.63 ± 3.65%) (P < 0.05). In summary, neoadjuvant chemotherapy can effectively shrink the breast mass and provide favorable conditions for subsequent surgery, and its clinical efficacy can be more accurately assessed by MRI. Neoadjuvant chemotherapy has little effect on the immune function of patients, but it will promote patients to experience depression. It provides a reference for the clinical treatment and prognosis of BC patients.

Circulating Tumor DNA After Neoadjuvant Chemotherapy in Breast Cancer Is Associated With Disease Relapse.

Detection of circulating tumor DNA (ctDNA) after neoadjuvant chemotherapy in patients with early-stage breast cancer may allow for early detection of relapse. In this study, we analyzed ctDNA using a personalized, tumor-informed multiplex polymerase chain reaction-based next-generation sequencing assay. Plasma samples (n = 157) from 44 patients were collected before neoadjuvant therapy (baseline), after neoadjuvant therapy and before surgery (presurgery), and serially postsurgery including a last follow-up sample. The primary end point was event-free survival (EFS) analyzed using Cox regression models. Thirty-eight (86%), 41 (93%), and 38 (86%) patients had baseline, presurgical, and last follow-up samples, respectively. Twenty patients had hormone receptor-positive/human epidermal growth factor receptor 2-negative, 13 had triple-negative breast cancer, and 11 had human epidermal growth factor receptor 2-positive disease. Baseline ctDNA detection was observed in 22/38 (58%) patients and was significantly associated with Ki67 > 20% (P = .036) and MYC copy-number gain (P = .0025, false discovery rate = 0.036). ctDNA detection at presurgery and at last follow-up was observed in 2/41 (5%) and 2/38 (5%) patients, respectively. Eight relapses (seven distant and one local) were noted (median follow-up 3.03 years [range, 0.39-5.85 years]). After adjusting for pathologic complete response (pCR), ctDNA detection at presurgery and at last follow-up was associated with shorter EFS (hazard ratio [HR], 53; 95% CI, 4.5 to 624; P < .01, and HR, 31; 95% CI, 2.7 to 352; P < .01, respectively). Association between baseline detection and EFS was not observed (HR, 1.4; 95% CI, 0.3 to 5.9; P = .67). The presence of ctDNA after neoadjuvant chemotherapy is associated with relapse in early-stage breast cancer, supporting interventional trials for testing the clinical utility of ctDNA monitoring in this setting.

An Alternatively Spliced p62 Isoform Confers Resistance to Chemotherapy in Breast Cancer.

Resistance to NAC in breast cancer is driven by a novel p62 mRNA isoform that escapes miRNA-mediated repression and leads to increased p62 protein expression.

Body composition change during neoadjuvant chemotherapy for breast cancer.

BackgroundSarcopenia is receiving attention in oncology as a predictor of increased chemotherapy toxicities. Research into body composition change during neoadjuvant chemotherapy for breast cancer is both urgently needed and generally lacking. This study assessed sarcopenia prevalence before and after neoadjuvant chemotherapy using CT imaging, evaluated body composition changes during neoadjuvant chemotherapy, and determined predictors of sarcopenia status after neoadjuvant chemotherapy for breast cancer.Materials and MethodsIn this retrospective, descriptive study, we used data collected from 2017 to 2020 to measure body composition parameters on cross-sectional CT slices for 317 Korean women with breast cancer patients before and at completion of neoadjuvant chemotherapy. Changes in skeletal muscle index, visceral fat index, subcutaneous fat index, and sarcopenia were assessed and correlated, and multivariate logistic regression was conducted to identify predictive factors associated with sarcopenia status at completion of neoadjuvant chemotherapy.ResultsOf the 80 breast cancer patients (25.2%) who had sarcopenia before beginning neoadjuvant chemotherapy, 64 (80.0%) retained their sarcopenia status after chemotherapy. Weight, body mass index, body surface area, and visceral fat index showed significant increases after neoadjuvant chemotherapy; notably, only skeletal muscle index significantly decreased, showing a reduction of 0.44 cm2/m2 (t (316) = 2.15, p <.5). Lower skeletal muscle index at baseline was associated with greater loss of muscle mass during neoadjuvant chemotherapy (r = −.24, p <.001). Multivariate logistic regression showed that baseline sarcopenia status was the only significant predictor of sarcopenia status after neoadjuvant chemotherapy (p <.001). Specifically, the log odds of sarcopenia after neoadjuvant chemotherapy were 3.357 higher in the baseline sarcopenia group than in the group without baseline sarcopenia (β = 3.357, p <.001).ConclusionSarcopenia during neoadjuvant chemotherapy can be obscured by an increasing proportion of fat in body composition if clinical assessment focuses on only body mass index or body surface area rather than muscle mass. For breast cancer patients who have sarcopenia when they begin neoadjuvant chemotherapy, the risk of muscle mass loss during treatment is alarmingly high. To reduce masking of muscle mass loss during treatment, comprehensive evaluation of body composition, beyond body surface area assessment, is clearly needed.

