Malignant Tumor In Women Research Articles

RecQ protein-like 4 drives cisplatin chemosensitivity of cervical cancer cells by modulating annexin A2.

Cervical cancer is a common malignant tumor in women with high morbidity and mortality. Chemotherapy drugs such as cisplatin (DDP) are easy to cause chemotherapy resistance and affect the therapeutic effect. Hence, it is critical to design new therapies that can reverse chemotherapy resistance and increase sensitivity to chemotherapy drugs. This study investigated the function of RecQ protein-like 4 (RECQL4) in DDP-resistant cervical cancer cells and its regulatory mechanism. By constructing DDP-resistant Hela and CaSki cell lines, it was found that RECQL4 expression was elevated. RECQL4 knockdown is able to promote apoptosis, DNA damage, and increase the DDP sensitivity in cervical cancer cells. In vivo experiments have demonstrated that knockdown of RECQL4 suppresses tumor growth and promotes tumor apoptosis. Next, we investigated the potential regulatory relationship of RECQL4 to Annexin A2 (ANXA2). The results demonstrated that RECQL4 binds to ANXA2. Knockdown of RECQL4 downregulates the ANXA2 expression via promoting ubiquitination. Furthermore, we also found that ANXA2 overexpression partially abolished the role of RECQL4 knockdown in promoting apoptosis and DNA damage of cervical cancer cells, suggesting that RECQL4 plays a role in DDP sensitivity of cervical cancer cells by mediating ANXA2. In conclusion, the present study suggests that knocking down RECQL4 reduces DDP sensitivity in cervical cancer cells by modulating ANXA2. Targeting RECQL4 therapy may be a new strategy to improve chemosensitivity of cervical cancer cells.

Overexpression of SLAP2 inhibits triple-negative breast cancer progression by promoting macrophage M1-type polarization

Breast cancer is the most common malignant tumor in women, and triple-negative breast cancer (TNBC) is a specific subtype of breast cancer characterized by high invasiveness, high metastatic potential, ease of recurrence, and poor prognosis. Src-like adaptor protein 2 (SLAP2), which can be involved in the regulation of multiple signaling pathways, may be a key target for TNBC. The aim of this study was to investigate the effect of overexpression of SLAP2 on TNBC and to explore the underlying mechanisms. First, we constructed and transfected SLAP2 overexpressing lentivirus based on MDA-MB-231 human TNBC cell line, screened for differential downstream target genes in combination with mRNA high-throughput sequencing (RNA-Seq), and predicted their functions and enriched pathways in conjunction with bioinformatics analysis. The effects of SLAP2 overexpression on macrophage polarization, as well as on tumor proliferation and apoptosis, were assessed by tail vein injection of a stable transfection line of 4T1 cells transfected with SLAP2 overexpressing lentivirus. The effect of SLAP2 on macrophage polarization was assessed by inducing M1/M2 polarization and transfecting SLAP2 overexpressing lentivirus. Meanwhile, a transwell co-culture system was constructed between differently treated macrophages and 4T1 cells to assess the effect of SLAP2 overexpression on the malignant behavior of the cells via macrophage polarization. Overexpression of SLAP2 revealed 179 genes up-regulated and 74 genes down-regulated by mRNA high-throughput sequencing, and the enriched functions and pathways of differential genes were mainly related to immunity response. In vivo experiments revealed that overexpression of SLAP2 inhibited the growth of tumor in nude mice, decreased the expression of ki67 in tumor tissues, and increased the rate of apoptosis in tumor tissues. Meanwhile, we found that overexpression of SLAP2 promoted macrophage polarization toward M1 type and inhibited M2 type polarization in tumors. In vitro experiments further verified its effect on M1/M2 polarization by transfecting SLAP2 overexpressing lentivirus. By transwell co-culture system, we further demonstrated that overexpression of SLAP2 inhibits cell proliferation and invasion, promotes apoptosis, up-regulates the expression of Bax in cells, and down-regulates the expression of Bcl-2 in cells by promoting macrophage M1-type polarization. Overexpression of SLAP2 inhibits TNBC progression by promoting macrophage M1-type polarization.

