Integrative bioinformatics approach yields a novel gene expression risk model for prognosis and progression prediction in prostate cancer.

Prostate cancer (PCa), a prevalent malignancy among elderly males, exhibits a notable rate of advancement, even when subjected to conventional androgen deprivation therapy or chemotherapy. An effective progression prediction model would prove invaluable in identifying patients with a higher progression risk. Using bioinformatics strategies, we integrated diverse data sets of PCa to construct a novel risk model predicated on gene expression and progression-free survival (PFS). The accuracy of the model was assessed through validation using an independent data set. Eight genes were discerned as independent prognostic factors and included in the prediction model. Patients assigned to the high-risk cohort demonstrated a diminished PFS, and the areas under the curve of our model in the validation set for 1-year, 3-year, and 5-year PFS were 0.9325, 0.9041 and 0.9070, respectively. Additionally, through the application of single-cell RNA sequencing to two castration-related prostate cancer (CRPC) samples and two hormone-related prostate cancer (HSPC) samples, we discovered that luminal cells within CRPC exhibited an elevated risk score. Subsequent molecular biology experiments corroborated our findings, illustrating heightened SYK expression levels within tumour tissues and its contribution to cancer cell migration. We found that the knockdown of SYK could inhibit migration in PCa cells. Our progression-related risk model demonstrated the potential prognostic value of SYK and indicated its potential as a target for future diagnosis and treatment strategies in PCa management.

Tumor Cell-Targeting and Tumor Microenvironment-Responsive Nanoplatforms for the Multimodal Imaging-Guided Photodynamic/Photothermal/Chemodynamic Treatment of Cervical Cancer.

Purpose: Phototherapy, known for its high selectivity, few side effects, strong controllability, and synergistic enhancement of combined treatments, is widely used in treating diseases like cervical cancer. Methods: In this study, hollow mesoporous manganese dioxide was used as a carrier to construct positively charged, poly(allylamine hydrochloride)-modified nanoparticles (NPs). The NP was efficiently loaded with the photosensitizer indocyanine green (ICG) via the addition of hydrogen phosphate ions to produce a counterion aggregation effect. HeLa cell membrane encapsulation was performed to achieve the final M-HMnO2@ICG NP. In this structure, the HMnO2 carrier responsively degrades to release ICG in the tumor microenvironment, self-generates O2 for sensitization to ICG-mediated photodynamic therapy (PDT), and consumes GSH to expand the oxidative stress therapeutic effect [chemodynamic therapy (CDT) + PDT]. The ICG accumulated in tumor tissues exerts a synergistic PDT/photothermal therapy (PTT) effect through single laser irradiation, improving efficiency and reducing side effects. The cell membrane encapsulation increases nanomedicine accumulation in tumor tissues and confers an immune evasion ability. In addition, high local temperatures induced by PTT can enhance CDT. These properties of the NP enable full achievement of PTT/PDT/CDT and targeted effects. Results: Mn2+ can serve as a magnetic resonance imaging agent to guide therapy, and ICG can be used for photothermal and fluorescence imaging. After its intravenous injection, M-HMnO2@ICG accumulated effectively at mouse tumor sites; the optimal timing of in-vivo laser treatment could be verified by near-infrared fluorescence, magnetic resonance, and photothermal imaging. The M-HMnO2@ICG NPs had the best antitumor effects among treatment groups under near-infrared light conditions, and showed good biocompatibility. Conclusion: In this study, we designed a nano-biomimetic delivery system that improves hypoxia, responds to the tumor microenvironment, and efficiently loads ICG. It provides a new economical and convenient strategy for synergistic phototherapy and CDT for cervical cancer.

Decoding the immune landscape: a comprehensive analysis of immune-associated biomarkers in cervical carcinoma and their implications for immunotherapy strategies.

