Residual Cancer Burden Score Research Articles

Abstract P5-02-09: Quantitative analysis of fiber-level collagen features in H&E whole-slide images predicts neoadjuvant therapy response in patients with HER2+ breast cancer

Abstract Background: Neoadjuvant treatment (NAT) combining chemotherapy and HER2-targeted agents is frequently administered to HER2-positive (HER2+) breast cancer (BC) patients, with some experiencing a pathological complete response (pCR) and others having residual disease measured by the residual cancer burden (RCB) score. Here, we use a physics-guided machine learning (ML)-based approach to extract fiber-level collagen features from hematoxylin and eosin (H&E)-stained whole slide images (WSIs) and identify collagen-related associations with treatment response in HER2+ patients receiving NAT. Methods: Clinical data and specimens from stage II-III HER2+ BC patients enrolled on the De-escalation to Adjuvant Antibodies Post-pCR to Neoadjuvant THP (DAPHNe; NCT03716180) clinical trial and treated with neoadjuvant paclitaxel/trastuzumab/pertuzumab were analyzed. An ML-based model trained to identify regions of BC tissue as invasive carcinoma, ductal carcinoma in situ (DCIS), diffuse inflammatory infiltrate, stroma, necrosis, or normal tissue was deployed on WSIs of H&E-stained diagnostic core needle biopsies (N=89) to generate tissue overlays. Additional tissue areas were computed from the tissue model predictions using heatmap transformation, including tumor nests (continuous regions predicted as invasive cancer epithelium or DCIS), tumor nest borders (stromal region boundaries 10 μm from tumor nests), and bulk tumor borders (stromal region boundaries 300 μm from aggregated tumor nests). A separate ML-based model trained to identify fiber-level collagen features in WSIs of H&E-stained specimens was also deployed to generate collagen overlays. A fiber feature extraction pipeline was utilized to characterize properties of all identified collagen fibers in the WSI (on the order of hundreds of thousands per slide), including length, width, tortuosity, and angle. These fiber features were then assessed based on their position within the tumor (e.g. relative to the tumor nest border). Combinatorial features (e.g. angle of fibers with respect to tumor boundary) were then explored univariately for associations (N=609) with treatment response. Patients with pCR (RCB=0; N=53) were considered responders, while all other cases (RCBI-III; N=36) were designated non-responders. Due to the small size of the cohort analyzed here, raw p-values are reported. Results: Using estrogen receptor status as a clinical covariate, a logistic regression-based univariate analysis of 609 collagen-associated features revealed six features to strongly associate with pCR (p< 0.05, AUC≥0.75; Table 1). Notable feature themes were identified: 1) fiber tortuosity in tumor nest borders and tumor borders, 2) angle of fibers in tumor border with respect to tumor boundary, and 3) distribution patterns of fiber width in tumor nest borders. The presence of fibers perpendicular to tumor boundary tangents was negatively associated with pCR, as was higher fiber tortuosity and thickness in tumor nest borders. Conclusions: Improved prediction of response to NAT in patients with BC is needed to determine appropriate treatment strategies for each patient. Here, using ML-based models to identify tissue features and collagen fibers, we identify collagen-associated features, measured directly from WSIs of H&E-stained diagnostic BC biopsies, that negatively correlate with pCR. Additional development of this strategy, including the addition of cell identification models and known clinical information, is underway to further refine this novel predictive model. Citation Format: Tan H. Nguyen, Mohammad Mirzadeh, Aaditya Prakash, Emma L. Krause, Jun Zhang, Michael Pyle, Esther R. Ogayo, Harry C. Cramer, Busem Binboga Kurt, Jacqueline Brosnan-Cashman, Michael G. Drage, Stuart Schnitt, Andrew H. Beck, Michael Montalto, Ilan Wapinski, Laura Chambre, Sara Tolaney, Adrienne Waks, Justin Lee, Elizabeth A. Mittendorf. Quantitative analysis of fiber-level collagen features in H&E whole-slide images predicts neoadjuvant therapy response in patients with HER2+ 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 P5-02-09.

Abstract P3-05-25: Clinical Factors associated with Survival Outcomes in Patients with Metaplastic Breast Cancer

Abstract Background Metaplastic breast cancer (MBC) is a rare and aggressive subtype of breast cancer (BC) defined by presence of both epithelial and mesenchymal components. Most are triple negative but are often chemo-refractory and associated with poor survival outcomes compared to non-metaplastic triple negative BC. Advances in therapy have led to improvements in survival outcomes of patients (pts) with BC over the last decade. Our multicenter retrospective study aims to assess (1) progression free survival (PFS) and overall survival (OS) (2) factors predictive of survival outcomes in MBC pts Methods We performed a retrospective analysis of pts diagnosed with MBC from 1997-2021 at Mayo Clinic (Florida, Arizona and Rochester) under IRB approval. Kaplan-Meier method was used to estimate OS and PFS at 1, 3 and 5 years. Cox regression models were used to examine the association between risk factors and survival outcomes. All tests were two-sided with p value < 0.05 considered statistically significant Results We evaluated 158 pts with MBC. Median age and tumor size was 61 (range: 20-91) years and 2.8 (range: 0.5-21) cm, respectively, with 80% of pts being postmenopausal. At diagnosis, 14.6% of pts had clinical T3/T4 disease, 16.4% were clinically node-positive, and 6.3% (10 pts) had distant metastases (DM). Spindle cell histology was seen in 36 pts. Most MBC pts were triple-negative (68.3%), high grade (77.2%) and high Ki-67 (36/47; 76.5%). Of the 61 pts tested for germline mutation, 8 (13.1%) were positive, with BRCA1/2, PTEN, NBN, CHEK2, and BARD1 mutations. Most pts had lumpectomy (53.8%), followed by simple mastectomy (38.5), and modified radical mastectomy (7.7%). Majority of pts had sentinel lymph node biopsy (71.8%). Adjuvant radiation therapy was performed in 65.6% of pts. Pathologic complete response (pCR) was noted in 4/38 (10.5%) evaluable pts who received neoadjuvant chemotherapy (NACT). Residual cancer burden (RCB) scores of 2 and 3 were seen in 76.2% of evaluable pts. Median follow-up time was 2.2 years (range: 6 days-24.6 years). Overall, 1-, 3-, and 5-year OS was 93.3%, 81.7%, and 76.0%, while PFS was 80.8%, 67.9%, and 60.9%, respectively. The presence of DM at diagnosis [HR 38.55 (11.18, 132.93), p < 0.001] and spindle cell histology (SC) [HR 2.57 (1.19, 5.53), p = 0.02] predicted worse OS in multivariable analysis. Inferior PFS was predicted by DM [HR 18.84 (6.53, 54.35), p < 0.001], SC [HR 2.46 (1.25, 4.86), p = 0.009], and node-positivity at diagnosis [HR 3.65 (1.5, 8.89), p = 0.004]. The 5-year OS and PFS were 22.2% and 0% for DM pts versus 80.0% and 65.6% for non-DM pts. The 5-year OS and PFS were 71.5% and 54.7% for SC pts versus 81% and 66.6% for non-SC pts. 5-year OS and PFS for NACT pts was 67.3% and 52.6% for NACT pts versus 78.2% and 62.8% for non-NACT pts. Age at diagnosis, menopausal status, family history of BC, grade, stage, tumor size, hormone-receptor and HER2 status, and use of NACT were not found to be significantly associated with OS or PFS in multivariate analysis. Conclusion This study is one of the largest and most recent review of institutional experiences with MBC. Overall, OS at 5 years was improved compared to prior older studies of MBC but still remains very low for those with DM, representing an area of unmet clinical need. SC and DM correlated with worse outcomes for both PFS and OS. Additionally, node positivity at diagnosis was a predictor of worse PFS. In contrast, no association was seen between survival and tumor size, stage, hormone receptor-positivity, HER2 receptor-positivity. The low pCR rates following NACT in our study are consistent with reported literature. Further, use of NACT does not impact survival, suggesting pts with resectable disease should proceed with surgery first. Citation Format: Siven Chinniah, Raza Zarrar, Zhuo Li, Kostandinos Sideras, Alvaro Moreno-Aspitia, Saranya Chumsri, Rohit Rao, Sarah McLaughlin, James Jakub, Emmanuel Gabriel, Sanjay Bagaria, Laura Vallow, Santo Maimone, Pooja Advani. Clinical Factors associated with Survival Outcomes in Patients with Metaplastic 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 P3-05-25.

