non-pCR Patients Research Articles

Enhanced CT-based radiomics predicts pathological complete response after neoadjuvant chemotherapy for advanced adenocarcinoma of the esophagogastric junction: a two-center study

PurposeThis study aimed to develop and validate CT-based models to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for advanced adenocarcinoma of the esophagogastric junction (AEG).MethodsPre-NAC clinical and imaging data of AEG patients who underwent surgical resection after preoperative-NAC at two centers were retrospectively collected from November 2014 to September 2020. The dataset included training (n = 60) and external validation groups (n = 32). Three models, including CT-based radiomics, clinical and radiomics–clinical combined models, were established to differentiate pCR (tumor regression grade (TRG) = grade 0) and nonpCR (TRG = grade 1–3) patients. For the radiomics model, tumor-region-based radiomics features in the arterial and venous phases were extracted and selected. The naïve Bayes classifier was used to establish arterial- and venous-phase radiomics models. The selected candidate clinical factors were used to establish a clinical model, which was further incorporated into the radiomics–clinical combined model. ROC analysis, calibration and decision curves were used to assess the model performance.ResultsFor the radiomics model, the AUC values obtained using the venous data were higher than those obtained using the arterial data (training: 0.751 vs. 0.736; validation: 0.768 vs. 0.750). Borrmann typing, tumor thickness and degree of differentiation were utilized to establish the clinical model (AUC-training: 0.753; AUC-validation: 0.848). The combination of arterial- and venous-phase radiomics and clinical factors further improved the discriminatory performance of the model (AUC-training: 0.838; AUC-validation: 0.902). The decision curve reflects the higher net benefit of the combined model.ConclusionThe combination of CT imaging and clinical factors pre-NAC for advanced AEG could help stratify potential responsiveness to NAC.

Predictive value of proteomic markers for advanced rectal cancer with neoadjuvant chemoradiotherapy

BackgroundPreoperative neoadjuvant chemoradiation (nCRT) has been the standard treatment for locally advanced rectal cancer. Serum biomarkers to stratify patients with respect to prognosis and response to nCRT are needed due to the diverse response to the therapy.MethodsThirteen paired pre- and post-nCRT sera from rectal cancer patients were analyzed by isobaric tags for relative and absolute quantitation (iTRAQ) method. Twenty-five proteins were selected for validation by parallel reaction monitoring (PRM) in ninety-one patients.ResultsTotally, 310 proteins were identified and quantified in sera samples. Reactome pathway analysis showed that the immune activation-related pathways were enriched in response to nCRT. Twenty-five proteins were selected for further validation. PRM result showed that the level of PZP was higher in pathological complete response (pCR) patients than non-pCR patients. The Random Forest algorithm identified a prediction model composed of 10 protein markers, which allowed discrimination between pCR patients and non-pCR patients (area under the curve (AUC) = 0.886 on testing set). Higher HEP2 and GELS or lower S10A8 in baseline sera were associated with better prognosis. Higher APOA1 in post nCRT sera was associated with better disease-free survival (DFS).ConclusionsWe identified and confirmed a 10-protein panel for nCRT response prediction and four potential biomarkers HEP2, GELS, S10A8 and APOA1 for prognosis of rectal cancer based on iTRAQ-based comparative proteomics screening and PRM-based targeted proteomic validation.

The role of 18F-FDG PET/CT in predicting the pathological response to neoadjuvant PD-1 blockade in combination with chemotherapy for resectable esophageal squamous cell carcinoma.

Accurate assessment of residual disease of tumor and lymph nodes after neoadjuvant immunochemotherapy is crucial in the active surveillance for patients with pathological complete response (pCR) and the optimal extent of lymphadenectomy for patients with non-pCR. This post hoc analysis aimed to evaluate the performance of 18F-FDG PET/CT to predict the pathological response to neoadjuvant immunochemotherapy for esophageal squamous cell carcinoma (ESCC). Fifty-eight resectable ESCC patients receivedtwo cycles of camrelizumab in combination with chemotherapy and were enrolled in the final analysis. The 18F-FDG PET/CT scans were acquired at baseline (scan-1) and after immunochemotherapy but prior to surgery (scan-2). Maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), tumor-to-blood pool SUVmax ratio (SUVTBR), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were evaluated for their association with the pathological response to immunochemotherapy. Nineteen patients (32.8%, 19/58) had pCR and thirty-nine patients (67.2%, 39/58) had non-pCR after two doses of camrelizumab and chemotherapy. At scan-2, the SUVmax, SUVmean, SUVTBR, TLG, and MTV were significantly lower in pCR than in non-pCR patients. Decrease in TLG and MTV between scan-2 and scan-1 of the same patient was significantly higher in the pCR than in the non-pCR group. In the receiver operating characteristic curve analysis, SUVmax, SUVmean, SUVTBR, TLG, and MTV in scan-2 showed excellent predictive value for the pCR of primary tumors. Furthermore, SUVmax in scan-2 were higher in positive lymph nodes than in negative ones, suggesting a high negative predictive ability (98.6%) with a cut-off value at 1.4. The parameters of 18F-FDG PET/CT have the excellent performance for predicting pCR after the combined neoadjuvant immunochemotherapy in resectable ESCC. ChiCTR2000028900. Registered on January 6,2020.

