Identification of Breast Cancer Subtypes Based on Endoplasmic Reticulum Stress-Related Genes and Analysis of Prognosis and Immune Microenvironment in Breast Cancer Patients.

Introduction: Endoplasmic reticulum stress (ERS) was a response to the accumulation of unfolded proteins and plays a crucial role in the development of tumors, including processes such as tumor cell invasion, metastasis, and immune evasion. However, the specific regulatory mechanisms of ERS in breast cancer (BC) remain unclear. Methods: In this study, we analyzed RNA sequencing data from The Cancer Genome Atlas (TCGA) for breast cancer and identified 8 core genes associated with ERS: ELOVL2, IFNG, MAP2K6, MZB1, PCSK6, PCSK9, IGF2BP1, and POP1. We evaluated their individual expression, independent diagnostic, and prognostic values in breast cancer patients. A multifactorial Cox analysis established a risk prognostic model, validated with an external dataset. Additionally, we conducted a comprehensive assessment of immune infiltration and drug sensitivity for these genes. Results: The results indicate that these eight core genes play a crucial role in regulating the immune microenvironment of breast cancer (BRCA) patients. Meanwhile, an independent diagnostic model based on the expression of these eight genes shows limited independent diagnostic value, and its independent prognostic value is unsatisfactory, with the time ROC AUC values generally below 0.5. According to the results of logistic regression neural networks and risk prognosis models, when these eight genes interact synergistically, they can serve as excellent biomarkers for the diagnosis and prognosis of breast cancer patients. Furthermore, the research findings have been confirmed through qPCR experiments and validation. Conclusion: In conclusion, we explored the mechanisms of ERS in BRCA patients and identified 8 outstanding biomolecular diagnostic markers and prognostic indicators. The research results were double-validated using the GEO database and qPCR.

Stratification and prognostic evaluation of breast cancer subtypes defined by obesity-associated genes.

OBJECTIVE: Breast cancer was the most common type of cancer among women worldwide, significantly impacting their quality of life and survival rates. And obesity has been widely accepted as an important risk factor for breast cancer. However, the specific mechanisms by which obesity affects breast cancer were still unclear. Therefore, studying the impact mechanisms of obesity as a risk factor for breast cancer was of utmost importance. METHODS: This study was based on TCGA breast cancer RNA transcriptomic data and the GeneCard obesity gene set. Through single and multiple factor Cox analysis and LASSO coefficient screening, seven hub genes were identified. The independent mechanisms of these seven hub genes were evaluated from various aspects, including survival data, genetic mutation data, single-cell sequencing data, and immune cell data. Additionally, the risk prognosis model and the neural network diagnostic model were established to further investigate these seven hub genes. In order to achieve precision treatment for breast cancer (BRCA), based on the RNA transcriptomic data of the seven genes, 1226 BRCA patients were divided into two subtypes: BRCA subtype 1 and BRCA subtype 2. By studying and comparing the immune microenvironment, investigating the mechanisms of differential gene expression, and exploring the mechanisms of subnetworks, we aim to explore the clinical differences in the presentation of BRCA subtypes and achieve precision treatment for BRCA. Finally, qRT-PCR experiments were conducted to validate the conclusions of the bioinformatics analysis. RESULTS: The 7 hub genes showed good diagnostic independence and can serve as excellent biomarkers for molecular diagnosis. However, they do not perform well as independent prognostic molecular markers for BRCA patients. When predicting the survival of BRCA patients, their AUC values at 1 year, 3 years, and 5 years are mostly below 0.5. Nevertheless, through the establishment of the risk prognosis model considering the combined effect of the seven hub genes, it was found that the survival prediction of BRCA patients can be significantly improved. The risk prognosis model, compared to the independent use of the seven hub genes as prognostic markers, achieved higher timeROC AUC values at 1 year, 3 years, and 5 years, with values of 0.651, 0.669, and 0.641 respectively. Additionally, the neural network diagnostic model constructed from the 7 genes performs well in diagnosing BRCA, with an AUC value of 0.94, accurately identifying BRCA patients. The two subtypes identified by the seven hub genes exhibited significant differences in survival period, with subtype 1 having a poor prognosis. The differential mechanisms between the two subtypes mainly originate from regulatory differences in the immune microenvironment. Finally, the results of this study's bioinformatics analysis were validated through qRT-PCR experiments. CONCLUSION: 7 hub genes serve as excellent independent biomarkers for molecular diagnosis, and the neural network diagnostic model can accurately distinguish BRCA patients. In addition, based on the expression levels of these seven genes in BRCA patients, two subtypes can be reliably identified: BRCA subtype 1 and BRCA subtype 2, and these two subtypes showed significant differences in BRCA patient survival prognosis, proportion of immune cells, and expression levels of immune cells. Among them, patients with subtype 1 of BRCA had a poor prognosis.

