Efficacy Of Neoadjuvant Chemotherapy Research Articles

Predictive analysis of breast cancer response to neoadjuvant chemotherapy through plasma metabolomics.

Preoperative chemotherapy is a critical component of breast cancer management, yet its effectiveness is not uniform. Moreover, the adverse effects associated with chemotherapy necessitate the identification of a patient subgroup that would derive the maximum benefit from this treatment. This study aimed to establish a method for predicting the response to neoadjuvant chemotherapy in breast cancer patients utilizing a metabolomic approach. Plasma samples were obtained from 87 breast cancer patients undergoing neoadjuvant chemotherapy at our facility, collected both before the commencement of the treatment and before the second treatment cycle. Metabolite analysis was conducted using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS). We performed comparative profiling of metabolite concentrations by assessing the metabolite profiles of patients who achieved a pathological complete response (pCR) against those who did not, both in initial and subsequent treatment cycles. Significant variances were observed in the metabolite profiles between pCR and non-pCR cases, both at the onset of preoperative chemotherapy and before the second cycle. Noteworthy distinctions were also evident between the metabolite profiles from the initial and the second neoadjuvant chemotherapy courses. Furthermore, metabolite profiles exhibited variations associated with intrinsic subtypes at all assessed time points. The application of plasma metabolomics, utilizing CE-MS and LC-MS, may serve as a tool for predicting the efficacy of neoadjuvant chemotherapy in breast cancer in the future after all necessary validations have been completed.

Safety and efficacy of neoadjuvant chemotherapy with paclitaxel, carboplatin, and cetuximab for locally advanced head and neck squamous cell carcinoma.

As a substantial waiting time is usually required for radical surgery, safe and effective preoperative neoadjuvant chemotherapy (NAC) is desired for the treatment of locally advanced head and neck squamous cell carcinoma (HNSCC). However, the significance of NAC in advanced HNSCC is still unclear. This study aimed to assess the safety and efficacy of NAC using the paclitaxel, carboplatin, and cetuximab (PCE) regimen. We retrospectively evaluated the background characteristics, incidence of adverse events, overall response rate (ORR), pathological response, recurrence-free survival (RFS), and overall survival (OS) in 26 patients. Patients receiving the PCE regimen were further divided into two groups based on the number of chemotherapy cycles (one cycle or more) and eligibility for cisplatin. Patients aged ≥ 75years and those with an estimated glomerular filtration rate (eGFR) < 60mL/min were classified as ineligible for cisplatin. The median age was 70 (27-81) years. The median eGFR at treatment initiation was 63.2 (41.1-89.7)mL/min. Fourteen (53.8%) patients were ineligible for cisplatin. Grade 3 or higher neutropenia was observed in 11 of 25 (42.3%) patients. No delay in or withdrawal from surgery was observed. The ORR was 65.4%. The 2-year RFS and OS were 61.5% and 76.7%, respectively. No significant differences in safety and efficacy between the number of chemotherapy cycles and cisplatin eligibility were observed. NAC using the PCE regimen for patients with locally advanced HNSCC, including cisplatin-ineligible patients, has acceptable toxicity and favorable efficacy.

The analysis of transcriptomic signature of TNBC—searching for the potential RNA-based predictive biomarkers to determine the chemotherapy sensitivity

