Prognostic Indicator In Breast Cancer Research Articles

Correlation of tumor budding with a novel and other established prognostic parameters in patients with invasive breast carcinoma.

Breast cancer is the most common malignancy among women. Established prognostic markers in breast carcinomas include tumor size, histologic grade, nodal status, lymphovascular invasion, perineural invasion, hormone receptor status, HER-2 status, and age. To correlate peripheral tumor budding (pTB) with stromal tumor-infiltrating lymphocytes (sTILs) and established prognostic factors in invasive breast carcinoma. It is a retrospective study conducted at multiple centers including a tertiary care center. 100 cases were included over a period of 2.5 years. All cases of invasive breast carcinoma (IBC) in which excision specimens with lymph node dissection were available were studied. Slides were reviewed for pTB and sTILs. Tumor budding of ≤20/10 hpf was considered low tumor budding, and >20 buds/10 hpf was considered high tumor budding. Tumor budding was correlated with age, tumor size, lymphovascular invasion, perineural invasion, tumor stage (pT, pN), stromal tumor-infiltrating lymphocytes, tumor grade, ductal carcinoma in situ, hormonal receptors, and HER2neu. Fisher exact test and Chi-square test were used. We found that high tumor budding was seen in 34 cases and low tumor budding in 66 cases. There was a statistically significant association between high tumor budding and tumor size (P = 0.007), lymphovascular invasion (P < 0.001), perineural invasion (P = 0.004), tumor staging/pT (P = 0.006), nodal staging/pN (P = 0.001), and low sTILs (P < 0.001). However, the association of high tumor budding with parameters like age (P = 0.979), histological type (P = 0.243), tumor grade (P = 0.052), DCIS (P = 0.478), and ER (P = 0.633), and PR (P = 0.544), HER2Neu status (P = 0.171) was not significant. This study suggests tumor budding score can be used as a prognostic indicator for breast cancer.

Prognostic value of PLEKHA4 and its correlation with tumor-infiltrating immune cells in breast cancer: a comprehensive study based on bioinformatics and clinical analysis validation.

Pleckstrin homology containing family A, number 4 (PLEKHA4) plays a role in a number of biological processes in human cells, including cell polarization, growth, and proliferation. However, the relationship between PLEKHA4 expression and survival in breast cancer (BC) remains unclear. The aim of this study is to investigate the potential of PLEKHA4 as a prognostic indicator in BC. We obtained gene expression profiles of BC and normal tissues from the Tumor Immune Estimation Resource (TIMER), UALCAN web. Immunohistochemistry (IHC) staining was performed to investigate the protein expression and prognostic value of PLEKHA4 in BC patients. The prognostic value was analyzed using Kaplan-Meier curve analysis and Cox regression analysis in R software after downloading The Cancer Genome Atlas (TCGA) databases. The correlations between PLEKHA4 and tumor immune infiltrates were investigated via gene set variation analysis (GSVA). Signaling pathways related to PLEKHA4 expression were identified by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Both bioinformatics and IHC results showed that PLEKHA4 was expressed at low levels in BC tissues compared with the adjacent tissues. Furthermore, the expression of PLEKHA4 was negatively correlated with ages (χ2=6.394, P=0.01), molecular subtype (χ2=15.606, P=0.001), lymph node metastasis (χ2=13.753, P=0.004), tumor-node-metastasis (TNM) stage (χ2=22.616, P<0.001). Kaplan-Meier curves implicated low expression of PLEKHA4 was associated with worse survival of BC patients [hazard ratio (HR) =0.46, P=0.01]. Cox regression models showed that low PLEKHA4 expression could be an independent risk factor for BC (HR =0.911, P=0.006). The results of gene set enrichment analysis (GSEA) showed that cell cycle, Notch signaling pathway, nuclear factor erythroid 2-related factor 2 (NRF2) signaling pathway, and Rho GTPases were highly enriched in the low PLEKHA4 expression group, as identified by GO and KEGG. Additionally, in BC, PLEKHA4 expression displayed a positive correlation with the infiltration of natural killer (NK) cells (P<0.001), CD8+ T cells (P<0.001), B cells (P<0.001), neutrophils (P<0.001), and dendritic cells (DCs) (P<0.001). The findings indicate that PLEKHA4 is an independent prognostic biomarker associated with key signaling pathways and immune infiltration in BC. Targeting PLEKHA4 may contribute to improving immunotherapy for BC.