Predictive Biomarkers of Response to Neoadjuvant Chemotherapy in Breast Cancer: Current and Future Perspectives for Precision Medicine.

Simple SummaryDespite the increased use of neoadjuvant chemotherapy in the early setting of breast cancer, there is a clinical need for predictive markers of response in daily practice. In the era of precision medicine and personalized treatment, new predictive markers that enable the better selection of patients for specific therapies are required. In this review, we describe the current knowledge about the molecular biomarkers used for clinical decision making for patients with breast cancer. We also report how microenvironment-driven intratumoral heterogeneity may influence the validation of biomarkers useful for precision medicine. We provide an overview of promising biomarkers, including pathological markers, genetic signatures, radiological techniques and liquid biopsies, with a great potential to be implemented in routine clinical practice. Finally, we discuss the use of relevant pre-clinical models of breast cancer to integrate microenvironmental specificities in order to identify and validate reliable biomarkers of (non-)response to neoadjuvant chemotherapy.Pathological complete response (pCR) after neoadjuvant chemotherapy in patients with early breast cancer is correlated with better survival. Meanwhile, an expanding arsenal of post-neoadjuvant treatment strategies have proven beneficial in the absence of pCR, leading to an increased use of neoadjuvant systemic therapy in patients with early breast cancer and the search for predictive biomarkers of response. The better prediction of response to neoadjuvant chemotherapy could enable the escalation or de-escalation of neoadjuvant treatment strategies, with the ultimate goal of improving the clinical management of early breast cancer. Clinico-pathological prognostic factors are currently used to estimate the potential benefit of neoadjuvant systemic treatment but are not accurate enough to allow for personalized response prediction. Other factors have recently been proposed but are not yet implementable in daily clinical practice or remain of limited utility due to the intertumoral heterogeneity of breast cancer. In this review, we describe the current knowledge about predictive factors for response to neoadjuvant chemotherapy in breast cancer patients and highlight the future perspectives that could lead to the better prediction of response, focusing on the current biomarkers used for clinical decision making and the different gene signatures that have recently been proposed for patient stratification and the prediction of response to therapies. We also discuss the intratumoral phenotypic heterogeneity in breast cancers as well as the emerging techniques and relevant pre-clinical models that could integrate this biological factor currently limiting the reliable prediction of response to neoadjuvant systemic therapy.

Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer.

There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are less likely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied artificial intelligence to comprehensive metabolic profiles to identify additional metabolites associated with treatment response. Using a deep learning model (DLM), a metabolite panel consisting of two polyamines as well as nine additional metabolites was developed for improved prediction of RCB-II/III. The DLM has potential clinical value for identifying TNBC patients who are unlikely to respond to NACT and who may benefit from other treatment modalities.

Patients' Experiences of Care With or Without the Support of an Interactive App During Neoadjuvant Chemotherapy for Breast Cancer: Interview Study.

