Impact of BSA and Au3+ concentration on the formation and fluorescence properties of Au nanoclusters.

Bovine serum albumin-stabilized Au nanoclusters (BSA-Au NCs) have emerged as promising contenders for imaging agents and highly sensitive fluorescence sensors due to their biocompatibility and strong photoluminescence. Optimizing the synthesis conditions of BSA-Au NCs is crucial for enhancing fluorescence imaging and other nanocluster applications. In this study, for the first time, we systematically investigated the effects of BSA concentration and Au3+ on both particle size and optical characteristics of BSA-Au NCs. When the two components achieved a suitable concentration ratio, it was beneficial to form BSA-Au NCs with a high quantum yield (QY = 74.30%) and good fluorescence stability. In contrast, an inappropriate concentration ratio would lead to the formation of gold nanoparticles (Au NPs), and their internal filtration effect (IFE) would attenuate the fluorescence emission of BSA-Au NCs. The BSA-Au NCs were then employed as efficient fluorescence sensors for detecting Hg2+. Furthermore, the growth mechanism of BSA-Au NCs was elucidated by monitoring fluorescence changes during different incubation times. The BSA-Au NCs with a high quantum yield introduce a novel synthetic concept for sensitive fluorescent probes and expanding versatile applications of BSA-Au NCs in catalysis, chemical sensing and biomedicine.

Characterization of starvation response-related genes for predicting prognosis in breast cancer.

Breast cancer (BRCA) cells typically exist in nutrient-deficient microenvironments and quickly adapt to states with fluctuating nutrient levels. The tumor microenvironment of starvation is intensely related to metabolism and the malignant progression of BRCA. However, the potential molecular mechanism has not been thoroughly scrutinized. As a result, this study aimed to dissect the prognostic implications of mRNAs involved in the starvation response and construct a signature for forecasting the outcomes of BRCA. In this research, we investigated how starvation could affect BRCA cells' propensities for invasion and migration. The effects of autophagy and glucose metabolism mediated by starved stimulation were examined through transwell assays, western blot, and the detection of glucose concentration. A starvation response-related gene (SRRG) signature was ultimately generated by integrated analysis. The risk score was recognized as an independent risk indicator. The nomogram and calibration curves revealed that the model had excellent prediction accuracy. Functional enrichment analysis indicated this signature was significantly enriched in metabolic-related pathways and energy stress-related biological processes. Furthermore, phosphorylated protein expression of the model core gene EIF2AK3 increased after the stimulus of starvation, and EIF2AK3 may play an essential role in the progression of BRCA in the starved microenvironment. To sum up, we constructed and validated a novel SRRG signature that could accurately predict outcomes and may be developed as a therapeutic target for the precise treatment of BRCA.

A mitochondrial function-related LncRNA signature predicts prognosis and immune microenvironment for breast cancer.

Mitochondrial function, as the core of the cell's energy metabolism, is firmly connected to cancer metabolism and growth. However, the involvement of long noncoding RNAs (lncRNAs) related to mitochondrial function in breast cancer (BRCA) has not been thoroughly investigated. As a result, the objective of this research was to dissect the prognostic implication of mitochondrial function-related lncRNAs and their link to the immunological microenvironment in BRCA. The Cancer Genome Atlas (TCGA) database was used to acquire clinicopathological and transcriptome information for BRCA samples. Mitochondrial function-related lncRNAs were recognized by coexpression analysis of 944 mitochondrial function-related mRNAs obtained from the MitoMiner 4.0 database. A novel prognostic signature was built in the training cohort using integrated analysis of mitochondrial function-related lncRNA and the corresponding clinical information through univariate analysis, lasso regression, and stepwise multivariate Cox regression analysis. The prognostic worth was judged in the training cohort and validated in the test cohort. In addition, functional enrichment and immune microenvironment analyses were performed to explore the risk score on the basis of the prognostic signature. An 8-mitochondrial function-related lncRNA signature was generated by integrated analysis. Individuals within the higher-risk category had a worse overall survival rate (OS) (training cohort: P < 0.001; validation cohort: P < 0.001; whole cohort: P < 0.001). The risk score was identified as an independent risk factor by multivariate Cox regression analysis (training cohort: HR 1.441, 95% CI 1.229-1.689, P < 0.001; validation cohort: HR 1.343, 95% CI 1.166-1.548, P < 0.001; whole cohort: HR 1.241, 95% CI 1.156-1.333, P < 0.001). Following that, the predictive accuracy of the model was confirmed by the ROC curves. In addition, nomograms were generated, and the calibration curves revealed that the model had excellent prediction accuracy for 3- and 5-year OS. Besides, the higher-risk BRCA individuals have relatively decreased amounts of infiltration of tumor-killing immune cells, lower levels of immune checkpoint molecules, and immune function. We constructed and verified a novel mitochondrial function-related lncRNA signature that might accurately predict the outcome of BRCA, play an essential role in immunotherapy, and might be exploited as a therapeutic target for precise BRCA therapy.