SEMA7A as a Novel Prognostic Biomarker and Its Correlation with Immune Infiltrates in Breast Cancer.

The role of Semaphorin 7a (SEMA7A) in the initiation and progression of different types of cancerous lesions has been extensively studied. However, the prognostic significance of SEMA7A, specifically in breast cancer (BC), lacks clarity. We conducted an evaluation on the relationship between SEMA7A and the prognosis, immune invasion and tumor mutation burden in different types of cancer by analyzing data from The Cancer Genome Atlas database. The present study focused on investigating the expression level, mutation, immune correlation and coexpression of SEMA7A in BC, utilizing various databases such as the University of Alabama at Birmingham Cancer data analysis portal, cBioPortal and tumor immune estimation resource. Survival analysis was carried out using the Kaplan-Meier Plotter. Furthermore, we employed the R software package to generate receiver operating characteristic (ROC) curves and nomograms. Notably, P<0.05 was considered to indicate statistical significance. Using pancancer analysis, it has been observed that the expression of SEMA7A is elevated in various types of cancer and is strongly correlated with the prognosis of different cancer types. SEMA7A also exhibits a significant association with the tumor mutation burden of diverse types of cancer. Moreover, SEMA7A displays a notable increase in BC cases, and was indicated to have a substantial association with the abundance of immune infiltration. In-depth survival analysis demonstrated that elevated levels of SEMA7A expression are notably linked to shorter overall survival and distant metastasis-free survival among patients with BC. The efficiency of SEMA7A as a reliable prognostic biomarker for BC has been substantiated by the validation of ROC curves and nomograms. SEMA7A has the potential to function as a prognostic indicator for BC, and its correlation with immune infiltration in BC is significant.

Expression of EMT Markers Snail, Slug, and Twist and their Association with Known Prognostic Indicators of Breast Cancer

Expression of EMT Markers Snail, Slug, and Twist and their Association with Known Prognostic Indicators of Breast Cancer

Pan-Cancer Analysis of the Prognostic and Immunological Role of TOMM40 to Identify Its Function in Breast Cancer.

Breast cancer (BRCA) is currently the most commonly diagnosed malignancy in women worldwide. Previous studies have demonstrated that mitophagy is important for the prevention and treatment of BRCA. However, few studies have focused on the individual mitochondrial autophagy-related genes (MARG) in human cancers. Based on bioinformatics analyses, TOMM40 was identified as a prognostic DEMARG (PDEMARGs); Kaplan-Meier (KM) survival analysis also indicates that TOMM40 can be useful as a prognostic indicator in BRCAs, with patients in the high expression group having a poorer prognosis. For 20 distinct cancer kinds, there were appreciable differences in the expression of TOMM40 between tumor and normal tissues; in addition, in 21 different cancer types, there were associations between the expression profile of TOMM40 and patient prognosis. Gene Set Enrichment Analysis (GSEA), functional enrichment analysis, and immunological and drug sensitivity analyses of TOMM40 have indicated its biological significance in pan-cancers. Knockdown of TOMM40 in MDA-MB-231 cells inhibited their proliferation, migration, and invasiveness. In conclusion, we found that TOMM40 has prognostic value in 21 cancers, including breast cancer, by bioinformatics analysis. Based on immune correlation analysis, TOMM40 may also be a potential immunotherapeutic target for the treatment of BRCA. Therefore, our results may provide researchers to further explore the role of MARGs, especially TOMM40, in the developmental process of breast cancer, which may provide new directions and targets for the improvement of prognosis of breast cancer patients and their treatment.

