Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer

Layered assembly of PEGylated graphene oxide and Mg-Al layered double hydroxide nanosheets with superior adsorption capacity and selective isolation of hemoglobin

This study developed a novel organic-inorganic hybrid composite, shortly as GO-PEG-LDHs, by self-assembly of exfoliated Mg-Al layer double hydroxide (LDHs) on the polyethylene glycol (PEG) grafted graphene oxide (GO) to achieve the selective adsorption of hemoglobin (Hb). The prepared GO-PEG-LDHs has a hierarchical structure with a homogeneous loading of exfoliated LDHs nano-sheets on its surface. The adsorption test reveals that GO-PEG-LDHs exhibits an adsorption efficiency of 95.03% for Hb and 3.45% for bovine serum albumin (BSA). The adsorption of Hb follows the Langmuir model, with an ultrahigh adsorption capacity of 55248.6 mg/g, which is higher than any previously reported materials. Meanwhile, the adsorbed Hb can be efficiently recovered through elution with a 50 mM Tris-HCl buffer, with an elution efficiency of 80.77%. Circular dichroism (CD) spectra indicate no conformational change for Hb during the process of adsorption/desorption. Furthermore, the composite demonstrates the ability to selectively isolate Hb in the presence of interfering protein BSA, indicating its potential for practical applications.

From degraded to deciphered: ATAC-seq's application potential in forensic diagnosis

In recent years, molecular biology-based diagnostic techniques have made remarkable strides and are now extensively utilized in clinical practice, providing invaluable insights for disease diagnosis and treatment. However, forensic medicine, especially forensic pathology, has witnessed relatively limited progress in the application of molecular biology technologies. A significant challenge in employing molecular techniques for forensic diagnoses lies in the quantitative and qualitative changes observed in diagnostic markers due to sample degradation-a recognized and formidable obstacle. Inspired by the success of DNA sequencing in forensic practices, which enables accurate individual identification even in cases involving degraded and deteriorated tissues and organs, we propose the application of the assay for transposase-accessible chromatin with sequencing (ATAC-seq) to identify targets at the transcriptional onset, exploring chromatin and DNA-level alterations for injury and disease inference in forensic samples. This study employs ATAC-seq to explore alterations in chromatin accessibility post-injury and their subsequent changes over a 2-h degradation period, employing traumatic brain injury (TBI) as a representative model. Our findings reveal high sensitivity of chromatin accessibility sites to injury, evidenced by shifts in thousands of peak positions post-TBI. Remarkably, these alterations remain largely unaffected by early degradation. Our results robustly endorse the notion that integrating and incorporating these specific loci for injury and disease diagnosis in forensic samples holds tremendous promise for practical application. We further validated the above results using human cortical tissue, which supported that early degradation did not significantly affect chromatin accessibility. This pioneering advancement in molecular diagnostic techniques may revolutionize the field of forensic science, especially forensic pathology.

Exploring novel protein-based biomarkers for advancing breast cancer diagnosis: A review

This review provides a contemporary examination of the evolving landscape of breast cancer (BC) diagnosis, focusing on the pivotal role of novel protein-based biomarkers. The overview begins by elucidating the multifaceted nature of BC, exploring its prevalence, subtypes, and clinical complexities. A critical emphasis is placed on the transformative impact of proteomics, dissecting the proteome to unravel the molecular intricacies of BC. Navigating through various sources of samples crucial for biomarker investigations, the review underscores the significance of robust sample processing methods and their validation in ensuring reliable outcomes. The central theme of the review revolves around the identification and evaluation of novel protein-based biomarkers. Cutting-edge discoveries are summarised, shedding light on emerging biomarkers poised for clinical application. Nevertheless, the review candidly addresses the challenges inherent in biomarker discovery, including issues of standardisation, reproducibility, and the complex heterogeneity of BC. The future direction section envisions innovative strategies and technologies to overcome existing challenges. In conclusion, the review summarises the current state of BC biomarker research, offering insights into the intricacies of proteomic investigations. As precision medicine gains momentum, the integration of novel protein-based biomarkers emerges as a promising avenue for enhancing the accuracy and efficacy of BC diagnosis. This review serves as a compass for researchers and clinicians navigating the evolving landscape of BC biomarker discovery, guiding them toward transformative advancements in diagnostic precision and personalised patient care.