The impact of postmastectomy radiotherapy on cT1-2N1 breast cancer patients with ypN0 after neoadjuvant chemotherapy: a retrospective study based on real-world data.

BACKGROUND: The role of postmastectomy radiation therapy (PMRT) in clinical T1-2N1 breast cancer patients who achieve axillary pathological complete response (ypN0) after neoadjuvant chemotherapy (NAC) is controversial. METHODS: Data from cT1-2N1 breast cancer patients who converted to ypN0 after NAC and subsequent surgery were retrospectively analyzed. Disease-free survival (DFS) and overall survival (OS) were estimated using the Kaplan‒Meier method. Univariate and multivariate Cox regression models were applied to investigate the correlations between clinical or pathological parameters and survival. RESULTS: From 2012-2019, we identified 116 cases for analysis, including 31 (26.7%) who received PMRT and 85 (73.3%) who did not. At a median follow-up time of 56.4 months, the 5-year DFS and OS rates were 90.2% and 96.7% with PMRT and 93.7% and 97.3% without PMRT, respectively. PMRT did not affect either DFS (p = 0.234) or OS (p = 0.878). On multivariate analyses, no differences in DFS or OS between the two groups were detected, taking into consideration the following factors: age, molecular subtype, Ki67 index, cT stage, and in-breast pathologic complete response (DFS: HR 2.260; 95% CI 0.465-10.982; p = 0.312. OS: HR 1.400; 95% CI 0.138-14.202; p = 0.776). This nonsignificant difference was also consistent in subgroup analyses (all p > 0.05). CONCLUSIONS: PMRT has limited ability to confer DFS or OS benefits for cT1-2N1 breast cancer patients who achieved axillary pathological complete response after NAC and total mastectomy. It is imperative to conduct prospective studies to investigate the safety and feasibility of omitting PMRT. TRIAL REGISTRATION: This research was approved by the Ethics Committee of The First Affiliated Hospital of Chongqing Medical University (ID: No. 2021-442).

A dual-targeting near-infrared biomimetic drug delivery system for HBV treatment.

Hepatitis B virus (HBV) infection is a serious global public health threat. It remains elusive to achieve a functional HBV cure with currently available antivirals. Herein, a photo-responsive delivery vehicle composed of Nd3+ -sensitized core-shell upconversion nanoparticle (UCNP), mesoporous silica nanoparticle (MSN), antisense oligonucleotides (ASOs), and capsid-binding inhibitor C39 was established, which was named UMAC according to the initials of its components. Subsequently, the as-synthesized delivery vehicle was encapsulated by ß- D-galactopyranoside (Gal) modified red blood cell (RBC) membrane vesicles, which enabled precise targeting of the liver cells (UMAC-M-Gal). Both in vitro and in vivo experiments demonstrated that this biomimetic system could successfully achieve controlled drug release under light conditions at 808 nm, leading to effective suppression of HBV replication in this dual-targeted therapeutic approach. Together, these results substantiate the system has huge prospects for application to achieve functional HBV cure, and provides a promising novel strategy for drug delivery.

Organoids from patient biopsy samples can predict the response of BC patients to neoadjuvant chemotherapy.