Dual amplification for PEC ultrasensitive aptasensing of biomarker HER-2 based on Z-scheme UiO-66/CdIn2S4 heterojunction and flower-like PtPdCu nanozyme

As an important prognostic indicator in breast cancer, human epithelial growth factor receptor-2 (HER-2) is of importance for assessing prognosis of breast cancer patients, whose accurate and facile analysis are imperative in clinical diagnosis and treatment. Herein, photoactive Z-scheme UiO-66/CdIn2S4 heterojunction was constructed by a hydrothermal method, whose optical property and photoactivity were critically investigated by a range of techniques, combined by elucidating the interfacial charge transfer mechanism. Meanwhile, PtPdCu nanoflowers (NFs) were fabricated by a simple aqueous wet-chemical method, whose peroxidase (POD)-mimicking catalytic activity was scrutinized by representative tetramethylbenzidine (TMB) oxidation in H2O2 system. Taken together, the UiO-66/CdIn2S4 based photoelectrochemical (PEC) aptasensor was established for quantitative analysis of HER-2, where the detection signals were further magnified through catalytic precipitation reaction towards 4-chloro-1-naphthol (4-CN) oxidation (assisted by the PtPdCu NFs nanozyme). The PEC aptasensor presented a broader linear range within 0.1 pg mL−1–0.1 μg mL−1 and a lower limit of detection of 0.07 pg mL−1. This work developed a new PEC aptasensor for ultrasensitive determination of HER-2, holding substantial promise for clinical diagnostics.

A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study.

Axillary lymph nodes (ALN) status serves as a crucial prognostic indicator in breast cancer (BC). The aim of this study was to construct a radiogenomic multimodal model, based on machine learning and whole-transcriptome sequencing (WTS), to accurately evaluate the risk of ALN metastasis (ALNM), drug therapeutic response and avoid unnecessary axillary surgery in BC patients. In this study, conducted a retrospective analysis of 1078 BC patients from The Cancer Genome Atlas (TCGA), The Cancer Imaging Archive (TCIA), and Foshan cohort. These patients were divided into the TCIA cohort ( N =103), TCIA validation cohort ( N =51), Duke cohort ( N =138), Foshan cohort ( N =106), and TCGA cohort ( N =680). Radiological features were extracted from BC radiological images and differentially expressed gene expression was calibrated using technology. A support vector machine model was employed to screen radiological and genetic features, and a multimodal model was established based on radiogenomic and clinical pathological features to predict ALNM. The accuracy of the model predictions was assessed using the area under the curve (AUC) and the clinical benefit was measured using decision curve analysis. Risk stratification analysis of BC patients was performed by gene set enrichment analysis, differential comparison of immune checkpoint gene expression, and drug sensitivity testing. For the prediction of ALNM, rad-score was able to significantly differentiate between ALN- and ALN+ patients in both the Duke and Foshan cohorts ( P <0.05). Similarly, the gene-score was able to significantly differentiate between ALN- and ALN+ patients in the TCGA cohort ( P <0.05). The radiogenomic multimodal nomogram demonstrated satisfactory performance in the TCIA cohort (AUC 0.82, 95% CI: 0.74-0.91) and the TCIA validation cohort (AUC 0.77, 95% CI: 0.63-0.91). In the risk sub-stratification analysis, there were significant differences in gene pathway enrichment between high and low-risk groups ( P <0.05). Additionally, different risk groups may exhibit varying treatment responses ( P <0.05). Overall, the radiogenomic multimodal model employs multimodal data, including radiological images, genetic, and clinicopathological typing. The radiogenomic multimodal nomogram can precisely predict ALNM and drug therapeutic response in BC patients.