Self-assembled lipid-based nanoparticles for chemotherapy against breast cancer

Self-assembled lipid-based nanoparticles have been shown to have improved therapeutic efficacy and lower toxic side effects. Breast cancer is a common type of malignant tumor in women. Conventional drugs such as doxorubicin (DOX) have shown low therapeutic efficacy and high drug toxicity in antitumor therapy. This paper surveys research on self-assembled lipid-based nanoparticles by categorizing them under three groups: self-assembled liposomal nanostructures, self-assembled niosomes, and self-assembled lipid–polymer hybrid nanoparticles. Subsequently, the structural features and operating mechanisms of each group are summarized individually along with examples of representative drugs from each group.

DLAT promotes triple-negative breast cancer progression via YAP1 activation

ABSTRACT Background Breast cancer (BC) is the most prevalent malignant tumor in women globally. Triple-negative breast cancer (TNBC) represents the most malignant and invasive subtype of BC. New therapeutic targets are urgently needed for TNBC owing to its receptor expression characteristics, which render it insensitive to traditional targeted and endocrine therapies for BC. The role and mechanisms of dihydrolipoamide S-acetyltransferase (DLAT) as a crucial molecule in glycometabolism and cuproptosis-related biological processes in tumors remain to be explored. Methods DLAT expression was investigated using bioinformatics methods and quantitative real-time polymerase chain reaction. Subsequently, the MTT assay, colony formation assay, and migration-invasion assay were performed to validate the effect of DLAT on TNBC cell viability, proliferation, and migration. Cytoplasmic-nuclear separation experiments, western blot analysis, and co-immunoprecipitation assays were performed to elucidate the underlying molecular mechanisms. Results This study revealed a robust correlation between elevated DLAT expression in BC and unfavorable prognosis in patients, with higher expression of DLAT compared to other subtypes in TNBC. Functional cytology experiments indicated that DLAT plays a tumor-promoting role in TNBC. Mechanistic studies showed that DLAT directly interacts with YAP1, leading to the dephosphorylation and activation of YAP1 and its increased nuclear translocation, thereby transcriptionally activating and regulating downstream oncogenes, promoting the malignant phenotype of TNBC. Rescue experiments indicated that DLAT promotes the malignant behavior of TNBC through a YAP1-dependent pathway. Conclusions Our research unveiled the significant involvement of DLAT in TNBC, along with the potential for modulating DLAT/YAP1 activity as a targeted treatment strategy for TNBC.

Simple ROS-responsive micelles loaded Shikonin for efficient ovarian cancer targeting therapy by disrupting intracellular redox homeostasis

Ovarian cancer is the most common malignant tumor in women. Shikonin (SHK), an herbal extract from Chinese medicine, shows promise in treating ovarian cancer by inducing reactive oxygen species (ROS). However, its clinical use is limited by poor tumor targeting and low bioavailability, and its therapeutic potential is further compromised by the elevated levels of antioxidants such as glutathione (GSH) within tumor cells. In this study, a novel formulation of ROS-responsive micelles loaded with SHK was developed using hyaluronic acid-phenylboronic acid pinacol ester conjugation (HA-PBAP) for targeted therapy of ovarian cancer through disruption of intracellular redox homeostasis. The SHK@HA-PBAP exhibits targeted delivery to ovarian cancer cells through the interaction between HA and CD44 receptors. Upon internalization by cancer cells, the high levels of intracellular ROS triggered the degradation of SHK@HA-PBAP and simultaneously released SHK and generated GSH scavenger quinone methide (QM). The SHK and QM released from the SHK@HA-PBAP effectively induce the production of ROS and deplete intracellular GSH, leading to the disruption of intracellular redox homeostasis and subsequent induction of cell death. These characteristics collectively inhibit the growth of ovarian cancer. In vitro and in vivo studies have demonstrated that SHK@HA-PBAP micelles exhibit superior antitumor efficacy compared to free SHK in both A2780 cells and A2780 tumor-bearing mice. The ROS-responsive SHK@HA-PBA presents a promising therapeutic approach for the treatment of ovarian cancer.

Vitamin D receptor is associated with prognostic characteristics of breast cancer after neoadjuvant chemotherapy-an observational study.