PROPOSE: Neoadjuvant chemotherapy has been widely used in locally advanced and inflammatory breast cancer. Generally, complete pathological response after neoadjuvant chemotherapy treatment predicts survival. Studies have shown that patient-derived organoids can be used in cancer research and drug development. Therefore, we aimed to generate a living organoid biobank from biopsy samples to predict the response of patients to neoadjuvant chemotherapy. METHOD: We generated a living organoid biobank from locally advanced breast cancer patients receiving neoadjuvant chemotherapy. When the patient received neoadjuvant chemotherapy, the organoids were treated with similar drugs, thereby simulating the situation of the patient receiving treatment. RESULT: We successfully constructed organoids from breast cancer biopsies, demonstrating that organoids can be generated from a small sample of tissue. The phenotype of breast cancer organoid often agreed with the original breast cancer according to the blinded histopathological analysis of H&E stain tissue and organoid sections. In addition, our data confirm that the patient's response to chemotherapy closely matches the organoids' response to drugs. CONCLUSION: Our data indicate that patient-derived organoids can be used to predict the clinical response of breast cancer patients to neoadjuvant chemotherapy in vitro and to screen drugs that have different effects on different patients. Key messageComplete pathological response (pCR) after adjuvant chemotherapy can predict, survival, therefore, predicting patient response to neoadjuvant chemotherapy is critical.Patient-derived organoids (PDOs) matched the original tumour in terms of histopathology, hormone receptor levels and HER2 receptor status.Patient-derived organoids can predict the responsiveness of patient to neoadjuvant chemotherapy.

MED16 Promotes Tumour Progression and Tamoxifen Sensitivity by Modulating Autophagy through the mTOR Signalling Pathway in ER-Positive Breast Cancer.

Recent studies have shown that the mediator complex (MED) plays a vital role in tumorigenesis and development, but the role of MED16 (mediator complex subunit 16) in breast cancer (BC) is not clear. Increasing evidence has shown that the mTOR pathway is important for tumour progression and therapy. In this study, we demonstrated that the mTOR signalling pathway is regulated by the expression level of MED16 in ER+ breast cancer. With the analysis of bioinformatics data and clinical specimens, we revealed an elevated expression of MED16 in luminal subtype tumours. We found that MED16 knockdown significantly inhibited cell proliferation and promoted G1 phase cell cycle arrest in ER+ BC cell lines. Downregulation of MED16 markedly reduced the sensitivity of ER+ BC cells to tamoxifen and increased the stemness and autophagy of ER+ BC cells. Bioinformatic analysis of similar genes to MED16 were mainly enriched in autophagy, endocrine therapy and mTOR signalling pathways, and the inhibition of mTOR-mediated autophagy restored sensitivity to tamoxifen by MED16 downregulation in ER+ BC cells. These results suggest an important role of MED16 in the regulation of tamoxifen sensitivity in ER+ BC cells, crosstalk between the mTOR signalling pathway-induced autophagy, and together, with the exploration of tamoxifen resistance, may indicate a new therapy option for endocrine therapy-resistant patients.

Association of serum reproductive hormones changes after neoadjuvant chemotherapy with hormone receptors expression alterations and survival outcomes in breast cancer.

Purpose: This study aimed to determine the effect of neoadjuvant chemotherapy (NAC) on circulating levels of reproductive hormones and evaluate the correlation of hormone changes after NAC with hormone receptors expression alterations and relapse-free survival (RFS) outcomes in breast cancer. Methods: Information from 181 breast cancer patients who received NAC was retrospectively analyzed. For hormones parameters, the median and interquartile range (IQR) were provided at baseline and the end of NAC then was compared by Wilcoxon signed-rank test. Categorical variables were represented as numbers and percentages and were compared via two-sided chi-square and Fisher's tests. The RFS outcomes were compared between patients according to hormone changes using the log-rank test. Univariate and multivariate survival analyses with hazard ratios (HR) and 95% confidence intervals (95% CI) were carried out using Cox regression. Results: Sex steroids including estradiol, progesterone, testosterone, and dehydroepiandrosterone sulfate (DHEAS) levels decreased significantly after NAC among both premenopausal and postmenopausal patients (all P < 0.05). Decreased estradiol levels were associated with reduced progesterone receptor (PR) expression (P = 0.030). In multivariate survival analysis, the non-decreased progesterone level was strongly associated with worse RFS (non-decreased vs. decreased, HR = 7.178, 95% CI 2.340-22.019, P = 0.001). Patients with decreased progesterone levels exhibited better 3-year RFS compared with those with non-decreased (87.6% vs. 58.3%, log-rank, P = 0.001). Conclusion: Multiple reproductive hormone levels were influenced by NAC. The change in estradiol level had a positive connection with PR expression alteration. Furthermore, an inverse association between the change in progesterone level and RFS outcomes was found. These findings may provide a theoretical basis for pre-operative endocrine therapy combined with NAC in breast cancer patients.