Abstract P6-04-08: Machine learning-based characterization of the breast cancer tumor microenvironment for assessment of neoadjuvant-treatment response

Abstract Background: Neoadjuvant treatment of breast cancer has been shown to potentially reduce the extent and morbidity of subsequent surgery. Response to neoadjuvant therapy may also be prognostic; complete pathologic response (pCR) following neoadjuvant treatment is associated with improved long-term outcomes. pCR, defined as the absence of residual invasive cancer, is determined by evaluation of H&E-stained breast resections and regional lymph nodes following neoadjuvant treatment; however, pathologist assessment is subject to intra- and inter-reader variability. Here we report machine learning (ML)-based models to identify tissue regions and cell types in the tumor microenvironment (TME) of H&E-stained breast cancer specimens. Model predictions were used to derive tumor bed area, a key component of the residual cancer burden score (RCB) used to assess neoadjuvant-treatment pathological response. Methods: Convolutional neural network (CNN) models were trained using digitized H&E-stained whole slide images (WSIs) of 2700 neoadjuvant-treated breast cancer specimens (resections and biopsies) from 4 sources, and an additional 1100 breast cancer primary resections from TCGA. 229,901 pathologist annotations were used to train CNN models to segment tissue regions (cancer epithelium, stroma, diffuse inflammatory infiltrate, ductal carcinoma in situ, lymph nodes and necrosis) and cell types (cancer epithelial cells, fibroblasts, lymphocytes, macrophages, foamy macrophages and plasma cells) at single-pixel resolution. These tissue region segmentations were then used to derive tumor bed area using a convex hull algorithm. Each model was evaluated by board certified pathologists for performance. Model predictions of tumor bed area were evaluated in comparison to mean measurements from 3 pathologists for each of 22 held-out test slides. To further assess cell model performance, 5 pathologists exhaustively annotated 120 frames (300 x 300 pixels) on test samples from a dataset not used in model development (N=536; resections and biopsies) to produce consensus ground truth cell labels. Model predictions were compared with pathologist annotations in these frames using Pearson correlation, precision, recall, and F1 metrics. Only those classes with greater than 50 consensus cells identified were evaluated. Results: CNN predictions of tissue and cell classes within H&E breast cancer WSIs showed concordance with manual pathologist consensus labels. The weighted average Pearson correlation (across the relevant cell types) between the model and consensus was 0.75, comparable to the correlation of 0.81 between pathologists and consensus. Classification metrics for each cell class are reported in Table 1. Reduced performance of the model relative to the average pathologist performance may be due to heterogeneous slide characteristics and infrequency of some cell types in the data. For prediction of tumor bed area, CNN model predictions showed moderate correlation with pathologist consensus (Pearson r=0.65, 95% CI: 0.38-0.81). Conclusions: CNN model classification of cell types and tissue regions across entire H&E breast cancer WSIs shows concordance with pathologist consensus. Model predictions of tumor bed area also show concordance with pathologist assessment and can be used to derive the RCB score. These models can be reproducibly applied to quantify diverse histological features in large datasets, potentially enabling improved standardization and efficiency of pathologist evaluation of the breast cancer TME and neoadjuvant response. Classification Metrics for Individual Cell Classes Citation Format: Christian Kirkup, Sanjana Vasudevan, Filip Kos, Benjamin Trotter, Murray Resnick, Andrew H. Beck, Michael Montalto, Ilan Wapinski, Ben Glass, Mary Lin, Stephanie Hennek, Archit Khosla, Michael G. Drage, Laura Chambre. Machine learning-based characterization of the breast cancer tumor microenvironment for assessment of neoadjuvant-treatment response [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 P6-04-08.

141MO Pathological response and early survival data according to TNBCtype4 classifier in operable triple-negative breast cancer (TNBC) treated with neoadjuvant carboplatin and docetaxel

141MO Pathological response and early survival data according to TNBCtype4 classifier in operable triple-negative breast cancer (TNBC) treated with neoadjuvant carboplatin and docetaxel

Stromal Tumor Infiltrating Lymphocytes (sTIL) as an Independent Predictor of Pathologic Response to Neadjuvant Chemotherapy in Breast Cancer in Indonesia: A Hospital-based Study.