Breast cancer (BC) is the most commonly diagnosed malignant tumor in women. The disease and its subsequent treatment pose a serious burden on the quality of life of patients. Neoadjuvant chemotherapy (NAC) has become one of the crucial strategies for the management of BC. Since the identification of the vitamin D receptor (VDR) in mammary tissues, extensive mechanistic research has been conducted on its function. The expression of VDR in BC cells and the tumor microenvironment could be a new prognostic factor for BC after NAC. This observational, single-center study compared data from clinical and histopathological records of 111 female subjects with the expression of VDR in different cellular and tissue components of breast specimens obtained from surgery after NAC. VDR expression was evaluated using an immunoreactive score assigned after immunohistochemistry. Intergroup comparisons and logistic regression were used to identify associations between VDR expression and clinicopathological features of BC. We found that the expression of VDR is associated with various clinical features (i.e., age, menopausal status, and NAC cycle number) and characteristics of prognostic significance, such as residual cancer burden class. Logistic regression analysis revealed that the expression of VDR in the nuclei and cytoplasm of surrounding normal mammary cells predicted vascular invasion and lymph node involvement. The expression of VDR in tumor cells and their microenvironment is related to the clinicopathological characteristics of BC after NAC.

Non-metabolic enzyme function of pyruvate kinase M2 in breast cancer.

Breast cancer (BC) is a prevalent malignant tumor in women, and its incidence has been steadily increasing in recent years. Compared with other types of cancer, it has the highest mortality and morbidity rates in women. So, it is crucial to investigate the underlying mechanisms of BC development and identify specific therapeutic targets. Pyruvate kinase M2 (PKM2), an important metabolic enzyme in glycolysis, has been found to be highly expressed in BC. It can also move to the nucleus and interact with various transcription factors and proteins, including hypoxia-inducible factor-1α (HIF-1α), signal transducer and activator of transcription 3 (STAT3), β-catenin, cellular-myelocytomatosis oncogene (c-Myc), nuclear factor kappa-light-chain enhancer of activated B cells (NF-κB), and mammalian sterile 20-like kinase 1 (MST1). This interaction leads to non-metabolic functions that control the cell cycle, proliferation, apoptosis, migration, invasion, angiogenesis, and tumor microenvironment in BC. This review provides an overview of the latest advancements in understanding the interactions between PKM2 and different transcription factors and proteins that influence the initiation and progression of BC. It also examined how natural drugs and noncoding RNAs affect various biological processes in BC cells through the regulation of the non-metabolic enzyme functions of PKM2. The findings provide valuable insights for improving the prognosis and developing targeted therapies for BC in the coming years.

Integrating Bioinformatics and Experimental Validation to Identify Mitochondrial Permeability Transition-Driven Necrosis-Related lncRNAs that can Serve as Prognostic Biomarkers and Therapeutic Targets in Endometrial Carcinoma.

Endometrial carcinoma (EC) is a common malignant tumor in women with high mortality and relapse rates. Mitochondrial permeability transition (MPT)-driven necrosis is a novel form of programmed cell death. The MPT-driven necrosis related lncRNAs (MRLs) involved in EC development remain unclear. We aimed to predict the outcomes of patients with EC by constructing a novel prognostic model based on MRLs and explore potential molecular functions. A risk prognostic model was developed utilizing multi-Cox regression in conjunction with the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm, which was based on MRLs. The predictive efficacy of the model was evaluated through receiver operating characteristic (ROC) curve analysis, as well as nomogram and concordance index (C-index) assessments. Patients were categorized into high- and low-risk groups based on their median risk scores. Notably, the high-risk group exhibited significantly poorer overall survival (OS) outcomes. Gene ontology (GO) and Gene set enrichment analysis (GSEA) demonstrated that Hedgehog and cell cycle pathways were enriched in the high-risk group. Tumor Immune Dysfunction and Exclusion (TIDE) displayed that patients in the high-risk group showed a high likelihood of immune evasion and less effective immunotherapy. A significant disparity in immune function was also observed between two groups. Based on the nine-MRLs, drug sensitivity analysis identified several anticancer drugs with potential efficacy in prognosis. Meanwhile, the results demonstrated that OGFRP1 plays a carcinogenic role by affecting mitochondrial membrane permeability in EC. Therefore, the risk model constructed by nine MRLs could be used to predict the clinical outcomes and therapeutic responses in patients with EC effectively.

Survey on Uterus Cancer and Its Types

Abstract: The vital component of the female reproductive system is the uterus. Women are currently dealing with a number of issues pertaining to reproduction. Additionally, the prevalence of cancer is rising daily, with a higher risk of malignant tumors in women. To effectively detect the cancer, a variety of techniques are being utilized, including image processing, machine learning, and datamining. This study describes the various machine learning algorithms used in the diagnosis of uterine cancer.

Elucidating the protective mechanism of ganoderic acid DM on breast cancer based on network pharmacology and in vitro experimental validation.