Cuprotosis-Related Genes: Predicting Prognosis and Immunotherapy Sensitivity in Pancreatic Cancer Patients.

Based on TCGA, GTEx, and TIMER databases and various bioinformatics analysis methods, the potential biological roles of cuprotosis-related genes in pancreatic cancer were deeply explored, and a predictive model for pancreatic cancer patients was constructed. We downloaded the RNA-Seq data and clinicopathological and predictive data of 179 pancreatic cancer tissues and 332 adjacent normal tissues from TCGA and GTEx databases. The differential expression of cuprotosis-related genes in pancreatic cancer tissue and adjacent normal tissue was analyzed, and the LASSO regression algorithm was used to construct a prediction model and verify the validity of the model prediction. Based on the LASSO regression algorithm, a predictive model composed of three genes LIPT1, LIAS, and DLAT was screened. The corresponding survival curves showed that the constructed prediction model could significantly distinguish the prognosis of pancreatic cancer patients, and the prognosis of patients in the high-risk group was worse (P = 0.00557). The ROC curve showed that the area under the curve of the predictive model for predicting the 4-, 5-, and 6-year survival rates in pancreatic cancer was 0.816, 0.836, and 0.956, respectively. The AUC value of this risk model was significantly higher than 0.7, which could more accurately predict the prognosis of pancreatic cancer patients. This study determined a risk-scoring model of cuprotosis-related genes, which can provide an essential basis for judging the prognosis of pancreatic cancer patients.

Study of the Antimicrobial Activity of the Chinese Dong Ethnic Minority Medicine, Madeng'ai.

The overuse of antibiotics has contributed to the emergence of multidrug-resistant bacteria, which poses a challenging task for clinical therapy. Thus, new agents with antibiotic efficacy against multidrug-resistant infections are needed. The traditional Dong ethnic minority medicines have emerged as a new source for prodrug selection. Among them, Madeng'ai (PotentillafreynianaBornm) is widely used by the folk for anti-infection and wound healing, although the mechanisms remain unclear. In this study, the antimicrobial activities of Dong medicine Madeng'ai were evaluated both in vitro and in vivo. S. aureus, E. coli, E. faecalis, P. aeruginosa, K. pneumoniae, and A. baumannii were cultured in LB media, different concentrations of Madeng'ai powder solution were added to the LB agar plates to evaluate minimal inhibitory concentration. An animal study was performed on a mouse excisional wound model combined with bacterial solution injection in the wound area. After Madeng'ai or PBS treatment, hematoxylin and eosin analysis were used for pathological analysis of skin tissues from the infected area. Madeng'ai powder solution over 2 mg/mL concentration completely inhibited E. coli growth. At 4.0 mg/mL, Madeng'ai significantly inhibited the growth of E. faecalis, Pseudomonas aeruginosa (PAE), Klebsiella pneumoniae, and Acinetobacter baumannii. The mouse model revealed that Madeng'ai could suppress the growth of MRSA and PAE and accelerate healing of cutaneous wounds. Madeng'ai, a newly discovered Dong ethnic minority medicine possesses considerable antimicrobial activity against both human normal pathogenic bacteria and multiresistance bacteria such as Pseudomonas aeruginosa, S. aureus, and Acinetobacter baumannii. Therefore, Madeng'ai has great potential for further study and clinical application.