Abstract 4278: Role of WNK1 in extracellular matrix modification in breast cancer

Abstract Introduction: Breast cancer (BCa) is the most common cancer and the second leading cause of cancer related deaths in women in the United States. Metastatic dissemination of cancer cells remains the leading cause of mortality in BCa. Therefore, determination of the mechanisms that promote metastasis is important for development of new therapeutic strategies. The extracellular matrix (ECM), which is the main non-cellular component of the tumor microenvironment (TME), plays an important role in BCa progression and metastasis. The cancer-associated fibroblasts (CAFs) are the principal cell types that together with BCa cells drive the modification of ECM during cancer development. Lysine deficient receptor protein kinase 1 (WNK1), a widely expressed serine threonine kinase that regulates blood pressure and electrolyte balance in the body, and is highly overexpressed in BCa microenvironment. The aim of the present study was to investigate the role of WNK1 in modification of ECM in BCa. Methods: The clinical relevance of WNK1 overexpression in BCa was determined by immunohistochemically staining human BCa sections, analyzing data from publicly available databases and creating orthotopic mouse models of BCa using 4T1 mouse BCa cells followed by treatment of the tumor bearing mice with WNK1 inhibitors, WNK-IN-11 and WNK463 (10 mg/kg , oral for 10 days). In vitro assays were conducted using 4T1 cells and mouse embryonic fibroblasts (MEFs) to determine the regulatory role of WNK1 on cancer cells and fibroblasts. Results and Conclusion: Our results indicated that WNK1 is strongly expressed in BCa cells and fibroblasts, the two most abundant cell types in the BCa microenvironment. Furthermore, WNK1 expression strongly correlated with expressions of matrix regulatory and cross-linking genes. Our results demonstrated that WNK1 inhibitors significantly reduced orthotopic 4T1 growth and metastasis. WNK1 inhibition also significantly inhibited collagen deposition in tumor tissues, which is a negative prognostic indicator in BCa. In vitro proliferation and migration assays using 4T1 cells and MEFs identified that WNK1 inhibitors (1-100nM) can significantly inhibit the proliferation and migration of 4T1 cells and MEFs. Results from co-culture studies with 4T1 cells and MEFs further indicated that WNK1 inhibition in MEFs could significantly reduce the invasive properties of 4T1 cells. Taken together, our results suggest that blocking the actions of WNK1 in BCa may be a promising therapeutic approach. Citation Format: Prabhat Suman, Sooraj Kakkat, Suhas S. Patil, Veronica Ramirez, Elba A. Turbat-Herrera, Seema Singh, Chandrani Sarkar, Debanjan Chakroborty. Role of WNK1 in extracellular matrix modification in 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 4278.

The residual cancer burden index as a valid prognostic indicator in breast cancer after neoadjuvant chemotherapy.

The residual cancer burden index (RCB) was proposed as a response evaluation criterion in breast cancer patients treated with Neoadjuvant Chemotherapy (NAC). This study evaluated the relevance of RCB with replase-free survival (RFS). The clinical data of 254 breast cancer patients who received NAC between 2016 and 2020 were retrospectively collected. The relationship between clinicopathologic factors and RFS was evaluated using Cox proportional hazards regression models. RFS estimates were determined by Kaplan-Meier(K-M) analysis and compared using the log-rank test. Multivariate logistic regression analysis was used to evaluate the risk factors associated with RCB.Receiver operating characteristic (ROC) curves showed the potential of the RCB and MP grading systems as biomarkers for RFS. At a median follow-up of 52months, 59 patients(23.23%) developed relapse. Multivariate Cox regression showed that older age (P = 0.022), high Pathologic T stage after NAC (P = 0.023) and a high RCB score(P = 0.003) were risk factors for relapse. The outcomes of the multivariate logistic analysis indicated that RCB 0 (pathologic complete response [pCR]) was associated with HER2-positive patients (P = 0.002) and triple-negative breast cancer (TNBC) patients (P = 0.013).In addition, the RCB and MP scoring systems served as prognostic markers for patients who receivedNAC, and their area under curves (AUCs) were 0.691 and 0.342, respectively. These data suggest that RCB can be equally applied to predict RFS in Chinese patients with NAC. The application of RCB may help guide the selection of treatment strategies.