Abstract 5980: Identification of pre-treatment tumor habitats for the prediction of neoadjuvant therapy response in triple negative breast cancer

Abstract Introduction: Triple negative breast cancer (TNBC) patients exhibit varied levels of response to neoadjuvant chemotherapy (NAC), with only 27-51% of patients achieving pathological complete response (pCR). This diverse response can be attributed in-part to heterogeneity of the tumor microenvironment, affecting therapeutic delivery and efficacy. Multiparametric magnetic resonance imaging (MRI) can be used to spatially resolve intratumoral heterogeneity into distinct tumor subregions, or habitats. We investigated whether MRI-derived tumor habitats identified prior to initiation of NAC were predictive of pathological response in TNBC patients. Methods: Women with stage II/III TNBC who received a pre-treatment (baseline) breast MRI and NAC at our institution (2012-2019) were retrospectively identified. Pathological response was determined at surgery, with pCR defined as no residual tumor within the breast or lymph nodes. Both diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI data were collected prior to initiation of NAC. The apparent diffusion coefficient (a measure of cell density) was calculated for each voxel from DW-MRI. Signal enhancement ratio, percent enhancement, and wash-out slope were calculated for each voxel from DCE-MRI, providing measures of vascularity. Hierarchical clustering of voxel data was used to identify tumor habitats, with each subregion labeled in terms of “high” or “low” vascularity and cellularity based on mean parameter values for the subregion. Tumor composition was quantified as percent tumor volume comprised by each habitat. Differences between pCR and non-pCR patients were assessed using Wilcoxon rank sum test, with p<0.05 considered significant. Results: 46 women with TNBC were retrospectively identified (median age: 48, range 31-77 yrs), of which 14 (30%) achieved pCR. No significant differences between pCR and non-pCR patients were observed in baseline tumor volume or longest diameter (p>0.05). Clustering analysis yielded four tumor habitats: low-vascularity low-cellularity (LV-LC), low-vascularity high-cellularity (LV-HC), high-vascularity low-cellularity (HV-LC), and high-vascularity high-cellularity (HV-HC). Patients who achieved pCR had significantly higher fraction of the HV-HC habitat at baseline (p=0.02). No significant differences were observed for other habitats. Discussion & Conclusion: Our findings suggest multiparametric MRI can identify physiologically-distinct tumor habitats prior to NAC, which are predictive of response. A higher fraction of HV-HC habitat was associated with pCR, potentially suggestive of increased therapeutic delivery/sensitivity. Clinical translation of this approach would enable more specific characterizations of tumor heterogeneity and prediction of response, which could aid in personalizing regimens for optimal outcomes. Citation Format: Anum S. Kazerouni, Laura C. Kennedy, Shaveta Vinayak, Suzanne Dintzis, Habib Rahbar, Savannah C. Partridge. Identification of pre-treatment tumor habitats for the prediction of neoadjuvant therapy response in triple negative breast cancer [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 5980.

Abstract 4011: Prognostic value of transcriptomic analysis in residual post neo-adjuvant triple negative breast cancer tumors

Abstract Background: Triple negative breast cancer is the most aggressive type of breast cancer. Approximately 50% of TNBC patients respond to pre-operative neo-adjuvant chemotherapy (NAC), however those patients with residual disease (non-pathological complete response or non-pCR) have a very poor prognosis. Recently, the use of capecitabine in the adjuvant setting was shown to increase disease-free survival in non-pCR patients. However, there are no biomarkers to identify patients who may benefit from adjuvant capecitabine. Moreover, novel therapeutic targets are needed to treat patients with non-pCR. Methods: RNA extracted from 32 Formalin Fixed Paraffin Embedded (FFPE) residual post-NAC tumor samples underwent NanoString nCounter gene expression analysis using the BC360 panel as well as RNAseq. Results: Comparison of tumors from poor (RFS<2 yrs) and good prognosis (RFS>2 yrs) patients showed 65 genes differentially expressed (≥1.5 fold change and p<0.05) by nCounter. 40 of these genes had differential expression also validated by RNAseq (R2= 0.96) and were selected for further pathway analysis. Gene Set Enrichment Analysis (GSEA) showed an enrichment for biological pathways involved in cell cycle, with all genes in this set upregulated in the poor prognosis group. GSEA analysis of 310 upregulated genes identified by RNAseq showed an enrichment for biological pathways associated with cell population proliferation and skin development. Interestingly, one of the upregulated genes identified was TYMS, encoding thymidylate synthase, the target of capecitabine, which showed 2-fold increased expression in the poor prognosis group (p≤0.005). Conclusion: Our results suggest that residual tumors from TNBC patients who relapse within two years of surgery show transcriptomic evidence of increased proliferation and that expression levels of TYMS may be a potential biomarker to select patients for capecitabine in the adjuvant setting. Citation Format: Adriana Aguilar-Mahecha, Yasamin Majedi, Oluwadara Elebute, Josiane Lafleur, Andreas Papadakis, Cathy Lan, Manuela Pelmus, Touhidur Rashid, Sarah Jenna, Mark Basik. Prognostic value of transcriptomic analysis in residual post neo-adjuvant triple negative breast cancer tumors [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 4011.