Development and Validation of a Novel PPAR Signaling Pathway-Related Predictive Model to Predict Prognosis in Breast Cancer.

This study is aimed at exploring the potential mechanism of the PPAR signaling pathway in breast cancer (BRCA) and constructing a novel prognostic-related risk model. We used various bioinformatics methods and databases to complete our exploration in this research. Based on TCGA database, we use multiple extension packages based on the R language for data conversion, processing, and statistics. We use LASSO regression analysis to establish a prognostic-related risk model in BRCA. And we combined the data of multiple online websites, including GEPIA, ImmuCellAI, TIMER, GDSC, and the Human Protein Atlas database to conduct a more in-depth exploration of the risk model. Based on the mRNA data in TCGA database, we conducted a preliminary screening of genes related to the PPAR signaling pathway through univariate Cox analysis, then used LASSO regression analysis to conduct a second screening, and successfully established a risk model consisting of ten genes in BRCA. The results of ROC curve analysis show that the risk model has good prediction accuracy. We can successfully divide breast cancer patients into high- and low-risk groups with significant prognostic differences (P = 1.92e - 05) based on this risk model. Combined with the clinical data in TCGA database, there is a correlation between the risk model and the patient's N, T, gender, and fustat. The results of multivariate Cox regression show that the risk score of this risk model can be used as an independent risk factor for BRCA patients. In particular, we draw a nomogram that can predict the 5-, 7-, and 10-year survival rates of BRCA patients. Subsequently, we conducted a series of pancancer analyses of CNV, SNV, OS, methylation, and immune infiltration for this risk model gene and used GDSC data to investigate drug sensitivity. Finally, to gain insight into the predictive value and protein expression of these risk model genes in breast cancer, we used GEO and HPA databases for validation. This study provides valuable clues for future research on the PPAR signaling pathway in BRCA.

Fabrication of avidin-stabilized gold nanoclusters with dual emissions and their application in biosensing.

Protein-stabilized gold nanoclusters (Prot-Au NCs) have been widely used in biosensing and cell imaging owing to their excellent optical properties and low biotoxicity. However, several Prot-Au NCs reported in the literature do not retain the biological role of the protein, which greatly limits their ability to directly detect biomarkers. This study demonstrated for the first time the successful synthesis of dual-function avidin-stabilized gold nanoclusters (Av-Au NCs) using a one-pot method. The resulting Av-Au NCs exhibited intense blue and red emissions under 374 nm excitation. Furthermore, the Av-Au NCs retained the native functionality of avidin to bind to biotin. When DNA strands modified with biotin at both ends (i.e., linker chains) were mixed with Av-Au NCs, large polymers were formed, indicating that Av-Au NCs could achieve fluorescence signal amplification by interacting with biotin. Taking advantage of the aforementioned properties, we constructed a novel enzyme-free fluorescent biosensor based on the Av-Au NCs-biotin system to detect DNA. The designed fluorescent biosensor could detect target DNA down to 0.043 nM, with a wide line range from 0.2 nM to 20 µM. Thus, these dual-functional Av-Au NCs were shown to be an excellent fluorescent material for biosensing.

Pre-treatment circulating reproductive hormones levels predict pathological and survival outcomes in breast cancer submitted to neoadjuvant chemotherapy.