Background and aims: Cervical cancer, a prevalent gynecological malignant tumor, poses a significant threat to women's health and lives. Immune checkpoint inhibitor (ICI) therapy has emerged as a promising avenue for treating cervical cancer. For patients with persistent or recurrent metastatic cervical cancer, If the sequence of dead receptor ligand-1 (PD-L1) is positive, ICI show significant clinical efficacy. PD-L1 expression serves as a valuable biomarker for assessing ICI therapeutic efficacy. However, the complex tumor immune microenvironment (TIME), encompassing immune cell composition and tumor-infiltrating lymphocyte (TIL) status, also exerts a profound influence on tumor immunity and prognosis. Given the remarkable strides made by ICI treatments in improving the survival rates of cervical cancer patients, it becomes essential to identify a comprehensive biomarker that integrates various TIME aspects to enhance the effectiveness of ICI treatment. Therefore, the quest for biomarkers linked to multiple facets of TIME in cervical cancer is a vital pursuit. Methods: In this study, we have developed an Immune-Associated Gene Prognostic Index (IRGPI) with remarkable prognostic value specifically for cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). The Cancer Genome Atlas CESC dataset (n = 305) was meticulously analyzed to pinpoint key immune-related genes via weighted gene co-expression network analysis and differential gene expression assays. Subsequently, we employed Cox regression analysis to construct the IRGPI. Furthermore, the composition of immune cells and TIL status were examined using CIBERSORT and TIDE. Tumor expression of Epigen, LCN10, and P73 were determined with immunohistochemistry. Results: The resulting IRGPI, composed of EPGN, LCN10, and TP73 genes, displayed a strong negative correlation with patient survival. The discovery was validated with a patient cohort from our hospital. The IRGPI not only predicts the composition of immune cell subtypes such as Macrophages M1, NK cells, Mast cells, Plasma cells, Neutrophils, Dendritic cells, T cells CD8, and T cells CD4 within CESC, but also indicates TIL exclusion, dysfunction, and PD-1 and PD-L1 expression. Therefore, the IRGPI emerges as a promising biomarker not only for prognostic assessment but also for characterizing multiple immune features in CESC. Additionally, our results underscored the significant associations between the IRGPI and immune cell composition, TIL exclusion, and dysfunction, along with PD-1 and PD-L1 expression in the TIME. Conclusion: Consequently, the IRGPI stands out as a biomarker intimately connected to both the survival and TIME status of CESC patients, offering potential insights into immunotherapy strategies for CESC.

Loss of AR-regulated AFF3 contributes to prostate cancer progression and reduces ferroptosis sensitivity by downregulating ACSL4 based on single-cell sequencing analysis.

Prostate cancer (PCa) is one of the most common cancers affecting the health of men worldwide. Castration-resistant prostate cancer (CRPC), the advanced and refractory phase of prostate cancer, has multiple mechanisms of resistance to androgen deprivation therapy (ADT) such as AR mutations, aberrant androgen synthase, and abnormal expression of AR-related genes. Based on the research of the AR pathway, new drugs for the treatment of CRPC have been developed in clinical practice, such as Abiraterone and enzalutamide. However, many areas in this pathway are still worth exploring. In this study, single-cell sequencing analysis was utilized to scrutinize significant genes in the androgen receptor (AR) pathway related to CRPC. Our analysis of single-cell sequencing combined with bulk-cell sequencing revealed a substantial downregulation of AR-regulated AFF3 in CRPC. Overexpression of AFF3 restricted the proliferation and migration of prostate cancer cells whilst also increasing their sensitivity towards enzalutamide, while knockdown of AFF3 had the opposite effect. To elucidate the mechanism of tumor inhibition by AFF3, we applied GSVA and GSEA to investigate the metabolic pathways related to AFF3 and revealed that AFF3 had an impact on fatty acids metabolism and ferroptosis through the regulation of ACSL4 protein expression. Based on correlation analysis and flow cytometry, we can speculate that AFF3 can impact the sensitivity of the CRPC cell lines to the ferroptosis inducer (RSL3) by regulating ACSL4. Therefore, our findings may provide new insights into the mechanisms of drug resistance in CRPC, and AFF3 may serve as a novel prognostic biomarker in prostate cancer.

Function, drug resistance and prognostic effect of AKR1C2 in human cancer.

Aldo-keto reductases (ARKs), a group of reductases that rely on nicotinamide adenine dinucleotide (NADH) and nicotinamide adenine dinucleotide phosphate (NADPH) to catalyze carbonyl, are widely found in various organisms, which play an important role in the physiological and pathological processes of human. Aldo-keto reductase family 1 member C2 (AKR1C2) as a member of the human ARKs family, can regulate steroid hormones and is abnormally expressed in many cancers. According to whether the tumor can be affected by hormones, we divide malignancies into hormone-dependent and hormone-independent types. Studies have shown that AKR1C2 is involved in regulating tumor invasion, migration, and other malignant phenotypes, eliminating reactive oxygen species (ROS), promoting chemotherapy resistance of tumor cells, and has prognostic value in some cancers. Here, we focus on the role and clinical significance of AKR1C2 in different types of tumors.