BackgroundNeoadjuvant chemotherapy (NACT) is often recommended for patients with breast cancer with more aggressive tumor characteristics. As with all chemotherapies, they can cause substantially disturbing symptoms. Most patients receive their treatment as outpatients, which means that they must take responsibility for self-care and management of symptoms at home for a long period. Patients with breast cancer undergoing chemotherapy may not receive sufficient support for management of treatment-related symptoms. For patients undergoing NACT, it has been concluded that information and supportive needs are not always met. In our previous study, the use of mobile health to support patients with breast cancer undergoing NACT reduced symptoms during treatment with the support of an interactive app. Therefore, it is important to investigate how patients experience their care and explore any specific contribution that the app may have brought in care.ObjectiveThis study aims to explore patients’ experiences of care with or without the support of an interactive app during NACT for breast cancer.MethodsThis qualitative study was part of a larger randomized controlled trial and included 40 individual face-to-face interviews conducted with patients in both intervention and control groups after the end of NACT. The interviews were audio recorded, and the data were analyzed inductively using thematic analysis.ResultsNo major differences in experience of care were observed between the groups. A total of 4 overarching themes emerged. In the first theme, The health care context, patients described care as assessible, although sometimes there was a lack of time and continuity with nurses. In the second theme, Being a recipient of care, it emerged that the patients experienced a warm and positive atmosphere at the clinics. In the third theme, Taking an active role as a patient, patients described being active in searching for information and various ways of participation in their own care. In the fourth theme, The value of the app, patients who had used the app experienced it as a complementary source of information, creating a sense of security. Using the app provided patients with the support of being contacted by a nurse if needed, enabled self-care, and facilitated the planning of daily activities.ConclusionsOverall, patients’ experiences of care were similar and mostly positive. However, for patients using the app, it provided additional support for information and self-care and enhanced participation in their own care. The easy access to a nurse gave patients a sense of security. The findings suggest integrating an interactive app as a complement to standard care to support patients with breast cancer during treatment.International Registered Report Identifier (IRRID)RR2-DOI: 10.1186/s12885-017-3450-y

Incidence of Brain Metastases in Women Treated With Neoadjuvant Chemotherapy for Breast Cancer: Implications for Screening

PurposePatients with metastatic breast cancer may develop brain metastases. Our study identified high-risk patients to refine selection criteria for BM screening approaches. PatientsWe reviewed breast cancer patients treated with neoadjuvant chemotherapy (NAC) at a single university center between 2005 and 2019. MethodsCompeting risks analysis was performed with the Fine and Gray model to analyze the cumulative incidence of BM and loco-regional recurrence. Overall survival (OS) and progression-free survival (PFS) were calculated using Kaplan-Meier and log-rank tests. Multivariable analysis was performed with Cox proportional hazards regression to identify factors predictive for development of BM. Statistical significance was determined as a 2-sided P value of <.05. ResultsIn total, 112 patients experienced distant failure (DF) and 49 patients developed BM. Twenty patients with BM (41%) presented with symptoms requiring craniotomy +/- whole brain radiation treatment. Patients with BM were significantly more likely to have local (P < .01) and regional (P < .01) failure. On multivariable analysis, age <40 years (P = .011), presence of lung metastases (P < .0001), and residual nodal disease with >4 lymph nodes positive after NAC (P = .024) all predicted for increased likelihood of BM. Patients with these criteria had higher likelihoods of having BM (P = .013) and worse PFS (P = .044). On multivariable analysis for OS, presence of lung metastases was the most significant predictor of poor outcome (P < .0001). ConclusionWe propose a study of screening brain MRI for young (<40 years) patients with breast cancer receiving NAC and patients who develop metastatic disease post-NAC, especially those with lung involvement.

Efficacy Evaluation of Neoadjuvant Chemotherapy in Breast Cancer by MRI.

Breast cancer is a highly harmful malignancy, which often causes great distress to patients and seriously affects their physical and mental health. Breast cancer causes patients to experience decreased appetite, decreased eating, and indigestion, which in turn leads to malnutrition, body wasting, resistance, immune compromise, progressive anemia, cachexia, and, as a result, severe secondary infections. To investigate the efficacy evaluation of neoadjuvant chemotherapy in breast cancer by MRI, forty-eight subjects treated at the hospital from June 2014 to August 2019 were recruited. After the neoadjuvant chemotherapy, the patients were divided into two groups based on the results of histopathological examination, namely, the ineffective group (n = 14) and the effective group (n = 34). Changes in MRI indicators were compared between the two groups before and after the neoadjuvant chemotherapy. The maximum diameter of lesions decreased significantly after the neoadjuvant chemotherapy than before. The apparent diffusion coefficient (ADC) increased considerably, and the time-intensity curve (TIC) showed a transition from type III to type II/I and from type II to type I. MRI can indicate the maximum diameter of the breast cancer lesion, ADC, and TIC type. Therefore, it can be used to evaluate the efficacy of neoadjuvant chemotherapy for breast cancer and be widely applied in clinical practice.