AbstractNeoadjuvant chemotherapy is the foundation treatment for triple-negative breast cancer (TNBC) and frequently results in pathological complete response (pCR). However, there are large differences in clinical response and survival after neoadjuvant chemotherapy of TNBC patients. The aim was to identify genes whose expression significantly associates with the efficacy of neoadjuvant chemotherapy in patients with TNBC. Transcriptomes of 46 formalin-fixed paraffin-embedded (FFPE) tumor samples from TNBC patients were analyzed by RNA-seq by comparing 26 TNBCs with pCR versus 20 TNBCs with pathological partial remission (pPR). Subsequently, we narrowed down the list of genes to those that strongly correlated with drug sensitivity of 63 breast cancer cell lines based on Dependency Map Consortium data re-analysis. Furthermore, the list of genes was limited to those presenting specific expression in breast tumor cells as revealed in three large published single-cell RNA-seq breast cancer datasets. Finally, we analyzed which of the selected genes were significantly associated with overall survival (OS) in TNBC TCGA dataset. A total of 105 genes were significantly differentially expressed in comparison between pPR versus pCR. As revealed by PLSR analysis in breast cancer cell lines, out of 105 deregulated genes, 42 were associated with sensitivity to docetaxel, doxorubicin, paclitaxel, and/or cyclophosphamide. We found that 24 out of 42 sensitivity-associated genes displayed intermediate or strong expression in breast malignant cells using single-cell RNAseq re-analysis. Finally, 10 out of 24 genes were significantly associated with overall survival in TNBC TCGA dataset. Our RNA-seq-based findings suggest that there might be transcriptomic signature consisted of 24 genes specifically expressed in tumor malignant cells for predicting neoadjuvant response in FFPE samples from TNBC patients prior to treatment initiation. Additionally, nine out of 24 genes were potential survival predictors in TNBC. This group of 24 genes should be further investigated for its potential to be translated into a predictive test(s).

Abstract PO5-01-04: HER2 Amplification Level and Focal/Broad Region Size as Predictors of Treatment Response in Neoadjuvant Chemotherapy and Anti-HER2 Therapy for HER2-Positive Breast Cancer

Abstract Background: Neoadjuvant chemotherapy combined with anti-HER2 therapy has become the standard treatment approach for HER2-positive breast cancer. However, not all HER2-positive patients can achieve pathological complete response after neoadjuvant therapy. This raises the question of which subset of HER2+ patients derive the greatest benefit from pre-operative HER2-targeted treatment. Therefore, this study aims to determine whether the level and amplification region size of HER2 amplification are associated with the efficacy of neoadjuvant chemotherapy combined with anti-HER2 therapy. Methods: A total of 523 breast cancer samples were collected from 2017 to 2018, among which 202 cases were HER2-positive patients. Among these, 55 HER2-positive patients received neoadjuvant chemotherapy combined with anti-HER2 targeted therapy. The amplification status of HER2 was assessed using immunohistochemistry/fluorescence in situ hybridization (IHC/FISH) and next-generation sequencing (NGS). The HER2/CEP17 ratio, determined by FISH, was used to represent the amplification level of HER2. The size of the amplification region was calculated using NGS and neighboring genes located in chr17q. Amplification regions smaller than 1 Mb were classified as focal amplification, while those larger than 1 Mb were classified as broad amplification. Results: We compared the HER2/ERBB2 status of 523 breast cancer patients using different detection methods and found a high concordance between ERBB2 amplification detected by NGS and HER2-positivity detected by IHC and FISH, with a sensitivity of 96.0%, specificity of 97.8%, and overall concordance of 97.1%. Based on the HER2/CEP17 ratio determined by FISH, we observed that using a threshold of 6 for classification, the high amplification group had a significantly higher pCR rate compared to the low amplification group (86.7% vs. 41.7%; p=0.037, odds ratio [OR]=0.121, 95% confidence interval [CI]: 0.009-0.919). Moreover, the focal amplification group showed a higher pCR rate compared to the broad amplification group (65.9% vs. 30.8%, p=0.051, OR=0.237, 95% CI: 0.045-1.035). Additionally, within the low amplification group (HER2/CEP17 &amp;lt; 6), the pCR rate was 66.7% for focal amplification and 20% for broad amplification, suggesting that focal amplification of ERBB2 may further guide clinical benefit in the low HER2/CEP17 ratio group. Conclusion: This study demonstrates a high concordance between ERBB2 amplification determined by NGS and HER2-positivity determined by IHC/FISH. High HER2/CEP17 ratio and focal amplification of ERBB2 are associated with a higher pCR rate in neoadjuvant chemotherapy combined with anti-HER2 targeted therapy. Citation Format: Ning Liao, Guochun Zhang, Xinze Lv, Kai Li, Ting Hou, Zhou Zhang. HER2 Amplification Level and Focal/Broad Region Size as Predictors of Treatment Response in Neoadjuvant Chemotherapy and Anti-HER2 Therapy for HER2-Positive Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-01-04.