Mechanistic Investigation of Calcium Channel Regulation-Associated Genes in Pulmonary Arterial Hypertension and Signatures for Diagnosis.

Pulmonary arterial hypertension (PAH) is a severe cardiopulmonary disorder with complex causes. Calcium channel blockers have long been used in its treatment. Our study aimed to validate experimental results showing increased calcium ion concentration in PAH patients. We investigated the impact of genes related to calcium channel regulation on PAH development and developed an accurate diagnostic model. Clinical trial data from serum of 18 healthy individuals and 18 patients with PAH were retrospectively analyzed. Concentrations of calcium and potassium ions were determined and compared. Datasets were retrieved, selecting genes associated with calcium ion release. R packages processed the datasets, filtering 174 common genes, and conducting Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Six hub genes were identified, and nomogram and logistic regression prediction models were constructed. Random forest filtered cross genes, and a diagnostic model was developed and validated using an artificial neural network. The 174 intersection genes related to calcium ions showed significant correlations with biological processes, cellular components, and molecular functions. Six key genes were obtained by constructing a protein-protein interaction network. A diagnostic model with high accuracy (> 90%) and diagnostic capability (AUC = 0.98) was established using a neural network algorithm. This study validated the experimental results, identified key genes associated with calcium ions, and developed a highly accurate diagnostic model using a neural network algorithm. These findings provide insights into the role of calcium release genes in PAH and demonstrate the potential of the diagnostic model for clinical application. However, due to limitations in sample size and a lack of prognosis data, the regulatory mechanisms of calcium ions in PAH patients and their impact on the clinical prognosis of PAH patients still need further exploration in the future.

Leveraging Cas13a's trans-cleavage on RNA G-quadruplexes for amplification-free RNA detection.

In this study, we investigated Cas13a's efficacy in trans-cleaving RNA G-quadruplexes (rG4s) as an alternative to ssRNA reporters in CRISPR-Cas13a diagnostics. Our findings demonstrate enhanced efficiency due to the structural arrangement of rG4s. Implementing a simplified CRISPR-Cas13a system based on rG4, we identified SARS-CoV-2 infections in 25 patient samples within 1 hour without target pre-amplification.

Employing the Anchor DSPE-PEG as a Redox Probe for Ratiometric Electrochemical Detection of Surface Proteins on Extracellular Vesicles with Aptamers.

Quantitative analysis of surface proteins on extracellular vesicles (EVs) has been considered to be a crucial approach for reflecting the status of diseases. Due to the diverse composition of surface proteins on EVs and the interference from nonvesicular proteins, accurately detecting the expression of surface proteins on EVs remains a challenging task. While membrane affinity molecules have been widely employed as EVs capture probes to address this issue, their inherent biochemical properties have not been effectively harnessed. In this paper, we found that the electrochemical redox activity of the DSPE-PEG molecule was diminished upon its insertion into the membrane of EVs. This observation establishes the DSPE-PEG molecule modified on the Au electrode surface as a capture and a redox probe for the electrochemical detection of EVs. By utilizing methylene blue-labeled aptamers, the targeted surface proteins of EVs can be detected by recording the ratio of the oxidation peak current of methylene blue and DSPE-PEG. Without complicated signal amplification, the detection limit for EVs is calculated to be 8.11 × 102 particles/mL. Using this platform, we directly analyzed the expression of CD63 and HER2 proteins on the surface of EVs in human clinical plasma samples, demonstrating its significant potential in distinguishing breast cancer patients from healthy individuals.