ASO Visual Abstract: A Noninvasive Tool Based onMagnetic Resonance ImagingRadiomics for the Preoperative Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

ASO Visual Abstract: A Noninvasive Tool Based onMagnetic Resonance ImagingRadiomics for the Preoperative Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

Feasibility of targeted axillary dissection for de-escalation of surgical treatment after neoadjuvant chemotherapy in breast cancer

BackgroundTargeted axillary dissection, which combines sentinel lymph node biopsy with removal of the proven involved node noted during the staging process, has been shown to improve axillary staging and decrease false negative rates after neoadjuvant chemotherapy in patients with breast cancer. Objective(s)The main goal of this study was to assess the ability to identify and remove the clipped node and the false negative rate of targeted axillary dissection. MethodsWe performed a prospective study among patients with biopsy-confirmed nodal metastases who received neoadjuvant chemotherapy. A clip was placed on the sample node prior systemic therapy. After neoadjuvant chemotherapy, all patients underwent sentinel lymph node biopsy (dual tracer), localization and excision of the clipped node and axillary lymph node dissection. The clipped node was preoperatively localized in all cases placing an iodine-125 seed guided by ultrasound. The pathology of the sentinel nodes and clipped node was compared with other nodes. ResultsA total of 455 patients with invasive breast cancer were studied. Of the 148 patients with NAC, 32 met the eligibility criteria and were enrolled in the study. Mean age at diagnosis was 52.3 years. Systematic lymphadenectomy was performed in all patients, with an average of 14.3 lymph nodes removed. Detection rate of the clipped node alone was 96.9%, and 100% for targeted axillary dissection. Ability of clipped node alone to predict nodal status showed a FNR of 10,5% while SLNB alone performed by dual tracer and targeted axillary dissection, showed FNRs of 5.3% and 5.0%, respectively. Sentinel lymph nodes matched clipped node in 23 patients (74.2%). Conclusion (s)In node positive breast cancer patients, targeted axillary dissection is a reliably approach for axillary staging after neoadjuvant chemotherapy. The preoperative location of the clipped node is mandatory to increase the detection rate and optimize the results of the technique.

ASO Visual Abstract: Neoadjuvant Chemotherapy for Breast Cancer in the Elderly-Are We Accomplishing Our Treatment Goals?

ASO Visual Abstract: Neoadjuvant Chemotherapy for Breast Cancer in the Elderly-Are We Accomplishing Our Treatment Goals?

Evaluating the Role of Circulating MicroRNAs to Aid Therapeutic Decision Making for Neoadjuvant Chemotherapy in Breast Cancer: A Prospective, Multicenter Clinical Trial.

Objective:To evaluate whether circulating micro ribonucleic acids (miRNAs) predict response to neoadjuvant chemotherapy (NAC) and inform decision-making in breast cancer patients.Introduction:Deciphering response to NAC remains a challenge. Those unlikely to respond may benefit from NAC de-escalation before completion, while “responders” should complete treatment. Establishing biomarkers which identify response to NAC is imperative to personalize treatment strategies. miRNAs are small noncoding RNA molecules which modulate genetic expression. miRNAs are believed to inform response to NAC.Methods:This prospective, multicenter trial (NCT01722851) recruited 120 patients treated with NAC across 8 Irish treatment sites. Predetermined miRNAs were quantified from patient whole bloods using relative quantification polymerase chain reactiond. Venous sampling was performed at diagnosis and midway during NAC. Trends in miRNA expression between timepoints were correlated with treatment response. Data analysis was performed using R 3.2.3.Results:A total of 120 patients were included (median age: 55 years). Overall, 49.2% had luminal breast cancers (59/120), 17.5% luminal B (L/HER2) (21/120), 12.5% human epidermal growth factor receptor-2 positive (HER2+) (15/120), and 20.8% triple negative disease (25/120). In total, 46.7% of patients responded to NAC (56/125) and 26.7% achieved a pathological complete response (pCR) (32/120). For patients with L/HER2, increased Let-7a predicted response to NAC (P=0.049), while decreased miR-145 predicted response to NAC in HER2+ (P=0.033). For patients with luminal breast cancers, reduced Let-7a predicted achieving a pCR (P=0.037) and reduced miR-145 predicted achieving a pCR to NAC in HER2+ (P=0.027).Conclusions:This study illustrates the potential value of circulatory miRNA measurement in predicting response to NAC. Further interrogation of these findings may see miRNAs personalize therapeutic decision-making for patients undergoing NAC for early breast cancer.