Abstract PO1-27-06: HER2 Amplification Level and Focal/Broad Region Size as Predictors of Treatment Response in Neoadjuvant Chemotherapy and Anti-HER2 Therapy for HER2-Positive Breast Cancer

Abstract Background: Neoadjuvant chemotherapy combined with anti-HER2 therapy has become the standard treatment approach for HER2-positive breast cancer. However, not all HER2-positive patients can achieve pathological complete response after neoadjuvant therapy. This raises the question of which subset of HER2+ patients derive the greatest benefit from pre-operative HER2-targeted treatment. Therefore, this study aims to determine whether the level and amplification region size of HER2 amplification are associated with the efficacy of neoadjuvant chemotherapy combined with anti-HER2 therapy. Methods: A total of 523 breast cancer samples were collected from 2017 to 2018, among which 202 cases were HER2-positive patients. Among these, 55 HER2-positive patients received neoadjuvant chemotherapy combined with anti-HER2 targeted therapy. The amplification status of HER2 was assessed using immunohistochemistry/fluorescence in situ hybridization (IHC/FISH) and next-generation sequencing (NGS). The HER2/CEP17 ratio, determined by FISH, was used to represent the amplification level of HER2. The size of the amplification region was calculated using NGS and neighboring genes located in chr17q. Amplification regions smaller than 1 Mb were classified as focal amplification, while those larger than 1 Mb were classified as broad amplification.&amp;gt; Results: We compared the HER2/ERBB2 status of 523 breast cancer patients using different detection methods and found a high concordance between ERBB2 amplification detected by NGS and HER2-positivity detected by IHC and FISH, with a sensitivity of 96.0%, specificity of 97.8%, and overall concordance of 97.1%. Based on the HER2/CEP17 ratio determined by FISH, we observed that using a threshold of 6 for classification, the high amplification group had a significantly higher pCR rate compared to the low amplification group (86.7% vs. 41.7%; p=0.037, odds ratio [OR]=0.121, 95% confidence interval [CI]: 0.009-0.919). Moreover, the focal amplification group showed a higher pCR rate compared to the broad amplification group (65.9% vs. 30.8%, p=0.051, OR=0.237, 95% CI: 0.045-1.035). Additionally, within the low amplification group (HER2/CEP17 &amp;lt; 6), the pCR rate was 66.7% for focal amplification and 20% for broad amplification, suggesting that focal amplification of ERBB2 may further guide clinical benefit in the low HER2/CEP17 ratio group. Conclusion: This study demonstrates a high concordance between ERBB2 amplification determined by NGS and HER2-positivity determined by IHC/FISH. High HER2/CEP17 ratio and focal amplification of ERBB2 are associated with a higher pCR rate in neoadjuvant chemotherapy combined with anti-HER2 targeted therapy. Citation Format: Ning Liao, Guochun Zhang, Xinze Lv, Kai Li, Ting Hou, Zhou Zhang. HER2 Amplification Level and Focal/Broad Region Size as Predictors of Treatment Response in Neoadjuvant Chemotherapy and Anti-HER2 Therapy for HER2-Positive Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-27-06.

Gastric cancer immune microenvironment score predicts neoadjuvant chemotherapy efficacy and prognosis.

The efficacy of neoadjuvant chemotherapy (NACT) in patients with advanced gastric cancer (GC) varies greatly. Thus, we aimed to verify the predictive value of tumor-infiltrating immune cells (TIICs) on the treatment response to NACT and the prognosis of patients with advanced GC, and to explore the impact of NACT on the tumor immune microenvironment (TIME). Paired tumor tissues (pre- and post-NACT) from patients with advanced GC were collected for this study. TIICs were assessed using immunohistochemistry staining and analyzed using logistic regression to establish an immune microenvironment score for GC (ISGC score) and predict NACT efficacy. Kaplan-Meier curves were used to evaluate the survival outcome of patients. The results showed that TIME was dramatically heterogeneous between NACT response and nonresponse patients. In the validation cohort, the ISGC score demonstrated good predictive performance for treatment response to NACT. Moreover, high ISGC indicated better long-term survival in patients with advanced GC. Furthermore, tumor-infiltrated T cells (CD3+ and CD8+) and CD11c+ macrophages were significantly increased in the response group, while CD163+ macrophages and FOXP3+ Treg cells were decreased after NACT. However, opposite results were exhibited in the nonresponse group. Finally, we found that the percentage of programmed cell death ligand 1 (PD-L1)-positive tumors was 31% (32/104) pre-NACT and 49% (51/104) post-NACT, and almost all patients with elevated PD-L1 were in the NACT response group. The ISGC model accurately predicted NACT efficacy and classified patients with GC into different survival groups. NACT regulates the TIME in GC, which may provide strategies for personalized immunotherapy.

