Prediction Of Neoadjuvant Chemotherapy Response Research Articles

Rapid organoid development, drug screening, and neoadjuvant chemotherapy response prediction for patients with locally advanced bladder cancer.

543 Background: Neoadjuvant chemotherapy prior to radical cystectomy (RC) for muscle-invasive urothelial carcinoma (UCCx) is the standard of care though the absolute survival benefit is small, and some patients progress during chemotherapy. While progress has been made in the prediction of sensitivity to platinum-based chemotherapies, providing more accurate, personalized, and clinically-relevant chemotherapy response prediction is an unmet need. We present our early and ongoing experience with rapid, organoid-based drug-screening. Methods: one gram of tumor was procured from patients undergoing TURBT or RC and divided between DNA/RNA sequencing, organoid drug-screening, and patient-derived xenografts. Tissue was dissociated, filtered, and resuspended in organoid media for serial passage and drug screening. Drugs were tested at “Cmax” concentration, which is the maximum plasma concentration in human trials so as to provide physiologic relevance. Results were normalized to control such that a value of 100 indicated no drug effect compared to control, and a value of 0 indicated complete response. Number of drugs screened was dependent upon tissue available, but was often 20-30. Results: 25 patients have undergone rapid organoid development and drug testing to date. Clinical correlations with chemotherapy response are ongoing. Drug response analyses were available 5-10 days following procedure. Select drug response data from the 9 most recent patient organoid samples are presented in the Table. DNA and RNA sequencing and PDX models are in progress. Conclusions: This platform allows for the rapid determination of neoadjuvant chemotherapy response and may further guide selection of therapeutic agents in patients with locally advanced bladder cancer.[Table: see text]

Abstract P1-10-06: Radiomic measurements of tumor-associated vasculature morphology and function on pretreatment dynamic MRI identifies responders to neoadjuvant chemotherapy

Abstract Background: Angiogenesis is crucial to a tumor's growth and an important factor in therapeutic outcome. Although quantitative analysis of tumors on dynamic contrast enhanced (DCE) MRI can provide indirect characterization of a tumor's vascularization, direct computational analysis of the tumor-associated vessel network remains a promising, but under-explored potential marker of therapeutic response. For instance, surrounding vasculature with a convoluted 3-dimensional shape and poor blood flow may indicate a more aggressive tumor and poorly facilitate delivery of therapeutic agents. In this work, we present a computational approach for the prediction of neoadjuvant chemotherapy response using quantitative imaging features describing the morphology and function of tumor associated vasculature on pretreatment MRI. Methods: 243 patients who received DCE-MRI scans prior to neo-adjuvant chemotherapy (NAC) at institution A [n=83], B [n=76], or one of nine other institutions as part of the ISPY1 Trial [n=84] were divided randomly into training (n=123) and testing (n=120) sets. 148 patients were HER2- and received neoadjuvant AC-T, while the 95 HER2+ patients were treated with TCHP (ISPY predates anti-HER2 therapy and HER2+ ISPY patients were excluded). 79 patients achieved pathological complete response [pCR, ypT0/is] following NAC. MRI exams were collected with a 1.5 or 3 Tesla scanner in the axial or sagittal plane. A baseline scan and 2-5 scans after injection of a gadolinium-based contrast agent with a median temporal resolution of 2.5 minutes were acquired. A portion of the tumor was manually delineated, then semi-automatically expanded to 3D. Vasculature was isolated from subtraction images with a specialized filtering approach to detect vessel-shaped objects. Features describing the 3D shape and architecture of the tumor-associated vessel network (e.g. curvature, torsion, and local orientation) and functional semi-quantitative pharmacokinetic (PK) measurements of temporal contrast enhancement changes (e.g. signal enhancement ratio, time to peak enhancement, and rates of uptake and washout) were calculated. Performance was assessed by area under the receiver operating characteristic curve (AUC), as well as the accuracy, sensitivity, and specificity at the operating point corresponding to the Youden Index. The most discriminating features were determined based on frequency of selection by the random forest classifier. Results: Within the training set, PK parameters of the vessels (AUC=.66) outperformed relative to the PK of tumor (AUC=.63) and the PK of peritumoral regions (AUC=.64); however, a combination of the three yielded best performance (AUC=.75). Vessel shape features alone achieved AUC=.67 in the training set. When multi-region PK features and tumor shape features were combined and applied to the 120-patient independent testing set, the random forest classifier achieved an AUC of 0.70 and identified 81% of patients who would achieve pCR. Non-pCR was best characterized by increased vessel curvature and PK parameters indicating poor perfusion, such as greater time to peak enhancement, slower uptake rate, and quicker washout. Conclusions: Our findings suggest that properties of the tumor-associated vessel network, such as its shape and enhancement profile, might provide value in identifying patients who will respond to NAC before administration of treatment. Accuracy (%)Sensitivity (%)Specificity (%)Full testing set (n=120)678160HER2+ (n=44)709548HER2- (n=76)646365HER2-, HR+ (n=51)678364Triple Negative (n=25)605067 Citation Format: Nathaniel Braman, Prateek Prasanna, Kaustav Bera, Mehdi Alilou, Manasa Vulchi, Maryam Etesami, Paulette Turk, Jame Abraham, Donna Plecha, Anant Madabhushi. Radiomic measurements of tumor-associated vasculature morphology and function on pretreatment dynamic MRI identifies responders to neoadjuvant chemotherapy [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-10-06.