Impact of the COVID-19 pandemic on the hospital attendance of patients with primary cervical cancer in Heilongjiang, China.

Information regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on cervical cancer in mainland China is lacking. We explored its impact on the hospital attendance of patients with primary cervical cancer. We included 1918 patients with primary cervical cancer who initially attended Harbin Medical University Cancer Hospital between January 23, 2019, and January 23, 2021. Attendance decreased by 31%, from 1135 in 2019 to 783 in 2020, mainly from January to June (𝜒2 = 73.362, P < .001). The percentage of patients detected by screening decreased from 12.1% in January-June 2019 to 5.8% in January-June 2020 (𝜒2 = 7.187, P = .007). Patients with stage I accounted for 28.4% in 2020 significantly lower than 36.6% in 2019 (𝜒2 = 14.085, P < .001), and patients with stage III accounted for 27.1% in 2020 significantly higher than 20.5% in 2019 (𝜒2 = 11.145, P < .001). Waiting time for treatment was extended from 8 days (median) in January-June and July-December 2019 to 16 days in January-June (𝜒2 = 74.674, P < .001) and 12 days in July-December 2020 (𝜒2 = 37.916, P < .001). Of the 179 patients who delayed treatment, 164 (91.6%) were for the reasons of the healthcare providers. Compared to 2019, the number of patients in Harbin or non-Harbin in Heilongjiang Province and outside the province decreased, and cross-regional medical treatment has been hindered. The COVID-19 pandemic has negatively impacted cervical cancer patient attendance at the initial phase. These results are solid evidence that a strategy and mechanism for the effective attendance of cervical cancer patients in response to public health emergencies is urgently needed.

Single-cell RNA sequencing reveals that HSD17B2 in cancer-associated fibroblasts promotes the development and progression of castration-resistant prostate cancer.

Castration-resistant prostate cancer (CRPC) responds poorly to existing therapy and appears as the lethal consequence of prostate cancer (PCa) progression. The tumour microenvironment (TME) has been thought to play a crucial role in CRPC progression. Here, we conducted single-cell RNA sequencing analysis on two CRPC and two hormone-sensitive prostate cancer (HSPC) samples to reveal potential leading roles in castration resistance. We described the single-cell transcriptional landscape of PCa. Higher cancer heterogeneity was explored in CRPC, with stronger cell cycling status and heavier copy number variant burden of luminal cells. Cancer-associated fibroblasts (CAFs), which are one of the most critical components of TME, demonstrated unique expression and cell-cell communication features in CRPC. A CAFs subtype with high expression of HSD17B2 in CRPC was identified with inflammatory features. HSD17B2 catalyses the conversion of testosterone and dihydrotestosterone to their less active forms, which was associated with steroid hormone metabolism in PCa tumour cells. However, the characteristics of HSD17B2 in PCa fibroblasts remained unknown. We found that HSD17B2 knockdown in CRPC-CAFs could inhibit migration, invasion, and castration resistance of PCa cells in vitro. Further study showed that HSD17B2 could regulate CAFs functions and promote PCa migration through the AR/ITGBL1 axis. Overall, our study revealed the important role of CAFs in the formation of CRPC. HSD17B2 in CAFs regulated AR activation and subsequent ITGBL1 secretion to promote the malignant behaviour of PCa cells. HSD17B2 in CAFs could serve as a promising therapeutic target for CRPC.

Large pneumothorax following thoracic and lumbar tumor surgery: Risk factors and management strategies.