Efficacy of neoadjuvant chemotherapy combined with surgery in patients with nonsmall cell lung cancer: A meta-analysis.

This meta-analysis sought to investigate the effect of neoadjuvant chemotherapy (NACT) combined with surgery in patients with nonsmall cell lung cancer (NSCLC). With time span from January 2010 to December 2022, PubMed, Web of Science and Embase, China National Knowledge Infrastructure, and WanFang databases were searched for randomized controlled trials on comparison between NACT combined with surgery and surgery alone in patients with NSCLC. Then a meta-analysis was performed in accordance with Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. A total of 1511 studies were retrieved and 12 were finally included. Meta-analysis results showed that compared with surgery alone, a combination of NACT and surgery was associated with higher treatment response rate (odds ratio, OR = 2.459, 95% confidence interval, CI [1.785, 3.388], P < 0.001), 1-year survival rate (OR = 2.185, 95% CI [1.608, 2.970], P < 0.001), and 3-year survival rate (OR = 2.195, 95% CI [1.568, 3.073], P < 0.001) and lower levels of intraoperative blood loss (standardized mean difference, SMD = -0.932, 95% CI [-1.588, -0.275], P = 0.005) and length of hospital stay (SMD = -0.481, 95% CI [-0.933, -0.028], P = 0.037). NACT combined with surgery is superior to surgery alone in the treatment of NSCLC and can promote postoperative recovery. Collectively, such combination is a safe and effective treatment for patients with NSCLC.

Research progress on ultrasound medicine in diagnosis and evaluation of chemotherapy effect of breast cancer

Breast cancer has the highest incidence rate among cancers in the world and is the main cause of death among female cancer patients around the world. The progress of ultrasound technology has continuously improved the ability to identify the shape and microvessels of breast masses. It plays an important role in the differentiation of benign and malignant breast masses and is the main auxiliary diagnostic method for breast cancer. The widespread implementation of neoadjuvant chemotherapy for breast cancer has improved the survival rate of patients. Evaluating the efficacy after chemotherapy and adjusting chemotherapy strategies as needed can help improve the prognosis of patients. Ultrasound can conduct multi-parameter measurements of breast tumor hardness, blood flow velocity and vascular distribution, which can be applied to evaluate the efficacy of neoadjuvant chemotherapy for breast cancer. This article reviewed the application and research progress of multi-modal ultrasound in the diagnosis and evaluation of chemotherapy efficacy of breast cancer.

Advancements in the Utilization of Deep Learning Techniques based on Histopathological Imaging for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer

Advancements in the Utilization of Deep Learning Techniques based on Histopathological Imaging for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer

18F-FDG PET/CT metabolism multi-parameter prediction of chemotherapy efficacy in locally progressive gastric cancer

PurposeThis study aimed to use an 18F-FDG PET/CT multiparametric quantitative analysis to determine the efficacy of neoadjuvant chemotherapy in patients with locally progressive gastric cancer.Materials and methodsWe conducted a retrospective analysis of 34 patients with pathologically identified gastric cancer who received neoadjuvant chemotherapy and surgery. Chemotherapy regimens were followed and 18F-FDG PET/CT was conducted. We ascertained multiparamaters of the target lesions pre- and post-treatment and determined the ideal cutoff values for the percentage change in biomarkers. Independent factors were evaluated using binary logistic regression. A response classification system was used to explore the association between metabolic and anatomical responses and the degree of pathological remission.ResultsBinary logistic regression analysis showed that Lauren bowel type and change in total lesion glycolysis >45.2% were risk predictors for the efficacy of neoadjuvant chemotherapy; total lesion glycolysis demonstrated the best predictive efficacy. The categorical variable system of the two-module response (metabolic and anatomical response) group had a higher predictive accuracy than that of the single-module response (metabolic or anatomical response) group.ConclusionsUsing 18F-FDG PET/CT multiparametric quantitative analysis, Lauren bowel type and change in total lesion glycolysis >45.2% were independent predictors of the efficacy of neoadjuvant chemotherapy in patients with gastric adenocarcinoma. Additionally, the dual-module assessment demonstrated high predictive efficacy.