Amplification of 7p12 Is Associated with Pathologic Nonresponse to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer

Pathologic downstaging (pDS) to neoadjuvant chemotherapy (NAC) is one of the most important predictors of survival in muscle-invasive bladder cancer (MIBC). The use of NAC is limited as pDS is only achieved in 30% to 40% of cases and predictive biomarkers are still lacking. We performed a comprehensive immunomolecular biomarker analysis to characterize the role of immune cells and inhibitory checkpoints, genome-wide frequencies of copy number alterations, mutational signatures in whole exome, and tumor mutational burden in predicting NAC response. Our retrospective study included 23 primary MIBC patients who underwent NAC, followed by radical cystectomy. pDS to NAC was a significant prognostic factor for better recurrence-free survival (P<0.001), with a median time to recurrence of 41.2 versus 5.5 months in nonresponders. DNA damage repair alterations were noticed in 38.1% (n = 8), confirming a positive correlation with high tumor mutational burden (P=0.007). Chromosomal 7p12 amplification, including the genes HUS1, EGFR, ABCA13, and IKZF1, predicted nonresponse in patients with a sensitivity, a negative predictive value, and a specificity of 71.4%, 87.5%, and 100%, respectively. Total count of CD3+ T cells/mm2 tumor was a significant predictor of NAC response. In conclusion, 7p12 amplification may predict nonresponse to NAC and worse survival in MIBC. Multicenter, prospective trials with sufficient statistical power may further fortify these findings.

Using Clinicopathomic Markers to Predict Neoadjuvant Chemotherapy Response in Breast Cancer

Using Clinicopathomic Markers to Predict Neoadjuvant Chemotherapy Response in Breast Cancer

Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer

Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer

Monitoring breast cancer response to neoadjuvant chemotherapy with ultrasound signal statistics and integrated backscatter.