We aim to describe the sTIL profiles of Indonesian breast cancer patient and its role in predicting neoadjuvant chemotherapy response. This retrospective cohort study used secondary data from the archive of Anatomic Pathology Department FMUI/CMH. We did total sampling of 62 cases of locally advanced breast cancer cases that were biopsied, had neoadjuvant chemotherapy, and operated on from 2015 to 2020. We collected the clinicopathological data of each sample, measured the sTIL intensity in the biopsy specimen and evaluated the chemotherapy response from the mastectomy specimen using residual cancer burden (RCB) scoring method. Multivariate linear regression determined the independent predictors of RCB score. There were 62 female patients, 45.2% were Luminal-HER2-, 43.5% were HER2+, and 11.3% were triple negative (TN). Most sTIL intensity (59.7%) were low (median 10%; 1%-60%). Moderate-high sTIL intensity was associated with HER2+ type, while low sTIL was with luminal-HER2- (p=0.038). Only 8.1% patients achieved pCR. Statistically different median sTIL intensity in minimal, moderate, and extensive burden group were 28%, 20%, and 8%, respectively (p=0.002). sTIL was an independent predictor for better response (lower RCB score), which were 0.07 (95% CI 0.04-0.09) lower for every 1% increase in sTIL intensity. sTIL intensity was mostly low in Indonesian breast cancer patient. However, it can predict neoadjuvant chemotherapy response, with 0.07 lower RCB score for every 1% increase of sTIL intensity.

Abstract 476: Predicting response to treatment in early breast cancer using dynamic integrative multi-omic profiling

Abstract Aim: We recently published the first machine learning framework that integrates multi-omic data derived from the pre-therapy breast tumor ecosystem to accurately predict response to neoadjuvant systemic therapy (Sammut et al, Nature 2021). We aimed to extend this framework to incorporate serially acquired multi-omic data to further improve response predictions and model tumor biology as it is perturbed by treatment. Methods: Breast tumor core biopsies were acquired at diagnosis from 168 women that went on to receive pre-operative chemotherapy (or chemotherapy plus anti-HER2 targeted therapy). Serial tumor core biopsies were obtained midway (n=78) and on completion (n=69) of neoadjuvant systemic therapy. Response was assessed at surgery using the Residual Cancer Burden score. Core biopsies were molecularly profiled by shallow whole genome, exome and RNA sequencing and their histological architecture characterized using digital pathology. Baseline clinical, molecular, and digital pathology imaging features associated with response were identified and their dynamics modelled throughout therapy. Results: At baseline, a total of 34 features derived from multi-omic data were associated with response to neoadjuvant therapy. These included: tumor mutation and neoantigen burden, subclonal diversity, HRD and chromosomal instability. A suppressed immune response, typified by the presence of T-cell dysfunction and immune exclusion, was associated with extensive chemoresistance. The changes in abundance of these features across the serially sampled on-therapy tumors were then mapped to response outcomes. An early increase in adaptive and innate immune infiltration and activation was associated with a linear decrease in expressed neoantigens, tumor proliferation and loss of subclonal mutational and copy number diversity, indicating early response to therapy. Conversely, a stable tumor and microenvironment transcriptional landscape throughout treatment, corresponding to a minimal change in tumor clonal architecture and microenvironment composition, was associated with a poor response to therapy. Notably, tumors with LOH HLA failed to engage a productive immune response during treatment and this was associated with resistance. A dynamic framework that models the change of these on-therapy features and extends the functionality of the published static machine learning model is being developed. Conclusion: Response to neoadjuvant therapy is determined by the baseline characteristics of the tumor ecosystem. During therapy, both the tumor and its microenvironment follow distinct evolutionary trajectories that can be mapped to outcome. The change in enrichment of features derived from the tumor and its microenvironment can be integrated within machine learning frameworks that leverage dynamic data from the entire therapy time course for more accurate response prediction. Citation Format: Stephen-John Sammut, Mireia Crispin-Ortuzar, Suet-Feung Chin, Elena Provenzano, Wei Cope, Ali Dariush, Sarah-Jane Dawson, Paul D. Pharoah, Florian Markowetz, Oscar M. Rueda, Helena M. Earl, Carlos Caldas. Predicting response to treatment in early breast cancer using dynamic integrative multi-omic profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 476.

Phase II neoadjuvant pyrotinib combined with epirubicin and cyclophosphamide followed by docetaxel in HER2-low–expressing and HR-positive early or locally advanced breast cancer (PILHLE-001): A single-arm trial.

TPS620 Background: As a latent new subtype, HER2-low-expressing breast cancer has attracted increasing attention. However, HER2-low-expressing/HR-positive early or locally advanced breast cancer (E/LABC) has the lowest pathological complete response (pCR) rate among all types of breast cancer. Pyrotinib, a small-molecule HER1/HER2/HER4 tyrosine kinase inhibitor, combined with chemotherapy regimen showed excellent efficacy and safety in the treatment of patients with HER2-positive early, locally advanced and metastatic breast cancer. In-vitro experiment showed pyrotinib can significantly inhibit colony formation in breast cancer cell lines with different HER2 expression levels including HER2-positive and HER2-low-expressimg [immunohistochemistry (IHC) 2+/in situ hybridization (ISH) negative]. Therefore, the investigator-driven, ongoing PILHLE-001 trial has been conducted to evaluate the potential role of neoadjuvant pyrotinib plus chemotherapy in the treatment of HER2-low-expressing/HR-positive E/LABC, which may provide a novel neoadjuvant therapeutic strategy for these patients. Methods: PILHLE-001, as a single-arm, phase Ⅱ study, is the first trial to evaluate the efficacy and safety of neoadjuvant pyrotinib combine with chemotherapy in HER2-low-expressing (defined as IHC 2+ with ISH negative) and HR-positive (ER or PR > 1% stained cells) E/LABC (cT1c with histologically involved lymph nodes or ≥cT2). Patients who have HER2 IHC 1+, or severe heart diseases or basic gastrointestinal diseases are excluded. The trial has 80% power to detect true difference from previous reported pCR rate of 17.5%, to an expected pCR rate of 35% at two-sided alpha level of 0.05. Considering a drop rate of 10%, a total of 46 patients will be needed. Since May 19, 2021 until now, 19 patients have been enrolled. All eligible patients will receive pyrotinib 320mg orally daily with all chemotherapy cycles (epirubicin 90 mg/m² intravenously plus cyclophosphamide 600 mg/m² intravenously on day 1 for four 3-week cycles followed by docetaxel 100 mg/m² intravenously on day 1 for four 3-week cycle). The primary outcome is the rate of total pCR, defined as no residual invasive tumor cells in the breast and axillary nodes, regardless of ductal carcinoma in situ (ypT0/is ypN0) after neoadjuvant treatment. The secondary outcomes include Miller-Payne grade, residual cancer burden score, overall response rate, breast conservation rate, disease-free survival, overall survival, exploratory biomarkers and drug related safety. Primary efficacy outcomes will be analyzed in the intention‐to‐treat population and safety outcomes in the safety set population. Long-term efficacy outcomes will be assessed later with enough follow-up. Clinical trial information: NCT05165225.