Objective: Large pneumothorax is a rare but dangerous complication following thoracic and lumbar tumor surgery. There is little discussion about the features of large pneumothorax following spinal tumor surgery. The purpose of this study was to analyze the characteristics of postoperative pneumothorax, identify factors related to large pneumothorax, and propose a management algorithm for prevention, diagnosis, and treatment. Methods: Included in this retrospective study were 118 patients who developed pneumothorax after receiving thoracic and lumbar tumor surgery between January 2015 and October 2021. A measurement of lung compression ≥20% on chest CT or x-ray was defined as large pneumothorax, and potential risk factors for large pneumothorax were identified by univariate analysis. Results: Spinal tumor history and intraoperative blood loss were risk factors for large pneumothorax. The common symptoms of postoperative pneumothorax were chest pain, chest tightness and dyspnea. The mean longest transverse diameter of tumors was 6.63 ± 2.4 cm. En bloc resection was performed in 70 patients, with a mean operation time of 6.9 ± 2.5 h and mean intraoperative blood loss of 1771 ± 1387 ml. The most common pathologies were chondrosarcoma, giant cell tumors of bone, and neurogenic tumors. Conclusion: During surgery, an artificial dura mater patch and a prolene suture can be used to repair the pleural and lung defects. We recommend chest CT as the preferred method for identifying postoperative pneumothorax. If a patient presents severe dyspnea, a large pneumothorax or concurrent pleural effusion, application of chest drainage is strongly recommended.

Integrating single-cell and bulk transcriptomic analyses to develop a cancer-associated fibroblast-derived biomarker for predicting prognosis and therapeutic response in breast cancer.

Background: Cancer-associated fibroblasts (CAFs) contribute to the progression and treatment of breast cancer (BRCA); however, risk signatures and molecular targets based on CAFs are limited. This study aims to identify novel CAF-related biomarkers to develop a risk signature for predicting the prognosis and therapeutic response of patients with BRCA. Methods: CAF-related genes (CAFRGs) and a risk signature based on these genes were comprehensively analyzed using publicly available bulk and single-cell transcriptomic datasets. Modular genes identified from bulk sequencing data were intersected with CAF marker genes identified from single-cell analysis to obtain reliable CAFRGs. Signature CAFRGs were screened via Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. Multiple patient cohorts were used to validate the prognosis and therapeutic responsiveness of high-risk patients stratified based on the CAFRG-based signature. In addition, the relationship between the CAFRG-based signature and clinicopathological factors, tumor immune landscape, functional pathways, chemotherapy sensitivity and immunotherapy sensitivity was examined. External datasets were used and sample experiments were performed to examine the expression pattern of MFAP4, a key CAFRG, in BRCA. Results: Integrated analyses of single-cell and bulk transcriptomic data as well as prognostic screening revealed a total of 43 prognostic CAFRGs; of which, 14 genes (TLN2, SGCE, SDC1, SAV1, RUNX1, PDLIM4, OSMR, NT5E, MFAP4, IGFBP6, CTSO, COL12A1, CCDC8 and C1S) were identified as signature CAFRGs. The CAFRG-based risk signature exhibited favorable efficiency and accuracy in predicting survival outcomes and clinicopathological progression in multiple BRCA cohorts. Functional enrichment analysis suggested the involvement of the immune system, and the immune infiltration landscape significantly differed between the risk groups. Patients with high CAF-related risk scores (CAFRSs) exhibited tumor immunosuppression, enhanced cancer hallmarks and hyposensitivity to chemotherapy and immunotherapy. Five compounds were identified as promising therapeutic agents for high-CAFRS BRCA. External datasets and sample experiments validated the downregulation of MFAP4 and its strong correlation with CAFs in BRCA. Conclusions: A novel CAF-derived gene signature with favorable predictive performance was developed in this study. This signature may be used to assess prognosis and guide individualized treatment for patients with BRCA.

Excavation of Molecular Subtypes of Endometrial Cancer Based on DNA Methylation.

Tumor heterogeneity makes the diagnosis and treatment of endometrial cancer difficult. As an important modulator of gene expression, DNA methylation can affect tumor heterogeneity and, therefore, provide effective information for clinical treatment. In this study, we explored specific prognostic clusters based on 482 examples of endometrial cancer methylation data in the TCGA database. By analyzing 4870 CpG clusters, we distinguished three clusters with different prognostics. Differences in DNA methylation levels are associated with differences in age, grade, clinical pathological staging, and prognosis. Subsequently, we screened out 264 specific hypermethylation and hypomethylation sites and constructed a prognostic model for Bayesian network classification, which corresponded to the classification of the test set to the classification results of the train set. Since the tumor microenvironment plays a key role in determining immunotherapy responses, we conducted relevant analyses based on clusters separated from DNA methylation data to determine the immune function of each cluster. We also predicted their sensitivity to chemotherapy drugs. Specific classifications of DNA methylation may help to address the heterogeneity of previously existing molecular clusters of endometrial cancer, as well as to develop more effective, individualized treatments.