BackgroundNeoadjuvant chemotherapy (NAC) is used in patients with breast cancer to reduce tumor focus, metastatic risk, and patient mortality. Monitoring NAC effects is necessary to capture resistant patients and stop or change treatment. The existing methods for evaluating NAC results have some limitations. The aim of this study was to assess the tumor response at an early stage, after the first doses of the NAC, based on the variability of the backscattered ultrasound energy, and backscatter statistics. The backscatter statistics has not previously been used to monitor NAC effects.MethodsThe B-mode ultrasound images and raw radio frequency data from breast tumors were obtained using an ultrasound scanner before chemotherapy and 1 week after each NAC cycle. The study included twenty-four malignant breast cancers diagnosed in sixteen patients and qualified for neoadjuvant treatment before surgery. The shape parameter of the homodyned K distribution and integrated backscatter, along with the tumor size in the longest dimension, were determined based on ultrasound data and used as markers for NAC response. Cancer tumors were assigned to responding and non-responding groups, according to histopathological evaluation, which was a reference in assessing the utility of markers. Statistical analysis was performed to rate the ability of markers to predict the final NAC response based on data obtained after subsequent therapeutic doses.ResultsStatistically significant differences (p<0.05) between groups were obtained after 2, 3, 4, and 5 doses of NAC for quantitative ultrasound markers and after 5 doses for the assessment based on maximum tumor dimension. Statistical analysis showed that, after the second and third NAC courses the classification based on integrated backscatter marker was characterized by an AUC of 0.69 and 0.82, respectively. The introduction of the second quantitative marker describing the statistical properties of scattering increased the corresponding AUC values to 0.82 and 0.91.ConclusionsQuantitative ultrasound information can characterize the tumor's pathological response better and at an earlier stage of therapy than the assessment of the reduction of its dimensions. The introduction of statistical parameters of ultrasonic backscatter to monitor the effects of chemotherapy can increase the effectiveness of monitoring and contribute to a better personalization of NAC therapy.

ASO Author Reflections: Role of Genomic Assay to Predict Neoadjuvant Chemotherapy Response in Breast Cancer.

ASO Author Reflections: Role of Genomic Assay to Predict Neoadjuvant Chemotherapy Response in Breast Cancer.

Abstract P3-11-16: Immunosuppressive profiles in liquid biopsy predict response to neoadjuvant chemotherapy in triple negative breast cancer

Abstract BACKGROUND Despite the recent advances in triple negative breast cancer (TNBC) stratification, TNBC is still a highly heterogeneous subtype that clusters distinct molecular and genetic alterations with diverse responses to neoadjuvant chemotherapy (NAC). Molecular profiling after NAC has unraveled a group of actionable targets in residual TNBC that supports the implementation of targeted therapies in a personalized manner. However, unresponsive or poor NAC responders after first line treatment are committed to poorer outcome. Therefore, early identification of poor NAC responders is essential to select patients that may benefit from alternative therapies, including initial tumor resection before chemotherapy. MATERIAL AND METHODS We have conducted a study on 37 non-metastatic TNBC patients at La Fe Hospital that were homogeneously treated with anthracycline and cyclophosphamide followed by paclitaxel. Tissue and blood-derived biopsies were obtained at diagnosis. Metabolites and miRNA exosomes in plasma were analyzed by ultra-performance liquid chromatography-electrospray ionization tandem mass spectrometric and by miRNA 3.0 arrays (Affymetrix) respectively. Immunosuppressive subpopulations of cells were quantified by flow cytometry with specific markers. IDO1 in situ expression was assessed by immunohistochemistry on the tissue biopsies. RESULTS In order to identify blood-derived liquid biopsy NAC predictor biomarkers in TNBC we have studied blood circulating cells and molecules known for their immunomodulation capacity and found that eMDSC and a profile of tryptophan-derived metabolites predict NAC response. In addition, we identified a circulating exosome miRNA profile that identifies poor NAC responders. Interestingly, this profile of miRNAs target pathways involved in the immune response. IDO1 expression in the tumor inversely correlated with circulating tryptophan levels and directly associated with eMDSC. We also observed a trend correlating IDO1 expression levels with poorer response. CONCLUSIONS Our results strongly support the role of immunosuppression in TNBC poor responders and establish an easy and non-invasive tool for the early identification of poor NAC responders, opening the possibility to use alternative strategies. Acknowledgements: The authors would like to thank the Cytomics Unit, Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain for its technical support. This work was partially financed with FEDER funds (CIBERONC (CB16/ 12/00284)) and AMACMA breast cancer association. Citation Format: Salvador-Coloma C, Font De Mora J, Cordón L, Palomar L, Santaballa A. Immunosuppressive profiles in liquid biopsy predict response to neoadjuvant chemotherapy in triple negative breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-11-16.