Primary analysis of MUKDEN 01: A multicenter, single-arm, prospective, phase 2 study of neoadjuvant treatment with pyrotinib and letrozole plus dalpiciclib in triple-positive breast cancer.

588 Background: Despite the use of multiple lines of targeted therapy has revolutionized treatment for HER2-positive breast cancer, these methods still have limited efficacy for triple-positive breast cancer (TPBC), which calls for persistent exploration for optimized treatment strategy. This MUKDEN-01 prospective trial aimed to evaluate the efficacy of oral, chemo-sparing neoadjuvant therapy with pyrotinib, letrozole and dalpiciclib, which also meet the need for treatment convenience under COVID-19 pandemic, for patients with TPBC. Methods: The MUKDEN 01 was an investigator-initiated, multicentre, single arm, prospective phase II trial, which was performed at twelve hospitals in China(NCT04486911). Treatment-naïve patients with stage II-III tumors that according to the AJCC 8th edition criteria were eligible. Patients were treated with each cycle of 4 weeks with oral administration of pyrotinib 320 mg, and letrozole 2.5mg once daily for 4 weeks, and dalpiciclib 125 mg once daily for three weeks, followed by one week off, for five cycles. The primary endpoint was pathological complete response (pCR) in the breast and axilla (ypT0/is ypN0). Secondary endpoints included pCR in the breast (ypT0/is). residual cancer burden (RCB) score, Ki67 index change at surgery compared with baseline, and safety. Safety was analyzed in all patients, who received treatment. The study is still ongoing, and the enrollment has been completed. Results: Between June 20, 2020 and Sep. 6, 2021, 68 patients were screened for eligibility and 61 patients were recruited into this first stage of study. After surgery, 18 (29.5%, 95% CI 18.5-42.6) out of 61 patients achieving tpCR(ypT0/is ypN0), 21 (34.4%, 95% CI 22.7-47.7) patients achieved bpCR(ypT0/is). The patients with excellent pathologic response (RCB 0-1) to the combined therapy accounted for 54.1% (33/61, 95% CI 40.9-66.9). Mean Ki67 expression was reduced from 38.7% (95%CI: 31.3-46.0) at baseline to 19.3% (95% CI:13.6-25.0; p=0.0001) in the surgical samples. The most frequent grade 3 AE were neutropenia (35 [57%]), leukopenia (13 [21%]), diarrhea (9 [15%]) and oral mucositis (4 [7%]). There were five grade 4 neutropenia (8%) and one grade 4 increased AST (2%), but without other SAE and death throughout the study. Conclusions: Neoadjuvant therapy with pyrotinib, letrozole and dalpiciclib yielded a pCR rate comparable to standard chemotherapy plus dual HER2 blockade in TPBC patients. The combined therapy was also well-tolerated and provided a chemo-sparing neoadjuvant approach for TPBC patients. To our knowledge, this is the first study to evaluate the therapeutic efficacy of a chemo-free neoadjuvant treatment with HER2 TKI pyrotinib and letrozole plus CDK4/6 inhibitor dalpiciclib for TPBC patients. Further validation in a large-scale randomized controlled trial is warranted. Clinical trial information: NCT04486911.

Development of a new HRD algorithm which was highly associated with anthracycline-containing neoadjuvant chemotherapy.

e13575 Background: Homologous recombination deficiency (HRD) can be resulted from dysfunction of BRCA and is associated with sensitivity to platinum, PARP inhibitor and other DNA-damaging drugs. The results from a neoadjuvant trial showed that pathological complete response (pCR) was not significantly higher with cisplatin than with doxorubicin-cyclophosphamide in BRCA1/2-mutated breast cancers (BC). It suggests that BC with HRD might benefit from anthracycline-containing regiment. There are many commercial HRD detection assays, including the FoundationFocus CDx BRCA LOH and myChoice CDx, but there is still no uniform standard in China. Methods: A total of 96 in-house BC samples and 6 HRD positive standard cells (Cat No. CBP90023) were analyzed by whole-genome sequencing (WGS). Besides, 122 BCs from the TCGA database were down-sampled to ̃1X WGS. We constructed a new algorithm for HRD score based on WGS at low coverage as input data to estimate large-scale copy number alteration (LCNA) events on the genome. The sensitivity and specificity were compared between our algorithm and the ShallowHRD. A clinical cohort of 50 BCs (15 cases carrying BRCA mutation) was used to assess the association between HRD status and anthracyclines-containing neoadjuvant treatment outcomes. Results: A 100kb-window was defined as the optimal size by using 41 in-house cases and the TCGA dataset. The threshold of HRD was determined as the number of 10 LCNAs by using 55 in-house BCs with BRCA mutation, with the goal of achieving 95% sensitivity. The sensitivity and specificity of our algorithm were both 100%, while those of the ShallowHRD were 40% and 100%, respectively, by testing standard samples with positive HRD. Meanwhile, similar results were also observed that the sensitivity of our algorithm was far superior to ShallowHRD (87% vs 13%) in the clinical cohort. The association between HRD status and BRCA mutations was compared between our algorithm and the ShallowHRD by 120 BC WGS samples (20 cases carrying BRCA mutation) from the TCGA database. The results showed that BRCA status was significantly associated with HRD status by our algorithm and ShallowHRD (P = 0.00838 and P = 0.00284, respectively). However, our algorithm had a higher positive concordance rate than the ShallowHRD algorithm (70% vs 60%). In the clinical cohort of neoadjuvant treatment, HRD group was more likely to respond to anthracycline-containing chemotherapy than non-HRD group, with outcomes of pCR (OR = 9.5, 95% CI: 1.11–81.5, p = 0.04) and residual cancer burden score of 0 or 1 (RCB0/1) (OR = 10.29, 95% CI: 2.02–52.36, p = 0.005). Among 35 patients lacking BRCA mutations, HRD group tended to have RCB0/1 responses compared to non-HRD group (OR = 6.0, 95% CI: 1.00–35.91, p = 0.05). Conclusions: Here, we developed a new stable algorithm for HRD score. It’s a promising assay for clinical application to predict sensitivity of DNA-damaging drugs.