Predicting pathologic complete response in locally advanced rectal cancer patients after neoadjuvant therapy: a machine learning model using XGBoost

PurposeWatch and wait strategy is a safe and effective alternative to surgery in patients with locally advanced rectal cancer (LARC) who have achieved pathological complete response (pCR) after neoadjuvant therapy (NAT); present restaging methods do not meet clinical needs. This study aimed to construct a machine learning (ML) model to predict pCR preoperatively.MethodsLARC patients who received NAT were included to generate an extreme gradient boosting-based ML model to predict pCR. The group was divided into a training set and a tuning set at a 7:3 ratio. The SHapley Additive exPlanations value was used to quantify feature importance. The ML model was compared with a nomogram model developed using independent risk factors identified by conventional multivariate logistic regression analysis.ResultsCompared with the nomogram model, our ML model improved the area under the receiver operating characteristics from 0.72 to 0.95, sensitivity from 43 to 82.2%, and specificity from 87.1 to 91.6% in the training set, the same trend applied to the tuning set. Neoadjuvant radiotherapy, preoperative carbohydrate antigen 125 (CA125), CA199, carcinoembryonic antigen level, and depth of tumor invasion were significant in predicting pCR in both models.ConclusionOur ML model is a potential alternative to the existing assessment tools to conduct triage treatment for patients and provides reference for clinicians in tailoring individual treatment: the watch and wait strategy is used to avoid surgical trauma in pCR patients, and non-pCR patients receive surgical treatment to avoid missing the optimal operation time window.

Assessment of tumour infiltrating subpopulations and pathological complete response using multiplex immunohistochemistry and digital pathology in early HER2+ breast cancer.

e15041 Background: The treatment of HER2+ breast cancer (BC) has improved substantially with the use of targeted therapies, and patients achieving pathological complete response (pCR) following neoadjuvant therapy have significantly improved disease free survival. However, there is currently no way to determine which patients are most likely to respond to neoadjuvant HER2-targeting treatment. Growing evidence indicates tumour infiltrating lymphocytes influence HER2+ BC outcome. We hypothesize that a deeper investigation of the immune landscape of HER2+ patient tumours may improve patient stratification and identify an immune profile associated with pCR. Methods: 3plex immunohistochemistry panels identifying immune cell subpopulations and tertiary lymphoid structures were applied to HER2+ BC tumors (pre-treatment N=19, post-treatment N=9) of patients of the neoadjuvant TCHL clinical trial (NCT01485926), who received HER2-targeting therapy. Quantitative analysis of CD3+, CD20+, DC-Lamp+, CD4+, and CD8+ immune cells on multi-labelled whole-slide images of TCHL tumor sections was performed using artificial intelligence image analysis models. Patient-specific densities of each cell type in tumor regions were determined to facilitate assessment of pre-treatment differences in target immune subpopulations in complete, partial, and non-responders. Results: Statistical analysis demonstrated a trend for higher densities of each immune subpopulation in pre-treatment biopsies of pCR vs. non-pCR patients. Patient categorisation based on median threshold demonstrated patients achieving pCR are more frequently high for each immune cell type assessed, while non-pCR patients are more frequently in the low category. Investigation of association of pre-treatment immune infiltrate with clinicopathological features demonstrated trends for higher levels of T-cell infiltration in later stage and hormone receptor negative patients. Conclusions: Multiplex IHC is an optimal technique for the concurrent assessment of multiple target markers in patient tissue, which can be quantitatively analyzed in a high throughput manner using AI models. The findings of this preliminary study support recent evidence regarding the role of tumor infiltrating immune cells in HER2+ BC outcome and warrant further investigation in a larger cohort.

Predictive value of DNA repair gene expression for response to neoadjuvant chemotherapy in breast cancer.

e12538 Background: Genome-wide analysis using microarrays has revolutionized the field of breast cancer (BC) research, classifying breast cancer by gene expression profiling. In patients with BC, a substantial body of evidence supports the clinical utility of gene expression profiling. For example, the 21-gene assay (Oncotype DX) and 70-gene assay (MammaPrint) predict BC recurrence and the magnitude of chemotherapy benefit. However, there is currently no gene-expression profiling able to predict chemosensitivity and chemoresistance to neoadjuvant chemotherapy (NACT) during BC treatment. Therefore, the development of specific predictive biomarkers for chemoresistance and chemosensitivity is desirable. In the present study, we explored the predictive value of DNA repair gene expression for response to NACT in BC by evaluating the mRNA expression of 11 selected genes which have a key role in DNA repair mechanisms. Methods: We selected 98 patients with BC treated with NACT. We assessed DNA repair expression in 98 formalin-fixed, paraffin-embedded core biopsy fragments used at diagnosis and in 32 formalin-fixed, paraffin-embedded post-NACT residual tumors using quantitative reverse transcription-polymerase chain reaction. The following genes were selected: BRCA1, PALB2, RAD51C, BRCA2, ATM, FANCA, MSH2, XPA, ERCC1, PARP1 and SNM1. We used the mean of 2 reference genes (GAPDH and ACTB) to minimize the risk of normalization bias that can result from variations in the expression of any single reference gene. Results: Of 98 patients, 33 (33.7%) achieved pathologic complete response (pCR). The DNA expression of 2 genes assessed in pre-NACT biopsies (PALB2 and ERCC1) was lower in pCR than in non-pCR patients (p=0.005 and p=0.009, respectively). After adjustment for tumor grade and molecular subtype, a linear regression model with rank transformation showed that the DNA expression of 2 genes (PALB2 and ERCC1) assessed in pre-NACT biopsies was lower in the pCR group than in the non-pCR group (p=0.014 and p=0.040 respectively). The genes BRCA2 (p=0.009), ATM (p=0.004), FANCA (p=0.001), and PARP1 (p=0.011) showed a lower expression in post-NACT residual tumor samples (n=32) than in pre-NACT biopsy samples (n=98). Conclusions: In the genomics era, treatment should be tailored to the individual patient. The present study showed that PALB2 and ERCC1 expressions, assessed in pre-NACT biopsies, were lower in pCR patients. These alterations in DNA repair could be considered suitable targets for cancer therapy. In addition, BRCA2, ATM, FANCA, and PARP1 expressions were lower in post-NACT residual tumor samples than in pre-NACT biopsies. The use of recently developed multiparameter gene-expression assays, based on the expression of genes involved in different DNA repair pathways, should be further explored in future studies, as they may facilitate the selection of patients most likely to benefit from NACT.