A novel prognostic model for prostate cancer based on androgen biosynthetic and catabolic pathways.

Prostate cancer (PCa) is one of the most common malignancies in males globally, and its pathogenesis is significantly related to androgen. As one of the important treatments for prostate cancer, androgen deprivation therapy (ADT) inhibits tumor proliferation by controlling androgen levels, either surgically or pharmacologically. However, patients treated with ADT inevitably develop biochemical recurrence and advance to castration-resistant prostate cancer which has been reported to be associated with androgen biosynthetic and catabolic pathways. Thus, gene expression profiles and clinical information of PCa patients were collected from TCGA, MSKCC, and GEO databases for consensus clustering based on androgen biosynthetic and catabolic pathways. Subsequently, a novel prognostic model containing 13 genes (AFF3, B4GALNT4, CD38, CHRNA2, CST2, ADGRF5, KLK14, LRRC31, MT1F, MT1G, SFTPA2, SLC7A4, TDRD1) was constructed by univariate cox regression, lasso regression, and multivariate cox regression. Patients were divided into two groups based on their risk scores: high risk (HS) and low risk (LS), and survival analysis was used to determine the difference in biochemical recurrence-free time between the two. The results were validated on the MSKCC dataset and the GEO dataset. Functional enrichment analysis revealed some pivotal pathways that may have an impact on the prognosis of patients including the CDK-RB-E2F axis, G2M checkpoint, and KRAS signaling. In addition, somatic mutation, immune infiltration, and drug sensitivity analyses were performed to further explore the characteristics of HS and LS groups. Besides, two potential therapeutic targets, BIRC5 and RHOC, were identified by us in prostate cancer. These results indicate that the prognostic model may serve as a predictive tool to guide clinical treatment and provide new insight into the basic research in prostate cancer.

CCNO mutation as a cause of primary ciliary dyskinesia: A case report.

BACKGROUND: Primary ciliary dyskinesia (PCD) is an uncommon and genetically diverse condition. According to reports, most patients had more than 50 visits before being diagnosed with PCD, and the age at diagnosis was mostly in preschool, with an average age of about (10.9 ± 14.4) years old. CCNO is a pathogenic gene that regulates the cell cycle, and its mutation is linked to the uncommon human genetic disorder PCD. Although the prevalence of the CCNO mutation is regarded to be exceptionally low, new reports of this mutation have increased in comparison to prior ones. PCD patients with CCNO are rare, and the incidence rate is no more than 2% in whole PCD patients. CASE SUMMARY: Here, we report a case of a young Chinese woman diagnosed with PCD, who was found to carry the CCNO gene by whole exon gene sequencing. In this case, a young non-smoking Chinese female exhibiting recurrent cough and sputum at birth. Chest computed tomography (CT) showed bronchiectasis with infection, and sinus CT showed chronic sinusitis. However, the patient had no visceral transposition and no history of infertility. Under electron microscope, it was found that cilia were short and reduced in number, and no power arm of cilia was observed. Whole exon sequencing analysis of the genome of the patient showed that the patient carried CCNO pathogenic gene, exon c.303C>A nonsense mutation and c.248_252dup frameshift mutation. Her clinical symptoms and CT images were improved after two months of treatment with aerosol inhalation and oral azithromycin. CONCLUSION: The results showed that CCNO is an important cause of PCD. More mutant genes that may contribute to genetically diverse disorders like PCD have been discovered as sequencing technology has advanced. Furthermore, the increase of genetic information makes it easier to diagnose uncommon diseases in clinical practice.

Efficacy and Safety of the Anti-PD-L1 mAb Socazolimab for Recurrent or Metastatic Cervical Cancer: a Phase I Dose-Escalation and Expansion Study.

