First Cycle Of Neoadjuvant Chemotherapy Research Articles

Mass spectrometry-based analysis of eccrine sweat supports predictive, preventive and personalised medicine in a cohort of breast cancer patients in Austria

ObjectiveMetabolomics measurements of eccrine sweat may provide novel and relevant biomedical information to support predictive, preventive and personalised medicine (3PM). However, only limited data is available regarding metabolic alterations accompanying chemotherapy of breast cancer patients related to residual cancer burden (RCB) or therapy response. Here, we have applied Metabo-Tip, a non-invasive metabolomics assay based on the analysis of eccrine sweat from the fingertips, to investigate the feasibility of such an approach, especially with respect to drug monitoring, assessing lifestyle parameters and stratification of breast cancer patients.MethodsEccrine sweat samples were collected from breast cancer patients (n = 9) during the first cycle of neoadjuvant chemotherapy at four time points in this proof-of-concept study at a Tertiary University Hospital. Metabolites in eccrine sweat were analysed using mass spectrometry. Blood plasma samples from the same timepoints were also collected and analysed using a validated targeted metabolomics kit, in addition to proteomics and fatty acids/oxylipin analysis.ResultsA total of 247 exogenous small molecules and endogenous metabolites were identified in eccrine sweat of the breast cancer patients. Cyclophosphamide and ondansetron were successfully detected and monitored in eccrine sweat of individual patients and accurately reflected the administration schedule. The non-essential amino acids asparagine, serine and proline, as well as ornithine were significantly regulated in eccrine sweat and blood plasma over the therapy cycle. However, their distinct time-dependent profiles indicated compartment-specific distributions. Indeed, the metabolite composition of eccrine sweat seems to largely resemble the composition of the interstitial fluid. Plasma proteins and fatty acids/oxylipins were not affected by the first treatment cycle. Individual smoking habit was revealed by the simultaneous detection of nicotine and its primary metabolite cotinine in eccrine sweat. Stratification according to RCB revealed pronounced differences in the metabolic composition of eccrine sweat in these patients at baseline, e.g., essential amino acids, possibly due to the systemic contribution of breast cancer and its impact on metabolic turnover.ConclusionMass spectrometry-based analysis of metabolites from eccrine sweat of breast cancer patients successfully qualified lifestyle parameters for risk assessment and allowed us to monitor drug treatment and systemic response to therapy. Moreover, eccrine sweat revealed a potentially predictive metabolic pattern stratifying patients by the extent of the metabolic activity of breast cancer tissue at baseline. Eccrine sweat is derived from the otherwise hardly accessible interstitial fluid and, thus, opens up a new dimension for biomonitoring of breast cancer in secondary and tertiary care. The simple sample collection without the need for trained personnel could also enable decentralised long-term biomonitoring to assess stable disease or disease progression. Eccrine sweat analysis may indeed significantly advance 3PM for the benefit of breast cancer patients.

MR tomographic evaluation of the effectiveness of neoadjuvant chemotherapy for breast cancer based on pharmacokinetic numerical analysis of tumor uptake of paramagnetic contrast in intravenous contrast enhancement

Background. In clinical practice, MRI pathophysiological and pharmacokinetic models with calculations of contrast transport indicators are unacceptably little used.Aim of the study. To propose a pharmacokinetic technique for the quantitative assessment of primary tumors and metastases, the effectiveness of breast cancer chemotherapy (BC), from dynamic contrast enhancement MRI. Material and methods. 18 patients were included who underwent neoadjuvant chemotherapy (NACHT) in four cycles for breast cancer T1-3N0-1M0, followed by radical surgical removal of the tumor. According to the results of a three — year follow-up, patients with a relapse — free course (n = 11) formed group 1, and seven patients with detected metastatic lesions (3 in the liver, 2 in the lungs, 2 in the brain) — group 2. For the initial 120–180 s of MRI with contrast after the injection of a paramagnetic, the simplification is valid for concentrations in tumor and blood and for tranfer coefficient: d{СОПУХОЛЬ(t)} / dt = ККр-Оп * СКРОВЬ (t) , from which it is obvious: ККр-Оп = (СОПУХОЛЬ(Т)) / (∫CКРОВЬ(t) dt), which was used in all calculations of the contrast transfer constant. Gadobutrol contrast is 0.1M/10 kg of body weight, TR = 5.5–6 ms, TE = 2.5 ms. Results. If, after the first cycle of NACHT, the ККр-Оп of the primary breast cancer is < 0.22 ml/min/g of tissue, the probability of subsequent relapse-free course = 0.78. Similarly, a decrease in the KCr-Op Ккр-Оп of the sentinel lymph node after the first cycle of NAHT < 0.08 ml/min/g of tissue with a probability of 0.75 predicts a relapse-free course. Conclusion. The proposed method for calculating the ККр-Оп transfer coefficient allows obtaining additional diagnostic and prognostic information in patients with local and locally advanced forms of breast cancer.

Dynamic Contrast Enhanced MRI Mapping of Vascular Permeability for Evaluation of Breast Cancer Neoadjuvant Chemotherapy Response Using Image-to-Image Conditional Generative Adversarial Networks.

Dynamic contrast enhanced (DCE) MRI is a non-invasive imaging technique that has become a quantitative standard for assessing tumor microvascular permeability. Through the application of a pharmacokinetic (PK) model to a series of T1-weighed MR images acquired after an injection of a contrast agent, several vascular permeability parameters can be quantitatively estimated. These parameters, including Ktrans, a measure of capillary permeability, have been widely implemented for assessing tumor vascular function as well as tumor therapeutic response. However, conventional PK modeling for translation of DCE MRI to PK vascular permeability parameter maps is complex and time-consuming for dynamic scans with thousands of pixels per image. In recent years, image-to-image conditional generative adversarial network (cGAN) is emerging as a robust approach in computer vision for complex cross-domain translation tasks. Through a sophisticated adversarial training process between two neural networks, image-to-image cGANs learn to effectively translate images from one domain to another, producing images that are indistinguishable from those in the target domain. In the present study, we have developed a novel image-to-image cGAN approach for mapping DCE MRI data to PK vascular permeability parameter maps. The DCE-to-PK cGAN not only generates high-quality parameter maps that closely resemble the ground truth, but also significantly reduces computation time over 1000-fold. The utility of the cGAN approach to map vascular permeability is validated using open-source breast cancer patient DCE MRI data provided by The Cancer Imaging Archive (TCIA). This data collection includes images and pathological analyses of breast cancer patients acquired before and after the first cycle of neoadjuvant chemotherapy (NACT). Importantly, in good agreement with previous studies leveraging this dataset, the percentage change of vascular permeability Ktrans derived from the DCE-to-PK cGAN enables early prediction of responders to NACT.