A pan-cancer analysis of RNASEH1, a potential regulator of the tumor microenvironment

Background RNASEH1 (Ribonuclease H1) encodes an endonuclease that specifically degrades the RNA of RNA–DNA hybrids and acts in DNA replication and repair. Although there are many studies on RNASEH1, the research of RNASEH1 in cancers is still insufficient. Therefore, in order to clarify the physiological mechanism of RNASEH1 in tumor cells, we evaluated the role of RNASEH1 by combining The Cancer Genome Atlas (TCGA) pan-cancer data and Genotype-Tissue Expression (GTEx) normal tissue data. Methods RNASEH1 expression was analyzed by using RNAseq data from TCGA and the GTEx database. The Human Protein Atlas (HPA), GeneCards and STRING database were used to explore the protein information of RNASEH1. The prognostic value of RNASEH1 was analyzed by using the clinical survival data from TCGA. Differential analysis of RNASEH1 in different cancers was performed by using R package “DESeq2”, and enrichment analysis of RNASEH1 was conducted by using R package “clusterProfiler”. We downloaded the immune cell infiltration score of TCGA samples from published articles and online databases, and the correlation analysis between immune cell infiltration levels and RNASEH1 expression was performed. Not only that, we further evaluated the association of RNASEH1 with immune activating genes, immunosuppressive genes, chemokines and chemokine receptors. At the end of the article, the differential expression of RNASEH1 in pan-cancer was validated by using GSE54129, GSE40595, GSE90627, GSE106937, GSE145976 and GSE18672, and qRT-PCR was also performed for verification. Finding RNASEH1 was significantly overexpressed in 19 cancers and the overexpression was closely correlated with poor prognosis. Moreover, the expression of RNASEH1 was significantly correlated with the regulation of the tumor microenvironment (AU)

A pan-cancer analysis of RNASEH1, a potential regulator of the tumor microenvironment.

BACKGROUND: RNASEH1 (Ribonuclease H1) encodes an endonuclease that specifically degrades the RNA of RNA-DNA hybrids and acts in DNA replication and repair. Although there are many studies on RNASEH1, the research of RNASEH1 in cancers is still insufficient. Therefore, in order to clarify the physiological mechanism of RNASEH1 in tumor cells, we evaluated the role of RNASEH1 by combining The Cancer Genome Atlas (TCGA) pan-cancer data and Genotype-Tissue Expression (GTEx) normal tissue data. METHODS: RNASEH1 expression was analyzed by using RNAseq data from TCGA and the GTEx database. The Human Protein Atlas (HPA), GeneCards and STRING database were used to explore the protein information of RNASEH1. The prognostic value of RNASEH1 was analyzed by using the clinical survival data from TCGA. Differential analysis of RNASEH1 in different cancers was performed by using R package "DESeq2", and enrichment analysis of RNASEH1 was conducted by using R package "clusterProfiler". We downloaded the immune cell infiltration score of TCGA samples from published articles and online databases, and the correlation analysis between immune cell infiltration levels and RNASEH1 expression was performed. Not only that, we further evaluated the association of RNASEH1 with immune activating genes, immunosuppressive genes, chemokines and chemokine receptors. At the end of the article, the differential expression of RNASEH1 in pan-cancer was validated by using GSE54129, GSE40595, GSE90627, GSE106937, GSE145976 and GSE18672, and qRT-PCR was also performed for verification. FINDINGS: RNASEH1 was significantly overexpressed in 19 cancers and the overexpression was closely correlated with poor prognosis. Moreover, the expression of RNASEH1 was significantly correlated with the regulation of the tumor microenvironment. In addition, RNASEH1 expression was closely associated with immune cell infiltration, immune checkpoints, immune activators, immunosuppressive factors, chemokines and chemokine receptors. Finally, RNASEH1 also was closely associated with DNA-related physiological activities and mitochondrial-related physiological activities. INTERPRETATION: Our studying suggests that RNASEH1 is a potential cancer biomarker. And RNASEH1 may be able to regulate the tumor microenvironment by regulating the relevant physiological activities of mitochondrial and thereby regulating the occurrence and development of tumors. Thus, it could be used to develop new-targeted drugs of tumor therapy.