Construction of a model for evaluating the efficacy of neoadjuvant chemotherapy for breast cancer and dynamic monitoring of ctDNA response to neoadjuvant chemotherapy.

e12600 Background: Neoadjuvant chemotherapy (NAC) is a routine treatment of choice for patients with locally advanced breast cancer. The pathological complete response (pCR) to NAC in breast cancer is closely related to a better prognosis. In addition, there have been few studies of the role of ctDNA in the dynamic monitoring of NAC, so we explored the prediction model of NAC to predict pCR and evaluated the role of ctDNA in the dynamic monitoring of NAC. Methods: A total of 269 breast cancer patients receiving NAC were enrolled, and a total of 266 tissue samples were collected. The tissue samples were sequenced using a panel covering 457 cancer-related genes to construct a pCR prediction model after NAC. A total of 267 blood samples were collected from 56 patients. Blood samples were collected at the indicated time points: before NAC (T0), after the first NAC and before cycle two (T1), during intermediate evaluation (T2), and after the end of NAC but before surgery (T3). We constructed a model to predict pCR after NAC by mutated genes and clinical factors, analyzed ctDNA of blood samples according to the mutated genes of the prediction model, and detected the dynamic monitoring role of ctDNA in NAC to predict prognosis. The median follow-up time for survival analysis was 898 days. Results: A total of 192 patients were enrolled to construct the prediction model. There were 51 patients in the additional validation set. We analysed the somatic mutations of 192 samples and constructed a predictive NAC response model including 5 SNV mutations (TP53, SETBP1, PIK3CA, NOTCH4 and MSH2), 4 CNV mutations (FOXP1-gain, EGFR-gain, IL7R-gain, and NFKB1A-gain), and 3 clinical factors (luminal A, Her2+ and Ki67). Analysing the ctDNA of 267 blood samples through a unique panel composed of 9 mutant genes in the prediction model, it was found that ctDNA positivity decreased with the passage of time during NAC, the ctDNA positive rates of ctDNA from T0, T1, T2 to T3 were 46%, 14%, 13% and 10%, respectively. According to survival data, pCR patients did not have disease progression after NAC. Among the non-pCR patients who had disease progression, the probability of non-pCR in patients with ctDNA cleared at T1, T2, and T3 was significantly lower than that in patients with uncleared ctDNA. Interestingly, patients who failed to achieve pCR but were ctDNA negative had a similar risk of metastasis and recurrence as those who achieved pCR. Finally, we found that the prediction model combined with ctDNA could predict pCR after NAC. It had high sensitivity and specificity and the AUC value reached 0.961. Conclusions: This study established a predictive model for predicting pCR after NAC. At the same time, ctDNA dynamic monitoring found that ctDNA status could predict NAC response and metastasis recurrence. Combining the prediction model and ctDNA status could better predict the NAC results.

Homologous recombination deficiency predicts response to platinum-based neoadjuvant chemotherapy in early-stage triple-negative breast cancer patients: Secondary analysis of the neocart randomized clinical trial.

e12606 Background: We recently performed the NeoCART trial to compare six cycles of docetaxel plus carboplatin (DCb) with four cycles of epirubicin/cyclophosphamide followed by four cycles of docetaxel (EC-D) in the neoadjuvant setting of triple-negative breast cancer (TNBC). The present study assessed the homologous recombination deficiency (HRD) score, stromal tumor-infiltrating lymphocytes (TILs), and Ki67 as predictors of pathological complete response (pCR) in the NeoCART trial cohort. Methods: Participants in the NeoCART trial (NCT03154749) were randomly assigned, at a 1:1 ratio, to an experimental DCb for 6 cycles (DCb group) or an EC for 4 cycles followed by docetaxel for 4 cycles group (EC-D group). Pretherapeutic formalin-fixed, paraffin-embedded tumor tissues were assessed retrospectively for DNA extraction and sequencing. Sequencing was performed using the Illumina HiSeq4000 platform. The HRD score was calculated based on the genome-wide allele-specific copy number result, and it was composed of three parts: 1) loss of heterozygosity (LOH): the number of segments >=15 Mb in length (but not covering the entire chromosome), mCN =0 and tCN > 0; 2) telomeric allelic imbalance (TAI): the number of segments with allelic imbalances (mCN!= tCN - mCN) extending to the telomeric end of a chromosome; 3) large-scale state transitions (LST), the number of chromosomal breaks between adjacent segments of at least 10 Mb, with a distance between them not larger than 3 Mb. Results: The primary and secondary endpoints, including pCR, event-free survival, overall survival, breast-conserving surgery rates, and treatment-related toxicities, were published previously. HRD testing was attempted on baseline FFPE tumor samples for 54 patients in the NeoCART cohort and was successfully completed for 43 patients (79.6%). It was unavailable for 11 patients due to inadequate tissue or the quality filter. Patients with HRD measurable tumors received DCb in 22 cases and EC-D in 21 cases. TP53 (93.0%), PIK3CA (27.9%), PTEN (11.6%), ATRX (9.3%), NF1 (9.3%), PIK3R1 (9.3%) and PKHD1 (9.3%) were the most frequently mutated genes. No significant association between BRCA1/2 mutation status and pCR was observed in the general population or the two treatment arms. Patients in the DCb group who achieved pCR had a higher HRD score (p =0.04), higher stromal TILs (p =0.02), and a higher Ki67 index (p =0.04) than non-pCR patients. RCB 0/1 was associated with higher stromal TILs (P =0.05) and a higher Ki67 index (P =0.008). However, no correlation between HRD score and pCR was observed in the EC-D group. Conclusions: PCR in TNBC patients correlated with a higher HRD score, higher stromal TILs, and a higher Ki67 index on carboplatin-based neoadjuvant chemotherapy regardless of BRCA status. Clinical trial information: NCT03154749.