An amino-rich polymer-coated magnetic nanomaterial for ultra-rapid separation of phosphorylated peptides in the serum of Parkinson's disease patients

The elucidation of disease pathogenesis can be achieved by analyzing the low-abundance phosphopeptides in organisms. Herein, we developed a novel and easy-to-prepare polymer-coated nanomaterial. By improving the hydrophilicity and spatial conformation of the material, we effectively enhanced the adsorption of phosphopeptides and demonstrated excellent enrichment properties. The material was able to successfully enrich the phosphopeptides in only 1 min. Meanwhile, the material has high selectivity (1:2000), good loading capacity (100 μg/mg), excellent sensitivity (0.5 fmol), and great acid and alkali resistance. In addition, the material was applied to real samples, and 70 phosphopeptides were enriched from the serum of Parkinson's disease (PD) patients and 67 phosphopeptides were enriched from the serum of normal controls. Sequences Logo showed that PD is probably associated with threonine, glutamate, serine, and glutamine. Finally, gene ontology (GO) analysis was performed on phosphopeptides enriched in PD patients' serum. The results showed that PD patients expressed abnormal expression of the cholesterol metabolic process and cell-matrix adhesion in the biological process (BP), endoplasmic reticulum and lipoprotein in the cellular component (CC), and heparin-binding, lipid-binding, and receptor-binding in the molecular function (MF) as compared with normal individuals. All the experiments indicate that the nanomaterials have great potential in proteomics studies.

Identification and Quantification of Human Relaxin Proteins by Immunoaffinity-Mass Spectrometry

The human relaxins belong to the Insulin/IGF/Relaxin superfamily of peptide hormones, and their physiological function is primarily associated with reproduction. In this study, we focused on a prostate tissue-specific relaxin RLN1 (REL1_HUMAN protein) and a broader tissue specificity RLN2 (REL2_HUMAN protein). Due to their structural similarity, REL1 and REL2 proteins were collectively named a 'human relaxin protein' in previous studies and were exclusively measured by immunoassays. We hypothesized that the highly selective and sensitive immunoaffinity-selected reaction monitoring (IA-SRM) assays would reveal the identity and abundance of the endogenous REL1 and REL2 in biological samples and facilitate the evaluation of these proteins for diagnostic applications. High levels of RLN1 and RLN2 transcripts were found in prostate and breast cancer cell lines by RT-PCR. However, no endogenous prorelaxin-1 or mature REL1 were detected by IA-SRM in cell lines, seminal plasma, or blood serum. The IA-SRM assay of REL2 demonstrated its undetectable levels (<9.4 pg/mL) in healthy control female and male sera and relatively high levels of REL2 in maternal sera across different gestational weeks (median 331 pg/mL; N = 120). IA-SRM assays uncovered potential cross-reactivity and nonspecific binding for relaxin immunoassays. The developed IA-SRM assays will facilitate the investigation of the physiological and pathological roles of REL1 and REL2 proteins.

Recent Advances in Lateral Flow Assays for Viral Protein Detection with Nanomaterial-Based Optical Sensors

Controlling the progression of contagious diseases is crucial for public health management, emphasizing the importance of early viral infection diagnosis. In response, lateral flow assays (LFAs) have been successfully utilized in point-of-care (POC) testing, emerging as a viable alternative to more traditional diagnostic methods. Recent advancements in virus detection have primarily leveraged methods such as reverse transcription-polymerase chain reaction (RT-PCR), reverse transcription-loop-mediated isothermal amplification (RT-LAMP), and the enzyme-linked immunosorbent assay (ELISA). Despite their proven effectiveness, these conventional techniques are often expensive, require specialized expertise, and consume a significant amount of time. In contrast, LFAs utilize nanomaterial-based optical sensing technologies, including colorimetric, fluorescence, and surface-enhanced Raman scattering (SERS), offering quick, straightforward analyses with minimal training and infrastructure requirements for detecting viral proteins in biological samples. This review describes the composition and mechanism of and recent advancements in LFAs for viral protein detection, categorizing them into colorimetric, fluorescent, and SERS-based techniques. Despite significant progress, developing a simple, stable, highly sensitive, and selective LFA system remains a formidable challenge. Nevertheless, an advanced LFA system promises not only to enhance clinical diagnostics but also to extend its utility to environmental monitoring and beyond, demonstrating its potential to revolutionize both healthcare and environmental safety.