Abstract PO1-06-04: Immune checkpoint inhibitors for triple-negative inflammatory breast cancer (INCORPORATE): an international multicenter retrospective analysis

Abstract Background: Inflammatory breast cancer (IBC) is an aggressive clinical presentation of breast cancer (BC). Immune checkpoint inhibitors (ICIs) combined with chemotherapy provided an overall survival (OS) benefit in the metastatic setting and an even-free survival (EFS) benefit in patients (pts) with early triple-negative (TN) BC, respectively. Patients with TN-IBC were under-represented or excluded in pivotal trials and commonly not evaluated in subgroup analyses. Methods: We conducted a retrospective, multicenter, international, observational study to evaluate the clinical benefit of ICIs in pts with TN-IBC (defined as cT4d per AJCC TNM, 8th ed., ER < 1% and PgR < 1%, HER2: negative). Pts with early-stage TN-IBC were included if they received an ICI combined with neoadjuvant chemotherapy (NACT) (Group 1). Pts with metastatic TN-IBC were included if they received ICI monotherapy or in association with first-line chemotherapy (Group 2). Treatment was administered according to guideline recommendations (in PD-L1+ metastatic IBC and regardless of PD-L1 in early IBC), in clinical trials, or off-label (regardless of PD-L1 expression status in metastatic IBC). Endpoints were pathological complete response (pCR) and 1-year EFS rate for group 1 (calculated from date of first cycle of NACT to any recurrence or death), and progression-free survival (PFS) for group 2. Correlative analyses were provided (significance at p-value < 0.05). Results: We included 59 pts from 8 international referral centers. 15 pts had early IBC (Group 1), and 44 pts had metastatic disease (Group 2). Patient characteristics and outcomes are shown in Table 1. Among the 15 pts from Group 1, 10 received anthracycline, taxane and carboplatin-based (AC-CbT) NACT with pembrolizumab, 3 neoadjuvant paclitaxel-carboplatin chemotherapy with pembrolizumab, 2 neoadjuvant nab-paclitaxel with atezolizumab. One pt progressed on NACT, 2 pts are still receiving NACT. Among 13 pts evaluable for response, 6/13 (46%) achieved a pCR. After a median follow-up of 7.1 months, the median EFS was 12.9 months and the 1-year EFS rate was 70%. The median OS was 15.7 months. Among pts from Group 2, PD-L1 status was positive (IC 1% or CPS 10) in 27/44 pts (61%), negative in 5/44 pts (11%) and unknown in 6/44 pts (13%). At a median follow-up of 24.3 months, median PFS and OS were 4.1 and 15.7 months. As backbone chemotherapy in first line setting, 6 pts received AC-CbT regardless of PD-L1 status (mPFS: 8.6 months), 21 taxane-based/anthracycline-free chemotherapy (mPFS: 5.3 months), 14 other chemotherapy regimens (mPFS: 2.1 months) and 3 single-agent immunotherapy (mPFS: 50.1 months). Three of 6 patients who received AC-CbT underwent surgery and radiotherapy. In Group 2, after adjusting for the number of metastatic sites (>1 vs. 0-1), PD-L1 status (positive vs. negative vs. unknown) and de novo metastatic disease (yes vs. no), AC-CbT chemotherapy (HR 0.05; 95% CI: 0.01-0.56; p=.015) and taxane-based chemotherapy (HR 0.20; 95% CI: 0.06-0.68; p=.009) were both associated with longer PFS. Conclusions: This multicenter retrospective analysis of TN-IBC treated with combination of chemotherapy and IOs showed relatively low pathology response, EFS and clinical benefit suggesting need to further investigate the role of immunotherapy in this aggressive disease. Table 1. Patient characteristics and outcomes Citation Format: Carmine Valenza, Dario Trapani, Paola Zagami, Gabriele Antonarelli, Luca Boscolo Bielo, Eleonora Nicolò, Joana Mourato Ribeiro, Lorenzo Guidi, Carolina REDUZZI, Martina Spotti, Elisabetta Munzone, Javier Cortés, Barbara Pistilli, Sara Tolaney, Naoto Ueno, Rachel Layman, Massimo Cristofanilli, Lisa Carey, Filipa Lynce, Wendy Woodward, Giuseppe Curigliano. Immune checkpoint inhibitors for triple-negative inflammatory breast cancer (INCORPORATE): an international multicenter retrospective analysis [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-06-04.

Abstract P2-26-23: Transcriptomic modification induced by the first cycle of neoadjuvant chemotherapy impacts response to treatment in triple negative breast cancer (TNBC)