Event-free survival by residual cancer burden after neoadjuvant pembrolizumab + chemotherapy versus placebo + chemotherapy for early TNBC: Exploratory analysis from KEYNOTE-522.

503 Background: KEYNOTE-522 (NCT03036488) tested the benefit from adding pembrolizumab (pembro) to chemotherapy (chemo) in patients (pts) with early TNBC. The primary results showed statistically significant and clinically meaningful improvements in pCR and EFS with pembro.Prior studies have shown the prognostic value of the residual cancer burden (RCB) method to quantify the extent of residual disease after neoadjuvant chemo. In this exploratory analysis, we assessed EFS by RCB in KEYNOTE-522. Methods: 1174 pts with previously untreated, nonmetastatic, stage T1c/N1-2 or T2-4/N0-2 TNBC were randomized 2:1 to pembro 200 mg Q3W or placebo (pbo) given with 4 cycles of paclitaxel + carboplatin, then 4 cycles of doxorubicin or epirubicin + cyclophosphamide. After definitive surgery, pts received pembro or pbo for 9 cycles or until recurrence or unacceptable toxicity. Dual primary endpoints are pCR and EFS. RCB was assessed by the local pathologist at the time of surgery. The association between RCB categories (RCB-0, -1, -2, -3, corresponding to increasingly larger residual cancer) and EFS was assessed based on a Cox regression model with treatment as a covariate. Results: Median follow-up was 39.1 months at data cutoff (23 MAR 2021). Pembro shifted RCB to lower categories across the entire spectrum (Table). The HRs (95% CI) for EFS were 0.70 (0.38 - 1.31) for RCB-0 (equivalent to pCR), 0.92 (0.39 - 2.20) for RCB-1, 0.52 (0.32 - 0.82) for RCB-2, and 1.24 (0.69 - 2.23) for RCB-3. The most common EFS event in both arms was distant recurrence, which occurred in fewer pts in the pembro arm in all RCB categories. Conclusions: Increased RCB score was associated with worse EFS. Pts with residual disease had lower RCB values in the pembro arm, including fewer pts with RCB-3. Pembro + chemo prolonged EFS vs chemo alone in the RCB-0, -1, and -2 categories; the small sample size limits interpretation in the RCB-3 category. The small subset of pts with extensive residual disease (RCB-3) in both arms, 5.1% and 6.7%, respectively, had a poor prognosis. These results highlight the importance of neoadjuvant treatment with pembro for improving survival in pts with early TNBC, and identified a subset of pts for whom additional therapies will be needed. Clinical trial information: NCT03036488. [Table: see text]

The association between breast density and breast cancer pathological response to neoadjuvant chemotherapy

PurposeMammographic Density (MD) refers to the amount of fibroglandular breast tissue present in the breast and is an established risk factor for developing breast cancer. The ability to evaluate treatment response dynamically renders neoadjuvant chemotherapy (NACT) the preferred treatment option in many clinical scenarios. Previous studies have suggested that MD can predict patients likely to achieve a pathological complete response (pCR) to NACT. We aimed to determine whether there is a causal relationship between BI-RADS breast composition categories for breast density at diagnosis and the pCR rate and residual cancer burden score (RCB) by performing a retrospective review on consecutive breast cancer patients who received NACT in a tertiary referral centre from 2015 to 2021.MethodsThe Mann–Whitney U Test was used to test for differences between two independent groups (i.e. those who achieved pCR and those who did not). A binary logistic regression model was used to estimate odds ratios (OR) and corresponding 95% confidence intervals (CI) for an association between the independent variables of molecular subtype, MD, histological grade and FNA positivity and the dependant variable of pCR. Statistical analysis was conducted with SPSS (IBM SPSS for Mac, Version 26.0; IBM Corp).Results292 patients were included in the current study. There were 124, 155 and 13 patients in the BI-RADS MD category b, c and d, respectively. There were no patients in the BI-RADS MD category a. The patients with less dense breast composition (MD category b) were significantly older than patients with denser breast composition (MD category c, d) (p = 0.001) and patients who had a denser breast composition (MD category d) were more likely to have ER+ tumours. There was no significant difference in PgR status, HER2 status, pathological complete response (pCR), FNA positivity, or RCB class dependent upon the three MD categories. A binary logistic regression revealed that patients with HER2-enriched breast cancer and triple-negative breast cancer are more likely to achieve pCR with an OR of 3.630 (95% CI 1.360–9.691, p = 0.010) and 2.445 (95% CI 1.131–5.288, p = 0.023), respectively.ConclusionWhilst dense MD was associated with ER positivity and these women were less likely to achieve a pCR, MD did not appear to independently predict pCR post-NACT.

HER2-low-positive breast cancer: evolution from primary tumor to residual disease after neoadjuvant treatment

Approximately a half of breast tumors classified as HER2-negative exhibit HER2-low-positive expression. We recently described a high instability of HER2-low-positive expression from primary breast cancer (BC) to relapse. Previous studies reporting discordance in HER2 status between baseline biopsy and residual disease (RD) in patients undergoing neoadjuvant treatment did not include the HER2-low-positive category. The aim of this study is to track the evolution of HER2-low-positive expression from primary BC to RD after neoadjuvant treatment. Patients undergoing neoadjuvant treatment with available baseline tumor tissue and matched samples of RD (in case of no pCR) were included. HER2-negative cases were sub-classified as HER2-0 or HER2-low-positive (IHC 1+ or 2+ and ISH negative). Four-hundred forty-six patients were included. Primary BC phenotype was: HR-positive/HER2-negative 23.5%, triple-negative (TN) 35%, HER2-positive 41.5%. HER2-low-positive cases were 55.6% of the HER2-negative cohort and were significantly enriched in the HR-positive/HER2-negative vs. TN subgroup (68.6% vs. 46.8%, p = 0.001 χ2 test). In all, 35.3% of non-pCR patients (n = 291) had a HER2-low-positive expression on RD. The overall rate of HER2 expression discordance was 26.4%, mostly driven by HER2-negative cases converting either from (14.8%) or to (8.9%) HER2-low-positive phenotype. Among HR-positive/HER2-negative patients with HER2-low-positive expression on RD, 32.0% and 57.1% had an estimated high risk of relapse according to the residual proliferative cancer burden and CPS-EG score, respectively. In conclusion, HER2-low-positive expression showed high instability from primary BC to RD after neoadjuvant treatment. HER2-low-positive expression on RD may guide personalized adjuvant treatment for high-risk patients in the context of clinical trials with novel anti-HER2 antibody-drug conjugates.