Electrochemical immunosensing of tumor markers

The rising incidence and mortality rates of cancer have led to a growing need for precise and prompt early diagnostic approaches to effectively combat this disease. However, traditional methods employed for detecting tumor cells, such as histopathological and immunological techniques, are often associated with complex procedures, high analytical expenses, elevated false positive rates, and a dependence on experienced personnel. Tracking tumor markers is recognized as one of the most effective approaches for early detection and prognosis of cancer. While onco-biomarkers can also be produced in normal circumstances, their concentration is significantly elevated when tumors are present. By monitoring the levels of these markers, healthcare professionals can obtain valuable insights into the presence, progression, and response to treatment of cancer, aiding in timely diagnosis and effective management. This review aims to provide researchers with a comprehensive overview of the recent advancements in tumor markers using electrochemical immunosensors. By highlighting the latest developments in this field, researchers can gain a general understanding of the progress made in the utilization of electrochemical immunosensors for detecting tumor markers. Furthermore, this review also discusses the current limitations associated with electrochemical immunosensors and offers insights into paving the way for further improvements and advancements in this area of research.

N-glycan biosignatures as a potential diagnostic biomarker for early-stage pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival rate of less than 10%, owing to its late-stage diagnosis. Early detection of pancreatic cancer (PC) can significantly increase survival rates.

AIM

To identify the serum biomarker signatures associated with early-stage PDAC by serum N-glycan analysis.

METHODS

An extensive patient cohort was used to determine a biomarker signature, including patients with PDAC that was well-defined at an early stage (stages I and II). The biomarker signature was derived from a case-control study using a case-cohort design consisting of 29 patients with stage I, 22 with stage II, 4 with stage III, 16 with stage IV PDAC, and 88 controls. We used multiparametric analysis to identify early-stage PDAC N-glycan signatures and developed an N-glycan signature-based diagnosis model called the "Glyco-model".

RESULTS

The biomarker signature was created to discriminate samples derived from patients with PC from those of controls, with a receiver operating characteristic area under the curve of 0.86. In addition, the biomarker signature combined with cancer antigen 19-9 could discriminate patients with PDAC from controls, with a receiver operating characteristic area under the curve of 0.919. Glyco-model demonstrated favorable diagnostic performance in all stages of PC. The diagnostic sensitivity for stage I PDAC was 89.66%.

CONCLUSION

In a prospective validation study, this serum biomarker signature may offer a viable method for detecting early-stage PDAC.

Glycan-specific molecularly imprinted polymers towards cancer diagnostics: merits, applications, and future perspectives

Aberrant glycans are a hallmark of cancer states. Notably, emerging evidence has demonstrated that the diagnosis of cancers with tumour-specific glycan patterns holds great potential to address unmet medical needs, especially in improving diagnostic sensitivity and selectivity. However, despite vast glycans having been identified as potent markers, glycan-based diagnostic methods remain largely limited in clinical practice. There are several reasons that prevent them from reaching the market, and the lack of anti-glycan antibodies is one of the most challenging hurdles. With the increasing need for accelerating the translational process, numerous efforts have been made to find antibody alternatives, such as lectins, boronic acids and aptamers. However, issues concerning affinity, selectivity, stability and versatility are yet to be fully addressed. Molecularly imprinted polymers (MIPs), synthetic antibody mimics with tailored cavities for target molecules, hold the potential to revolutionize this dismal progress. MIPs can bind a wide range of glycan markers, even those without specific antibodies. This capacity effectively broadens the clinical applicability of glycan-based diagnostics. Additionally, glycoform-resolved diagnosis can also be achieved through customization of MIPs, allowing for more precise diagnostic applications. In this review, we intent to introduce the current status of glycans as potential biomarkers and critically evaluate the challenges that hinder the development of in vitro diagnostic assays, with a particular focus on glycan-specific recognition entities. Moreover, we highlight the key role of MIPs in this area and provide examples of their successful use. Finally, we conclude the review with the remaining challenges, future outlook, and emerging opportunities.