Ganoderma lucidum, a popular medicinal fungus, has been utilized to treat a variety of diseases. It possesses a unique therapeutic and pharmacological reputation in suppressing cancer/tumor progression, especially breast cancer, due to its embedded rich bioactive chemical constituents, mainly triterpenoids (ganoderic acids). The most prevalent malignant tumor in women with a high mortality and morbidity rate is breast cancer. Ganoderic acids A, D, DM, F, and H are evidenced in previous research to have breast cancer-preventive properties by exhibiting autophagic and apoptosis, anti-proliferative, and anti-angiogenesis effects. However, the anti-breast cancer mechanism remains unclear. The putative targets of the ganoderic acids were further determined using bioinformatics techniques and molecular docking calculation. Finally, the key targets were verified in vitro. A total of 53 potential target proteins associated with 202 pathways were predicted to be related to breast cancer. The potential targets were narrowed down to six key targets (AKT1, PIK3CA, epidermal growth factor receptor [EGFR], STAT1, ESR1, and CTNNB1), using different algorithms of the CytoHubba plugin, which were further validated using molecular docking analysis. The ganoderic acid DM (GADM) and the targets (PIK3CA and EGFR) with the strongest interactions were validated via MDA-MB-231 and MCF7 cells. The expression level of PIK3CA in both MDA-MB-231 and MCF7 cells was dose-dependently suppressed by GADM, whereas EGFR expression was unexpectedly increased, which warrants further investigation. These data indicated that the network pharmacology-based prediction of GADM targets for treating human breast cancer could be reliable.

An Investigation on Breast Cancer Knowledge in Developing Nations

The most common malignant tumor in women diagnosed globally, breast cancer is the leading cause of cancer-related death. Globally, the prevalence of breast cancer is continuously increasing. Breast cancer is the most prevalent type of cancer in the world. Hereditary and genetic predispositions are among the risk factors linked to the incidence of breast cancer. Breast cancers come in a wide variety of forms. The molecular characteristics of breast cancer, including hormone receptor activation (PR, ER, and HER2) and human epidermal growth factor receptor 2 (HER2), genetic changes (BRCA1/2 and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha [PIK3CA] mutations), and immune system markers (PD L1, tumour-infiltrating lymphocytes [TIL], and programmed death-ligand 1 [PD L1]) may impact treatment approaches.

Application and prospect of organoid technology in breast cancer.

Breast cancer is the most common malignant tumor in women. Due to the high heterogeneity of breast cancer cells, traditional in vitro research models still have major limitations. Therefore, it is urgent to establish an experimental model that can accurately simulate the characteristics of human breast cancer. Breast cancer organoid technology emerged as the times required, that is, to construct tissue analogs with organ characteristics by using a patient's tumor tissue through 3D culture in vitro. Since the breast cancer organoid can fully preserve the histology and genetic characteristics of the original tumor, it provides a reliable model for preclinical drug screening, establishment of breast cancer organoid biobanks, research into the mechanisms of tumor development, and determination of cancer targets. It has promoted personalized treatment for clinical breast cancer patients. This article mainly focuses on recent research progress and applications of organoid technology in breast cancer, discussing the current limitations and prospects of breast cancer organoid technology.

Hypoxia-inducible factor-1α can reverse the Adriamycin resistance of breast cancer adjuvant chemotherapy by upregulating transferrin receptor and activating ferroptosis.