Correlation between choline kinase alpha expression and 11C-choline accumulation in breast cancer using positron emission tomography/computed tomography: a retrospective study

Choline kinase (CK) is reportedly overexpressed in various malignancies. Among its isoforms, CKα overexpression is presumably related to oncogenic change. Choline positron emission tomography (PET) is reportedly useful for detecting and evaluating therapy outcomes in malignancies. In this study, we investigated the correlation between CKα expression and 11C-choline accumulation in breast cancer cells. We also compared the CKα expression level with other pathological findings for investigating tumour activity. Fifty-six patients with breast cancer (mean age: 51 years) who underwent their first medical examination between May 2007 and December 2008 were enrolled. All the patients underwent 11C-choline PET/computed tomography imaging prior to surgery. The maximum standardised uptake value was recorded for evaluating 11C-choline accumulation. The intensity of CKα expression was classified using immunostaining. A significant correlation was observed between CKα expression and 11C-choline accumulation (P < 0.0001). A comparison of breast cancer mortality demonstrated that strong CKα expression was associated with a shorter survival time (P < 0.0001). 11C-choline accumulation was also negatively correlated with survival time (P < 0.0001). Tumours with strong CKα expression are reportedly highly active in breast cancer. A correlation was observed between CKα expression and 11C-choline accumulation, suggesting their role as prognostic indicators of breast cancer.

BRD4 Inhibition as a Strategy to Prolong the Response to Standard of Care in Estrogen Receptor-Positive Breast Cancer.

Breast cancer is the most commonly occurring malignancy in women and the second most common cause of cancer-related deaths. ER+ breast cancer constitutes approximately 70% of all breast cancer cases. The standard of care for ER+ breast cancer involves estrogen antagonists such as tamoxifen or fulvestrant in combination with CDK4/6 inhibitors such as palbociclib. However, these treatments are often not curative, with disease recurrence and metastasis being responsible for patient mortality. Overexpression of the epigenetic regulator, BRD4, has been shown to be a negative prognostic indicator in breast cancer, and BET family inhibitors such as ARV-825 and ABBV-744 have garnered interest for their potential to improve and prolong the response to current therapeutic strategies. The current work examined the potential of utilizing ARV-825 and ABBV-744 to increase the effectiveness of tamoxifen or fulvestrant plus palbociclib. ARV-825 was effective in both p53 wild-type (WT) breast tumor cells and in cells lacking functional p53 either alone or in combination with tamoxifen, while the effectiveness of ABBV-744 was limited to fulvestrant plus palbociclib in p53 WT cells. These differential effects may be related to the capacity to suppress c-Myc, a downstream target of BRD4.

Influence of Prognostic Nutritional Index on the Surveillance After Surgery-Based Systematic Therapy for Breast Cancer.

Prognostic nutritional index (PNI) is a comprehensive reflection of the nutritional and immune status of the patient, which is closely related to the ability of the organism to clear tumor cells and reduce local recurrence. Several findings suggested that PNI was a prognostic indicator for breast cancer, but the conclusions were conflicting. We aimed to comprehensively elucidate the prognostic value of PNI in breast cancer patients. Relevant studies in PubMed, Embase, Cochrane Library, and Web of Science databases were searched through March 2023. Data extraction and literature quality assessment of the screened studies were performed. The associations between PNI and overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS) in breast cancer patients who received clinical treatment were assessed by hazard ratios (HR) and 95% confidence intervals (CIs). A total of 7 studies involving 2212 patients met the inclusion criteria. High PNI was a favorable independent predictor of prolonged OS and PFS after clinical treatment in breast cancer patients compared to low PNI (for OS: HR = .38, 95% CIs .31 ∼ .46, P < .001; for DFS: HR = .32, 95% CIs .19 ∼ .51, P < .001). In subgroup analysis, high PNI was a prognostic factor for extended DFS in the context of a study sample size ≥300 (HR = .39, 95% CIs .28 ∼ .54, P < .001) and patients not receiving neoadjuvant chemotherapy (HR = .51, 95% CIs .37 ∼ .70, P < .001). The PNI has a significant correlation with the prognosis of breast cancer patients. We suggest that individualized targeted treatment and long-term surveillance should be implemented for patients with different levels of PNI.