Are biomarkers expression and clinical-pathological factors predictive markers of the efficacy of neoadjuvant chemotherapy for locally advanced cervical cancer?

IntroductionTo predict the overall pathologic response to neoadjuvant chemotherapy (NACT) of patients with locally advanced cervical cancer (LACC) creating a prediction model based on clinical-pathological factors and biomarkers (p53, Bcl1 and Bcl2) and to evaluate the prognostic outcomes of NACT. Materials and methodsThis is a retrospective study of 88 consecutive patients with LACC who underwent NACT followed by nerve sparing surgery with retroperitoneal lymphadenectomy at National Cancer Institute of Milan, between January 2000 and June 2013. Clinical pathologic data were retrieved from the institutional database. Biomarkers (p53, Bcl1 and Bcl2) were evaluated before and after NACT in the specimen. To investigate their role as predictors of response, we tried several statistical machine learning algorithms. ResultsResponders to NACT showed a 5-years survival between 100%(CR) and 85.7%(PR). Clinical factors were the most important predictor of response. Age, BMI and grade represented the most important predictors of response at random forest analysis. Tree-based boosting revealed that after adjusting for other prognostic factors, age, grade, BMI and tumor size were independent predictors of response to NACT, while p53 was moderately related to response to NACT. Area under the curve (crude estimate): 0.871. Whereas Bcl1 and Bcl2, were not predictors for response to NACT. The final logistic regression reported that grade was the only significant predictor of response to NACT. ConclusionCombined model that included clinical pathologic variables plus p53 cannot predict response to NACT. Despite this, NACT remain a safe treatment in chemosensitive patients avoiding collateral sequelae related to chemo-radiotherapy.

Abstract 6433: Anti-CD36 monoclonal antibody can sensitize the neoadjuvant chemotherapy response in PDAC by eliminating the senescent tertiary lymphatic structure

Abstract Objective: Pancreatic ductal adenocarcinoma (PDAC) is deadly and aggressive. Neoadjuvant chemotherapy (NAC) may reduce tumor volume and alter the resectability of the tumor. The efficacy of neoadjuvant chemotherapy in patients is still limited. Tertiary lymphoid structures (TLSs) develop in peripheral non-lymphoid tissues and are essential for the immune response and correlate with chemotherapy in various tumor types. However, more research is needed to determine how TLSs affect neoadjuvant chemotherapy in PDAC. We aim to determine how neoadjuvant chemotherapy affects tumor-infiltrating lymphocytes (TLSs) in PDAC patients. We also want to find a biomarker to boost PDAC neoadjuvant chemotherapy response. Methods: We retrospectively collected formalin-fixed paraffin embedded (FFPE) tissues from 115 PDAC patients without preoperative treatment and 72 patients pretreated with neoadjuvant chemotherapy. Multispectral images were processed using AI-powered image analysis software (Tissue Gnostics; Zeiss, Germany). The 10X Genomics platform was used to sequence single cells in tissue samples from five patients who received neoadjuvant chemotherapy (NAC) and five patients who had not received any treatment before analysis (pretreatment naïve, PN). TLS was separated using Laser Microdissection. The mouse model was created by orthotopically injecting tumor cells into the pancreas. Results: Patients who received NAC have a senescent microenvironment. High-throughput single-cell sequencing showed that the senescent gene signature score was enriched in the NAC group, especially in immune cells. The percentage of p16+ CD20+ B cells and P16+ CD3+ T cells in TLSs also increased in the NAC group. Spatial transcriptomics analysis exhibited that CD36 is highly expressed in senescent TLSs, which suggested that CD36 may be a marker for senescent TLSs. Moreover, CD36+ TLSs induced the infiltration of MDSCs and regulatory T cells. CD36+ TLSs were an independent prognostic factor for poor overall survival (OS) (HR=0.67, p=0.002) and progression-free survival (PFS) (HR=0.71, p=0.003). A mice orthotopic xenograft model showed that an anti-CD36 monoclonal antibody eliminated senescent TLSs in pancreatic tissue. MDSCs and Tregs in the surrounding tissue also decreased. Additionally, in vivo KPC mice model showed that the combination of an anti-CD36 and chemotherapy reduced tumor volume and increased survival compared to chemotherapy alone. Conclusion: NAC has the potential to induce the senescence of tumor-associated TLSs, a phenomenon that has been linked to unfavorable prognosis in PDAC. CD36 serves as a viable marker for senescent TLSs that can be targeted. The administration of an anti-CD36 monoclonal antibody can potentially enhance the efficacy of chemotherapy in PDAC by selectively eliminating CD36+ senescent TLSs in mouse models. Citation Format: Jingrui Yan, Tianxing Zhou, Chao Yang, Yongjie Xie, Jun Yu, Jihui Hao. Anti-CD36 monoclonal antibody can sensitize the neoadjuvant chemotherapy response in PDAC by eliminating the senescent tertiary lymphatic structure [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6433.