Breast cancer is a common malignant tumor in women. Ferroptosis, a programmed cell death pathway, is closely associated with breast cancer and its resistance. The transferrin receptor (TFRC) is a key factor in ferroptosis, playing a crucial role in intracellular iron accumulation and the occurrence of ferroptosis. This study investigates the influence and significance of TFRC and its upstream transcription factor hypoxia-inducible factor-1α (HIF1α) on the efficacy of neoadjuvant therapy in breast cancer. The differential gene obtained from clinical samples through genetic sequencing is TFRC. Bioinformatics analysis revealed that TFRC expression in breast cancer was significantly greater in breast cancer tissues than in normal tissues, but significantly downregulated in Adriamycin (ADR)-resistant tissues. Iron-responsive element-binding protein 2 (IREB2) interacts with TFRC and participates in ferroptosis. HIF1α, an upstream transcription factor, positively regulates TFRC. Experimental results indicated higher levels of ferroptosis markers in breast cancer tissue than in normal tissue. In the TAC neoadjuvant regimen-sensitive group, iron ion (Fe2+) and malondialdehyde (MDA) levels were greater than those in the resistant group (all p < .05). Expression levels of TFRC, IREB2, FTH1, and HIF1α were higher in breast cancer tissue compared to normal tissue. Additionally, the expression of the TFRC protein in the TAC neoadjuvant regimen-sensitive group was significantly higher than that in the resistant group (all p < .05), while the difference in the level of expression of IREB2 and FTH1 between the sensitive and resistant groups was not significant (p > .05). The dual-luciferase assay revealed that HIF1α acts as an upstream transcription factor of TFRC (p < .05). Overexpression of HIF1α in ADR-resistant breast cancer cells increased TFRC, Fe2+, and MDA content. After ADR treatment, the cell survival rate decreased significantly, and ferroptosis could be reversed by the combined application of Fer-1 (all p < .05). In conclusion, ferroptosis and chemotherapy resistance are correlated in breast cancer. TFRC is a key regulatory factor influenced by HIF1α and is associated with chemotherapy resistance. Upregulating HIF1α in resistant cells may reverse resistance by activating ferroptosis through TFRC overexpression.

In Situ Colorimetric LAMP Based on One-Step Modified Filter Paper to Screen Human Papillomavirus (HPV)16/18 from Clinical Samples.

Cervical cancer is among the most common malignant tumors in women. The development of rapid screening techniques plays an important role in early screening for cancer treatment. We have developed an HPV screening method, which effectively combines the high-efficiency nucleic acid enrichment of chitosan-modified filter paper and the rapid visual detectability of colorimetric LAMP, along with the enhancement of the tolerance ability of the pH-sensitive LAMP reagent to acidic original samples, making the detection of HPV 16/18 easy to carry out and reliable, which is helpful for the epidemiological prevention and control strategies of HPV-induced cancer. This technique can simultaneously exhibit the "in situ amplification" capability of chitosan-modified filter paper and the nontemperature cycle dependence of visual LAMP detection. Therefore, DNA extraction and amplification can be performed efficiently and quickly within a single reaction where all DNA is concentrated in the QF paper disc. By embedding amino-modified filter paper into the plastic chip, a simple and reliable disposable chip was prepared for rapid HPV16 and HPV18 detection from clinical endometrial samples, and the results were 100% consistent with clinical diagnosis. More importantly, even after the sample was diluted 100-fold, HPV16/18-infected cells could be accurately identified, showing the advantages of the system in early cancer screening. Moreover, for endometrial samples containing plenty of cells, the filter paper could be used to enrich cells by filtration, preventing the acidic fluid from impacting pH-induced colorimetric LAMP detection and realizing direct amplification for HPV identification without nucleic acid extraction. This easy-to-operate system that can analyze a wide range of samples will be suitable for routine on-site HPV screening, dramatically extending the applications and utility for rapid, near-patient nucleic acid testing.

Development and validation of an artificial intelligence model for predicting de novo distant bone metastasis in breast cancer: a dual-center study

ObjectiveBreast cancer has become the most prevalent malignant tumor in women, and the occurrence of distant metastasis signifies a poor prognosis. Utilizing predictive models to forecast distant metastasis in breast cancer presents a novel approach. This study aims to utilize readily available clinical data and advanced machine learning algorithms to establish an accurate clinical prediction model. The overall objective is to provide effective decision support for clinicians.MethodsData from 239 patients from two centers were analyzed, focusing on clinical blood biomarkers (tumor markers, liver and kidney function, lipid profile, cardiovascular markers). Spearman correlation and the least absolute shrinkage and selection operator regression were employed for feature dimension reduction. A predictive model was built using LightGBM and validated in training, testing, and external validation cohorts. Feature importance correlation analysis was conducted on the clinical model and the comprehensive model, followed by univariate and multivariate regression analysis of these features.ResultsThrough internal and external validation, we constructed a LightGBM model to predict de novo bone metastasis in newly diagnosed breast cancer patients. The area under the receiver operating characteristic curve values of this model in the training, internal validation test, and external validation test1 cohorts were 0.945, 0.892, and 0.908, respectively. Our validation results indicate that the model exhibits high sensitivity, specificity, and accuracy, making it the most accurate model for predicting bone metastasis in breast cancer patients. Carcinoembryonic Antigen, creatine kinase, albumin-globulin ratio, Apolipoprotein B, and Cancer Antigen 153 (CA153) play crucial roles in the model’s predictions. Lipoprotein a, CA153, gamma-glutamyl transferase, α-Hydroxybutyrate dehydrogenase, alkaline phosphatase, and creatine kinase are positively correlated with breast cancer bone metastasis, while white blood cell ratio and total cholesterol are negatively correlated.ConclusionThis study successfully utilized clinical blood biomarkers to construct an artificial intelligence model for predicting distant metastasis in breast cancer, demonstrating high accuracy. This suggests potential clinical utility in predicting and identifying distant metastasis in breast cancer. These findings underscore the potential prospect of developing economically efficient and readily accessible predictive tools in clinical oncology.

