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.

Prognostic Signature and Therapeutic Value Based on Membrane Lipid Biosynthesis-Related Genes in Breast Cancer.

There is a need to improve diagnostic and therapeutic approaches to enhance the prognosis of breast cancer, the most common malignancy worldwide. Membrane lipid biosynthesis is a hot biological pathway in current cancer research. It is unclear whether membrane lipid biosynthesis is involved in the prognosis of BRCA. With LASSO regression, a 14-gene prediction model was constructed using data from the TCGA-BRCA cohort. The prediction model includes GPAA1, PIGF, ST3GAL1, ST6GALNAC4, PLPP2, ELOVL1, HACD1, SGPP1, PRKD2, VAPB, CERS2, SGMS2, ALDH3B2, and HACD3. BRCA patients from the TCGA-BRCA cohort were divided into two risk subgroups based on the model. Kaplan-Meier survival curves showed that patients with lower risk scores had significantly improved overall survival (P=2.49e - 09). In addition, risk score, age, stage, and TNM classification were used to predict mortality in BRCA patients. In addition, the 14 genes in the risk model were analyzed for gene variation, methylation level, drug sensitivity, and immune cell infiltration, and the miRNA-mRNA network was constructed. Afterward, the THPA website then analyzed the protein expression of 14 of these risk model genes in normal and pathological BRCA tissues. In conclusion, the membrane lipid biosynthesis-related risk model and nomogram can be used to predict BRCA clinical prognosis.

Ferroptosis Biology and Implication in Cancers.

Ferroptosis, a novel form of regulated cell death (RCD), has garnered increasing attention in studies on numerous human diseases in the last decade. Emerging evidence has indicated that the pathological process of ferroptosis involves the overloaded production of reactive oxygen species (ROS), followed by aberrant accumulation of lipid peroxidation in an iron-dependent manner, accompanied with an increased uptake of polyunsaturated fatty acids into the cellular membrane, further unfolding an ancient vulnerability in multiple context. The unique nature of ferroptosis differentiates it from other forms of RCD, as it is intricately associated with several biological processes, including the metabolism of iron, amino acids, synthesis of ROS and lipid peroxidation. Accordingly, inducers and inhibitors designed to target the key processes of ferroptosis have been extensively studied. Characterized by its distinct properties as mentioned above and its inducible nature, ferroptosis has been widely implicated in several diseases, and numerous studies have focused on identifying effective therapeutic targets for multiple human diseases, including in cancer, by targeting this process. In the present review, recent studies on the involvement of ferroptosis in several types of cancer are summarized and the findings discussed, highlighting the need for increased contemplation of its involvement in the study of cancer, particularly in the clinical setting. A comprehensive summary of the biological mechanisms underlying ferroptosis, the implications of the multiple inducers of ferroptosis, as well as immunotherapy targeting ferroptosis in different types of cancer is provided in this review to highlight the pathophysiological role of ferroptosis in carcinogenesis, to serve as an aid in future studies on the role of ferroptosis in 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.

JAM2 predicts a good prognosis and inhibits invasion and migration by suppressing EMT pathway in breast cancer.

OBJECTIVES: Large-scale epidemiological surveys have shown that patients with Down syndrome, which is caused by a chromosomal abnormality (an extra chromosome 21), are significantly less likely to develop solid tumors, including breast cancer, than those without. This feature has prompted the search for oncogenes located on chromosome 21. Junctional adhesion molecule 2 (JAM2), which is located on chromosome 21, is expressed at low levels in breast cancer and is associated with a good prognosis. These findings strongly suggest that JAM2 may be a potential oncogene suppressor in breast cancer. However, the role and function of JAM2 in breast cancer are not yet clear. Therefore, this study aimed to explore the biological functions and mechanisms of JAM2 in breast cancer. METHODS: Several databases were used to explore JAM2 expression in breast cancer and to analyze its diagnostic and prognostic value in breast cancer. Changes in relevant markers were examined at the gene and protein levels using RT-qPCR and Western blot techniques, in addition, cell migration and invasion abilities were identified by scratch assays and transwell assays. Untargeted metabolomics, transcriptome sequencing and Luminex liquid suspension chip detection were performed in combination to study the mechanisms. RESULTS: JAM2 is expressed at low levels in breast cancer, and patients with high JAM2 expression have a good prognosis, indicating that JAM2 has good clinical diagnostic and prognostic value. Overexpression of JAM2 can block the invasion and migration of breast cancer cells, and the mechanism may be that JAM2 inhibits the EMT pathway. Finally, combined multiomics analysis revealed that JAM2 may affect the immune microenvironment of breast cancer by influencing the secretion of CXCL9/10 from tumor cells.

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.

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.

Overexpression of SERPINA3 promotes tumor invasion and migration, epithelial-mesenchymal-transition in triple-negative breast cancer cells.