PURPOSE: This study aimed to evaluate the correlation of pre-treatment circulating reproductive hormones levels with pathological and survival outcomes in breast cancer patients received neoadjuvant chemotherapy (NAC). METHODS: Information from 196 premenopausal and 137 postmenopausal breast cancer patients who received NAC were retrospectively analyzed. Treatment response to NAC, with odds ratios (OR) and 95% confidence intervals (95% CI) was estimated using logistic regression adjusted for key confounders. Survival outcomes with hazard ratios (HR) and 95% CI were estimated using Cox regression adjusted for key confounders. The Kaplan-Meier method was applied in the survival analysis. RESULTS: Premenopausal patients with lower testosterone levels (OR = 0.996, 95% CI 0.992-0.999, P = 0.026), and postmenopausal patients with higher follicle-stimulating hormone (FSH) levels (OR = 1.045, 95% CI 1.014-1.077, P = 0.005) were likely to achieve pathological complete response (pCR). In multivariate survival analysis, the lowest tertile (T) progesterone was associated with worse overall survival (OS) in premenopausal patients (T2 vs T1, HR = 0.113, 95% CI 0.013-0.953, P = 0.045; T3 vs T1, HR = 0.109, 95% CI 0.013-0.916, P = 0.041). Premenopausal patients with the lowest tertile progesterone exhibited worse 3-year OS compared with those with higher tertiles (72.9% vs 97.4%, log-rank, P = 0.007). CONCLUSION: Pre-treatment testosterone and FSH are significant independent predictors for pCR to NAC in premenopausal and postmenopausal patients, respectively. Low progesterone levels are correlated with worse OS in premenopausal patients. These findings may provide a theoretical basis for pre-operative endocrine therapy combined with NAC in breast cancer.

A novel pyroptosis-related signature predicts prognosis and response to treatment in breast carcinoma.

BACKGROUND: Pyroptosis is a new form of programmed cell death (PCD), also known as cellular inflammatory necrosis. Its discovery has resulted in a novel approach to the progression and medication resistance of breast cancer (BC). However, there is still a significant gap in the investigation of pyroptosis-related genes in BC. METHODS: The mRNA expression profiles and clinical data of BC patients were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Then, using the TCGA cohort, we created a predictive multigene signature including pyroptosis-related genes and verified it using the two GEO cohorts. A pyroptosis-related gene signature was created by combining several bioinformatics and statistical methodologies to predict patient prognosis and responses to immunotherapy and chemotherapy. Furthermore, a nomogram based on the gene signature and clinicopathological markers was created to better classify the risk and quantify the risk assessment of individual patients. RESULTS: A pyroptosis-related gene signature consisting of 15 genes was established. The pyroptosis-related gene signature classified the patients into two groups: high-risk and low-risk. When combined with clinical variables, the risk score was discovered to be an independent predictor of overall survival (OS) in BC patients. Some immunological pathways and genes were linked to pyroptosis, according to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) evaluations. Patients in the high-risk group had a worse prognosis and were not very sensitive to immunotherapy. However, several chemotherapeutic agents were predicted to have greater potential for patients in the high-risk group. Finally, a nomogram was developed that included a classifier based on the 15 pyroptosis-related genes, tumor stage, age, and histologic grade. This nomogram demonstrated good classification capacity and might help with clinical decision-making in BC.

Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer.

Breast cancer (BC) is a lethal malignancy with a poor prognosis. Necroptosis is critical in the progression of cancer. However, the expression of genes involved in necroptosis in BC and their association with prognosis remain unclear. We investigated the predictive potential of necroptosis-related genes in BC samples from the TCGA dataset. We used LASSO regression to build a risk model consisting of twelve necroptosis-related genes in BC. Using the necroptosis-related risk model, we were able to successfully classify BC patients into high- and low-risk groups with significant prognostic differences (p = 4.872 × 10 -7). Additionally, we developed a matched nomogram predicting 5, 7, and 10-year overall survival in BC patients based on this necroptosis-related risk model. Our next step was to perform multiple GSEA analyses to explore the biological pathways through which these necroptosis-related risk genes influence cancer progression. For these twelve risk model genes, we analyzed CNV, SNV, OS, methylation, immune cell infiltration, and drug sensitivity in pan-cancer. In addition, immunohistochemical data from the THPA database were used to validate the protein expression of these risk model genes in BC. Taken together, we believe that necroptosis-related genes are considered potential therapeutic targets in BC and should be further investigated.

A ferroptosis-associated gene signature for the prediction of prognosis and therapeutic response in luminal-type breast carcinoma.