PURPOSE: This study (ClinicalTrials.gov identifier, NCT03676959) is an open, phase I dose-escalation and expansion study investigating the safety and efficacy of the recombinant, fully human anti-programmed death ligand 1 (PD-L1) mAb socazolimab in patients diagnosed with recurrent or metastatic cervical cancer. PATIENTS AND METHODS: Patients received socazolimab every 2 weeks until disease progression. The study was divided into a dose-escalation phase and a dose-expansion phase. Safety and tolerability were primary endpoints of the dose-escalation phase. The primary endpoints of the dose-expansion phase were safety and the objective response rate (ORR) of the 5 mg/kg dose. Efficacy was assessed by the third-party independent review committee (IRC) using the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1). RESULTS: 104 patients were successfully enrolled into the study. Twelve patients were included in the dose-escalation phase, with one complete response and two partial responses in the 5 mg/kg treatment group. Ninety-two patients (5 mg/kg) were enrolled in the dose-expansion phase. Fifty-four patients (59.3%) had baseline PD-L1-positive tumor expression (combined positive score ≥1). ORR was 15.4% [95% confidence interval (CI), 8.7%-24.5%]. Median PFS was 4.44 months (95% CI, 2.37-5.75 months), and the median OS was 14.72 months (95% CI, 9.59-NE months). ORR of PD-L1-positive patients was 16.7%, and the ORR of PD-L1-negative patients was 17.9%. No treatment-related deaths occurred. CONCLUSIONS: Our study demonstrates that socazolimab has durable safety and efficacy for the treatment of recurrent or metastatic cervical cancer and exhibits a safety profile similar to other anti-PD-1/PD-L1 mAbs.

A Corrective Method for Different Hematocrit Values of Whole Blood Samples on the Detection of Procalcitonin.

BACKGROUND: We have explored that quantitative PCT detection can be conducted in different sample types (whole blood and/or plasma samples) with good correlation and consistency in clinical use. These findings reduce the sample volume and turnover time of PCT detection in clinical labs. However, different hematocrit (HCT) percentages of whole blood samples may affect the final results, especially abnormal hematocrit (HCT) percentages. To overcome this problem, we established a mathematical model to modify the whole blood test results and evaluated the effects of HCT correction. METHODS: First, we prepared a preliminary experiment - various hematocrit (HCT) percentages (15% - 65%) of whole blood samples with different PCT concentrations and established a mathematic model to correct the effects of PCT detection. Then, in this paper, we evaluated the consistency with Pearson's correlation and Kappa analysis between whole bloods detected by the i-Reader S system and plasma detected by the Biomerieux system. Besides, we prepared different HCT values about 15%, 40%, 60% of 9 samples with different PCT concentrations to evaluate the effects of HCT correction Results and Conclusions: Pearson's correlative studies and Kappa analysis indicated that PCT levels measured by i-Reader S (plasma & whole blood samples) were comparable to results from the VIDAS system, and HCT correction could improve consistency of PCT detection between whole blood and plasma. Analysis of samples with abnormal HCT values showed that the mathematical correction model could offset the influences of various HCT values.

Mesenchymal stem cell-derived extracellular vesicles alleviate cervical cancer by delivering microRNA-331-3p to reduce LIM zinc finger domain containing 2 methylation in tumor cells.

The aim of this study is to investigate if extracellular vesicles (EVs) from bone marrow mesenchymal stem cells (BMSCs) deliver microRNA (miR)-331-3p to regulate LIM zinc finger domain containing 2 (LIMS2) methylation in cervical cancer cells. Cervical cancer cells were incubated with EVs from BMSCs with altered expression of miR-331-3p, DNA methyltransferase 3 alpha (DNMT3A) or/and LIMS2 and then subjected to 5-ethynyl-2'-deoxyuridine, Transwell, flow cytometry and western blotting analyses. Dual-luciferase reporter assay was conducted to verify the binding between miR-331-3p and DNMT3A. A xenograft model was established to evaluate the effect of BMSC-derived EV-miR-331-3p on cervical tumor growth. miR-331-3p was lowly and DNMT3A was highly expressed in cervical cancer. BMSC-derived EVs delivered miR-331-3p to control the behaviors of cervical cancer cells. miR-331-3p inhibited the expression of DNMT3A by binding DNMT3A mRNA. DNMT3A promoted LIMS2 methylation and reduced the expression of LIMS2. Overexpression of DNMT3A or silencing of LIMS2 in BMSCs counteracted the tumor suppressive effects of miR-331-3p. BMSC-derived EV-miR-331-3p also inhibited the growth of cervical tumors in vivo. BMSC-derived EVs alleviate cervical cancer partially by delivering miR-331-3p to reduce DNMT3A-dependent LIMS2 methylation in tumor cells.

MRI radiomics in overall survival prediction of local advanced cervical cancer patients tread by adjuvant chemotherapy following concurrent chemoradiotherapy or concurrent chemoradiotherapy alone.