Biomarkers for response to immunotherapy in triple-negative breast cancer: Differences between survival and pCR biomarkers.

583 Background: Immunotherapy is entering clinical practice as a promising new neoadjuvant therapeutic approach in triple-negative breast cancer, and it is important to identify biomarkers to focus this therapy on those patients that have the highest benefit. Interestingly, an improved survival outcome is observed in pCR and non-pCR patients, which raises the hypothesis that biomarkers might also be different for pCR prediction as well as prognosis. In this study, we investigated this hypothesis in the neoadjuvant GeparNuevo trial. Methods: A total of 174 patients were randomized to receive neoadjuvant chemotherapy with durvalumab vs. placebo. HTG EdgeSeq mRNA analysis was performed for a total of 2549 genes in 162 pretherapeutic core biopsies. In addition, tumor-infiltrating lymphocytes (stromal and intratumoural) as well as PD-L1 protein expression was evaluated by IHC. We systematically compared the distant disease-free survival (DDFS) of 5 predefined gene signatures (including the GeparSixto immune signature) as well as 12 single mRNA markers identified in previous projects between treatment arms using univariate Cox proportional-hazard regression analyses. In addition, exploratory biomarker analyses were performed. Results: The PSIP1 gene expression (per 1 unit hazard ratio [HR]: 0.58 95%CI 0.41-0.83; p=0.002), TAP1 (per 1 unit HR: 0.68 95%CI 0.48-0.95; p=0.025) as well as stromal TILs (sTILs) (per 10% HR: 0.73 95%CI 0.56-0.95; p=0.019) were significant for improved DDFS in the complete cohort. In the placebo arm PSIP1 (HR 0.50 95%CI 0.29-0.87; p=0.014) as well as sTILs (HR 0.73 95%CI 0.53-0.99; p=0.044) were significant for improved DDFS. In the durvalumab arm, the gene expression of PSIP1 (HR 0.54 95%CI 0.31-0.94; p=0.029), PD-L1/CD274 (per 1 unit HR: 0.41 95%CI 0.21-0.77; p=0.006), CD38 (per 1 unit: HR 0.52 95%CI 0.29-0.92; p=0.026) as well as the GeparSixto immune signature (per 1 unit HR: 0.51 95%CI 0.27-0.97; p=0.041) were significant for improved DDFS, with a positive test for interaction with treatment arm for PD-L1/CD274 (interaction p=0.020). Additional analyses, including multivariate Cox regressions for DDFS as well as systematic comparisons for biomarkers for DDFS and for pCR, will be presented. Conclusions: Our analysis suggests that biomarkers for immune response are linked to improved survival with neoadjuvant durvalumab therapy and that in this setting, survival biomarkers are not identical to pCR biomarkers. The results are a basis for a further dissection of the contribution of pCR to survival effects of immunotherapy.

Non-invasive cell-free DNA monitoring for predicting the response to neoadjuvant immunotherapy in locally advanced esophageal squamous cell carcinoma.

e16040 Background: The combined modality therapy including neoadjuvant chemoradiotherapy has been selected as the standard care for locally advanced Esophageal squamous cell carcinoma (ESCC). However, the conclusive evidences to support the effectiveness of neoadjuvant immunotherapy for ESCC are rarely discussed. This study aims to investigate the molecular features of cell-free DNA (cfDNA) and the impact of their dynamic changes on the response to neoadjuvant immunotherapy in locally advanced ESCC patients. Methods: Twenty-four eligible locally advanced ESCC patients with received neoadjuvant immunotherapy were enrolled in this study. 7 patients achieved pathological complete regression (pCR) and the other 17 patients had non-pCR. The baseline, second and third blood samples (before neoadjuvant immunotherapy, at one month and two months after neoadjuvant immunotherapy, respectively) were collected from Cancer Institute and Hospital, Chinese Academy of Medical Sciences. Both cfDNA fragments and genomic DNA were extracted for enrichment of a customized panel covering exon regions of 599 genes. The dynamic analysis of gene alterations, which allows the monitoring of the response to neoadjuvant immunotherapy in locally advanced ESCC patients, were conducted based on multiple blood sampling strategy. Results: The most frequently mutated genes among all cases were TP53, KMT2D, CREBBP and KMT2B. MSI scores of both second and third blood samples were remarkablely higher than those in baseline blood samples (p = 0.002, 0.04). On the contrary, the TMB values and mean variant allele frequency (VAF) of second and third blood samples were significantly decreased compared with the baseline blood (TMB, p = 0.04, 0.03; mean VAF, p = 0.01, 0.02). Moreover, a decreasing trend of mean VAF was observed at the time-series blood samples from ESCC patients with pCR, while the mean VAF of ESCC patients with non-pCR declined in the blood samples from the second time point then increased in the blood samples from the thrid time point. Conclusions: The detection of dynamic changes of mean VAF could distinguish the pCR and non-pCR ESCC patients with neoadjuvant immunotherapy. These findings warrant further expanded prospective cohorts to validate.