Theprognostic indicator in breast cancer treated with CDK4/6 inhibitors: the prognostic nutritional index.

Aims: The aim of this study was to evaluate the effect of prognostic nutritional index (PNI) on prognosis in patients with hormone receptor-positive, HER2-negative metastatic breast cancer who received CDK4/6 inhibitor+endocrine therapy. Methods: Patients receiving a CDK4/6 inhibitor were evaluated retrospectively. The PNI was calculated as: (10×serum albumin [g/dl]) + (total lymphocyte count [×109/l] ×5). Results: In a study of 106 patients, a statistically significant survival advantage was observed in the high-PNI group over the low-PNI group (mean overall survival: 28.03±0.487months vs 22.46±1.14months; p=0.013). Conclusion: For the first time in the literature, this study demonstrated the prognostic role of PNI in patients with hormone receptor-positive, HER2-negative metastatic breast cancer treated with CDK4/6 inhibitors.

Systemic Inflammatory Response as a Prognostic Factor in Breast Cancer. Part I. Tumor-Promoting Inflammation. Serum Inflammatory Markers

Chronic inflammation caused by exposure to external or internal factors increases the risk of developing malignancies and promotes tumor progression due to the influence on the key elements of carcinogenic mechanisms. At the system level signs of a chronic inflammation are manifested by an increase of inflammatory mediators and acute phase proteins levels in the blood, a change in the ratio of circulating leukocyte populations, and disturbances in the hemostasis system. This review is devoted to serum and hematological parameters of the systemic inflammatory response (SIR) in breast cancer (BC). The first part of the review outlines general concept about the role of inflammatory factors in the development of malignant tumors. It provides information on the most well studied serum inflammatory markers in breast cancer: cytokines, including interleukin-6 (IL-6), interleukin-8 (IL-8), tumor necrosis factor-alpha (TNF-), as well as C-reactive protein (CRP). The main properties of these polypeptides, which link them with tumor-promoting inflammation, are considered. An analysis of the data on the clinical significance of the serum level of cytokines and CRP in breast cancer accumulated to date is presented. Correlations of the elevated levels of the serum inflammatory markers with clinical and morphological characteristics of the disease, tumor response to chemotherapy, overall and relapse-free survival of patients indicate the feasibility of in-depth investigation of the issue for the purpose of the practical application of the systemic inflammatory markers as predictive and prognostic indicators in BC.

Internal mammary lymph nodal response to neoadjuvant chemotherapy on imaging and breast cancer prognosis.

Pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) is an important prognostic indicator in breast cancer. Internal mammary lymph node involvement is not currently included in pCR determination, as sampling at the time of surgery is not routinely performed. Pre and post neoadjuvant chemotherapy MRI or PET/CT imaging response of the internal mammary lymph node chain was utilized as a surrogate to pCR and imaging data was correlated with patient outcomes. Internal mammary lymph node response to NAC was associated with disease free survival over the course of this study, regardless of whether axillary nodal pCR was achieved. Internal mammary lymph nodal response to NAC is an important prognostic indicator. Potential use of internal mammary lymph node resolution as an imaging data input for AI models that predict pCR post-NAC may improve accuracy and other metrics in pCR prediction.

The prognostic role of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy: A dose-response meta-analysis.