Saliva as a potential non-invasive liquid biopsy for early and easy diagnosis/prognosis of head and neck cancer

Head and neck squamous cell carcinomas (HNSCCs) are the most devastating diseases in India and southeast Asia. It is a preventable and curable disease if detected early. Tobacco and alcohol consumption are the two major risk-factors but infection of high-risk HPVs are also associated with development of predominantly oral and oropharyngeal carcinomas. Interestingly, unlike cervical cancer, HPV-induced HNSCCs show good prognosis and better survival in contrast, majority of tobacco-associated HPV-ve HNSCCs are highly aggressive with poor clinical outcome. Biomarker analysis in circulatory body-fluids for early cancer diagnosis, prognosis and treatment monitoring are becoming important in clinical practice. Early diagnosis using non-invasive saliva for oral or other diseases plays an important role in successful treatment and better prognosis. Saliva mirrors the body's state of health as it comes into direct contact with oral lesions and needs no trained manpower to collect, making it a suitable bio-fluid of choice for screening. Saliva can be used to detect not only virus, bacteria and other biomarkers but variety of molecular and genetic markers for an early detection, treatment and monitoring cancer and other diseases. The performance of saliva-based diagnostics are reported to be highly (≥95 %) sensitive and specific indicating the test's ability to correctly identify true positive or negative cases. This review focuses on the potentials of saliva in the early detection of not only HPV or other pathogens but also identification of highly reliable gene mutations, oral-microbiomes, metabolites, salivary cytokines, non-coding RNAs and exosomal miRNAs. It also discusses the importance of saliva as a reliable, cost-effective and an easy alternative to invasive procedures.

Serum IGFBP-1 as a promising diagnostic and prognostic biomarker for colorectal cancer

Our previous study showed that levels of circulating insulin-like growth factor binding protein-1 (IGFBP-1) has potential diagnostic value for early-stage upper gastrointestinal cancers. This study aimed to assess whether serum IGFBP-1 is a potential diagnostic and prognostic biomarker for CRC patients. IGFBP-1 mRNA expression profile data of peripheral blood in colorectal cancer (CRC) patients were downloaded and analyzed from Gene Expression Omnibus database. We detected serum IGFBP-1 in 138 CRC patients and 190 normal controls using enzyme-linked immunosorbent assay. Blood IGFBP-1 mRNA levels were higher in CRC patients than those in normal controls (P = 0.027). In addition, serum IGFBP-1 protein levels in the CRC group were significantly higher than those in normal control group (P < 0.0001). Serum IGFBP-1 demonstrated better diagnostic accuracy for all CRC and early-stage CRC, respectively, when compared with carcinoembryonic antigen (CEA), carbohydrate antigen19-9 (CA 19-9) or the combination of CEA and CA19-9. Furthermore, Cox multivariate analysis revealed that serum IGFBP-1 was an independent prognostic factor for OS (HR = 2.043, P = 0.045). Our study demonstrated that serum IGFBP-1 might be a potential biomarker for the diagnosis and prognosis of CRC. In addition, the nomogram might be helpful to predict the prognosis of CRC.

Comprehensive analysis of PSME3: from pan-cancer analysis to experimental validation

PSME3 plays a significant role in tumor progression. However, the prognostic value of PSME3 in pan-cancer and its involvement in tumor immunity remain unclear. We conducted a comprehensive study utilizing extensive RNA sequencing data from the TCGA (The Cancer Genome Atlas) and GTEx (Genotype-Tissue Expression) databases. Our research revealed abnormal expression levels of PSME3 in various cancer types and unveiled a correlation between high PSME3 expression and adverse clinical outcomes, especially in cancers like liver cancer (LIHC) and lung adenocarcinoma (LUAD). Functional enrichment analysis highlighted multiple biological functions of PSME3, including its involvement in protein degradation, immune responses, and stem cell regulation. Moreover, PSME3 showed associations with immune infiltration and immune cells in the tumor microenvironment, indicating its potential role in shaping the cancer immune landscape. The study also unveiled connections between PSME3 and immune checkpoint expression, with experimental validation demonstrating that PSME3 positively regulates CD276. This suggests that PSME3 could be a potential therapeutic target in immunotherapy. Additionally, we predicted sensitive drugs targeting PSME3. Finally, we confirmed in both single-factor Cox and multiple-factor Cox regression analyses that PSME3 is an independent prognostic factor. We also conducted preliminary validations of the impact of PSME3 on cell proliferation and wound healing in liver cancer. In summary, our study reveals the multifaceted role of PSME3 in cancer biology, immune regulation, and clinical outcomes, providing crucial insights for personalized cancer treatment strategies and the development of immunotherapy.