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.

The breast cancer immune microenvironment is modified by neoadjuvant chemotherapy

Neoadjuvant chemotherapy (NAT) in breast cancer (BC) has been used to reduce tumor burden prior to surgery. However, the impact on prognosis depends on the establishment of Pathological Complete Response (pCR), which is influenced by tumor-infiltrating lymphocyte levels and the activation of the antitumor immune response. Nonetheless, NAT can affect immune infiltration and the quality of the response. Here, we showed that NAT induces dynamic changes in the tumor microenvironment (TME). After NAT, an increase of regulatory T cells and a decrease of CD8+ T cells was found in tumor, correlated with the presence of metastatic cells in lymph nodes. In addition, an increase of polymorphonuclear myeloid-derived suppressor like cells was found in luminal patients post-NAT. pCR patients showed a balance between the immune populations, while non-pCR patients presented an inverse relationship in the frequency of CD68+ versus CD3+, CD8+, and CD20+ cells. Moreover, activated T cells were found in peripheral blood, as well as an increase in T cell clonality with a lower diversity post-NAT. Overall, these results shown that NAT induces an activation of immune response, however, a balance in the TME seems to be related to a better antigenic presentation and therefore a better response to treatment.

Tumor Immune Microenvironment and Response to Neoadjuvant Chemotherapy in Hormone Receptor/HER2+ Early Stage Breast Cancer

BackgroundPathologic response at the time of surgery after neoadjuvant therapy for HER2 positive early breast cancer impacts both prognosis and subsequent adjuvant therapy. Comprehensive descriptions of the tumor microenvironment (TME) in patients with HER2 positive early breast cancer is not well described. We utilized standard stromal pathologist-assessed tumor infiltrating lymphocyte (TIL) quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting. MethodsWe utilized standard stromal pathologist-assessed TIL quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in 28 patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting. ResultsPathologist-assessed stromal TILs were significantly associated with pathologic complete response (pCR). By quantitative multiplex immunofluorescence, univariate analysis revealed significant increases in CD3+, CD3+CD8-FOXP3-, CD8+ and FOXP3+ T-cell densities as well as increased immune cell aggregates in pCR patients. In subsets of paired pre/post-treatment samples, we observed significant changes in gene expression signatures in non-pCR patients and significant decreases in CD8+ densities after treatment in pCR patients. No RNA based pathway signature was associated with pCR. ConclusionTME characterization HER2 positive breast cancer patients revealed several stromal T-cell densities and immune cell aggregates associated with pCR. These results demonstrate the feasibility of these novel methods in TME evaluation and contribute to ongoing investigations of the TME in HER2+ early breast cancer to identify robust biomarkers to best identify patients eligible for systemic de-escalation strategies.

Incidence of brain metastases in patients with early HER2-positive breast cancer receiving neoadjuvant chemotherapy with trastuzumab and pertuzumab

The addition of pertuzumab (P) to trastuzumab (H) and neoadjuvant chemotherapy (NAC) has decreased the risk of distant recurrence in early stage HER2-positive breast cancer. The incidence of brain metastases (BM) in patients who achieved pathological complete response (pCR) versus those who do not is unknown. In this study, we sought the incidence of BM in patients receiving HP-containing NAC as well as survival outcome. We reviewed the medical records of 526 early stage HER2-positive patients treated with an HP-based regimen at Memorial Sloan Kettering Cancer Center (MSKCC), between September 1, 2013 to November 1, 2019. The primary endpoint was to estimate the cumulative incidence of BM in pCR versus non-pCR patients; secondary endpoints included disease free-survival (DFS) and overall survival (OS). After a median follow-up of 3.2 years, 7 out of 286 patients with pCR had a BM while 5 out of 240 non-pCR patients had a BM. The 3-year DFS was significantly higher in the pCR group compared to non-pCR group (95% vs 91 %, p = 0.03) and the same trend was observed for overall survival. In our cohort, despite the better survival outcomes of patients who achieved pCR, we did not observe appreciable differences in the incidence of BM by pCR/non-pCR status. This finding suggests that the BM incidence could not be associated with pCR. Future trials with new small molecules able to cross the blood brain barrier should use more specific biomarkers rather than pCR for patients’ selection.

Plasma Cell-Free DNA Integrity Assessed by Automated Electrophoresis Predicts the Achievement of Pathologic Complete Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer.