Abstract Background Despite adequate neoadjuvant chemotherapy, TNBC remains poor prognosis. Non-responding patient have 25-40% risk of relapse at 5 years. pCR is therefore currently considered as a major goal in TNBC and new tools of early prediction of residual disease should be identified. TransTep is a phase 2 monocentric clinical trial which aims to identify transcriptomic profile of triple-negative cancer cells associated with early tumor chemoresistance, as identified by FDG PET after the first course of neoadjuvant chemotherapy. Twenty patients were included between January 2015 and October 2017, with stage II or III of the UICC classification (except stage T4d). All patients received neoadjuvant chemotherapy with anthracyclines and taxanes sequentially, none of them had a dose-dense chemotherapy. Six patients obtained metabolic response (Delta SUV < -30%) after one cycle of anthracycline. Methods Total RNA was extracted from biopsies (HES > 30%) and used to prepare libraries thanks to TruSeq RNA library Prep kit (Illumina) and sequenced on NextSeq500 device. Results Transcriptomic expression analysis between tumors before chemotherapy and tumors after one course of chemotherapy showed that tumors showing a significant decrease of their Delta SUV (←30%) had a much higher gene expression variation than tumors with a Delta SUV >-30%. These tumors presented, after one course of chemotherapy, a decrease of cell cycle, DNA replication and Fanconi anemia pathway related genes, while they harbored an increase of genes belonging to immunity related pathways such as natural killer cell mediated toxicity, TH17 cell differentiation, or chemokine signaling pathway. As patients had a surgery after neoadjuvant chemotherapy, we had Chevalier tumor response. As observed with FDG PET data, patients with a good response according to Chevalier (class 1) criteria presented a much higher transcriptomic modification after one course of chemotherapy. Patients with a little gene expression modification were classified as Chevalier 3. When we focused on pathways impacted by chemotherapy in tumors classified as Chevalier 1, we observed a significant decrease of cell cycle, DNA replication and DNA repair pathways related gene after one course of chemotherapy, whereas a high number of genes belonging to immunity related genes (NK cells, antigen processing and presentation, or chemokine signaling pathway) were increased. Conclusion Our results tend to indicate that transcriptomic tumor response after one course of chemotherapy could forecast final response to treatment. Moreover, it seems that one cycle of anthracycline-based chemotherapy is able to get hot some breast tumors, and that this tumor warming could be a marker of good response to the full treatment. In the following months, we will test whether transcriptomic could predict progression free survival and/or overall survival of patients. We will also look for the best early marker of response between PET FDG and tumor transcriptomic modifications. Based on these results, a new trial will be organized. A therapeutic adaptation depending on the transcriptomic or metabolic data will be proposed to increase pCR rate and prognosis of patients. Moreover, with years and therapeutic innovations, patient managment obviously evolves. This was recently the case with a new standard of care in triple negative breast cancer with combination of platinum salt and immunotherapy. Therefore, a new trial, similar to TRANSTEP, will be carried out with this new standard of care. Citation Format: Isabelle Desmoulins, David Chardin, Corentin Richard, Laurent Arnould, ALEXANDRE COCHET, Olivier Humbert, Romain Boidot. Transcriptomic modification induced by the first cycle of neoadjuvant chemotherapy impacts response to treatment in triple negative breast cancer (TNBC) [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-26-23.

Abstract P6-01-37: Tumor microenvironment subtype influence the response of neoadjuvant chemotherapy in breast cancer

Abstract Introduction Recent transcriptome analysis developed a holistic tumor microenvironment (TME) classification platform based on immune and fibrotic markers. This TME classification had four categories, immune enriched, fibrotic (IE/F); immune enriched, non-fibrotic (IE); Fibrotic (F); and Immune Desert (D). And these four TME subtypes are a predictive biomarker to immunotherapy in multiple cancer and four subtypes have been changed during treatment. Previously our study suggested baseline immune features and dynamic immune response on-treatment were predictive of treatment outcome in BC with neoadjuvant chemotherapy (NAC). In this study, we evaluated the impact of TME classification and dynamic change of TME classification on treatment outcome in BC with NAC. Methods Early and locally advanced BCs which would be planned to receive standard NAC (four cycles of anthracycline plus cyclophosphamide and four cycles of docetaxel or docetaxel plus trastuzumab for human epidermal growth factor receptor 2[HER2+] disease or six cycles of docetaxel, carboplatin, trastuzumab and pertuzumab for HER2+ disease) followed by curative surgery. We prospectively collected tumor tissue and matched blood three times for each patients: at BC diagnosis (T1), three weeks after the first cycle of NAC (T2), and curative surgery (T3). RNASeq was performed to classify TME subtype. In terms of clinical variables, clinical stage and IHC subtype at diagnosis, pathologic complete response (pCR), distant recurrence free survival (DRFS) and overall survival (OS) were used. Generalized logistic regression was used for predicting RCB class and pCR with clinical and genomic characteristics at T1. Kaplan-Meier analysis were performed to analysis DRFS and OS. Results In total, 210 patients who were treated with scheduled NAC were enrolled. Finally, RNASeq in 240 BC tissues (T1:119, T2:91 and T3:30) were conducted from 142 patients. In 119 BCs which was performed RNASeq at T1, hormone receptor(HR)+, HER2- BC was 32 (26.9%), 29 of HR+HER2+ BC (24.4%), 18 of HR-HER2+ BC (15.1%) and 44 of triple negative BC (TNBC) (37.0%). In TME classification, immune desert (D) was most frequently observed (45.3%), followed by IE (35.3%), F (10.1%) and IE/F (9.2%). The association between BC subtype and TME subtype suggested that HR+HER2- BC was frequently categorized into D (22 of 32, 68.8%) whereas TNBC was into IE (24 of 44, 54.5%) (p< 0.001). TME subtype has been dynamically changed during NAC. At T2, IE subtype was most frequently observed (27.5%) followed by D (25.3%), IE/F (24.2%) and F (23.1%). The inclination of TME change were different according to NAC response. In BC achieved pCR, IE/F subtype had increased (4 at T1 and 10 at T2) and decrease of D subtype (15 at T1 and 3 at T2). In BC with non-pCR, IE/F subtype had slightly increased at T2 (7 at T1 and 12 at T2) but there was no IE/F subtype at T3 point. Contrarily, D subtype had decreased at T2 but increased at T3 (39 at T1, 20 at T2 and 24 at T3). The impact of TME subtype was different according to pCR status. In BC with pCR, F subtype had poor prognosis in DRFS and OS compared to other subtype ([5year DRFS rate for F vs. others: 66.7% vs. 93.2%, p=0.028], [5year OS rate for F vs. others: 70.7% vs. 100%, p< 0.001]). In BC without pCR, there was no different DRFS and OS according to TME subtypes. Conclusion Our data suggested that TME subtype has been changed during NAC and the subtype switching was affected by the NAC response. Moreover, TME subtype may have prognostic role in DRFS and OS according to pCR status. Citation Format: ji-Yeon Kim, Kyunghee Park, woong-Yang Park, Jeong Eon Lee, Seok Won Kim, Seok Jin Nam, Se Kyung Lee, Yeon Hee Park. Tumor microenvironment subtype influence the response of neoadjuvant chemotherapy in breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-01-37.

Serum Cytokeratin 18 as a Potential Early Marker for Chemotherapy Response in Breast Cancer Patients: A Prospective Study.