Neoadjuvant Chemotherapy for Breast Cancer In the Elderly: Are We Accomplishing Our Treatment Goals?

Rates of downstaging and tolerability to NAC in women age ≥70 years with operable breast cancer have not been well studied. We sought to compare downstaging rates and NAC completion between women age 50-69 years and age ≥70 years. Consecutively treated women age ≥50 years with cT1-3N0-1 breast cancer receiving NAC followed by surgery from November 2013 to April 2020 were studied. Rates of downstaging from breast-conserving surgery (BCS)-ineligible to BCS-eligible and avoidance of axillary dissection (ALND) in cN1 patients were compared between patients age 50-69 and ≥70 years. NAC regimens and rates of completion also were assessed. Overall, 651 women, age ≥50 years, with 668 cT1-3N0-1 breast cancers that were treated with NAC, were identified; 75 (11.1%) were age ≥70 years. Patients age ≥70 years were less likely to have lobular cancers (5% vs. 10%, p=0.03), receive an anthracycline-based regimen (69% vs. 93%, p<0.001), and complete their entire prescribed regimen (57% vs. 78%, p<0.001). Of 312 BCS-ineligible patients eligible for downstaging, conversion rates to BCS-eligibility were similar between age groups (72% [≥70] vs. 74% [50-69], p>0.9). Women age ≥70 years who converted to BCS-eligible post-NAC were more likely to undergo BCS than younger patients (93% vs. 74%, p=0.04). Of 390 cN1 patients, 162 (42%) achieved a nodal pCR; ALND avoidance was similar between age groups (43% [≥70] vs. 42% [50-69], p>0.9). While patients age ≥70 years received less anthracycline-based NAC and were less likely to complete their prescribed regimen, they experienced high rates of breast and axillary downstaging, similar to younger patients, suggesting that well-selected elderly patients can safely receive NAC with substantial clinical benefit.

Effect of Neoadjuvant Chemotherapy on Angiogenesis and Cell Proliferation of Breast Cancer Evaluated by Dynamic Enhanced Magnetic Resonance Imaging.

Background Breast cancer is the uncontrolled proliferation of breast epithelial cells under the action of various carcinogenic factors. The evaluation of early efficacy of neoadjuvant chemotherapy for breast cancer is helpful to change the treatment plan in time. On this basis, dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) was used to evaluate the effects of neoadjuvant chemotherapy on angiogenesis and cell proliferation in breast cancer. Objective To evaluate the effect of neoadjuvant chemotherapy on angiogenesis and cell proliferation of breast cancer by dynamic enhanced DCE-MRI. Method 80 breast cancer patients were divided into the routine chemotherapy group (3 cycles) and neoadjuvant chemotherapy groups (3 cycles) of 40 cases each from January 2018 to June 2021. Based on conventional imaging, DCE-MRI was performed with Intera Achieva 3.0 TMR superconducting MR scanner before and after treatment. The quantitative indexes, MRI parameters, cell proliferation expression, and DCE-MRI angiogenesis were compared between the two groups. Result The inhibition rate, Vepost, Ktranspre, ADC, Bax, Alexi, and Aurora in the neoadjuvant chemotherapy group were significantly higher than those in the conventional chemotherapy group (P < 0.05), while Kep, Ktrans, and Nek2 were significantly lower than those in the conventional chemotherapy group (P < 0.05). Vepre (cm3), Ktranspre (ml/min/100 cm3), and Ve had no significant difference (P > 0.05). Conclusion The quantitative parameters, MRI parameters, proliferation, and expression of DCE-MRI in breast cancer patients with different chemotherapy regimens are quite different. They can be applied to the diagnosis of neoadjuvant chemotherapy in breast cancer patients with angiogenesis and cell proliferation.