OBJECTIVES: To build radiomics based OS prediction tools for local advanced cervical cancer (LACC) patients treated by concurrent chemoradiotherapy (CCRT) alone or followed by adjuvant chemotherapy (ACT). And, to construct adjuvant chemotherapy decision aid. METHODS: 83 patients treated by ACT following CCRT and 47 patients treated by CCRT were included in the ACT cohort and non-ACT cohort. Radiomics features extracted from primary tumor area of T2-weighted MRI. Two radiomics models were built for ACT and non-ACT cohort in prediction of 3 years overall survival (OS). Elastic Net Regression was applied to the the ACT cohort, meanwhile least absolute shrinkage and selection operator plus support vector machine was applied to the non-ACT cohort. Cox regression models was used in clinical features selection and OS predicting nomograms building. RESULT: The two radiomics models predicted the 3 years OS of two cohorts. The receiver operator characteristics analysis was used to evaluate the 3 years OS prediction performance of the two radiomics models. The area under the curve of ACT and non-ACT cohort model were 0.832 and 0.879, respectively. Patients were stratified into low-risk group and high-risk group determined by radiomics models and nomograms, respectively. And, the low-risk group patients present significantly increased OS, progression-free survival, local regional control, and metastasis free survival compare with high-risk group (P < 0.05). Meanwhile the prognosis prediction performance of radiomics model and nomogram is superior to the prognosis prediction performance of Figo stage. CONCLUSION: The two radiomics model and the two nomograms is a prognosis predictor of LACC patients treated by CCRT alone or followed by ACT.

Signature involved in immune-related lncRNA pairs for predicting the immune landscape of cervical cancer.

BACKGROUND: Immune-related long non-coding RNAs (irlncRNAs) are known to hold great promise as superior biomarkers for cervical cancer-related immunotherapeutic response and the tumor immune microenvironment. Here, we constructed a prognostic signature based on irlncRNA pairs (IRLPs). METHODS: The samples were downloaded from The Cancer Genome Atlas and the Genotype-Tissue Expression databases. The least absolute shrinkage and selection operator Cox regression was performed to construct the prognostic model. Receiver operating characteristic (ROC) curve and nomogram were plotted to validate accuracy of the model. Next, we estimated the immune cell infiltration and the correlation between risk score and the expression of genes related to immune checkpoint. Finally, we calculated the score of the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and the half maximal inhibitory concentration of the chemotherapeutic agent to evaluate the response to immunotherapy and chemotherapy. RESULTS: We constructed a prognostic signature that consisted of 11 irlncRNAs. The area under the curve values of the 1-, 3-, and 5-year ROC curves were 0.844, 0.891, and 0.871, respectively. The expression of CTLA-4, HAVCR2, IDO1, LAG3, and PDCD1 were negatively correlated with risk scores. The score of TIDE in the high-risk group was significantly higher than in the low-risk group (P < 0.01). Patients in the low-risk subgroup were more sensitive to chemotherapeutic agents, such as axitinib and docetaxel, whereas patients in the low-risk subgroup were more sensitive to mitomycin C. CONCLUSION: Our study highlighted the value of the 11 IRLPs signatures to predict the prognosis and the response to immunotherapy and chemotherapeutics for patients with cervical cancer.

Covalent Biosensing Polymer Chain Reaction Enabling Periphery Blood Testing to Predict Tumor Invasiveness with a Platelet Procancerous Protein.

Periphery blood testing is an attractive and relatively less invasive way of early cancer screening. In this work, based on the latest understanding of the pivotal role of platelets in promoting cancer invasion, a method for detecting a procancerous protein overexpressed both on platelets and in cancer cells is developed. As a kinase, the enzymatic activity, abundance, and self-phosphorylation of this protein are all important factors influencing its procancerous activity. To simultaneously determine these three important biochemical parameters, electrochemical control is called upon to connect or disconnect a polymer chain reaction (PCR) primer with a small-molecule synthetic probe, and with the target protein, in a target-specific manner. The resulting PCR signal amplification greatly improves the sensitivity of the design and also enables direct detection of the protein and its catalytic activity as well as its self-phosphorylation in clinical periphery blood samples from hepatocellular carcinoma (HCC) patients. This may point to future application of the proposed method in the early screening of HCC to assist its diagnosis and treatment.

miR­30a­5p induces the adipogenic differentiation of bone marrow mesenchymal stem cells by targeting FAM13A/Wnt/ß­catenin signaling in aplastic anemia.