Currently, it is well recognized that response to neoadjuvant chemotherapy is an important predictive factor for survival in breast cancer patients. However, it is still an area of research about which patient would respond to the neoadjuvant chemotherapy. Serum CK18 levels were measured using ELISA from 52 newly diagnosed breast cancer patients, at presentation and after first cycle of neo-adjuvant chemotherapy. Pre- and post-treatment CK-18 levels were correlated with several clinical and pathological parameters. At the end of neoadjuvant treatment, changes in serum CK18 levels were correlated with tumors' response to therapy. Significant elevation of pre-chemotherapy CK18 level was observed in patients who had progressive disease compared to those who had complete or partial response to therapy (P=0.006 and P<0.001, respectively). Significantly higher CK18 levels were observed post-chemotherapy in complete and partial responders, in contrast to patients with stable or progressive disease (P=0.012% and P=0.001%, respectively). The percent of change was significantly higher in complete responders compared to patients who had stable or progressive disease (P=0.043% and P=0.045%, respectively). Our results suggest that patients with increasing CK18 level following chemotherapy are potential responders to their neoadjuvant protocol. Thus, the measurement of serum CK18 early in the treatment course could be a simple, noninvasive way to predict tumor response to neoadjuvant chemotherapy.

A delta-radiomic lymph node model using dynamic contrast enhanced MRI for the early prediction of axillary response after neoadjuvant chemotherapy in breast cancer patients

BackgroundThe objective of this paper is to explore the value of a delta-radiomic model of the axillary lymph node (ALN) using dynamic contrast-enhanced (DCE) MRI for early prediction of the axillary pathological complete response (pCR) of breast cancer patients after neoadjuvant chemotherapy (NAC).MethodsA total of 120 patients with ALN-positive breast cancer who underwent breast MRI before and after the first cycle of NAC between October 2018 and May 2021 were prospectively included in this study. Patients were divided into a training (n = 84) and validation (n = 36) cohort based on the temporal order of their treatments. Radiomic features were extracted from the largest slice of targeted ALN on DCE-MRI at pretreatment and after one cycle of NAC, and their changes (delta-) were calculated and recorded. Logistic regression was then applied to build radiomic models using the pretreatment (pre-), first-cycle(1st-), and changes (delta-) radiomic features separately. A clinical model was also built and combined with the radiomic models. The models were evaluated by discrimination, calibration, and clinical application and compared using DeLong test.ResultsAmong the three radiomic models, the ALN delta-radiomic model performed the best with AUCs of 0.851 (95% CI: 0.770–0.932) and 0.822 (95% CI: 0.685–0.958) in the training and validation cohorts, respectively. The clinical model yielded moderate AUCs of 0.742 (95% CI: 0.637–0.846) and 0.723 (95% CI: 0.550–0.896), respectively. After combining clinical features to the delta-radiomics model, the efficacy of the combined model (AUC = 0.932) in the training cohort was significantly higher than that of both the delta-radiomic model (Delong p = 0.017) and the clinical model (Delong p < 0.001) individually. Additionally, in the validation cohort, the combined model had the highest AUC (0.859) of any of the models we tested although this was not statistically different from any other individual model’s validation AUC. Calibration and decision curves showed a good agreement and a high clinical benefit for the combined model.ConclusionThis preliminary study indicates that ALN-based delta-radiomic model combined with clinical features is a promising strategy for the early prediction of downstaging ALN status after NAC. Future axillary MRI applications need to be further explored.

Contrast-enhanced ultrasonography for early prediction of response of neoadjuvant chemotherapy in breast cancer.

Neoadjuvant chemotherapy (NAC) is widely accepted as a primary treatment for inoperable or locally advanced breast cancer before definitive surgery. However, not all advanced breast cancers are sensitive to NAC. Contrast-enhanced ultrasonography (CEUS) has been considered to assess tumor response to NAC as it can effectively reflect the condition of blood perfusion and lesion size. Therefore, this study aimed to evaluate the diagnostic performance of CEUS to predict early response in different regions of interest in breast tumors under NAC treatment. This prospective study included 82 patients with advanced breast cancer. Parameters of TIC (time-intensive curve) between baseline and after the first cycle of NAC were calculated for the rate of relative change (Δ), including Δpeak, ΔTTP (time to peak), ΔRBV (regional blood volume), ΔRBF (regional blood flow) and ΔMTT (mean transit time). The responders and non-responders were distinguished by the Miller-Payne Grading (MPG) system and parameters from different regions of tumors were compared in these two groups. For ROI 1(the greatest enhancement area in the central region of the tumor), there were significant differences in Δpeak1, ΔRBV1 and ΔRBF1 between responders and non-responders. For ROI 2 (the greatest enhancement area on edge of the tumor), there were significant differences in Δpeak2 and ΔRBF2 between the groups. The Δpeak1 and ΔRBF2 showed good prediction (AUC 0.798-0.820, p ≤ 0.02) after the first cycle of NAC. When the cut-off value was 0.115, the ΔRBF2 had the highest diagnostic accuracy and the maximum NPV. Quantitative TIC parameters could be effectively used to evaluate early response to NAC in advanced breast cancer.

The Value of Semiquantitative Parameters Derived from 18F-FDG PET/CT for Predicting Response to Neoadjuvant Chemotherapy in a Cohort of Patients with Different Molecular Subtypes of Breast Cancer

Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) is a strong prognostic factor in breast cancer (BC). The aim of this study was to investigate whether semiquantitative parameters derived from baseline [18F]Fluorodeoxyglucose ([18F]FDG) positron emission computed tomography/computed tomography (PET/CT) could predict pCR after NAC and survival outcomes in patients affected by different molecular subtypes of BC. We retrospectively retrieved patients from the databases of two Italian hospitals (Centre A: University Hospital of Ferrara; Centre B: University of Padua) meeting the following inclusion criteria: (1) diagnosis of BC; (2) history of NAC; (3) baseline [18F]FDG PET/CT performed before the first cycle of NAC; (4) available follow-up data (response after NAC and survival information). For each [18F]FDG PET/CT scan, semiquantitative parameters (SUVmax, SUVmean, MTV and TLG) related to the primary tumor (B), to the reference lesion for both axillary (N) and distant lymph node (DN), and to the whole-body burden of disease (WB) were evaluated. Patients enrolled were 133: 34 from centre A and 99 from centre B. Patients' molecular subtypes were: 9 luminal A, 49 luminal B, 33 luminal B + HER-2, 10 HER-2 enriched, and 32 triple negative (TNBC). Luminal A and HER-2 enriched BC patients were excluded from the analysis due to the small sample size. pCR after NAC was achieved in 47 patients (41.2%). [18F]FDG PET/CT detected the primary tumor in 98.3% of patients and lymph node metastases were more frequently detected in Luminal B subgroup. Among Luminal B patients, median SUVmean_B values were significantly higher (p = 0.027) in responders (7.06 ± 5.9) vs. non-responders (4.4 ± 2.1) to NAC. Luminal B + HER-2 non-responders showed a statistically significantly higher median MTV_B (7.3 ± 4.2 cm3 vs. 3.5 ± 2.5 cm3; p = 0.003) and TLG_B (36.5 ± 24.9 vs. 18.9 ± 17.7; p = 0.025) than responders at baseline [18F]FDG PET/CT. None of the semiquantitative parameters predicted pCR after NAC in TNBC patients. However, among TNBC patients who achieved pCR after NAC, 4 volumetric parameters (MTV_B, TLG_B, MTV_WB and TLG_WB) were significantly higher in patients dead at follow-up. If confirmed in further studies, these results could open up a widespread use of [18F]FDG PET/CT as a baseline predictor of response to NAC in luminal B and luminal B + HER-2 patients and as a prognostic tool in TNBC.

Changes in Degree Centrality and Functional Connectivity after the First Cycle of Neoadjuvant Chemotherapy in Newly Diagnosed Breast Cancer: A Longitudinal Study.

To evaluate the longitudinal changes of brain degree centrality (DC) and functional connectivity (FC) in breast cancer patients after the first cycle of neoadjuvant chemotherapy (NAC). Thirty-five breast cancer patients were included in the NAC group. Resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological test were performed at baseline before NAC (time point 0, TP0) and after the first cycle of NAC (time point 1, TP1). The healthy controls (HC) included 30 healthy subjects and received the same rs-fMRI scan and neuropsychological test as the above-mentioned NAC group at one time point. DC and FC analyses were conducted to assess brain connectivity of all participants. Receiver operating characteristic (ROC) curve was used to assess the ability of DC and FC in distinguishing patients before and after chemotherapy. In the NAC group, the Self-Rating Anxiety Scale scores decreased significantly over time. At TP0 and TP1, the Digital Span Test forward score of the NAC group was significantly lower than that of the HC group. In the NAC group, DC in the right middle frontal gyrus and left precentral gyrus/middle frontal gyrus decreased significantly at TP1, and FC between the left precentral gyrus/middle frontal gyrus and bilateral precuneus was significantly reduced at TP1. Through ROC analysis, we found that the area under the curve (AUC) of DC, FC, and the combined model in distinguishing patients in TP0 or TP1 was 0.7886, 0.7665, and 0.8278, respectively. Brain connectivity, involving executive and motor function related brain areas, changes in the short term after NAC treatment in breast cancer patients.

An Integrative Clinical Model for the Prediction of Pathological Complete Response in Patients with Operable Stage II and Stage III Triple-Negative Breast Cancer Receiving Neoadjuvant Chemotherapy

Simple SummaryNeoadjuvant chemotherapy (NAC) is widely used to treat stage II and III primary, operable triple-negative breast cancer (TNBC). The response to NAC critically affects the subsequent treatment plan, including not only curative surgical planning but also adjuvant therapy. There is no standard prediction model that accurately predicts NAC response. Therefore, the development of an easy-to-apply and cost-effective clinical prediction model for NAC treatment response would improve clinical practice. We propose an integrative clinical prediction model for the prediction of pathologically complete response in patients with operable stage II and stage III TNBC receiving NAC based on findings from tumor ultrasound and blood tests. All included parameters were readily available during and before NAC. This clinical prediction model could provide a reference to guide clinicians’ decisions in planning a patient’s NAC treatment as early as after the first cycle of NAC.Triple-negative breast cancer (TNBC) is treated with neoadjuvant chemotherapy (NAC). The response to NAC, particularly the probability of a complete pathological response (pCR), guides the surgical approach and adjuvant therapy. We developed a prediction model using a nomogram integrating blood tests and pre-treatment ultrasound findings for predicting pCR in patients with stage II or III operable TNBC receiving NAC. Clinical data before and after the first cycle of NAC collected from patients between 2012 and 2019 were analyzed using univariate and multivariate analyses to identify correlations with pCR. The coefficients of the significant parameters were calculated using logistic regression, and a nomogram was developed based on the logistic model to predict the probability of pCR. Eighty-eight patients were included. Five parameters correlated with the probability of pCR, including the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte (PLR) ratio, percentage change in PLR, presence of echogenic halo, and tumor height-to-width ratio. The discrimination performance of the nomogram was indicated by an area under the curve of 87.7%, and internal validation showed that the chi-square value of the Hosmer–Lemeshow test was 7.67 (p = 0.363). Thus, the integrative prediction model using clinical data can predict the probability of pCR in patients with TNBC receiving NAC.

Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI Predicts Pathologic Complete Response in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy.