O055 Tenascin-C Expression and distribution following neoadjuvant chemotherapy for breast cancer

Abstract Introduction Tenascin-C (TNC), a matricellular glycoprotein linked to breast cancer invasion and metastasis, has never been studied exclusively in post-neoadjuvant chemotherapy (NACT) patients. This retrospective cohort analysis investigates whether TNC is expressed post-NACT and establishes potential links with patients’ clinicopathological characteristics. Methods Twenty-four invasive breast cancer patients who had received NACT and surgery were recruited from a single centre. The distribution and intensity of TNC expression in paraffin embedded breast specimens were analysed using a pre-determined scoring system. These scores were then correlated with the patients’ clinicopathological characteristics and ‘PREDICT’ scores. Results TNC was well expressed by the post-NACT cancer tissue, albeit more strongly in the tumour-associated stroma than in the tumour cells. More pronounced expression overall was seen in PR-positive patients, but greater TNC expression in the tumour invasive border was linked to ER-negativity, TNBC, and lack of lymph node involvement. A greater TNC expression in the central region of the tumour was linked to a better pathologic response to NACT. The degree of TNC expression was not statistically different between areas of response to NACT and areas with residual tumour. Patients with better post-surgical ‘PREDICT 10’ scores had greater TNC expression in the tumour. Conclusion This study shows that TNC remains well-expressed in the stroma of post-NACT breast cancer tissue, and may be linked to tumour phenotype, pathologic response to NACT, and prognosis. There are many potential clinical applications, including using TNC as a: (1) therapeutic target, (2) predictor of responsiveness to NACT and/or adjuvant therapies, (3) prognostic marker. Take-home message Tenascin-C is well-expressed in post-NACT breast cancer tissue obtained at the point of margin resection, and the degree and distribution of its expression is linked to tumour phenotype, pathologic response to NACT, and prognosis. This has potentially impactful implications for its use as a therapeutic target, predictor of responsiveness to chemotherapy, and prognostic marker.

Machine Learning Models and Multiparametric Magnetic Resonance Imaging for the Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer

Simple SummaryAchieving pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer (BC) is crucial, as pCR is a surrogate marker for survival. However, only 10–30% of patients achieve it. It is therefore essential to develop tools that enable to accurately predict response. Recently, different studies have demonstrated the feasibility of applying machine learning approaches to non-invasively predict pCR before NAC administration from magnetic resonance imaging (MRI) data. Some of those models are based on radiomics, an emerging field that allows the automated extraction of clinically relevant information from radiologic images. However, the research is still at an early stage and further data are needed. Here, we determine whether the combination of imaging data (radiomic features and perfusion/diffusion imaging biomarkers) extracted from multiparametric MRIs and clinical variables can improve pCR prediction to NAC compared to models only including imaging or clinical data, potentially avoiding unnecessary treatment and delays to surgery.Background: Most breast cancer (BC) patients fail to achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). The aim of this study was to evaluate whether imaging features (perfusion/diffusion imaging biomarkers + radiomic features) extracted from pre-treatment multiparametric (mp)MRIs were able to predict, alone or in combination with clinical data, pCR to NAC. Methods: Patients with stage II-III BC receiving NAC and undergoing breast mpMRI were retrospectively evaluated. Imaging features were extracted from mpMRIs performed before NAC. Three different machine learning models based on imaging features, clinical data or imaging features + clinical data were trained to predict pCR. Confusion matrices and performance metrics were obtained to assess model performance. Statistical analyses were conducted to evaluate differences between responders and non-responders. Results: Fifty-eight patients (median [range] age, 52 [45–58] years) were included, of whom 12 showed pCR. The combined model improved pCR prediction compared to clinical and imaging models, yielding 91.5% of accuracy with no false positive cases and only 17% false negative results. Changes in different parameters between responders and non-responders suggested a possible increase in vascularity and reduced tumour heterogeneity in patients with pCR, with the percentile 25th of time-to-peak (TTP), a classical perfusion parameter, being able to discriminate both groups in a 75% of the cases. Conclusions: A combination of mpMRI-derived imaging features and clinical variables was able to successfully predict pCR to NAC. Specific patient profiles according to tumour vascularity and heterogeneity might explain pCR differences, where TTP could emerge as a putative surrogate marker for pCR.