Deep Learning-Assisted Single-Molecule Detection of Protein Post-translational Modifications with a Biological Nanopore

Protein post-translational modifications (PTMs) play a crucial role in countless biological processes, profoundly modulating protein properties on both spatial and temporal scales. Protein PTMs have also emerged as reliable biomarkers for several diseases. However, only a handful of techniques are available to accurately measure their levels, capture their complexity at a single molecule level, and characterize their multifaceted roles in health and disease. Nanopore sensing provides high sensitivity for the detection of low-abundance proteins, holding the potential to impact single-molecule proteomics and PTM detection, in particular. Here, we demonstrate the ability of a biological nanopore, the pore-forming toxin aerolysin, to detect and distinguish α-synuclein-derived peptides bearing single or multiple PTMs, namely, phosphorylation, nitration, and oxidation occurring at different positions and in various combinations. The characteristic current signatures of the α-synuclein peptide and its PTM variants could be confidently identified by using a deep learning model for signal processing. We further demonstrate that this framework can quantify α-synuclein peptides at picomolar concentrations and detect the C-terminal peptides generated by digestion of full-length α-synuclein. Collectively, our work highlights the advantage of using nanopores as a tool for simultaneous detection of multiple PTMs and facilitates their use in biomarker discovery and diagnostics.

Engineered poly(A)-surrogates for translational regulation and therapeutic biocomputation in mammalian cells

Here, we present a gene regulation strategy enabling programmable control over eukaryotic translational initiation. By excising the natural poly-adenylation (poly-A) signal of target genes and replacing it with a synthetic control region harboring RNA-binding protein (RBP)-specific aptamers, cap-dependent translation is rendered exclusively dependent on synthetic translation initiation factors (STIFs) containing different RBPs engineered to conditionally associate with different eIF4F-binding proteins (eIFBPs). This modular design framework facilitates the engineering of various gene switches and intracellular sensors responding to many user-defined trigger signals of interest, demonstrating tightly controlled, rapid and reversible regulation of transgene expression in mammalian cells as well as compatibility with various clinically applicable delivery routes of in vivo gene therapy. Therapeutic efficacy was demonstrated in two animal models. To exemplify disease treatments that require on-demand drug secretion, we show that a custom-designed gene switch triggered by the FDA-approved drug grazoprevir can effectively control insulin expression and restore glucose homeostasis in diabetic mice. For diseases that require instantaneous sense-and-response treatment programs, we create highly specific sensors for various subcellularly (mis)localized protein markers (such as cancer-related fusion proteins) and show that translation-based protein sensors can be used either alone or in combination with other cell-state classification strategies to create therapeutic biocomputers driving self-sufficient elimination of tumor cells in mice. This design strategy demonstrates unprecedented flexibility for translational regulation and could form the basis for a novel class of programmable gene therapies in vivo.

Exploiting the design of surface plasmon resonance interfaces for better diagnostics: A perspective review

Surface Plasmon Resonance based-sensors are promising tools for precision diagnostics as they can provide tests useful for early and, whenever possible, non-invasive disease detection and monitoring. The design of novel, robust and effective interfaces enabling the sensing of a variety of molecular interactions in a highly selective and sensitive manner is a necessary step to obtain both accurate and reliable detection by SPR. This review covers the recent research efforts in this area, specifically emphasizing well-designed interfaces and applications in real-life samples. In particular, after a short introduction which identifies some of the critical challenges, the emerging strategies for the integration of the linker, the metal substrate and the recognition element on the sensing interface will be explored and discussed in three sections, as well as the opportunities for building SPR biosensors, easy to use, and with excellent sensitivities. Finally, a summary of some of the more promising and latest diagnostic applications will be provided, presenting a new window into the near-future perspectives.

Miniaturized microarray-format digital ELISA enabled by lithographic protein patterning

The search for reliable protein biomarker candidates is critical for early disease detection and treatment. However, current immunoassay technologies are failing to meet increasing demands for sensitivity and multiplexing. Here, the authors have created a highly sensitive protein microarray using the principle of single-molecule counting for signal amplification, capable of simultaneously detecting a panel of cancer biomarkers at sub-pg/mL levels. To enable this amplification strategy, the authors introduce a novel method of protein patterning using photolithography to subdivide addressable arrays of capture antibody spots into hundreds of thousands of individual microwells. This allows for the total sensor area to be miniaturized, increasing the total possible multiplex capacity. With the immunoassay realized on a standard 75x25 mm form factor glass substrate, sample volume consumption is minimized to <10 μL, making the technology highly efficient and cost-effective. Additionally, the authors demonstrate the power of their technology by measuring six secretory factors related to glioma tumor progression in a cohort of mice. This highly sensitive, sample-sparing multiplex immunoassay paves the way for researchers to track changes in protein profiles over time, leading to earlier disease detection and discovery of more effective treatment using animal models.