Simple SummaryNeoadjuvant chemotherapy (NAC) followed with surgery is the standard strategy in the treatment of locally advanced breast cancer, but the individual efficacy varies. Early and accurate prediction of complete responders determines the NAC regimens and prognosis. Breast MRI has been recommended to monitor NAC response before, during, and after treatment. Radiomics has been heralded as a breakthrough in medicine and regarded to have changed the landscape of biomedical research in oncology. Delta-radiomics characterizing the change in feature values by applying radiomics to multiple time points, is a promising strategy for predicting response after NAC. In our study, the delta-radiomics model built with the change of radiomic features before and after one cycle NAC could effectively predict pathological complete response (pCR) in breast cancer. The model provides strong support for clinical decision-making at the earliest stage and helps patients benefit the most from NAC.Objective: To investigate the value of delta-radiomics after the first cycle of neoadjuvant chemotherapy (NAC) using dynamic contrast-enhanced (DCE) MRI for early prediction of pathological complete response (pCR) in patients with breast cancer. Methods: From September 2018 to May 2021, a total of 140 consecutive patients (training, n = 98: validation, n = 42), newly diagnosed with breast cancer who received NAC before surgery, were prospectively enrolled. All patients underwent DCE-MRI at pre-NAC (pre-) and after the first cycle (1st-) of NAC. Radiomic features were extracted from the postcontrast early, peak, and delay phases. Delta-radiomics features were computed in each contrast phases. Least absolute shrinkage and selection operator (LASSO) and a logistic regression model were used to select features and build models. The model performance was assessed by receiver operating characteristic (ROC) analysis and compared by DeLong test. Results: The delta-radiomics model based on the early phases of DCE-MRI showed a highest AUC (0.917/0.842 for training/validation cohort) compared with that using the peak and delay phases images. The delta-radiomics model outperformed the pre-radiomics model (AUC = 0.759/0.617, p = 0.011/0.047 for training/validation cohort) in early phase. Based on the optimal model, longitudinal fusion radiomic models achieved an AUC of 0.871/0.869 in training/validation cohort. Clinical-radiomics model generated good calibration and discrimination capacity with AUC 0.934 (95%CI: 0.882, 0.986)/0.864 (95%CI: 0.746, 0.982) for training and validation cohort. Delta-radiomics based on early contrast phases of DCE-MRI combined clinicopathology information could predict pCR after one cycle of NAC in patients with breast cancer.

Early alterations in cortical morphology after neoadjuvant chemotherapy in breast cancer patients: A longitudinal magnetic resonance imaging study.

There is growing evidence that chemotherapy may have a significant impact on the brains of breast cancer patients, causing changes in cortical morphology. However, early morphological alterations induced by chemotherapy in breast cancer patients are unclear. To investigate the patterns of those alterations, we compared female breast cancer patients (n = 45) longitudinally before (time point 0, TP0) and after (time point 1, TP1) the first cycle of neoadjuvant chemotherapy, using voxel‐based morphometry (VBM) and surface‐based morphometry (SBM). VBM and SBM alteration data underwent correlation analysis. We also compared cognition‐related neuropsychological tests in the breast cancer patients between TP0 and TP1. Reductions in gray matter volume, cortical thickness, sulcal depth, and gyrification index were found in most brain areas, while increments were found to be mainly concentrated in and around the hippocampus. Reductions of fractal dimension mainly occurred in the limbic and occipital lobes, while increments mainly occurred in the anterior and posterior central gyrus. Significant correlations were found between altered VBM and altered SBM mainly in the bilateral superior frontal gyrus. We found no significant differences in the cognition‐related neuropsychological tests before and after chemotherapy. The altered brain regions are in line with those associated with impaired cognitive domains in previous studies. We conclude that breast cancer patients showed widespread morphological alterations soon after neoadjuvant chemotherapy, despite an absence of cognitive impairments. The affected brain regions may indicate major targets of early brain damage after chemotherapy.

Cell-free DNA methylation as a predictive biomarker of response to neoadjuvant chemotherapy for patients with muscle-invasive bladder cancer in SWOG S1314.

4506 Background: Neoadjuvant chemotherapy is the standard of care in muscle-invasive bladder cancer patients. However, treatment is intense, the overall benefit is small, and there is no established marker to identify patients who benefit most. The aim of the study is to characterize cell-free DNA (cfDNA) methylation from patients receiving neoadjuvant chemotherapy in SWOG S1314, a prospective cooperative group trial, and to correlate the methylation signatures with pathologic response. Methods: Blood samples were collected prospectively from 73 patients before and during standard neoadjuvant chemotherapy. At radical cystectomy, pathologic response was documented. Plasma cfDNA was profiled using Infinium MethylationEPIC BeadChip array. Differential methylation between pathologic responders (≤pT1N0M0) and non-responders was analyzed, and a Random Forest model was used to generate a classifier predictive of treatment response. Results: Using pre-chemotherapy plasma cfDNA, we developed a methylation-based response score (mR-score) predictive of pathologic response. The mR-score also could be calculated using plasma samples collected after the first cycle of neoadjuvant chemotherapy, resulting in a similar predictive ability. Furthermore, we used cfDNA methylation data to calculate the circulating bladder DNA fraction, which had a modest but independent predictive ability for treatment response. When we combined the mR-score and circulating bladder DNA fraction, we successfully predicted pathologic response outcomes in 79% of patients based on their plasma collected before chemotherapy and after 1 cycle of chemotherapy. Conclusions: Our study provides proof of concept that cfDNA methylation may be used to predict treatment response in bladder cancer patients receiving neoadjuvant chemotherapy. Clinical trial information: NCT02177695.

Dual-Branch Convolutional Neural Network Based on Ultrasound Imaging in the Early Prediction of Neoadjuvant Chemotherapy Response in Patients With Locally Advanced Breast Cancer.

The early prediction of a patient’s response to neoadjuvant chemotherapy (NAC) in breast cancer treatment is crucial for guiding therapy decisions. We aimed to develop a novel approach, named the dual-branch convolutional neural network (DBNN), based on deep learning that uses ultrasound (US) images for the early prediction of NAC response in patients with locally advanced breast cancer (LABC). This retrospective study included 114 women who were monitored with US during pretreatment (NAC pre) and after one cycle of NAC (NAC1). Pathologic complete response (pCR) was defined as no residual invasive carcinoma in the breast. For predicting pCR, the data were randomly split into a training set and test set (4:1). DBNN with US images was proposed to predict pCR early in breast cancer patients who received NAC. The connection between pretreatment data and data obtained after the first cycle of NAC was considered through the feature sharing of different branches. Moreover, the importance of data in various stages was emphasized by changing the weight of the two paths to classify those with pCR. The optimal model architecture of DBNN was determined by two ablation experiments. The diagnostic performance of DBNN for predicting pCR was compared with that of four methods from the latest research. To further validate the potential of DBNN in the early prediction of NAC response, the data from NAC pre and NAC1 were separately assessed. In the prediction of pCR, the highest diagnostic performance was obtained when combining the US image information of NAC pre and NAC1 (area under the receiver operating characteristic curve (AUC): 0.939; 95% confidence interval (CI): 0.907, 0.972; F1-score: 0.850; overall accuracy: 87.5%; sensitivity: 90.67%; and specificity: 85.67%), and the diagnostic performance with the combined data was superior to the performance when only NAC pre (AUC: 0.730; 95% CI: 0.657, 0.802; F1-score: 0.675; sensitivity: 76.00%; and specificity: 68.38%) or NAC1 (AUC: 0.739; 95% CI: 0.664, 0.813; F1-score: 0.611; sensitivity: 53.33%; and specificity: 86.32%) (p<0.01) was used. As a noninvasive prediction tool, DBNN can achieve outstanding results in the early prediction of NAC response in patients with LABC when combining the US data of NAC pre and NAC1.