The Role of Neutrophil-lymphocyte Ratio and Platelet-lymphocyte Ratio in Predicting Neoadjuvant Chemotherapy Response in Breast Cancer.

PurposeThe role of the host immunologic environment is crucial in cancer progression. Recent studies revealed that neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR), are possible surrogate markers of outcome in various cancers. In breast cancer, the therapeutic effect of neoadjuvant chemotherapy (NAC) differs in patients, and higher response rate reflects better outcomes. This study aimed to determine the predictive value of peripheral blood NLR and PLR for NAC response along with their prognostic role in breast cancer.MethodA total of 105 patients with breast cancer treated with NAC between 2009 and 2017 were analyzed retrospectively. NAC response and prognosis (disease-free-survival [DFS], progression-free-survival [PFS] and overall survival [OS]) according to NLR and PLR were evaluated. According to the optimal cut-off values for NAC response obtained from receiver operating characteristic (ROC) curves, patients satisfying both low NLR and PLR levels (low-ratio group) were compared to those who did not (high-ratio group).ResultsThe NLR cut-off value was ≤ 2.21 (area under the ROC curve [AUC], 0.617; 95% confidence interval [CI], 0.517–0.710; p=0.030) with 94.1% sensitivity and 38.0% specificity. The PLR cut-off value was ≤ 143.36 (AUC, 0.618; 95% CI, 0.518–0.711; p = 0.040) with 85.3% sensitivity and 39.4% specificity. The low-ratio group demonstrated a better NAC response (p = 0.006) in multivariate analysis than the high-ratio group. The low-ratio group showed better DFS and PFS (p = 0.046 and p = 0.040, respectively) and longer OS (p = 0.078) in univariate survival analysis than the high-ratio group. In multivariate analysis, the low-ratio group had significantly better PFS (p = 0.049) and higher DFS (p = 0.054) than the high-ratio group.ConclusionsThe combination of NLR and PLR showed improved prediction of NAC response, revealing their potential as screening tools, significant prognostic role in breast cancer patients who receive NAC. Further studies with subgroup analysis, larger population and longer follow up duration are required.

Predicting neo-adjuvant chemotherapy response and progression-free survival of locally advanced breast cancer using textural features of intratumoral heterogeneity on F-18 FDG PET/CT and diffusion-weighted MR imaging.

Predicting response to neo-adjuvant chemotherapy (NAC) and survival in locally advanced breast cancer (LABC) is important. This study investigated the prognostic value of tumor heterogeneity evaluated with textural analysis through F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and diffusion-weighted imaging (DWI). We enrolled 83 patients with LABC who had completed NAC and curative surgery. Tumor texture indices from pretreatment FDG PET and DWI were extracted from histogram analysis and 7 different parent matrices: co-occurrence matrix, the voxel-alignment matrix, neighborhood intensity difference matrix, intensity size-zone matrix (ISZM), normalized gray-level co-occurrence matrix (NGLCM), neighboring gray-level dependence matrix (NGLDM), and texture spectrum matrix. The predictive values of textural features were tested regarding both pathologic NAC response and progression-free survival. Among 83 patients, 46 were pathologic responders, while 37 were nonresponders. The PET texture indices from 7 parent matrices, DWI texture indices from histogram, and 1 parent matrix (NGLCM) showed significant differences according to NAC response. On multivariable analysis, number nonuniformity of PET extracted from the NGLDM was an independent predictor of pathologic response (P = .009). During a median follow-up period of 17.3 months, 14 patients experienced recurrence. High-intensity zone emphasis (HIZE) and high-intensity short-zone emphasis (HISZE) from PET extracted from ISZM were significant textural predictors (P = .011 and P = .033). On Cox regression analysis, only HIZE was a significant predictor of recurrence (P = .027), while HISZE showed borderline significance (P = .107). Tumor texture indices are useful for NAC response prediction in LABC. Moreover, PET texture indices can help to predict disease recurrence.