As neoadjuvant chemotherapy is widely used in breast cancer patients, the lymph node ratio has not been fully validated as a prognostic indicator of breast cancer received neoadjuvant chemotherapy. This study was conducted to investigate the prognostic value of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy. Systematic searches were performed in the PubMed, Embase, and Cochrane Library databases until 15 December 2021 for studies on the association between lymph node ratio and the prognosis of breast cancer after neoadjuvant chemotherapy. Overall survival and disease-free survival were used as outcome events, and hazard ratio was chosen as the parameter to evaluate the correlation. The dose-response relationship was assessed by restricted cubic splines. In the subgroup analyses, which were used to explore potential heterogeneity among the included studies according to study region and sample size. Sensitivity analysis was performed to assess the stability of individual studies, and publication bias was determined with funnel plots, Begg's test, and Egger&apos;s test. All statistical analyses were performed using Stata 15.1. A total of 12 studies with 4,864 patients were included in this meta-analysis. In this study, high lymph node ratio was significantly associated with decreased overall survival (HR: 4.74; 95%CI: 3.36-6.67; P < 0.001) and disease-free survival (HR: 4.77; 95%CI: 3.69-6.17; P < 0.001). Moreover, the dose-response meta-analysis showed a linear association between higher lymph node ratio and shorter overall survival and disease-free survival in breast cancer patients after neoadjuvant chemotherapy. The meta-analysis suggested that high lymph node ratio was significantly associated with short overall survival and disease-free survival in breast cancer patients after neoadjuvant chemotherapy. Therefore, lymph node ratio is an independent predictive factor for the prognosis of breast cancer patients after neoadjuvant chemotherapy, which may better refine the cancer staging system.

Expert consensus on the clinical diagnosis and targeted therapy of HER2 breast cancer (2023 edition).

Human epidermal growth factor receptor 2 (HER2) is an important driver gene and prognostic indicator of breast cancer and also a key predictor of HER2-targeted therapies. The emerging anti-HER2 drugs have greatly changed the diagnosis and treatment modalities of breast cancer and dramatically improved the prognosis of HER2-positive breast cancer patients. To optimize the treatment of HER2 breast cancer an update of expert consensus on HER2 positive breast cancer was made to adjust the different recommendation levels from early stage to metastatic stage. Meanwhile, antibody-drug conjugate (ADC) like trastuzumab deruxtecan (T-Dxd) has been shown to have great efficacy in HER2-positive and HER2 low expression breast cancer patients. Clinically, on the basis of the original definition for HER2-negative breast cancer, patients with HER2 immunohistochemistry (IHC) 1+ or IHC 2+ and in-situ hybridization (ISH)-negative are defined as low HER2 expression (HER2-low). As both the low expression and the positive expression of the HER2 protein is clinically significant for disease treatment and prognosis, we added a new chapter of HER2 low to recommend a proper regimen for this kind of patients. In this consensus, we also talk about the importance of clinical research, real world evidence, biosimilars and so on. In addition, the whole-course management of HER2 breast cancer is even more critical during pandemic of coronavirus disease 2019 (COVID-19). An approach that gives preference to "low-toxicity regimens and oral preparations" are also recommended.

Tumor Microenvironment Characterization in Breast Cancer and an Immune Cell Infiltration Score Development, Validation, and Application

The tumor microenvironment (TME) refers to the cellular environment in which tumors exist. An increasing number of reports have emphasized its role in tumor progression, prognosis, relapse, metastasis, and therapeutic response with breast cancer (BRCA). Few studies have revealed a systematic landscape of immune cell infiltration (ICI) in BRCA. In this study, we comprehensively analyzed the immune cells infiltrating TME in BRCA. Three ICI patterns were identified through an unsupervised clustering method and an ICI score was developed by a principal component analysis (PCA). A Kaplan-Meier survival with log-rank test revealed a significant overall survival (OS) difference of BRCA patients with these three ICI patterns. We also found that a high ICI score was characterized by an elevated tumor mutation burden (TMB), effector T-cell infiltration, INF-γ-related cytotoxicity, and cytolytic activity score. An independent cohort validated that this ICI score could be a prognostic indicator for BRCA. Two immunotherapeutic cohorts and two chemotherapeutic cohorts confirmed that patients with higher ICI scores showed significant chemotherapeutic and immunotherapeutic advantages. In summary, these results suggest that the ICI patterns could act as a prognostic indicator and that the ICI score could precisely predict the clinical outcome for BRCA patients.