Abstract 7609: Potential gene expression meta-signatures predict neoadjuvant chemotherapy response in invasive breast cancer

Abstract Early prediction of Neoadjuvant Chemotherapy (NAC) response is crucial for women with locally advanced breast cancer (BC), given their low response rates. This study aims to identify gene expression patterns and tumor microenvironment (TME) characteristics associated with resistance to NAC, which could significantly impact tumor progression and treatment outcomes. The study encompassed differential gene expression comparing non-responders and responders, enrichment analysis, tumor microenvironment estimation, and cytokines identification from a female patient's cohort with distinct molecular subtypes and candidates to NAC at the Colombian National Cancer Institute. Candidate differentially expressed genes validated with RT-PCR in a larger validation cohort and corroborated in several publicly available databases, including associated treatment drugs. Distinct gene expression profiles were observed between responders and non-responders, emphasizing immune system-related pathways such as IL-17 signaling, B cell receptor signaling, complement and coagulation cascades, natural killer cell-mediated cytotoxicity, and NF-kB signaling. Immune-related genes (AGTR1, APOD, CCL19, CGA, ECEL1, NPY1R, NTNG1, PCSK1, PFDN2, S100B, TPRG1, WDR5B, ZNF385B) were identified as biomarkers correlated with non-response and worse prognosis. Responders showed increased B cell populations, CD4+ and CD8+ effector memory T-cells in lymphoid groups, while non-responders displayed elevated levels of CD8+ naive T-cells. Additionally, responders revealed upregulated myeloid cell populations like macrophages and dendritic cells. Several cytokines like IL1B, IL-2, IL-4, IL-12, IL-21, IL-22, IL-36, and TWEAK showed elevated expression in non-responders. Dexamethasone, Vinblastine, and Streptozocin were candidate drugs that interacted with AGTR1, CGA, and S100B, respectively and are associated with progression and metastasis. Logistic regression revealed that overexpression of CGA showed a higher probability (OR:1.83, p=0.03) while ECEL1 had a lower probability (OR=0.44, p=0.04) in non-responders compared to responders who lacked expression of these genes. Immune-related genes and various subtypes of immune cells within the TME exhibit correlations with response to NAC, and several cell fractions significantly changed before and after NAC. These results suggest meta-signatures that warrant further evaluation as concordance assessment between immunohistochemistry (IHC) and gene expression profiling, in addition to an extensive validation to triage patients before NAC and target personalized interventions. Detection and evaluation of TME components are essential to predict NAC efficacy and avoid disease relapse. Finally, these findings emphasize the importance of assessing admixed populations to facilitate novel findings and alleviate disparities. Citation Format: Hedda Michelle Guevara-Nieto, Rafael S. Parra-Medina, Jovanny Zabaleta, Liliana Lopez-Kleine, Alba L. Combita. Potential gene expression meta-signatures predict neoadjuvant chemotherapy response in invasive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7609.