342 (PB-137) - Prediction of neoadjuvant chemotherapy response in breast cancer

342 (PB-137) - Prediction of neoadjuvant chemotherapy response in breast cancer

Positron emission mammography in the evaluation of interim response to neoadjuvant chemotherapy in patients with locally advanced breast cancer

Neoadjuvant chemotherapy (NAC) has an important role in patients with locally advanced cancers, treating distant micrometastases, downstaging tumors, improving operability, and sometimes allowing breast-conserving surgery to take place. We studied the association between two Positron Emission Mammography with 18F-FDG (18F-FDG-PEM) semi-quantitative parameters in 108 patients and correlated with pathologic response in each of the following breast cancer subtype: Triple negative breast cancer (TPN), HER2-positive, and ER-positive/HER2-negative cancers. AimExamine the association between two Positron Emission Mammography (PEM) semi-quantitative parameters: PUVmax (maximum uptake value) and LTB (lesion to background) baseline and the end of NAC with pathologic response in each breast cancer subtype. Methods108 patients, 71 with invasive ductal carcinoma and 37 with infiltrating lobular carcinoma were evaluate with 18F-FDG-PEM scans baseline and after end of NAC. We assessed the impact of 2 PEM semi-quantitative parameters for molecular subtype correlated with pathologic response according Miller-Payne grade (MPG). ResultsAfter NAC, an overall reduction of 2 PEM semi-quantitative parameters was found. Neither breast cancer subtypes nor Ki67 modified chemotherapy responses. Compared to PUVmax, an overall increase of LTB was found in baseline condition, independent of the expressed immunophenotype. Post-treatment values of PUVmax revealed a significant reduction compared to baseline values (4.8 ± 0.26 vs. 1.9 ± 0.18; p < 0.001) and LTB exhibited a significant decay after the first course of NACT (15.8 ± 1.36 vs. 5.5 ± 0.49; p < 0.001). Using the Kruskal–Wallis H test which showed no correlation between the different molecular subtypes and the MPG and PUVmax and LTB (p = 0.52), but if a correlation was found between the response rate by MPG and both semiquantitative parameters (p = 0.05). Conclusion2 PEM semi-quantitative parameters demonstrated a statically significant correlation and equivalence across the different breast cancer subtypes correlated with pathologic response according to MPG. PEM did not allow for prediction of NAC response in terms of breast cancer biomarkers, it is not discarded that this technology might be helpful for individual treatment stratification in breast cancer.

Multiparametric Evaluation of Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer Using Integrated PET/MR

The aim of this study was to investigate whether integrated PET/MR system can predict the treatment response to neoadjuvant chemotherapy (NAC) early in the course of breast cancer treatment. Fourteen women with newly diagnosed invasive breast cancer (median age, 54.5 years) were recruited. Each participant underwent 2 PET/MR studies. Study 1 was pre-NAC; study 2 was early in NAC treatment (after the first or second cycle). PET parameters included SUVmax and total lesion glycolysis (TLG). MRI parameters included choline signal-to-noise ratio (ChoSNR), peak enhancement ratio (PER), and the minimum apparent diffusion coefficient (ADCmin). The pathologic response was categorized as a pathologic complete response or residual cellularity of less than 10% (group 1) and residual cellularity of 10% or greater (group 2). The accuracy of the NAC response prediction was obtained by receiver operating characteristic analysis. Group 1 showed a greater reduction of SUVmax (percentage change, [INCREMENT]% SUVmax, P = 0.013; area under the receiver operating characteristic curve [AUC], 0.898), TLG ([INCREMENT]%TLG, P = 0.018; AUC = 0.878), and PER ([INCREMENT]% PER, P = 0.035; AUC = 0.837) than did group 2. The ChoSNR, ADCmin, [INCREMENT]%ChoSNR, and [INCREMENT]%ADCmin did not differ significantly between the 2 groups. The hybrid markers, [INCREMENT]%SUVmax/[INCREMENT]%ADCmin (AUC = 0.976) and [INCREMENT]%TLG/[INCREMENT]%ADCmin (AUC = 0.905), showed greater accuracy in predicting NAC response than the individual PET/MR parameters. The PET/MR parameters can predict the NAC response early in the course of breast cancer treatment. The hybrid markers more accurately predicted treatment response than the individual PET/MR parameters.