Predicting and Interpreting Protein Developability Via Transfer of Convolutional Sequence Representation

Engineered proteins have emerged as novel diagnostics, therapeutics, and catalysts. Often, poor protein developability─quantified by expression, solubility, and stability─hinders utility. The ability to predict protein developability from amino acid sequence would reduce the experimental burden when selecting candidates. Recent advances in screening technologies enabled a high-throughput (HT) developability dataset for 105 of 1020 possible variants of protein ligand scaffold Gp2. In this work, we evaluate the ability of neural networks to learn a developability representation from a HT dataset and transfer this knowledge to predict recombinant expression beyond observed sequences. The model convolves learned amino acid properties to predict expression levels 44% closer to the experimental variance compared to a non-embedded control. Analysis of learned amino acid embeddings highlights the uniqueness of cysteine, the importance of hydrophobicity and charge, and the unimportance of aromaticity, when aiming to improve the developability of small proteins. We identify clusters of similar sequences with increased recombinant expression through nonlinear dimensionality reduction and we explore the inferred expression landscape via nested sampling. The analysis enables the first direct visualization of the fitness landscape and highlights the existence of evolutionary bottlenecks in sequence space giving rise to competing subpopulations of sequences with different developability. The work advances applied protein engineering efforts by predicting and interpreting protein scaffold expression from a limited dataset. Furthermore, our statistical mechanical treatment of the problem advances foundational efforts to characterize the structure of the protein fitness landscape and the amino acid characteristics that influence protein developability.

Circulating proteome for pulmonary nodule malignancy

BACKGROUND

Although lung cancer screening with low-dose computed tomography is rolling out in many areas of the world, differentiating indeterminate pulmonary nodules remains a major challenge. We conducted one of the first systematic investigations of circulating protein markers to differentiate malignant from benign screen-detected pulmonary nodules.

METHODS

Based on 4 international low-dose computed tomography screening studies, we assayed 1078 protein markers using prediagnostic blood samples from 1253 participants based on a nested case-control design. Protein markers were measured using proximity extension assays, and data were analyzed using multivariable logistic regression, random forest, and penalized regressions. Protein burden scores (PBSs) for overall nodule malignancy and imminent tumors were estimated.

RESULTS

We identified 36 potentially informative circulating protein markers differentiating malignant from benign nodules, representing a tightly connected biological network. Ten markers were found to be particularly relevant for imminent lung cancer diagnoses within 1 year. Increases in PBSs for overall nodule malignancy and imminent tumors by 1 standard deviation were associated with odds ratios of 2.29 (95% confidence interval: 1.95 to 2.72) and 2.81 (95% confidence interval: 2.27 to 3.54) for nodule malignancy overall and within 1 year of diagnosis, respectively. Both PBSs for overall nodule malignancy and for imminent tumors were substantially higher for those with malignant nodules than for those with benign nodules, even when limited to Lung Computed Tomography Screening Reporting and Data System (LungRADS) category 4 (P < .001).

CONCLUSIONS

Circulating protein markers can help differentiate malignant from benign pulmonary nodules. Validation with an independent computed tomographic screening study will be required before clinical implementation.

Imprinted Hydrogel Nanoparticles for Protein Biosensing: A Review

Over the past decade, molecular imprinting (MI) technology has made tremendous progress, and the advancements in nanotechnology have been the major driving force behind the improvement of MI technology. The preparation of nanoscale imprinted materials, i.e., molecularly imprinted polymer nanoparticles (MIP NPs, also commonly called nanoMIPs), opened new horizons in terms of practical applications, including in the field of sensors. Currently, hydrogels are very promising for applications in bioanalytical assays and sensors due to their high biocompatibility and possibility to tune chemical composition, size (microgels, nanogels, etc.), and format (nanostructures, MIP film, fibers, etc.) to prepare optimized analyte-responsive imprinted materials. This review aims to highlight the recent progress on the use of hydrogel MIP NPs for biosensing purposes over the past decade, mainly focusing on their incorporation on sensing devices for detection of a fundamental class of biomolecules, the peptides and proteins. The review begins by directing its focus on the ability of MIPs to replace biological antibodies in (bio)analytical assays and highlight their great potential to face the current demands of chemical sensing in several fields, such as disease diagnosis, food safety, environmental monitoring, among others. After that, we address the general advantages of nanosized MIPs over macro/micro-MIP materials, such as higher affinity toward target analytes and improved binding kinetics. Then, we provide a general overview on hydrogel properties and their great advantages for applications in the field of Sensors, followed by a brief description on current popular routes for synthesis of imprinted hydrogel nanospheres targeting large biomolecules, namely precipitation polymerization and solid-phase synthesis, along with fruitful combination with epitope imprinting as reliable approaches for developing optimized protein-imprinted materials. In the second part of the review, we have provided the state of the art on the application of MIP nanogels for screening macromolecules with sensors having different transduction modes (optical, electrochemical, thermal, etc.) and design formats for single use, reusable, continuous monitoring, and even multiple analyte detection in specialized laboratories or in situ using mobile technology. Finally, we explore aspects about the development of this technology and its applications and discuss areas of future growth.