Predicting pathological complete response to neoadjuvant chemotherapy in breast cancer patients: use of MRI radiomics data from three regions with multiple machine learning algorithms

ObjectiveTo construct a multi-region MRI radiomics model for predicting pathological complete response (pCR) in breast cancer (BCa) patients who received neoadjuvant chemotherapy (NACT) and provide a theoretical basis for the peritumoral microenvironment affecting the efficacy of NACT.MethodsA total of 133 BCa patients who received NACT, including 49 with confirmed pCR, were retrospectively analyzed. The radiomics features of the intratumoral region, peritumoral region, and background parenchymal enhancement (BPE) were extracted, and the most relevant features were obtained after dimensional reduction. Then, combining different areas, multivariate logistic regression analysis was used to select the optimal feature set, and six different machine learning models were used to predict pCR. The optimal model was selected, and its performance was evaluated using receiver operating characteristic (ROC) analysis. SHAP analysis was used to examine the relationship between the features of the model and pCR.ResultsFor signatures constructed using three individual regions, BPE provided the best predictions of pCR, and the diagnostic performance of the intratumoral and peritumoral regions improved after adding the BPE signature. The radiomics signature from the combination of all the three regions with the XGBoost machine learning algorithm provided the best predictions of pCR based on AUC (training set: 0.891, validation set: 0.861), sensitivity (training set: 0.882, validation set: 0.800), and specificity (training set: 0.847, validation set: 0.84). SHAP analysis demonstrated that LZ_log.sigma.2.0.mm.3D_glcm_ClusterShade_T12 made the greatest contribution to the predictions of this model.ConclusionThe addition of the BPE MRI signature improved the prediction of pCR in BCa patients who received NACT. These results suggest that the features of the peritumoral microenvironment are related to the efficacy of NACT.

Retracted: Efficacy of Neoadjuvant Chemotherapy with Epirubicin and Cyclophosphamide and Weekly Paclitaxel and Trastuzumab in Human Epidermal Growth Factor Receptor 2-Positive Breast Carcinoma: A Real-World Study.

[This retracts the article DOI: 10.1155/2020/3208391.].

Computed tomography-based radiomics nomogram for predicting therapeutic response to neoadjuvant chemotherapy in locally advanced gastric cancer : A scale for treatment predicting.

Neoadjuvant chemotherapy results in various responses when used to treat locally advanced gastric cancer, we aimed to develop and validate a predictive model of the response to neoadjuvant chemotherapy in patients with gastric cancer. A total of 128 patients with locally advanced gastric cancer who underwent pre-treatment computed tomography (CT) scanning followed by neoadjuvant chemoradiotherapy were included (training cohort: n=64; validation cohort: n=64). We built a radiomics score combined with laboratory parameters to create a nomogram for predicting the efficacy of neoadjuvant chemotherapy and calculating scores for risk factors. The radiomics score system demonstrated good stability and prediction performance for the response to neoadjuvant chemotherapy, with the area under the curve of the training and validation cohorts being 0.8 and 0.64, respectively. The radiomics score proved to be an independent risk factor affecting the efficacy of neoadjuvant chemotherapy. In addition to the radiomics score, four other risk factors were included in the nomogram, namely the platelet-to-lymphocyte ratio, total bilirubin, ALT/AST, and CA199. The model had a C-index of 0.8. Our results indicated that radiomics features could be potential biomarkers for the early prediction of the response to neoadjuvant treatment.

An ultrasound-based nomogram model in the assessment of pathological complete response of neoadjuvant chemotherapy in breast cancer.