The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients

BackgroundNeoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. This is presumably due to differences in the molecular mechanisms that underlie each tumor’s disease pathology. Developing genomic clinical assays that accurately categorize responders from non-responders can provide patients with the most effective therapy for their individual disease.MethodsWe applied our previously developed E2F4 genomic signature to predict neoadjuvant chemotherapy response in breast cancer. E2F4 individual regulatory activity scores were calculated for 1129 patient samples across 5 independent breast cancer neoadjuvant chemotherapy datasets. Accuracy of the E2F4 signature in predicting neoadjuvant chemotherapy response was compared to that of the Oncotype DX and MammaPrint predictive signatures.ResultsIn all datasets, E2F4 activity level was an accurate predictor of neoadjuvant chemotherapy response, with high E2F4 scores predictive of achieving pathologic complete response and low scores predictive of residual disease. These results remained significant even after stratifying patients by estrogen receptor (ER) status, tumor stage, and breast cancer molecular subtypes. Compared to the Oncotype DX and MammaPrint signatures, our E2F4 signature achieved similar performance in predicting neoadjuvant chemotherapy response, though all signatures performed better in ER+ tumors compared to ER- ones. The accuracy of our signature was reproducible across datasets and was maintained when refined from a 199-gene signature down to a clinic-friendly 33-gene panel.ConclusionOverall, we show that our E2F4 signature is accurate in predicting patient response to neoadjuvant chemotherapy. As this signature is more refined and comparable in performance to other clinically available gene expression assays in the prediction of neoadjuvant chemotherapy response, it should be considered when evaluating potential treatment options.

Diffusion weighted imaging in early prediction of neoadjuvant chemotherapy response in breast cancer

BackgroundNeoadjuvant chemotherapy (NAC) has clinically important outcome. Early evaluation of the treatment response is important to avoid unnecessary therapy in non-responders. MRI is the most sensitive imaging for monitoring NAC response. Aim of this studyIs to test the ability of DWI to detect early response to NAC. ResultsThe study was performed on 20 patients, proved pathologically to have invasive breast cancer. All patients underwent breast MRI before initiation of NAC, after one cycle and after completion of the NAC protocol. Regarding the mass size, results showed no significant change in maximum mass diameters occur after the 1st NAC cycle. Absolute value of the ADC show increase all along the treatment course which has no significant correlation with the pathological response. The relative increase ADC more than 20% calculated from subtraction of the pre-treatment ADCmean value from that after the first NAC, subdividing the result on the pre-treatment ADCmean value and multiply it by 100 reflected significantly on the pathological response (p value of 0.011). ConclusionADC value can predict responder from non-responder as early as after the first cycle of chemotherapy.

P168 - Prediction of neoadjuvant chemotherapy response in breast cancer

P168 - Prediction of neoadjuvant chemotherapy response in breast cancer

DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response.