BACKGROUND: Recent studies have indicated that serpin peptidase inhibitor, clade A, member 3 (SERPINA3) is a potential marker associated with tumor progression, which connoted that SERPINA3 is related to malignant phenotypes in cancer. However, the biological function of SERPINA3 in breast cancer (BC) remains unclear. METHODS: Bioinformatics data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Immunohistochemical staining (IHC) was conducted to determine SERPINA3 expression. With strong aggressive abilities, triple-negative breast cancer (TNBC) cell lines (MDA-MB-231, BT549 and MDA-MB-436) were obtained to examine SERPINA3 expression and functions. Wound healing and Transwell assays were performed to measure cell migration and invasion. Cell Counting Kit-8 (CCK-8) assay was conducted to detect cell proliferation abilities and cell viabilities. RESULTS: SERPINA3 was upregulated in BC tissues. Functional assays suggested that overexpression of SERPINA3 significantly promoted cell proliferation, where migration and invasion of TNBC cells were accelerated. Knockdown of SERPINA3 had the opposite effects. These results causing by overexpression of SERPINA3 were also confirmed in non-TNBC cell lines. Overexpression of SERPINA3 remarkably enhanced the epithelial-mesenchymal transition (EMT) by upregulating the EMT markers and EZH2. In addition, the overexpression of SERPINA3 reduced the sensitivity of TNBC cells to cisplatin. CONCLUSION: SERPINA3 can regulate the migration, invasion and EMT of TNBC cells and increased expression of SERPINA3 confers resistance to cisplatin in TNBC cells. We discern it is required for the regulation of BC progression and is a critical target for the clinical treatment of BC.

A cerium-based fluorescent nanosensor for highly specific detection of glutathione over cysteine and homocysteine.

Ever-increasing attention has been focused on constructing a sensing system for specific detection of glutathione (GSH) over cysteine (Cys) and homocysteine (Hcy), which usually interfere with the GSH detection due to their similar structures and the presence of thiol groups in these amino acids. Here, a novel fluorescence-sensing system is developed for highly specific GSH detection over Cys and Hcy. The sensing system is constructed through facilely mixing dipicolinic acid (DPA) and guanosine 5'-monophosphate (GMP) with cerium acetate at ambient conditions, denoted as DPA-Ce-GMP. The resultant DPA-Ce-GMP possesses fluorescence emission with excellent thermal stability and anti-light bleaching, which can be quenched by copper ions (Cu2+). The GSH, and not Cys or Hcy, can trap Cu2+ from DPA-Ce-GMP, resulting in the restoration of the fluorescence of the sensing system. The limit of detection reaches as low as 7.1 nM. The GSH detection in a real sample of human serum was further explored and exhibits satisfactory recovery. The developed sensing system has the advantages of ease-of-preparation, excellent selectivity and stability, demonstrating its potential application in disease diagnosis in the future.

Prognostic value of programmed cell death ligand-1 expression in breast cancer: A meta-analysis.

BACKGROUND: The correlation between programmed cell death-ligand 1 (PD-L1) which may affect T cell to form the immune tolerance and breast cancer (BC) still maintains to be uncovered. This meta-analysis was about to explore PD-L1 expression as well as its prognostic role in BC. METHODS: First of all, we performed 3 databases: PubMed, Embase, and Web of Science to explore publications between January of 2015 and January of 2020. Strict inclusion and exclusion criteria were conducted: immunohistochemistry shall be used to detect target molecule expression and at least 1 survival indicator and related data we need should be included. The hazard ratio and 95% confidence interval were pooled related with survival as well as clinicopathological parameters. The effects of PD-L1 in differed aspects like sample size and age of each cohort were demonstrated by subgroup analyses as well as sensitivity analyses which may complain the potential source of heterogeneity. P < .05 indicates factors were charge of the heterogeneity of prognosis. Begg and Egger tests were used to identify publication bias. RESULTS: We identified 12 studies containing a blanket of 4336 patients with BC for whom PD-L1 positive tumor cells were related with higher tumor stage, lymph node metastasis, estrogen receptor negativity, human epidermal growth factor receptor 2 positivity, luminal B and triple negative BC molecular subtype and high nuclear-associated antigen Ki- 67 expression. Meanwhile, compared to patients with PD-L1 negative expression, PD-L1 positivity associated with worse overall survival (Hazard ratio [HR]:1.43; 95% CI:0.98-2.10; P < .001) and might have no obvious tight connection with disease free survival (HR:1.40; 95% CI:1.11-1.78; P = .101) and recurrence free survival (HR:2.36; 95% CI:1.04-5.34; P = .145). The outcome of the meta-analysis was confirmed to be credible by sensitivity analysis. Publication bias was not existed indicated (P = .640). CONCLUSION: Positive PD-L1 expression has a worse clinical outcome in patients with BC demonstrated by our meta-analysis. Being urgent to catch attention to the role of PD-L1 in BC, it may be considered as prognostic marker of immune microenvironment for improving therapy efficacy.

A look into the link between centrosome amplification and breast cancer.

Centrosome amplification (CA) is a common feature of human tumors, but it is not clear whether this is a cause or a consequence of cancer. The centrosome amplification observed in tumor cells may be explained by a series of events, such as failure of cell division, dysregulation of centrosome cycle checkpoints, and de novo centriole biogenesis disorder. The formation and progression of breast cancer are characterized by genomic abnormality. The centrosomes in breast cancer cells show characteristic structural aberrations, caused by centrosome amplification, which include: an increase in the number and volume of centrosomes, excessive increase of pericentriolar material (PCM), inappropriate phosphorylation of centrosomal molecular, and centrosome clustering formation induced by the dysregulation of important genes. The mechanism of intracellular centrosome amplification, the impact of which on breast cancer and the latest breast cancer target treatment options for centrosome amplification are exhaustively elaborated in this review.