Small-molecule probes from bench to bedside: advancing molecular analysis of drug-target interactions toward precision medicine

Over the past decade, remarkable advances have been witnessed in the development of small-molecule probes. These molecular tools have been widely applied for interrogating proteins, pathways and drug-target interactions in preclinical research. While novel structures and designs are commonly explored in probe development, the clinical translation of small-molecule probes remains limited, primarily due to safety and regulatory considerations. Recent synergistic developments - interfacing novel chemical probes with complementary analytical technologies - have introduced and expedited diverse biomedical opportunities to molecularly characterize targeted drug interactions directly in the human body or through accessible clinical specimens (e.g., blood and ascites fluid). These integrated developments thus offer unprecedented opportunities for drug development, disease diagnostics and treatment monitoring. In this review, we discuss recent advances in the structure and design of small-molecule probes with novel functionalities and the integrated development with imaging, proteomics and other emerging technologies. We further highlight recent applications of integrated small-molecule technologies for the molecular analysis of drug-target interactions, including translational applications and emerging opportunities for whole-body imaging, tissue-based measurement and blood-based analysis.

Rationally Tailored Mesoporous Hosts for Optimal Protein Encapsulation

Proteins play important roles in the therapeutic, medical diagnostic, and chemical catalysis industries. However, their potential is often limited by their fragile and dynamic nature outside cellular environments. The encapsulation of proteins in solid materials has been widely pursued as a route to enhance their stability and ease of handling. Nevertheless, the experimental investigation of protein interactions with rationally designed synthetic hosts still represents an area in need of improvement. In this work, we leveraged the tunability and crystallinity of metal-organic frameworks (MOFs) and developed a series of crystallographically defined protein hosts with varying chemical properties. Through systematic studies, we identified the dominating mechanisms for protein encapsulation and developed a host material with well-tailored properties to effectively encapsulate the protein ubiquitin. Specifically, in our mesoporous hosts, we found that ubiquitin encapsulation is thermodynamically favored. A more hydrophilic encapsulation environment with favorable electrostatic interactions induces enthalpically favored ubiquitin-MOF interactions, and a higher pH condition reduces the intraparticle diffusion barrier, both leading to a higher protein loading. Our findings provide a fundamental understanding of host-guest interactions between proteins and solid matrices and offer new insights to guide the design of future protein host materials to achieve optimal protein loading. The MOF modification technique used in this work also demonstrates a facile method to develop materials easily customizable for encapsulating proteins with different surface properties.

Ultrasound stiffness and perfusion markers correlate with tumor volume responses to immunotherapy

Immunotherapy has revolutionized the treatment of dozens of cancers and became a standard of care for some tumor types. However, the majority of patients do not benefit from current immunotherapeutics and many develop severe toxicities. Therefore, the identification of biomarkers to classify patients as likely responders or non-responders to immunotherapy is a timely task. Here, we test ultrasound imaging markers of tumor stiffness and perfusion. Ultrasound imaging is non-invasive and clinically available and can be used both for stiffness and perfusion evaluation. In this study, we employed syngeneic orthotopic models of two breast cancers, a fibrosarcoma and melanoma, to demonstrate that ultrasound-derived measures of tumor stiffness and perfusion (i.e., blood volume) correlate with the efficacy of immune checkpoint inhibition (ICI) in terms of changes in primary tumor volume. To modulate tumor stiffness and perfusion and thus, get a range of therapeutic outcomes, we employed the mechanotherapeutic tranilast. Mechanotherapeutics combined with ICI are advancing through clinical trials, but biomarkers of response have not been tested until now. We found the existence of linear correlations between tumor stiffness and perfusion imaging biomarkers as well as strong linear correlations between the stiffness and perfusion markers with ICI efficacy on primary tumor growth rates. Our findings set the basis for ultrasound imaging biomarkers predictive of ICI therapy in combination with mechanotherapeutics. STATEMENT OF SIGNIFICANCE: Hypothesis: Monitoring Tumor Microenvironment (TME) mechanical abnormalities can predict the efficacy of immune checkpoint inhibition (ICI) and provide biomarkers predictive of response. Tumor stiffening and solid stress elevation are hallmarks of tumor patho-physiology in desmoplastic tumors. They induce hypo-perfusion and hypoxia by compressing tumor vessels, posing major barriers to immunotherapy. Mechanotherapeutics is a new class of drugs that target the TME to reduce stiffness and improve perfusion and oxygenation. In this study, we show that measures of stiffness and perfusion derived from ultrasound shear wave elastography and contrast enhanced ultrasound can provide biomarkers of tumor response.