Abstract P2-13-08: Combined peri-operative lapatinib and trastuzumab in early HER2-positive breast cancer - Long term results of the randomized UK EPHOS-B trial

Abstract Background: EPHOS-B is a multi-centre randomized trial designed to investigate whether anti-HER2 therapy given 11 days pre-surgery inhibited proliferation and/or increased apoptosis in HER2-positive early breast cancer. Significant differences in Ki67 response (≥30% change between baseline and surgery) were observed between treatment groups and control, although no significant increases in apoptosis were seen [1]. We report here 5-year outcomes and their association with peri-operative response, including post-hoc exploratory analyses on stromal tumour infiltrating lymphocytes (TILs). Methods: Patients were randomized (1:2:2) to no treatment (control), trastuzumab or lapatinib (Part-1), and (1:1:2) to control, trastuzumab, or lapatinib and trastuzumab combination (Part-2). Relapse free survival (RFS) is defined as the time from randomisation to local, regional, or distant tumour recurrence or death from any cause, with second primary cancers censored. Five-year RFS rates were estimated by Kaplan-Meier across treatment and peri-operative response groups, and compared by Log-Rank tests. Central scoring of stromal tumour infiltrating lymphocytes (TILs) on scanned H&E baseline and surgery slides was conducted post-hoc according to the International TILs Working Group. Baseline TILs (bTILS) were explored across treatment groups, and associated with trial outcomes. Changes in TILS in patients without pathological regression were correlated with Ki67 changes and RFS. Results: Overall, 257 patients were randomized (Part-1: control 22, trastuzumab 57, lapatinib 51; Part-2: control 29, trastuzumab 32, trastuzumab+lapatinib 66). Central pathology review identified six patients achieving complete pathological response (pCR), and 13 RCB1 (as per the Residual Cancer Burden score), all but two in the combination group. After 6 years median follow-up, 28 women (11%) had recurrence, and 19 (7%) died; no differences between groups were found (Table). No recurrences were observed amongst pCR patients; only 1 local recurrence observed amongst RCB1. Patients with Ki67 falls ≥50% had better RFS than those with modest falls or no falls (Table). In patients with no evidence of disease regression at surgery, those with higher TILs (≥20%) at surgery had better RFS than those with lower TILs. Conclusions: Early response (pCR/RCB1 or Ki67 reductions >50%) after 11 days pre-operative anti-HER2 dual therapy identifies cancers dependent on the HER2 pathway and provides a strategy for individualising treatment, including de-escalation of therapy. [1] Bundred N, Cameron D, Amstrong A et al (2016) Effects of perioperative lapatinib and trastuzumab, alone and in combination, in early HER2+ breast cancer − the UK EPHOS-B trial (CRUK/08/002) European Journal of Cancer;57:S1-S8. Table - Relapse-free survival by treatment and by peri-operative responseN randomisedNRFS event5-year RFS95%CILog-rank p-valueRandomised treatmentTrastuzumab (P1)577 (12.3%)88%76-94%T vs L p=0.75Lapatinib (P1)515 (9.8%)90%77-96%L vs C p=0.41Control (P1)221 (4.6%)95%92-99%Trastuzumab (P2)327 (21.9%)87%69-95%T vs T+L p=0.048Combination (P2)665 (7.6%)92%83-97%T+L vs C p=0.64Control (P2)293 (10.3%)90%71-97%%Ki67 change:>50% decrease722 (2.8%)99%90-100%0.002>10% decrease7717 (22.1%)80%69-88%<10% or no decrease827 (8.5%)91%83-96%Disease responseRCB060100%-0.63RCB1131 (7.7%)92%57-99RCB2/3/no evidence of regression23626 (11%)90%85-93Baseline TILS<=20%18023 (13%)89%83-930.10>20%502 (4%)96%85-99Surgery TILS (only RCB2/3)<=20%12220 (16.4%)86%78-910.021>20%653 (4.6%)95%86-98Change in TILS (only RCB2/3)No significant increase15221 (13.8%)88%81-920.16Increase >20%352 (5.7%)94%79-99 Citation Format: Nigel Bundred, Nuria Porta, Adrian Murray Brunt, Angela Cramer, Andrew Hanby, Abeer Shaaban, Emad Rakha, Anne Armstrong, Ramsey Cutress, David Dodwell, Marie Emson, Abigail Evans, Sue Hartup, Kieran Horgan, Stuart McIntosh, Jay Naik, Samkaran Narayanan, Jane Oii, Anthony Skene, David Cameron, Judith Bliss. Combined peri-operative lapatinib and trastuzumab in early HER2-positive breast cancer - Long term results of the randomized UK EPHOS-B trial [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 P2-13-08.