Breast Thermography as an Adjunct Tool to Monitor the Chemotherapy Response in a Triple Negative BIRADS V Cancer Patient: A Case Study.

Prior studies have reported that breast thermography is a potential adjunct tool to mammography in early cancer detection, especially in developing countries with limited medical facilities. This non-invasive, safe, and painless screening tool can reduce the mortality due to cancer by early detection and monitoring. This prospective study aims to analyze changes in static breast thermograms of a BIRADS V category breast cancer patient to assess the response to Neoadjuvant chemotherapy (NACT) in locally advanced cancer and to compare with thermograms of a BIRADS II category benign patient. Breast thermograms of the malignant and benign patients in five different views were taken using FLIR E40 thermal camera under strict acquisition protocols. Details of the patient along with the thermograms were recorded pre and post NACT. There is a qualitative reduction in the warm region of the surface after the first cycle of chemotherapy treatment. Thermal, fractal, and statistical analysis of thermograms is performed for both patients. In the patient with aggressive ductal carcinoma, the difference in the mean surface temperature between contralateral breasts is high, which is reduced after the first cycle of NACT. This preliminary study indicates that breast thermography can potentially be used as an effective non-invasive, non-contact, and radiation-free tool to analyze the effect of NACT on patients with different stages of breast cancer. This study also signifies the role of the thermography technique in reaching a largely rural population with limited medical resources for early cancer screening.

Abstract P1-08-07: Prediction model of the response of neoadjuvant chemotherapy and long term survival according to multi-omic profiling in cooperation with clinicopathologic features in patients with breast cancer

Abstract Background: The advance of next generation sequencing (NGS) leads to give the abundant genetic information of breast cancer (BC). We developed the prediction model of neoadjuvant chemotherapy (NAC) response and long term survival using genetic characteristics in cooperation with clinicpathologic features. Methods: Early and locally advanced BCs which would be planned to receive standard NAC (four cycles of anthracycline plus cyclophosphamide and four cycles of docetaxel or docetaxel plus trastuzumab for human epidermal growth factor receptor 2[HER2+] disease) followed by curative surgery. We prospectively collected tumor tissue and matched blood three times for each patients: at BC diagnosis (T1), three weeks after the first cycle of NAC (T2), and curative surgery (T3). Whole exome sequencing (WES) and RNASeq were performed to detect somatic mutation, mutational signature, tumor mutational burden (TMB) and PAM50 prediction was to classify intrinsic subtype. In terms of clinical variables, clinical stage and IHC subtype at diagnosis, pathologic complete response (pCR), residual cancer burden (RCB) class and distant recurrence free survival (DRFS) were used for prediction model development. Logistic regression was used for predicting RCB class and pCR with clinical and genomic variables at T1. Univariate and multivariate Cox regression were performed to identify prognostic factors for DRFS. Results: In total, 210 patients who were treated with scheduled NAC were enrolled. Finally, WES in 252 BC tissues (T1:123, T2:106 and T3:23) RNASeq in 198 BC tissues (T1:100, T2:77 and T3:21) were conducted from 123 patients. In NAC response, 52 patients achieved pCR(42.3%) and 14 patients were in RCB class 3, 39 in class 2, 14 in class 1 and 51 in class 0. Median follow up duration was 44months and distant recurrence was observed in 13 patients. TP53 mutation (60%) was the most commonly detected genetic alteration followed by TTN(31%), ERBB2(25%) and PIK3CA(18%). Eight BCL11A (3%) and 3 MPL mutations (1%) were also observed respectively. Serial tumor sequencing suggested that mutation profile have not changed during NAC. In terms of mutational signature, signature 3 was most frequently observed and no difference was observed in serial sequencing data. In addition, APOBEC (sig.2) and HRD (sig.3) were observed differently according to intrinsic subtype. In terms of intrinsic subtype, basal subtype decreased during NAC and luminal A type increased. Median TMB was 87 (range, 14-570). In prediction model, clinical N3(cN3) stage (Odds ratio [OR] of cN3 vs. not : 4.536, 95% confidence interval [CI]: 0.925, 44.016, p=0.042) and intrinsic subtype at BC diagnosis (OR of non-luminal vs. luminal types: 0.208, 95% CI: 0.062, 0.604, p=0.001) were associated with pCR. Clinical stage (OR of clinical stage III vs. II: 4.115, 95% CI: 1.094, 19.217, p=0.021), TMB (OR of TMB high vs. low: 0.255, 95% CI: 0.043,1.042, p.value=0.045), MPL genetic alteration (OR of mutation vs. wild type: 16.347, 95% CI: 0.797,1013.88, p.value=0.037), BCL11A (OR of mutation vs. wild type: 16.347, 95% CI: 0.797,1013.88, p.value=0.037) were associated with RCB class (3 vs. others). In terms of DRFS, prediction model consisted of clinical stage (Hazard ratio [HR] of stage III vs. II: 3.496, 95% confidence interval [CI]:1.337, 5.654), PIK3CA (HR of mutation vs. wild type: 1.572, 95% CI:-0.008, 3.152) TMB (HR of high vs. low: -1.999. 95% CI:-3.669, -0.329) had c-index of 0.861(95% CI:0.805, 0.916). Conclusions: During NAC, somatic mutation and mutation signature were consistently maintained while intrinsic subtype dynamically changed. In prediction model, TMB, PIK3CA mutation and clinical stage showed predictive roles on DRFS of BC in NAC setting. Citation Format: Ji-Yeon Kim, Kyunghee Park, Woong-Yang Park, Jeong Eon Lee, Seok Won Kim, Seok Jin Nam, Se Kyung Lee, Zhengyan Kan, Yeon Hee Park. Prediction model of the response of neoadjuvant chemotherapy and long term survival according to multi-omic profiling in cooperation with clinicopathologic features in patients with breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-08-07.