Handyfuge Microfluidic for On-Site Antibiotic Susceptibility Testing.

Low-cost, rapid, and accurate acquisition of minimum inhibitory concentrations (MICs) is key to limiting the development of antimicrobial resistance (AMR). Until now, conventional antibiotic susceptibility testing (AST) methods are typically time-consuming, high-cost, and labor-intensive, making them difficult to accomplish this task. Herein, an electricity-free, portable, and robust handyfuge microfluidic chip was developed for on-site AST, termed handyfuge-AST. With simply handheld centrifugation, the bacterial-antibiotic mixtures with accurate antibiotic concentration gradients could be generated in less than 5 min. The accurate MIC values of single antibiotics (including ampicillin, kanamycin, and chloramphenicol) or their combinations against Escherichia coli could be obtained within 5 h. To further meet the growing demands of point-of-care testing, we upgraded our handyfuge-AST with a pH-based colorimetric strategy, enabling naked eye recognition or intelligent recognition with a homemade mobile app. Through a comparative study of 60 clinical data (10 clinical samples corresponding to six commonly used antibiotics), the accurate MICs by handyfuge-AST with 100% categorical agreements were achieved compared to clinical standard methods (area under curves, AUCs = 1.00). The handyfuge-AST could be used as a low-cost, portable, and robust point-of-care device to rapidly obtain accurate MIC values, which significantly limit the progress of AMR.

Integrating CRISPR-Cas12a into a Microfluidic Dual-Droplet Device Enables Simultaneous Detection of HPV16 and HPV18.

Fast, simplified, and multiplexed detection of human papillomaviruses (HPVs) is of great importance for both clinical management and population screening. However, current HPV detection methods often require sophisticated instruments and laborious procedures to detect multiple targets. In this work, we developed a simple microfluidic dual-droplet device (M-D3) for the simultaneous detection of HPV16 and HPV18 by combining the CRISPR-Cas12a system and multiplexed recombinase polymerase amplification (RPA) assay. A new approach of combining pressure/vacuum was proposed for efficient droplet generation with minimal sample consumption. Two groups of droplets that separately encapsulate the relevant Cas12a/crRNA and the fluorescent green or red reporters are parallelly generated, followed by automatic imaging to discriminate the HPV subtypes based on the specific fluorescence of the droplets. The M-D3 platform performs with high sensitivity (∼0.02 nM for unamplified plasmids) and specificity in detecting HPV16 and HPV18 DNA. By combining the RPA and Cas12a assay, M-D3 allows on-chip detection of HPV16 and HPV18 DNA simultaneously within 30 min, reaching a detection limit of 10-18 M (∼1 copy/reaction). Moreover, the outstanding performance of M-D3 was validated in testing 20 clinical patient samples with HPV infection risk, showing a sensitivity of 92.3% and a specificity of 100%. By integrating the dual-droplet generator, CRISPR-Cas12a, and multiplexed RPA, the M-D3 platform provides an efficient way to discriminate the two most harmful HPV subtypes and holds great potential in the applications of multiplexed nucleic acid testing.

Coupling CRISPR/Cas12a and Recombinase Polymerase Amplification on a Stand-Alone Microfluidics Platform for Fast and Parallel Nucleic Acid Detection.