Ferroptosis is a new form of regulated cell death (RCD), and its emergence has provided a new approach to the progression and drug resistance of breast cancer (BRCA). However, there is still a great gap in the study of ferroptosis-related genes in BRCA, especially luminal-type BRCA patients. We downloaded the mRNA expression profiles and corresponding clinical data of BRCA patients from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas (TCGA) databases. Then, we built a prognostic multigene signature with ferroptosis-related differentially expressed genes (DEGs) in the METABRIC cohort and validated it in the TCGA cohort. The predictive value of this signature was investigated in terms of the immune microenvironment and the probability of a response to immunotherapy and chemotherapy. The patients were divided into a high-risk group and a low-risk group according to the ferroptosis-associated gene signature, and the high-risk group had a worse overall survival (OS). The risk score based on the 10 ferroptosis-related gene-based signature was determined to be an independent prognostic predictor in both the METABRIC and TCGA cohorts (HR, 1.41, 95% CI, 1.14-1.76, P = 0.002; HR, 2.19, 95% CI, 1.13-4.26, P = 0.02). Gene set enrichment analysis indicated that the term "cytokine-cytokine receptor interaction" was enriched in the high-risk score subgroup. Moreover, the immune infiltration scores of most immune cells were significantly different between the two groups, the low-risk group was much more sensitive to immunotherapy, and six drugs might have potential therapeutic implications in the high-risk group. Finally, a nomogram incorporating a classifier based on the 10 ferroptosis-related genes, tumor stage, age and histologic grade was established. This nomogram showed favorable discriminative ability and could help guide clinical decision-making for luminal-type breast carcinoma.

Ki67 Index Changes and Tumor-Infiltrating Lymphocyte Levels Impact the Prognosis of Triple-Negative Breast Cancer Patients With Residual Disease After Neoadjuvant Chemotherapy.

PURPOSE: The aim of this study was to assess the prognostic influence of Ki67 index changes in patients with primary triple-negative breast cancer (TNBC) treated with neoadjuvant chemotherapy (NAC), and to evaluate whether the combination of Ki67 index changes and residual disease (RD) tumor-infiltrating lymphocytes (TILs) provides additional prognostic information for this group. MATERIALS AND METHODS: Data from 109 patients with primary TNBC and RD after NAC were analyzed retrospectively. Ki67 changes and RD TIL levels were investigated for associations with recurrence-free survival (RFS) and overall survival (OS) using Kaplan-Meier and Cox analyses. RESULTS: Ki67 index decreased after NAC in 53 patients (48.6%) and high RD TIL levels (≥30%) were observed in 54 patients (49.5%). In multivariate Cox analyses, no Ki67 decrease status and low RD TIL levels were significantly associated with reduced RFS (hazard ratio (HR): 2.038, 95% confidence interval (CI): 1.135-3.658, P = 0.017; HR: 2.493, 95% CI: 1.335-4.653, P = 0.004), and OS (HR: 2.187, 95% CI: 1.173-4.077, P = 0.014; HR: 2.499, 95% CI: 1.285-4.858, P = 0.007), respectively. Notably, low RD TIL levels were significantly associated with reduced RFS (HR: 3.567, 95% CI: 1.475-8.624, P = 0.005) and reduced OS (HR: 3.873, 95% CI: 1.512-9.918, P = 0.005) in only the no Ki67 decrease group. The differences in 3-year RFS and OS between patients with no Ki67 decrease and low or high RD TIL levels were 24.4% vs 79.1% (P = 0.0001) and 33.1% vs 87.5% (P = 0.0001), respectively. CONCLUSION: Ki67 index changes and RD TIL levels were associated with the prognosis of patients with primary TNBC with RD after NAC. RD TIL levels had greater prognostic significance in the no Ki67 decrease group.

Plasma fibrinogen acts as a predictive factor for pathological complete response to neoadjuvant chemotherapy in breast cancer: a retrospective study of 1004 Chinese breast cancer patients.