Abstract P1-08-30: Validation of the AAGAB gene as a novel on-treatment biomarker predicting pCR in patients receiving NACT for early breast cancer

Abstract Background: Neoadjuvant chemotherapy (NACT) for breast cancer is given prior to surgery, aiming to reduce tumour burden and provide early information on response to treatment. Tumours with a pathological complete response (pCR) following NACT are less likely to recur than those in patients with residual disease following NACT, suggesting that pCR following NACT may be a surrogate of good prognosis. In addition, NACT provides a “window of opportunity” where sequential sampling of a tumour enables observation of changes occurring in response to treatment. We previously demonstrated that on-treatment biomarkers improve the accuracy of predicting response before resection, by performing differential gene expression analysis across sequential samples from 50 patients, across 3 time points; pre NACT, mid chemo and post NACT (Bownes et al, 2019). A single gene marker (AAGAB) was identified as a novel potential on-treatment biomarker for pCR, with greater predictive accuracy than currently established prognostic tests, supporting the potential value of on-treatment biomarker monitoring in breast cancer to improve the accuracy of tumour response prediction. Aim: To validate and test the finding that increased expression of AAGAB at mid-chemotherapy associates with pCR in ER+ve and HER+ve breast cancer patients receiving NACT. Method: mRNA extracted from tumour from the mid-chemotherapy time point during NACT, from 28 breast cancer patients, was analysed using real-time reverse transcription-PCR (real-time RT-PCR). Firstly, mRNA was reverse transcribed using Invitrogen SuperScript IV Reverse Transcriptase (RT), then cDNA was used in an Applied Biosystems real-time RT-PCR Taqman Gene Expression Assay to measure AAGAB gene expression. GAPDH and SYMPK Taqman assays were used as endogenous controls, to allow calculation of (ΔΔCt) using the Comparative CT Method. Quantitative PCR was carried out on the Applied Biosystems StepOnePlusTM Real-Time PCR System and Relative Quantitation (RQ) was calculated using 2^-(ΔΔCt). For each patient RCB (residual cancer burden) was plotted against AAGAB expression and statistical significance calculated using the Wilcoxon rank sum exact test. Results: As a group, patients with RCB scores of 0 and I demonstrated a significantly higher level of expression that patients with RCB II and RCB III. We also observed that patients with pCR after NACT demonstrated higher levels of AAGAB expression. This increased expression was also seen in patients with a decrease in tumour cellularity of more than 85%. Conclusion: Our data suggest that measurement of AAGAB expression may provide an informative on-treatment biomarker of response to NACT. Citation Format: Fiona Semple, Alastair Ironside, Richard Bownes, Carlos Martinez-Perez, Natalie Wilson, Arran Turnbull, Olga Oikonomidou. Validation of the AAGAB gene as a novel on-treatment biomarker predicting pCR in patients receiving NACT for early 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 P1-08-30.

Real World Evidence of Neoadjuvant Docetaxel/Carboplatin/Trastuzumab/Pertuzumab (TCHP) in Patients with HER2-Positive Early or Locally Advanced Breast Cancer: A Single-Institutional Clinical Experience.

PurposeDocetaxel/carboplatin/trastuzumab/pertuzumab (TCHP) regimen is frequently used to treat early and locally advanced human epidermal growth factor receptor 2 (HER2)–positive breast cancer (BC) in neoadjuvant setting. However, large-scaled real-world evidence did not exist.Materials and MethodsWe retrospectively reviewed medical records of patients with early or locally advanced HER2-positive BC who underwent neoadjuvant TCHP followed by curative surgery at Samsung Medical Center between January 2016 and August 2020.ResultsOf 447 patients, 316 (70.7%) received breast-conserving surgery and 131 (29.3%) received total mastectomy. In terms of neoadjuvant chemotherapy response, pathologic complete response (pCR) and residual cancer burden (RCB) score were analyzed. The rate of pCR was 64% a class of RCB 0 was observed in 65% of cases, RCB class I in 12%, RCB class II in 14%, and RCB class III in 2%. The 3-year event-free survival rate was 90.6%, BC with pCR occurred in 92.8%, and BC with non-pCR in 86.3% (p=0.016). In terms of distant metastasis, the 3-year distant recurrence-free survival rate was 93.5%; BC with pCR occurred in 95.9% and BC with non-pCR in 89.2% (p=0.013). Mucositis (85.2%), pain (83.2%), and diarrhea (70.5%) were the most common non-hematologic adverse events. In terms of hematologic adverse events, anemia (89.9%) was the most commonly observed adverse events followed by thrombocytopenia (29.8%).ConclusionNeoadjuvant TCHP therapy had a pCR rate of 64% and a 3-year event-free survival of 90% in real world experience. In terms of toxicity profile, anemia was frequently observed and adequate management including occasional transfusion was required.

Residual cancer burden after neoadjuvant chemotherapy and long-term survival outcomes in breast cancer: a multicentre pooled analysis of 5161 patients.

SummaryBackgroundPrevious studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings.MethodsIn this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, from patients (aged ≥18 years) with primary stage I–III breast cancer treated with neoadjuvant chemotherapy followed by surgery. We assessed the association between the continuous RCB score and the primary study outcome, event-free survival, using mixed-effects Cox models with the incorporation of random RCB and cohort effects to account for between-study heterogeneity, and stratification to account for differences in baseline hazard across cancer subtypes defined by hormone receptor status and HER2 status. The association was further evaluated within each breast cancer subtype in multivariable analyses incorporating random RCB and cohort effects and adjustments for age and pretreatment clinical T category, nodal status, and tumour grade. Kaplan-Meier estimates of event-free survival at 3, 5, and 10 years were computed for each RCB class within each subtype.FindingsWe analysed participant-level data from 5161 patients treated with neoadjuvant chemotherapy between Sept 12, 1994, and Feb 11, 2019. Median age was 49 years (IQR 20–80). 1164 event-free survival events occurred during follow-up (median follow-up 56 months [IQR 0–186]). RCB score was prognostic within each breast cancer subtype, with higher RCB score significantly associated with worse event-free survival. The univariable hazard ratio (HR) associated with one unit increase in RCB ranged from 1·55 (95% CI 1·41–1·71) for hormone receptor-positive, HER2-negative patients to 2·16 (1·79–2·61) for the hormone receptor-negative, HER2-positive group (with or without HER2-targeted therapy; p<0·0001 for all subtypes). RCB score remained prognostic for event-free survival in multivariable models adjusted for age, grade, T category, and nodal status at baseline: the adjusted HR ranged from 1·52 (1·36–1·69) in the hormone receptor-positive, HER2-negative group to 2·09 (1·73–2·53) in the hormone receptor-negative, HER2-positive group (p<0·0001 for all subtypes).InterpretationRCB score and class were independently prognostic in all subtypes of breast cancer, and generalisable to multiple practice settings. Although variability in hormone receptor subtype definitions and treatment across patients are likely to affect prognostic performance, the association we observed between RCB and a patient’s residual risk suggests that prospective evaluation of RCB could be considered to become part of standard pathology reporting after neoadjuvant therapy.