Aplastic anemia (AA) is a bone marrow failure syndrome with high morbidity and mortality. Bone marrow (BM)­mesenchymal stem cells (MSCs) are the main components of the BM microenvironment, and dysregulation of BM­MSC adipogenic differentiation is a pathologic hallmark of AA. MicroRNAs (miRNAs/miRs) are crucial regulators of multiple pathological processes such as AA. However, the role of miR­30a­5p in the modulation of BM­MSC adipogenic differentiation in AA remains unclear. The present study aimed to explore the effect of miR­30a­5p on AA BM­MSC adipogenic differentiation and the underlying mechanism. The levels of miR­30a­5p expression and family with sequence similarity 13, member A (FAM13A) mRNA expression in BM­MSCs were quantified using reverse transcription­quantitative (RT­q) PCR. The mRNA expression levels of adipogenesis­associated factors [fatty acid­binding protein 4 (FABP4), lipoprotein lipase (LPL), perilipin­1 (PLIN1), peroxisome proliferator­activated receptor γ (PPARγ) and CCAAT/enhancer binding protein α (C/EBPα)] were analyzed using RT­qPCR. Lipid droplet accumulation was evaluated using Oil Red O staining in BM­MSCs. The interaction between miR­30a­5p and the FAM13A 3'­untranslated region was identified by TargetScan, and a dual­luciferase reporter assay was used to confirm the interaction. The expression levels of FAM13A and Wnt/ß­catenin pathway­related proteins were examined via western blotting. The results showed that miR­30a­5p expression levels were significantly elevated in BM­MSCs from patients with AA compared with those in control subjects (iron deficiency anemia). miR­30a­5p expression levels were also significantly increased in adipose­induced BM­MSCs in a time­dependent manner. miR­30a­5p significantly promoted AA BM­MSC adipogenic differentiation, and significantly enhanced the mRNA expression levels of FABP4, LPL, PLIN1, PPARγ and C/EBPα as well as lipid droplet accumulation. miR­30a­5p was also demonstrated to target FAM13A in AA BM­MSCs. FAM13A significantly reduced BM­MSC adipogenic differentiation by activating the Wnt/ß­catenin signaling pathway. In conclusion, miR­30a­5p was demonstrated to serve a role in AA BM­MSC adipogenic differentiation by targeting the FAM13A/Wnt/ß­catenin signaling pathway. These findings suggest that miR­30a­5p may be a therapeutic target for AA.

Development of an esterase fluorescent probe based on naphthalimide-benzothiazole conjugation and its applications for qualitative detection of esterase in orlistat-treated biosamples.

Esterase is a large hydrolysis family, and widely distributed in many kinds of cells. It is responsible for multiple physiological and pathological functions including metabolism, gene expression. While abnormality of esterase is associated with many pathological activities in obesity, Wolman's disease, and cancer. Thereby, it is essential to design an effective tool for esterase in situ detection in biological systems. Herein, a novel fluorescent probe Y-1 for monitoring esterase in living cells was rationally designed. Probe Y-1 was synthesized by the conjugation between an acetylation of 4-hydroxy naphthalimide and benzothiazole group. Benzothiazole moiety is a typical Excited-state intramolecular proton transfer (ESIPT) controller. Acetate group was selected as the responsive site and ESIPT initiator. As the acetate group could block the ESIPT effect, the probe emits no fluorescence under the excitation of 455 nm. When binding with esterase, Y-1 shows distinct fluorescence with the peak at 560 nm with short time when ESIPT is on. Y-1 displays high sensitivity (LOD is 0.216 × 10-3 U/mL), fast response (within 5 min), high selectivity and photostability towards esterase. Furthermore, the %RSD (relative standard deviation) of within-day and day-to-day precision was no more than 13.0% and the accuracy ranged from -6.5 to -12.3%. Kinetics performance of Y-1 indicates that esterase has high affinity and hydrolysis to Y-1. For biological applications, our probe is a time-dependent visualizing esterase in living HepG2 and CoLo205 cells within 15 min. After the treatment of orlistat (1 and 5 µM) for inhibiting the activity of esterase, the bright fluorescence has also been detected using our probe. Furthermore, it has been successful in monitoring the esterase in zebrafish, the data were consistent with cellular phenomena. Therefore, all these findings indicate that the robust probe Y-1 is a useful qualitative tool for detecting esterase in biological systems.