BACKGROUND: The aim of this study was to evaluate the relationship between pre-treatment plasma fibrinogen (Fib) level and pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients and to assess the role of plasma Fib as a predictive factor. METHODS: Data from 1004 consecutive patients with invasive breast cancer who received NAC and subsequent surgery were retrospectively analysed. Both univariate and multivariate analyses based on logistic regression model were performed to identify clinicopathological factors associated with pCR to NAC. Cox regression model was used to determine the correlation between clinical or pathological parameters and recurrence-free survival (RFS). The Kaplan-Meier method and the log-rank test were applied in the survival analysis. RESULTS: The median value of Fib, rather than other plasma coagulation parameters, was significantly increased in non-pCR patients compared with pCR patients (P = 0.002). Based on the cut-off value estimated by the receiver operating characteristic (ROC) curve analysis, patients were divided into low or high Fib groups (Fib < 3.435 g/L or ≥ 3.435 g/L). Low Fib levels were significantly associated with premenopausal or perimenopausal status (P <  0.001), tumour size ≤5 cm (P = 0.002), and positive hormone receptor status (P = 0.002). After adjusted for other clinicopathological factors in the multivariate logistic regression model, low Fib status was strongly associated with pCR to NAC (OR = 3.038, 95% CI 1.667-5.537, P <  0.001). Survival analysis showed that patients with low Fib levels exhibited better 3-year RFS compared with patients with high Fib levels in the tumour size>5 cm group (77.5% vs 58.4%, log-rank, P = 0.0168). CONCLUSIONS: This study demonstrates that low pre-treatment plasma Fib (Fib < 3.435 g/L) is an independent predictive factor for pCR to NAC in breast cancer patients. Moreover, T3-featured breast cancer patients with lower Fib level exhibit better RFS outcomes after NAC compared with high Fib status.

Construction and Validation of an Immune Infiltration-Related Gene Signature for the Prediction of Prognosis and Therapeutic Response in Breast Cancer.

Breast cancer patients show significant heterogeneity in overall survival. Current assessment models are insufficient to accurately predict patient prognosis, and models for predicting treatment response are lacking. We evaluated the relationship between various immune cells and breast cancer and confirmed the association between immune infiltration and breast cancer progression. Different bioinformatics and statistical approaches were combined to construct a robust immune infiltration-related gene signature for predicting patient prognosis and responses to immunotherapy and chemotherapy. Our research found that a higher immune infiltration-related risk score (IRS) indicates that the patient has a worse prognosis and is not very sensitive to immunotherapy. In addition, a new nomogram was constructed based on the gene signature and clinicopathological features to improve the risk stratification and quantify the risk assessment of individual patients. Our study might contribute to the optimization of the risk stratification for survival and the personalized management of breast cancer.

Treatment response correlation between primary tumor and axillary lymph nodes after neoadjuvant therapy in breast cancer: a retrospective study based on real-world data.

BACKGROUND: Excellent response of the primary tumor after neoadjuvant therapy may indicate a better axillary status in breast cancer. However, this treatment response correlation has not been investigated in Chinese breast cancer patients. METHODS: Patients diagnosed with breast cancer and treated with neoadjuvant therapy were included in this retrospective study, conducted at a comprehensive breast cancer institution in China. Clinicopathological factors at baseline were analyzed by univariate and multivariate analyses. Furthermore, association rules analyses were used to investigate the correlation between the pathologic response of the primary tumor and that of the axillary lymph nodes based on such factors. RESULTS: Multivariate logistic regression analysis showed that breast pathologic response was influenced by tumor size, classification of regional lymph nodes, histological grade, progesterone receptor status, and Ki67 expression. The potential influencing factor for the pathologic response of the axilla was found to be regional lymph node classification. The findings from association rules analyses demonstrated that when a pathologic complete response (pCR) in the breast was achieved among patients with cT2N0 and hormone receptor-negative disease, the axilla response in these patients was also highly likely to be pCR (the likelihood for axilla pCR was more than 90%). However, cT3N1-2 patients hardly achieved pCR for both the primary tumor and axillary lymph nodes (mean confidence, 0.9637). The clinicopathological factors accounting for the inconsistent response between the breast and the axilla were found to be hormone receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative, and low Ki67 expression. CONCLUSIONS: Our findings suggest a strong correlation between breast pCR and axilla pCR among patients with specific characteristics. These findings provide a basis for the selection of candidates for clinical trials on the omission of axillary surgery.