This study investigates the effectiveness of hundreds of texture features extracted from voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps for early prediction of breast cancer response to neoadjuvant chemotherapy (NAC). In total, 38 patients with breast cancer underwent DCE-MRI before (baseline) and after the first of the 6–8 NAC cycles. Quantitative pharmacokinetic (PK) parameters and semiquantitative metrics were estimated from DCE-MRI time-course data. The residual cancer burden (RCB) index value was computed based on pathological analysis of surgical specimens after NAC completion. In total, 1043 texture features were extracted from each of the 13 parametric maps of quantitative PK or semiquantitative metric, and their capabilities for early prediction of RCB were examined by correlating feature changes between the 2 MRI studies with RCB. There were 1069 pairs of feature–map combinations that showed effectiveness for response prediction with 4 correlation coefficients >0.7. The 3-dimensional gray-level cooccurrence matrix was the most effective feature extraction method for therapy response prediction, and, in general, the statistical features describing texture heterogeneity were the most effective features. Quantitative PK parameters, particularly those estimated with the shutter-speed model, were more likely to generate effective features for prediction response compared with the semiquantitative metrics. The best feature–map pair could predict pathologic complete response with 100% sensitivity and 100% specificity using our cohort. In conclusion, breast tumor heterogeneity in microvasculature as measured by texture features of voxel-based DCE-MRI parametric maps could be a useful biomarker for early prediction of NAC response.

Biomarkers from in vivo molecular imaging of breast cancer: pretreatment 18F-FDG PET predicts patient prognosis, and pretreatment DWI-MR predicts response to neoadjuvant chemotherapy

ObjectiveHuman cancers display intra-tumor phenotypic heterogeneity and recent research has focused on developing image processing methods extracting imaging descriptors to characterize this heterogeneity. This work assesses the role of pretreatment 18F-FDG PET and DWI-MR with respect to the prognosis and prediction of neoadjuvant chemotherapy (NAC) outcomes when image features are used to characterize primitive lesions from breast cancer (BC).Materials and methodsA retrospective protocol included 38 adult women with biopsy-proven BC. Patients underwent a pre-therapy 18F-FDG PET/CT whole-body study and a pre-therapy breast multi-parametric MR study. Patients were then referred for NAC treatment and then for surgical resection, with an evaluation of the therapy response. Segmentation methods were developed in order to identify functional volumes both on 18F-FDG PET images and ADC maps. Macroscopic and histogram features were extracted from the defined functional volumes.ResultsOur work demonstrates that macroscopic and histogram features from 18F-FDG PET are able to biologically characterize primitive BC, and define the prognosis. In addition, histogram features from ADC maps are able to predict the response to NAC.ConclusionOur work suggests that pre-treatment 18F-FDG PET and pre-treatment DWI-MR provide useful complementary information for biological characterization and NAC response prediction in BC.

Abstract PD3-05: Effect of MR imaging contrast kinetic thresholds for prediction of neoadjuvant chemotherapy response in breast cancer subtypes – Results from ACRIN 6657 / I-SPY 1 trial