We aim to predict the pathological complete response (pCR) of neoadjuvant chemotherapy (NAC) in breast cancer patients by constructing a Nomogram based on radiomics models, clinicopathological features, and ultrasound features. Ultrasound images of 464 breast cancer patients undergoing NAC were retrospectively analyzed. The patients were further divided into the training cohort and the validation cohort. The radiomics signatures (RS) before NAC treatment (RS1), after 2 cycles of NAC (RS2), and the different signatures between RS2 and RS1 (Delta-RS/RS1) were obtained. LASSO regression and random forest analysis were used for feature screening and model development, respectively. The independent predictors of pCR were screened from clinicopathological features, ultrasound features, and radiomics models by using univariate and multivariate analysis. The Nomogram model was constructed based on the optimal radiomics model and clinicopathological and ultrasound features. The predictive performance was evaluated with the receiver operating characteristic (ROC) curve. We found that RS2 had better predictive performance for pCR. In the validation cohort, the area under the ROC curve was 0.817 (95%CI: 0.734-0.900), which was higher than RS1 and Delta-RS/RS1. The Nomogram based on clinicopathological features, ultrasound features, and RS2 could accurately predict the pCR value, and had the area under the ROC curve of 0.897 (95%CI: 0.866-0.929) in the validation cohort. The decision curve analysis showed that the Nomogram model had certain clinical practical value. The Nomogram based on radiomics signatures after two cycles of NAC, and clinicopathological and ultrasound features have good performance in predicting the NAC efficacy of breast cancer.

Neoadjuvant Chemotherapy in Patients With T4b or Obstructive Colon Cancer: A Single Center Retrospective Cohort Study.

The efficacy of neoadjuvant chemotherapy (NAC) for colon cancer remains unestablished. This study aimed to investigate the outcomes of NAC in patients with locally advanced T4b or obstructive T4a colon cancers (LACC). Data of patients with LACC who underwent colon surgery between 2010 and 2022 after NAC at our institution were retrospectively reviewed. Patient characteristics, surgical outcomes, tumor features, and prognosis were analyzed. Among 800 patients with LACC who underwent radical resection, 11 received NAC because of cT4b or cT4a with mechanical obstruction. NAC, administered as a doublet regimen, had a median duration of three months, without grade ≥3 adverse events. R0 resection was achieved in all patients and downstaging was observed in eight patients. One patient developed a postoperative abdominal abscess, and adjuvant chemotherapy was administered to eight patients. Four patients experienced recurrence: liver metastasis in two, and local recurrence in two. Among these, three patients underwent resection of recurrent tumors. Median follow-up was 30 months. NAC is feasible for T4b or obstructive T4a colon cancer and may be a treatment option for LACC. Further large-scale studies are required to confirm the efficacy of NAC in these patients.

Development of a clinical nomogram for prediction of response to neoadjuvant chemotherapy in patients with advanced gastric cancer.

The efficacy of neoadjuvant chemotherapy (NAC) in advanced gastric cancer (GC) is still a controversial issue. To find factors associated with chemosensitivity to NAC treatment and to provide the optimal therapeutic strategies for GC patients receiving NAC. The clinical information was collected from 230 GC patients who received NAC treatment at the Central South University Xiangya School of Medicine Affiliated Haikou Hospital from January 2016 to December 2020. Least absolute shrinkage and selection operator logistic regression analysis was used to find the possible predictors. A nomogram model was employed to predict the response to NAC. In total 230 patients were finally included in this study, including 154 males (67.0%) and 76 females (33.0%). The mean age was (59.37 ± 10.60) years, ranging from 24 years to 80 years. According to the tumor regression grade standard, there were 95 cases in the obvious response group (grade 0 or grade 1) and 135 cases in the poor response group (grade 2 or grade 3). The obvious response rate was 41.3%. Least absolute shrinkage and selection operator analysis showed that four risk factors significantly related to the efficacy of NAC were tumor location (P < 0.001), histological differentiation (P = 0.001), clinical T stage (P = 0.008), and carbohydrate antigen 724 (P = 0.008). The C-index for the prediction nomogram was 0.806. The calibration curve revealed that the predicted value exhibited good agreement with the actual value. Decision curve analysis showed that the nomogram had a good value in clinical application. A nomogram combining tumor location, histological differentiation, clinical T stage, and carbohydrate antigen 724 showed satisfactory predictive power to the response of NAC and can be used by gastrointestinal surgeons to determine the optimal treatment strategies for advanced GC patients.

Retraction: The value, diagnostic efficacy and clinical significance of functional magnetic resonance imaging in evaluating the efficacy of neoadjuvant chemotherapy in patients with triple negative breast cancer.

[This retracts the article DOI: 10.3389/fonc.2023.1132186.].