Timely identification of human papillomavirus (HPV) infection is crucial for the prevention of cervical cancer. Current HPV detection methods mainly rely on polymerase chain reaction (PCR), which often requires bulky equipment and a long assay time. In this work, we report a heating-membrane-assisted multiplexed microfluidics platform that couples recombinase polymerase amplification (RPA) and CRISPR technology (termed M3-CRISPR) for fast and low-cost detection of multiple HPV subtypes. The heating membrane can provide convenient temperature control for the on-chip RPA and CRISPR assays. This stand-alone system allows simultaneous detection of HPV16 and HPV18 with high specificity and detection sensitivity (0.5 nM and 1 × 10-18 M for unamplified and amplified plasmids, respectively) in 30 min with a fluorescence-based readout. Furthermore, we introduced an optimized lateral flow dipstick (LFD) into the portable system to allow visualized detection of HPV DNA. The LFD-based readout also reached a detection sensitivity of 1 × 10-18 M for amplified plasmids and realized successful detection of HPV subtypes in the clinical samples. Finally, we established an automatic microfluidic system that enables the sample-in-answer-out detection of HPV subtypes. We believe that this fast, convenient, and affordable molecular diagnostic platform can serve as a useful tool in point-of-care testing of HPV or other pathogens.

Elucidating common pathogenic transcriptional networks in infective endocarditis and sepsis: integrated insights from biomarker discovery and single-cell RNA sequencing.

Background: Infective Endocarditis (IE) and Sepsis are two closely related infectious diseases, yet their shared pathogenic mechanisms at the transcriptional level remain unclear. This research gap poses a barrier to the development of refined therapeutic strategies and drug innovation. Methods: This study employed a collaborative approach using both microarray data and single-cell RNA sequencing (scRNA-seq) data to identify biomarkers for IE and Sepsis. It also offered an in-depth analysis of the roles and regulatory patterns of immune cells in these diseases. Results: We successfully identified four key biomarkers correlated with IE and Sepsis, namely CD177, IRAK3, RNASE2, and S100A12. Further investigation revealed the central role of Th1 cells, B cells, T cells, and IL-10, among other immune cells and cytokines, in the pathogenesis of these conditions. Notably, the small molecule drug Matrine exhibited potential therapeutic effects by targeting IL-10. Additionally, we discovered two Sepsis subgroups with distinct inflammatory responses and therapeutic strategies, where CD177 demonstrated significant classification value. The reliability of CD177 as a biomarker was further validated through qRT-PCR experiments. Conclusion: This research not only paves the way for early diagnosis and treatment of IE and Sepsis but also underscores the importance of identifying shared pathogenic mechanisms and novel therapeutic targets at the transcriptional level. Despite limitations in data volume and experimental validation, these preliminary findings add new perspectives to our understanding of these complex diseases.

Microfluidic space coding for multiplexed nucleic acid detection via CRISPR-Cas12a and recombinase polymerase amplification.

Fast, inexpensive, and multiplexed detection of multiple nucleic acids is of great importance to human health, yet it still represents a significant challenge. Herein, we propose a nucleic acid testing platform, named MiCaR, which couples a microfluidic device with CRISPR-Cas12a and multiplex recombinase polymerase amplification. With only one fluorescence probe, MiCaR can simultaneously test up to 30 nucleic acid targets through microfluidic space coding. The detection limit achieves 0.26 attomole, and the multiplexed assay takes only 40 min. We demonstrate the utility of MiCaR by efficiently detecting the nine HPV subtypes targeted by the 9-valent HPV vaccine, showing a sensitivity of 97.8% and specificity of 98.1% in the testing of 100 patient samples at risk for HPV infection. Additionally, we also show the generalizability of our approach by successfully testing eight of the most clinically relevant respiratory viruses. We anticipate this effective, undecorated and versatile platform to be widely used in multiplexed nucleic acid detection.

G-triplex: A new type of CRISPR-Cas12a reporter enabling highly sensitive nucleic acid detection.