PURPOSEThe study of plasma cell-free DNA integrity (cfDI) has shown potential for providing useful information in neoplastic patients. The aim of this study is to estimate the accuracy of an electrophoresis-based method for cfDI evaluation in the assessment of pathologic complete response (pCR) in patients with breast cancer (BC) undergoing neoadjuvant chemotherapy (NACT).PATIENTS AND METHODSFifty-one patients with BC undergoing anthracycline-/taxane-based NACT were recruited. Plasma samples were collected from each patient at diagnosis (t0), after anthracycline administration (t1), and after NACT completion (t2). The concentration of differently sized cell-free DNA fragments was assessed by automated electrophoresis. cfDI, expressed as cfDI index, was calculated as the ratio of 321-1,000 bp sized fragment concentration to 150-220 bp sized fragment concentration assessed at t2. cfDI index was then used to build an exploratory classifier for BC response to NACT, directly comparing its sensitivity and specificity with magnetic resonance imaging (MRI), through bootstrapped logistic regression.RESULTScfDI index was assessed on 38 plasma samples collected from as many patients at t2, maintaining a 30/70 ratio between pCR and non-pCR patients. cfDI index showed an area under the receiver operating characteristic curve in predicting the achievement of pCR of 81.6, with a cutoff above 2.71 showing sensitivity = 81.8 and specificity = 81.5. The combination of cfDI index and MRI showed, in case of concordance, an area under the receiver operating characteristic curve of 92.6 with a predictive value of complete response of 87.5 and a predictive value of absence of complete response of 94.7.CONCLUSIONcfDI index measured after NACT completion shows great potential in the assessment of pCR in patients with BC. The evaluation of its use in combination with MRI is strongly warranted in prospective studies.

Clinical analysis of pathologic complete responders in advanced-stage ovarian cancer

ObjectiveTo determine the clinical characteristics of patients who attained pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) and to identify specific predictive or prognostic factors associated with pCR. MethodsTwo distinct populations of patients who underwent NACT followed by interval tumor reductive surgery (TRS) were used in this retrospective study. The first contained 472 patients from a single institution. The second contained only pCR patients (67); those identified from population one, plus 44 obtained through collaborative institutions. Cox analysis and log-rank tests were performed to assess associations between clinical characteristics and pCR outcome, recurrence-free survival (RFS), and overall survival (OS). ResultsThe median RFS and OS in our pCR-only population was 24.2 and 80.8 months, respectively, with a median follow-up time of 32.4 months. In our single institution population, 23 patients attained pCR (4.9%) and had longer RFS compared to non-pCR patients with viable microscopic, optimal, or suboptimal residual disease (24.3 vs. 12.1 vs. 11.6 vs. 9.6 months, p = 0.025, 0.012, 0.008, respectively), and longer OS compared to those with optimal or suboptimal residual disease (54.5 vs. 29.4 vs. 25.7 months, p = 0.027, 0.007, respectively). Patients were more than three-fold likely to attain pCR if their CA125 value was normal at the time of surgery (OR 3.54, 95% CI: 1.14–11.05, p = 0.029). ConclusionsWomen with pCR after NACT have significantly longer RFS compared to those with residual viable tumor at the time of interval tumor-reductive surgery, and CA125 is plausible biomarker for identifying these extreme responders preoperatively.

Abstract PD11-08: Associations of baseline breast MRI metrics and immune infiltration with chemotherapy response in triple negative breast cancer