Development of a Novel Immune-Related Gene Prognostic Index for Breast Cancer.

ObjectiveTo construct an immune-related gene prognostic index (IRGPI) for breast cancer (BC) and investigate its prognostic specificity and the molecular and immune characteristics.MethodsBC hub genes were identified from The Cancer Genome Atlas and immune-related databases using weighted gene co-expression network analysis (WGCNA). IRGPI was constructed using univariate, LASSO, and multivariate regression analyses, and was validated with GSE58812 and GSE97342 in the Gene Expression Omnibus database (GEO). At the same time, we evaluated the predictive ability of IRGPI for different BC subtypes. Subsequently, the molecular and immune characteristics, clinical relevance, and benefits of immune checkpoint inhibitor treatment were analyzed for different IRGPI subgroups.ResultsIRGPI consisted of six genes: SOCS3, TCF7L2, TSLP NPR3, ANO6, and HMGB3. The IRGPI 1-, 5-, and 10-years area under curve (AUC) values were 0.635, 0.752, and 0.753, respectively, indicating that IRGPI has good potential in predicting the long-term survival of BC patients, consistent with the results in the GEO cohort. IRGPI showed good predictive power in four different breast cancer subtypes: ER positive, PR positive, HER2 positive and triple-negative (P<0.01). Compared with the low-IRGPI group, the high-IRGPI group had a worse prognosis and a lower degree of immune infiltrating cells (p < 0.05). IRGPI showed specificity in distinguishing age, TNM stage, ER, and HER2 statuses, and our study found that the high-IRGPI group had low tumor immune dysfunction and exclusion (TIDE), microsatellite instability (MSI), and T cell dysfunction scores (p < 0.05). In addition, compared with the TIDE and TIS models, showed that the AUCs of IRGPI were better during the 5-year follow-up.ConclusionIRGPI can be used as an independent prognostic indicator of breast cancer, providing a method for monitoring the long-term treatment of BC.

Breast Cancer Patients With Positive Apical or Infraclavicular/Ipsilateral Supraclavicular Lymph Nodes Should Be Excluded in the Application of the Lymph Node Ratio System.

Aim: Increasing studies have demonstrated lymph node ratio (LNR) to be an accurate prognostic indicator in breast cancer and an alternative to pN staging; however, the AJCC-TNM staging system classified apical or infraclavicular/ipsilateral supraclavicular lymph node-positive (APN(+)) patients with a worse prognosis as the pN3 stage. Until now, different reports on LNR in breast cancer have ignored this possibility. Consequently, it is necessary to discuss the role of APN(+) patients in the LNR system to obtain a precise LNR that predicts the prognosis accurately. Materials and Methods: We collected data on 10,120 breast cancer patients, including 3,936 lymph node-positive patients (3,283 APN(−) and 653 APN(+) patients), who visited our hospital from 2007 to 2012. Then we applied X-tile analysis to calculate cut-off values and conduct survival analysis and multivariate analysis to evaluate patients’ prognosis. Results: We confirmed that some APN(+) patients were mis-subgrouped according to previously reported LNR, indicating that APN(+) patients should be excluded in the application of LNR to predict prognosis. Then we applied X-tile analysis to calculate two cut-off values (0.15 and 0.34) for LNR-APN(−) patients and conducted survival analysis and found that LNR-APN(−) staging was superior to pN staging in predicting the prognosis of APN(−) breast cancer patients. Conclusion: From this study, we conclude that excluding APN(+) patients is the most necessary condition for effective implementation of the LNR system. LNR-APN(−) staging could be a more comprehensive approach in predicting prognosis and guiding clinicians to provide accurate and appropriate treatment.