Interobserver variability in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative invasive breast carcinoma influences the association with pathological complete response: the IVITA study

High stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative breast cancer (TNBC) are associated with pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Histopathological assessment of sTILs in TNBC biopsies is characterized by substantial interobserver variability, but it is unknown whether this affects its association with pCR. Here, we aimed to investigate the degree of interobserver variability in an international study, and its impact on the relationship between sTILs and pCR. Forty pathologists assessed sTILs as a percentage in digitalized biopsy slides, originating from 41 TNBC patients who were treated with NAC followed by surgery. Pathological response was quantified by the MD Anderson Residual Cancer Burden (RCB) score. Intraclass correlation coefficients (ICCs) were calculated per pathologist duo and Bland–Altman plots were constructed. The relation between sTILs and pCR or RCB class was investigated. The ICCs ranged from −0.376 to 0.947 (mean: 0.659), indicating substantial interobserver variability. Nevertheless, high sTILs scores were significantly associated with pCR for 36 participants (90%), and with RCB class for eight participants (20%). Post hoc sTILs cutoffs at 20% and 40% resulted in variable associations with pCR. The sTILs in TNBC with RCB-II and RCB-III were intermediate to those of RCB-0 and RCB-I, with lowest sTILs observed in RCB-I. However, the limited number of RCB-I cases precludes any definite conclusions due to lack of power, and this observation therefore requires further investigation. In conclusion, sTILs are a robust marker for pCR at the group level. However, if sTILs are to be used to guide the NAC scheme for individual patients, the observed interobserver variability might substantially affect the chance of obtaining a pCR. Future studies should determine the ‘ideal' sTILs threshold, and attempt to fine-tune the patient selection for sTILs-based de-escalation of NAC regimens. At present, there is insufficient evidence for robust and reproducible sTILs-guided therapeutic decisions.

Prognostic value of residual cancer burden and Miller-Payne system after neoadjuvant chemotherapy for breast cancer.

To verify the feasibility of using the residual cancer burden (RCB) index to stratify prognosis of patients after neoadjuvant chemotherapy (NAC) and to compare RCB with the Miller-Payne system. We retrospectively analyzed clinicopathological data of patients receiving treatment between January 1, 2010 and December 31, 2018. Kaplan-Meier curves were used to compare the survival outcomes and estimate disease-free survival (DFS) and disease-specific survival (DSS). Harrell's concordance index (C-index) was used to evaluate the predictive accuracy of RCB and Miller-Payne system. A total of 423 female patients with complete data were included in the analysis, with a median follow-up time of 58.5 months (range, 7-126 months); 84 patients experienced recurrence, and 48 experienced breast cancer related death. RCB index and the Miller-Payne system were associated with prognosis in the whole cohort. Patients who achieved RCB-I had similar survival outcomes as those with pathological complete response (pCR, RCB-0). In whole cohort, for the RCB index and the Miller-Payne system, respectively, C-indexes for DFS were 0.73 and 0.64, for DSS were 0.74 and 0.64. The average RCB score was different among three subtypes (F=9.335, P<0.001). The RCB index and the Miller-Payne system can stratify survival outcome of patients after NAC, and RCB had a superior prediction accuracy, especially for triple-negative breast cancer (TNBC). New cut-off value should be sought in order to improve prediction accuracy.

Valor predictivo de los índices 18F-FDG PET/TC sobre la carga tumoral residual en pacientes con cáncer de mama extenso tratadas con quimioterapia neoadyuvante

AimWe investigated the correlation between 18F-FDG PET/CT indices and pathological response in breast cancer treated with neoadjuvant chemotherapy (NACT) which was scored with Residual Cancer Burden (RCB) system after surgery. Our aim is to detect extensive residual cancer burden earlier by using PET/CT indices. MethodsCharacteristics of patients were retrieved retrospectively. Baseline maximum Standart Uptake Value (SUVmax), Metabolic Tumor Volume (MTV) and Total Lesion Glycolysis (TLG) indices and reduction rate (RR) between baseline and interim evaluation were calculated with FDG PET/CT scan. All patients were evaluated according to RCB scores after surgery. Pathological responses and PET/CT measurement results were analyzed with demographic and clinical parameters. ResultsA total of 95 patients were included in the study. According to pathological responses, the distribution of RCB-0, -1, -2, -3 were 13 (13.7%), 11 (11.6%), 30 (31.6%), 41 (43.2%), respectively. Disease-free survival was significantly lower in the RCB-3 group compared to the pathological responder group (P=.01). According to multivariate analysis, RR of SUVmax was determined as an independent variable predicting extensive residual cancer burden with an optimal cut-off value of 86% (P<.05). ConclusionsWe determined RR of SUVmax as an independent factor for predicting extensive residual tumor burden. We believe that RR of SUVmax is sufficient to predict pathological response in daily practice. In addition, MTV and TLG measurements do not contribute additionally to SUVmax alone and can cause unnecessary labor loss.

The effect of metformin when combined with neoadjuvant chemotherapy in breast cancer patients.

Metformin has been used to treat type 2 Diabetes Mellitus since long time. It has two proposed anti-neoplastic mechanisms, direct (insulin-independent) and indirect (insulin-dependent) actions. To assess the effect of Metformin on pathological response when combined with neoadjuvant chemotherapy in breast cancer. A prospective study included stage II, III non-diabetic breast cancer patients who received neoadjuvant chemotherapy in our center during the period from May 2017 to March 2019. 59 patients met our inclusion criteria and completed the study, 27 patients received 850mg Metformin every 12h with chemotherapy (group A), and 32 patients received chemotherapy without Metformin (group B). Pathological response was assessed by Chevallier classification and residual cancer burden score (RCB). Both groups were well balanced regarding baseline characteristics. The results of our study showed that the rate of pathological complete response (pCR) was 14.8% in group (A) vs. 6.3% in group (B) with a P value of 0.39. RCB class 3 was 40.7% in group (A) vs. 68.8% in group (B) which was statistically significant with a (P value of 0.031). Patients with triple-positive histology who had RCB class 3 were only (14.3%) in group (A) versus (60%) in group B. Patients with body mass index (BMI) ≥ 25 who had RCB 3 were 40% and 66.7% in group (A) and (B), respectively. Metformin may increase the pCR especially in patients with BMI ≥ 25 and patients with triple-positive histology, a larger phase III study is needed to confirm this finding.