The role of RRS1 in breast cancer cells metastasis and AEG-1/AKT/c-Myc signaling pathway.

Breast cancer is the most common malignant tumor in women. Recurrence, metastasis, and chemotherapy resistance are the main causes of death in breast cancer patients. The inhibition of breast cancer metastasis is of great significance for prolonging its survival. Ribosome biogenesis regulatory protein homolog (RRS1) is overexpressed in breast cancer tissues and is involved in regulating the carcinogenic process of breast cancer cells. However, the exact signaling pathway and molecular mechanism of RRS1 promoting breast cancer metastasis are not fully understood. Hence, the primary objective of our study is to investigate the correlation between RRS1 and breast cancer metastasis. Bioinformatic analysis was used to identify the expression levels and prognostic significance of RRS1 in breast cancer. Lenti-sh RRS1 lentivirus was constructed and employed to downregulate the RRS1 expression in MDA-MB-231 and BT549 cells, which had a high-level expression of RRS1. Subsequently, we assessed the impact of RRS1 downregulation on the proliferation, migration, and invasion of breast cancer cells using CCK-8, apoptosis, and cell cycle by flow cytometry, wound healing test, Transwell migration, and invasion experiments. Moreover, we utilized an in vivo imaging system to examine the metastatic potential of breast cancer cells after RRS1 knockdown. Picrate staining and hematoxylin-eosin staining were employed to evaluate the presence of metastatic lesions. To gain a deeper understanding of the molecular mechanism, we conducted co-immunoprecipitation and western blot. The significant overexpression of RRS1 in breast cancer indicates a worse prognosis, as determined through TCGA databases (p<0.01). Additionally, RRS1 exhibits upregulation in breast cancer (p<0.001), which is tightly linked to the occurrence of lymph node metastasis (p<0.001). Clinical breast cancer tissues and breast cancer cell lines also demonstrated a noteworthy upregulation of RRS1 (p<0.05). Loss-of-function experiment illustrated that the inhibiting of RRS1 expression reduced the rapid proliferation capacity of MDA-MB-231 and BT549 cells and hindered their migration and invasion capabilities (p<0.05). Importantly, the suppression of RRS1 significantly diminished lung metastasis in Balb/c nude mice that were injected with MDA-MB-231 cells (p<0.01). Mechanistically, RRS1 may interact with the AEG-1 to modulate the phosphorylation of AKT at T308 and S473, consequently impeding the activity of c-Myc (p<0.05). To conclude, RRS1 functions as a potential oncogene in breast cancer by leveraging the AEG-1/AKT/c-Myc signaling.

Recent Advances in Immunotherapy for Breast Cancer: A Review.

Breast cancer is one of the most common malignant tumors in women in the world, and its incidence is increasing year by year, which seriously threatens the physical and mental health of women. Triple negative breast cancer (TNBC) is a special molecular type of breast cancer in which estrogen receptor, progesterone receptor and human epidermal growth factor receptor-2 are negative. Compared with other molecular types of breast cancer, triple-negative breast cancer (TNBC) has high aggressiveness and metastasis, high recurrence rate, lack of effective therapeutic targets, and usually poor clinical treatment effect. Chemotherapy was the main therapeutic means used in the past. With the advent of the immune era, immunotherapy has made a lot of progress in the treatment of triple-negative breast cancer (TNBC), bringing new therapeutic hope for the treatment of triple-negative breast cancer. This review combines the results of cutting-edge medical research, mainly summarizes the research progress of immunotherapy, and summarizes the main treatment methods of triple-negative breast cancer (TNBC) immunotherapy, including immune checkpoint inhibitors, tumor vaccines, adoptive immunotherapy and the application of traditional Chinese and western medicine. It provides a new idea for the treatment of triple negative breast cancer (TNBC).