Abstract PD10-09: Comparison of early modulation of biological pathways and immune microenvironment by anthracyclines- or taxane-based treatment

Abstract Background - Chemotherapy is the current backbone of immune checkpoint inhibitors (ICIs) for approved indications in triple negative breast cancer (TNBC). While it is expected that different chemotherapeutic agents might have distinct immunomodulatory effects, data in patients is scarce. Here we compared the early modulation of molecular pathways and immune-related features in TNBC patients receiving neoadjuvant doxorubicin/cyclophosphamide (AC) or nab-paclitaxel/carboplatin (nab/C). Methods - Two cohorts of TNBC patients with available RNA-seq for paired core biopsies obtained before (baseline) and after the first cycle of neoadjuvant chemotherapy (day 21, D1C2) were selected: i) 84 patients treated with nab/C from the control arm of the NeoTRIPaPDL1 trial (Gianni L SABCS 2019, Bianchini G ESMO 2021); ii) 22 patients treated with AC from a publicly available dataset (Park Nat Comms 2020). Presence of immune cell populations was estimated by gene expression profile deconvolution using ConsensusTME R package (n=19). Hallmark gene set collection and custom signature activation status were estimated in each sample using singscore R package (n=63). We also assessed modulation of PD-L1 gene expression and selected immune-related genes. To minimize batch effects between the two cohorts, in each dataset, median score expression at baseline was subtracted from all samples. Continuous scores were compared by 2-sided t-test. Results - Thirty-nine pathways were significantly and similarly modulated in both cohorts (all p&amp;lt;0.01) at D1C2 compared to baseline. They included upregulation of all immune cell related signatures (e.g. T cells, dendritic cells, monocytes and macrophages, B cells and NK), immune function-related signatures and apoptosis, and downregulation of proliferation related signatures. PD-L1 gene expression was upregulated in both cohorts (p&amp;lt;0.001). A comparison between D1C2 of the two cohorts was performed to evaluate whether chemotherapies differently modulated gene signatures. Nab/C more strongly downregulated signatures of G2M checkpoint, mitotic spindle, DNA repair, MYC targets and oxidative phosphorylation. AC more strongly upregulated some immune-related signatures (e.g. cytotoxic cells, CD4+ T-cells, regulatory T cells, IL2/STAT5 and JAK/STAT3) and apoptosis. PD-L1 was more upregulated in AC cohort (p=0.006). For each signature, we identified, in each cohort, patients ‘signature high’ and ‘signature low’ using the median value at baseline as a threshold. We then investigated whether signature modulation at D1C2 was different in the two groups. In ‘signature high’ patients, immune-related signatures were similarly upregulated, whereas nab/C showed downregulation of proliferation related markers. In ‘signature low’ patients, a more robust upregulation of all immune-related signatures was observed in both cohorts (all p&amp;lt;0.0001), but it was quantitatively stronger in AC arm for several immune signatures (e.g. cytotoxic cells, gamma/delta T cells, CD4+ T-cells, regulatory T cells, NK) (p&amp;lt;0.01). PD-L1 was significantly upregulated at D1C2 only in PD-L1 low group in both cohorts (p&amp;lt;0.0001), but the effect was stronger in AC (p=0.014). Chemotherapy induced modulation of other individual genes will be presented at the meeting. Conclusions - The two investigated chemotherapy regimens had a strong early immunomodulatory and chemoattractant effect, which confirms the rationale for combination with ICIs. Anthracyclines elicit a quantitatively stronger immune modulatory effect compared to nab/C, which is particularly evident in. “immune low” tumors. These observations can have clinical implications for the selection of the ideal chemotherapy partner to ICIs in not-inflamed/PD-L1 negative tumors. Citation Format: Maurizio Callari, Marco Barreca, Matteo Dugo, Barbara Galbardi, Lucia Viganò, Alberta Locatelli, Luca Licata, Giulia Viale, Pinuccia Valagussa, Giuseppe Viale, Luca Gianni, Giampaolo Bianchini. Comparison of early modulation of biological pathways and immune microenvironment by anthracyclines- or taxane-based treatment [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD10-09.

Circulating tumor cells may serve as a supplement to RECIST in neoadjuvant chemotherapy of patients with locally advanced breast cancer.

Circulating tumor cells (CTCs) have been shown to be associated with the response to neoadjuvant chemotherapy (NCT) and the prognosis of locally advanced breast cancer (LABC) patients. Our study aimed to investigate whether the change of CTC status during NCT could serve as a supplement to the Response Evaluation Criteria in Solid Tumors (RECIST) in the treatment and evaluation of LABC patients. 6ml of blood samples were collected before NCT, after the first cycle of NCT and after the completion of NCT, respectively. According to the change of CTC number during NCT, the patients were divided into "CTC low-response (low-R)" group and "CTC high-response (high-R)" group. Survival data of each group of patients were obtained through long-term follow-up. A total of 35 patients diagnosed with LABC were enrolled. The median follow-up for distant metastasis was 27months (range 7-36months). There was no significant difference in distant metastasis-free survival (DMFS) between PR/CR group and PD/SD group (P = 0.0914), while CTC low-R group had a worse DMFS than CTC high-R group (P = 0.0199). In PR/CR subgroup, patients with CTC low-R showed a lower DMFS compared with those with CTC high-R (P = 0.0159). However, in PD/SD subgroup, there was no significant difference in DMFS between CTC low-R and CTC high-R group (P = 0.7521). In terms of assessing response to NCT, CTC change or RECIST classification alone had an AUC of 0.533 (95% CI 0.277-0.790) and 0.700 (95% CI 0.611-0.789), respectively. When combining the two, the AUC slightly increased to 0.713 (95% CI 0.532-0.895). The change of CTC number during NCT has a potential to serve as a supplement to RECIST in the assessment of NCT efficacy and the prognosis of LABC patients.