CRISPR-Cas12a (Cpf1) trans-cleaves ssDNA and this feature has been widely harnessed for nucleic acid detection. Herein, we introduce a new type of Cas12a reporter, G-triplex (G3), and a highly sensitive biosensor termed G-CRISPR. We proved that Cas12a trans-cleaves G3 structures in about 10 min and G3 can serve as an excellent reporter based on the cleavage-induced high-order structure disruption. G3 reporter improves the analytical sensitivity up to 20 folds, enabling the detection of unamplified and amplified DNA as low as 50 pmol and 0.1 amol (one copy/reaction), respectively. G-CRISPR has been utilized for the analysis of 27 PCR-amplified patient samples with HPV infection risk based on both fluorescence and lateral flow assays, resulting in 100% concordance between the two. In comparison with the clinical results, it achieved overall specificity and sensitivity of 100% and 94.7%, respectively. These results suggest that G-CRISPR can serve as a rapid, sensitive, and reliable biosensor, and could further expand the CRISPR toolbox in biomedical diagnostics.

Single Cell Chemical Proteomics with Membrane-Permeable Activity-Based Probe for Identification of Functional Proteins in Lysosome of Tumors.

Proteomics at single-cell resolution can help to identify the heterogeneity among cell populations, shows more and more significance in current chemistry and biology. In this work, we demonstrated a new single cell chemical proteomic (SCCP) strategy with a membrane-permeable activity-based probe (ABP) to characterize the functional proteins in lysosome located in the cytosol. The ABP targeted to the cysteine cathepsin family protein, CpFABP-G, was designed for cysteine cathepsins labeling. The labeled HeLa cell of a cancer cell line was injected into a capillary and was lysed by SDS solution with heating. The lysate was then online readout by capillary electrophoresis-laser-induced fluorescence method. Due to the employment of highly specified ABP kicking out the uncorrelated proteins, the expression of cysteine cathepsins in individual HeLa cells was easily detected, and heterogeneity among those HeLa cells was readily discriminated. Further work was concentrated on SCCP analysis of the mouse leukemia cell of monocyte macrophage (RAW264.7). It was for the first time identifying two expression modes of cysteine cathepsins in RAW264.7, which could be undermined by the analysis of cell populations. We believed that SCCP would be one of the powerful alternatives for proteomics at single-cell resolution.

A microfluidic digital single-cell assay for the evaluation of anticancer drugs.

Digital single-cell assays hold high potentials for the analysis of cell apoptosis and the evaluation of chemotherapeutic reagents for cancer therapy. In this paper, a microfluidic hydrodynamic trapping system was developed for digital single-cell assays with the capability of monitoring cellular dynamics over time. The microfluidic chip was designed with arrays of bypass structures for trapping individual cells without the need for surface modification, external electric force, or robotic equipment. After optimization of the bypass structure by both numerical simulations and experiments, a single-cell trapping efficiency of ∼90 % was achieved. We demonstrated the method as a digital single-cell assay for the evaluation of five clinically established chemotherapeutic reagents. As a result, the half maximal inhibitory concentration (IC50) values of these compounds could be conveniently determined. We further modeled the gradual decrease of active drugs over time which was often observed in vivo after an injection to investigate cell apoptosis against chemotherapeutic reagents. The developed method provided a valuable means for cell apoptotic analysis and evaluation of anticancer drugs.

Single-cell chemical proteomics with an activity-based probe: identification of low-copy membrane proteins on primary neurons.

We propose a novel single-cell chemical proteomics (SCCP) strategy to profile low-abundance membrane proteins in single cells. In this approach, the membrane protein GB1 and its splicing variants were targeted on cultured cell lines and primary neurons using a specifically designed activity-based probe. The functionally labeled single cells were encapsulated in individual buffer droplets on a PDMS microwell array, and were further picked up one at a time and loaded into a capillary electrophoresis system for cell lysis, separation, and laser-induced fluorescence detection of the targeted proteins. The results revealed the expression of GB1 splicing variants in HEK and MEF cells, which was previously only suggested at the transcriptional level. We further applied this method to investigate single primary cells and observed significant heterogeneity among individual mouse cerebellar granule neurons. Interference experiments with GB1 antagonist and agonist validated this observation.