Prediction Model for Therapeutic Responses in Ovarian Cancer Patients using Paclitaxel-resistant Immune-related lncRNAs.

Ovarian cancer (OC) is the deadliest malignant tumor in women with a poor prognosis due to drug resistance and lack of prediction tools for therapeutic responses to anti- cancer drugs. The objective of this study was to launch a prediction model for therapeutic responses in OC patients. The RNA-seq technique was used to identify differentially expressed paclitaxel (PTX)- resistant lncRNAs (DE-lncRNAs). The Cancer Genome Atlas (TCGA)-OV and ImmPort database were used to obtain immune-related lncRNAs (ir-lncRNAs). Univariate, multivariate, and LASSO Cox regression analyses were performed to construct the prediction model. Kaplan- meier plotter, Principal Component Analysis (PCA), nomogram, immune function analysis, and therapeutic response were applied with Genomics of Drug Sensitivity in Cancer (GDSC), CIBERSORT, and TCGA databases. The biological functions were evaluated in the CCLE database and OC cells. The RNA-seq defined 186 DE-lncRNAs between PTX-resistant A2780-PTX and PTXsensitive A2780 cells. Through the analysis of the TCGA-OV database, 225 ir-lncRNAs were identified. Analyzing 186 DE-lncRNAs and 225 ir-lncRNAs using univariate, multivariate, and LASSO Cox regression analyses, 9 PTX-resistant immune-related lncRNAs (DEir-lncRNAs) acted as biomarkers were discovered as potential biomarkers in the prediction model. Single-cell RNA sequencing (scRNA-seq) data of OC confirmed the relevance of DEir-lncRNAs in immune responsiveness. Patients with a low prediction score had a promising prognosis, whereas patients with a high prediction score were more prone to evade immunotherapy and chemotherapy and had poor prognosis. The novel prediction model with 9 DEir-lncRNAs is a valuable tool for predicting immunotherapeutic and chemotherapeutic responses and prognosis of patients with OC.

An Investigation on Breast Cancer Knowledge in Developing Nations

Breast cancer is the most common malignant tumor in women diagnosed globally and the leading cause of cancer-related death. Globally, the prevalence of breast cancer is increasing with time. Globally, breast cancer is the most prevalent type of cancer. The incidence of breast cancer is linked to several risk factors, such as genetic and inherited predispositions. Breast cancers can be of many different forms. The molecular features of breast cancer, such as the activation of hormone receptors (PR, ER, and HER2) and human epidermal growth factor receptor 2, genetic alterations (BRCA1/2 and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha [PIK3CA] mutations), and immune system markers (PD L1, tumour-infiltrating lymphocytes [TIL], and programmed death-ligand 1 [PD L1]) may impact treatment strategies. sufferers.

COL5A1 overexpression correlates with poor prognosis in human cervical cancer.

Cervical cancer is the most prevalent malignant tumor in women. This study aims to detect collagen type V α1 chain (COL5A1) expression and its clinical relevance in the prognosis of patients with cervical cancer. Cervical cancer tissues and their paired adjacent normal tissues were prepared for tissue microarray. The expression of COL5A1 protein and the scores of the expression were evaluated by immunohistochemistry (IHC) staining. The prognostic value of COL5A1 was analyzed by R software version 4.2.1 with "survival, survminer, ggplot2" packages and Gene Expression Profiling Interactive Analysis (GEPIA). The cBioPortal database was utilized for the analysis of COL5A1 gene mutations. COL5A1 protein was overexpressed in human cervical cancer tissues compared to their paired adjacent normal tissues detected by IHC (P < 0.001). High expression of COL5A1 tends to be in elderly patients with cervical cancer. Survival analyses of clinical data of patients with cervical cancer showed that a high level of COL5A1 expression was significantly correlated with shorter overall survival (P = 0.031) and disease-free survival (P = 0.042) of patients. Further analyses of The Cancer Genome Atlas-Cervical Squamous Cell Carcinoma and the GEPIA survival datasets confirmed the association of high COL5A1 expression with poor overall survival of patients (P = 0.040 and P = 0.018, respectively). The analysis of genomic alterations of COL5A1 using the cBioPortal tool revealed that the COL5A1 gene was altered in 4% of cervical cancer patients and COL5A1 corresponding protein alterations with post-translational modifications were hydroxylation. COL5A1 is a tissue biomarker correlated with the poor prognosis of patients with cervical cancer, which may lead to a new clinical application.