Abstract Background: Breast MRI has the potential to non-invasively measure response to neoadjuvant chemotherapy (NACT). We studied the effect of varying two analytic parameters used to define MRI-measured tumor volume in the prediction of pathologic complete response (pCR) to NACT and to determine if optimization of these parameter thresholds would improve the prediction of pCR. Methods: Women with locally advanced breast cancer (tumor size ≥ 3cm) were enrolled in the ACRIN 6657 / I-SPY 1 TRIAL. Each patient had up to four dynamic contrast-enhanced MRI examinations: before NACT (MR1), after one cycle of NACT (MR2), between the anthracycline-based regimen and taxane (MR3), and after NACT and prior to surgery (MR4). Breast cancer was stratified by subtypes of hormone receptor (HR), and human epidermal growth factor receptor 2 (HER2) status: HR+/HER2, HER2+, and triple negative ((TN) HR-/HER2-). MRI-measured functional tumor volume (FTV) and change in FTV (ΔFTV) were investigated as predictors of the outcome pCR. FTV is defined as the image volume with enhancement kinetics exceeding both an early percentage enhancement threshold (PEt) and a signal enhancement ratio threshold (SERt). Primary study analysis used empirically determined values. For this study PEt was varied from 30% to 200% in 10% intervals, and SERt was varied from 0.0 to 2.0 in 0.2 unit intervals. FTV was measured at each examination (FTV1, FTV2, FTV3, FTV4). ΔFTV was measured relative to the first examination (ΔFTV2, ΔFTV3, ΔFTV4). For each pair of varied PEt and SERt thresholds, the absolute and relative FTVs were re-measured and analyzed for discrimination of pCR using the area under the curve (AUC) of the receiver operating characteristic curve. Results: A total of 116 patients were included from the ACRIN 6657 / I-SPY 1 TRIAL who had complete data on all four MRI visits, HR/HER2 status, and pCR outcome. Mean age was 48 years old (range 29-69). The full cohort of 116 patients was divided into subgroups: 45 (39%) HR+/HER2-; 39 (34%) HER2+; and 30 (26%) TN. When stratified by subtypes, lower AUCs with less variation were observed in patients with HER2+ cancer than patients with HR+/HER2- and TN breast cancer. When examining prediction by visit, maximum AUCs were found at later time points in all patient cohorts. Specifically, maximum AUC was observed for the full cohort at ΔFTV3 with AUC of 0.78 (CI: 0.69–0.87) when PEt=130% and SERt=0; for HR+/HER2- subtype at ΔFTV3 with AUC of 0.9 (CI: 0.84–0.97) when PEt=130% and SERt=0 were the same as in the full cohort; for HER2+ subtype at FTV3 with AUC of 0.77 (CI: 0.62–0.92) when PEt=70%/SERt=1.4; for triple negative at FTV4 with AUC of 0.89 (CI: 0.76–1) when PEt=40%/SERt=2.0. Conclusion: This analysis suggests that the thresholds of MRI quantitative DCE measurements may need to be adjusted by breast cancer subtype to improve the predictive performance. The PEt threshold may need to be set higher in HR+/HER2- than other subtypes, which may be due to higher background parenchymal enhancement among HR+ patients. SER threshold may need to be set at higher level for triple negative subtype. A validation is underway in I-SPY 2, with a larger patient population. Citation Format: Li W, Arasu V, Jones EF, Newitt DC, Wilmes LJ, Kornak J, Esserman LJ, Hylton NM. Effect of MR imaging contrast kinetic thresholds for prediction of neoadjuvant chemotherapy response in breast cancer subtypes – Results from ACRIN 6657 / I-SPY 1 trial [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr PD3-05.

Effect of MR Imaging Contrast Thresholds on Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes: A Subgroup Analysis of the ACRIN 6657/I-SPY 1 TRIAL.

Functional tumor volume (FTV) measurements by dynamic contrast-enhanced magnetic resonance imaging can predict treatment outcomes for women receiving neoadjuvant chemotherapy for breast cancer. Here, we explore whether the contrast thresholds used to define FTV could be adjusted by breast cancer subtype to improve predictive performance. Absolute FTV and percent change in FTV (ΔFTV) at sequential time-points during treatment were calculated and investigated as predictors of pathologic complete response at surgery. Early percent enhancement threshold (PEt) and signal enhancement ratio threshold (SERt) were varied. The predictive performance of resulting FTV predictors was evaluated using the area under the receiver operating characteristic curve. A total number of 116 patients were studied both as a full cohort and in the following groups defined by hormone receptor (HR) and HER2 receptor subtype: 45 HR+/HER2−, 39 HER2+, and 30 triple negatives. High AUCs were found at different ranges of PEt and SERt levels in different subtypes. Findings from this study suggest that the predictive performance to treatment response by MRI varies by contrast thresholds, and that pathologic complete response prediction may be improved through subtype-specific contrast enhancement thresholds. A validation study is underway with a larger patient population.