Abstract Introduction: In triple-negative breast cancer (TNBC), both response to neoadjuvant chemotherapy (NAC) and the degree of pre-treatment (pre-tx) tumor immune infiltration as defined by tumor-infiltrating lymphocytes (TILs) are prognostic. Improving NAC response prediction in early TNBC would provide the opportunity to consider adjustments to the NAC regimen prior to initiating therapy. Breast magnetic resonance imaging (MRI) enables noninvasive whole-tumor measurement of microenvironment features. We investigated the value of pre-tx MRI metrics in addition to TILs for the prediction of NAC response in early TNBC patients. Methods: Women with Stage I-III TNBC who underwent pre-tx clinical breast MRI and NAC at our institution (2005-2019) were retrospectively identified. Response to NAC was noted, with pathologic complete response (pCR) defined as no residual invasive cancer present within the breast. When tissue was available, diagnostic biopsy was used to quantify pre-tx TILs as deciles from 10-100% by a breast pathologist. Patients underwent pre-tx breast MRI on either a 1.5T or 3T scanner including diffusion-weighted (DW-) and dynamic contrast-enhanced (DCE-) MRI. From DCE-MRI, tumor longest diameter (LD) and T stage (1-4), as well as contrast kinetics including percent enhancement (PE) at 2 minutes post-contrast and signal enhancement ratio (SER) were determined. Tumor peak PE and peak SER (representing the highest mean PE and SER, respectively, for 3×3 voxel subregions) and functional tumor volume (FTV, tumor volume exhibiting PE ≥ 50%) were calculated. Mean apparent diffusion coefficient (ADC) was calculated from DW-MRI. TIL levels and imaging features were compared between pCR and non-pCR groups by Wilcoxon rank sum test and performance for prediction of pCR was evaluated using areas under the curve (AUC) measures from receiver operating characteristic curve analysis. Results: 115 TNBC patients (median age: 49, range 26-79 years) were evaluated, of which 45 (39%) achieved pCR. The majority received an anthracycline-containing regimen. Pre-tx TILs (evaluated in N=60 with available biopsy specimens) ranged from 10% to 80% (median, 10%) and were significantly higher in pCR vs. non-pCR patients (p = 0.02, AUC = 0.63). Pre-tx lesion size on imaging was predictive of response (Table 1), with pCR patients having significantly lower LD (p < 0.01, AUC = 0.68) and FTV (p = 0.01, AUC = 0.67). Peak PE was also associated with response, significantly lower in pCR patients (p = 0.04, AUC = 0.62), while SER and ADC were not (p > 0.05). Stratifying by T stage, both peak PE (p = 0.03) and FTV (p = 0.05) were predictive of response in T1/T2 patients, while no imaging metrics reached significance in T3/T4 patients. Discussion: In a large cohort of TNBC patients undergoing NAC, measures of tumor size and immune infiltration were strongly predictive of NAC response. Preliminary results suggest that baseline peak PE and FTV are associated with NAC response, particularly in earlier stage TNBC patients. These findings support the utility of imaging and TILs assessments to predict response in TNBC and potentially guide NAC regimens for improved outcomes. Future work will extend these analyses to assess the value of changes in imaging metrics over the course of NAC to predict response. Acknowledgments: NIH P30CA015704, R01CA248192, and Roger E. Moe Fellowship, ASCO/CCF Hayden Family Foundation Young Investigator Award in Breast Cancer Summary of imaging characteristics across TNBC cohort. Values indicate mean (standard deviation).Whole cohort. N=115T1/T2. N=80T3/T4. N=35pCR. N=45non-pCR. N=70pAUCpCR. N=39non-pCR. N=41pAUCpCR. N=6non-pCR. N=29pAUCLongest dimension (mm)34 (15)50 (27)<0.010.6829 (11)31 (10)0.410.5561 (6)76 (20)0.060.75FTV (cm3)14.7 (17.0)31.2 (43.4)0.010.6710.4 (11.0)19.0 (20.2)0.050.6446.1 (24.5)52.0 (58.0)0.720.57Peak SER1.77 (0.26)1.78 (0.23)0.960.501.76 (0.26)1.79 (0.23)0.690.531.91 (0.19)1.78 (0.26)0.270.68Peak PE (%)234 (61)268 (69)0.040.62237 (61)275 (71)0.030.66247 (70)256 (63)1.000.5ADC(×10-3 mm2/s)1.19 (0.29)1.31 (0.36)0.180.581.16 (0.28)1.24 (0.30)0.390.561.40 (0.30)1.4 (0.43)0.900.48 Citation Format: Anum S Kazerouni, Laura C. Kennedy, Michael Hirano, Bonny Chau, Debosmita Biswas, Shaveta Vinayak, Matthew J. Nyflot, Habib Rahbar, Suzanne Dintzis, Savannah C. Partridge. Associations of baseline breast MRI metrics and immune infiltration with chemotherapy response in triple negative 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 PD11-08.

Abstract OT1-16-01: A multicenter phase II study of vaccines to prevent recurrence in patients with HER-2 positive breast cancer

Abstract Background: HER2-positive breast cancer patients are commonly treated with neoadjuvant therapy including HER2-targeted therapy. Patients who have residual invasive disease have less favorable outcomes with an increased risk of recurrent disease than patients with complete pathologic response (pCR). It has also been observed that these non-pCR patients have low or absent anti-HER-2 CD4 Th1 responses. We hypothesized that correcting the anti-HER-2 CD4 Th1 response using vaccines will increase interferon gamma production which we have shown is a potent inducer of apoptosis and senescence in HER2-positive breast cancer. This study will be evaluating safety and immunogenicity of two vaccines (multivalent anti-oncodriver DNA vaccine (WOKVAC) or HER-2-pulsed dendritic cell vaccine (DC1)). Methods: This is a multi-center, phase 2, randomized study to determine the safety and tolerability of HER2 vaccines (DC1 and WOKVAC), assess immunogenicity, and evaluate recurrence free survival. Patients with HER2-positive early breast cancer (stage I-III) are eligible if they have residual invasive disease in the breast or axilla at surgery after receiving neoadjuvant chemotherapy plus HER2 -targeted therapy. Patients are randomly assigned in a 1:1 ratio to receive 1 of 2 adjuvant HER2 vaccines, either DC1 or WOKVAC for 1 year. A permuted-block randomization scheme was used with stratification according to residual cancer burden (RCB) (1+2 vs 3). The primary end points are safety and immunogenicity (immune response rate measured by ELISPOT). Each treatment arm will be assessed separately. Any statistical comparison between arms is purely exploratory, as this study is neither designed nor powered for comparative hypotheses. Secondary endpoints include recurrence-free survival. Exploratory analyses include the assessment of prognostic and predictive biomarkers including circulating tumor cells, serum HER2 levels, and other immune markers. The enrollment began in 2018 and we plan to accrue the total of 110 patients. ClinicalTrials.gov Identifier: NCT03384914 Citation Format: Hyo S Han, Mary Disis, Robert Wesolowski, Carla Fisher, Shipra Gandhi, Nancy Chan, William Gwin, Keerthi Gogineni, Rosemarie Mick, Christina Sierra Rodriguez, Deanna Hogue, Hien Liu, Ricardo Costa, Brian Czerniecki. A multicenter phase II study of vaccines to prevent recurrence in patients with HER-2 positive 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 OT1-16-01.