Systematic and Comprehensive Analysis of tRNA-Derived Small RNAs Reveals Their Potential Regulatory Roles and Clinical Relevance in Sarcoidosis

Introduction

The pathogenesis of sarcoidosis, which involves several systems, is unclear, and its pathological type is non-caseating epithelioid granulomas. tRNA-derived small RNA (tsRNA) is a novel class of short non-coding RNAs with potential regulatory functions. However, whether tsRNA contributes to sarcoidosis pathogenesis remains unclear.

Methods

Deep sequencing technology was used to identify alterations in tsRNA relative abundance profiles between patients with sarcoidosis and healthy controls and quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate. The clinical parameters were analysis to evaluate the clinical feature correlations initially. Target prediction and bioinformatics analysis of validated tsRNA were conducted to explore the mechanisms of tsRNAs in sarcoidosis pathogenesis.

Results

A total of 360 tsRNAs were identified for exact matches. Among them, the relative abundance of three tRNAs (tiRNA-Glu-TTC-001, tiRNA-Lys-CTT-003, and tRF-Ser-TGA-007) was markedly regulated in sarcoidosis. The levels of various tsRNAs were significantly correlated with age, the number of affected systems, and calcium levels in the blood. Additionally, target prediction and bioinformatics analyses revealed that these tsRNAs may play roles in chemokine, cAMP, cGMP-PKG, retrograde endorphin, and FoxO signalling pathways. The related genes, APP, PRKACB, ARRB2, and NR5A1 finding may participate in the occurrence and development of sarcoidosis through immune inflammation.

Conclusion

This study provides novel insights to explore tsRNA as a novel and efficacious pathogenic target of sarcoidosis.

Mucins as contrast agent targets for fluorescence-guided surgery of pancreatic cancer

Pancreatic cancer is difficult to resect due to its unique challenges, often leading to incomplete tumor resections. Fluorescence-guided surgery (FGS), also known as intraoperative molecular imaging and optical surgical navigation, is an intraoperative tool that can aid surgeons in complete tumor resection through an increased ability to detect the tumor. To target the tumor, FGS contrast agents rely on biomarkers aberrantly expressed in malignant tissue compared to normal tissue. These biomarkers allow clinicians to identify the tumor and its stage before surgical resection and provide a contrast agent target for intraoperative imaging. Mucins, a family of glycoproteins, are upregulated in malignant tissue compared to normal tissue. Therefore, these proteins may serve as biomarkers for surgical resection. Intraoperative imaging of mucin expression in pancreatic cancer can potentially increase the number of complete resections. While some mucins have been studied for FGS, the potential ability to function as a biomarker target extends to the entire mucin family. Therefore, mucins are attractive proteins to investigate more broadly as FGS biomarkers. This review summarizes the biomarker traits of mucins and their potential use in FGS for pancreatic cancer.

Analytical device miniaturization for the detection of circulating biomarkers

Diverse (sub)cellular materials are secreted by cells into the systemic circulation at different stages of disease progression. These circulating biomarkers include whole cells, such as circulating tumour cells, subcellular extracellular vesicles and cell-free factors such as DNA, RNA and proteins. The biophysical and biomolecular state of circulating biomarkers carry a rich repertoire of molecular information that can be captured in the form of liquid biopsies for disease detection and monitoring. In this Review, we discuss miniaturized platforms that allow the minimally invasive and rapid detection and analysis of circulating biomarkers, accounting for their differences in size, concentration and molecular composition. We examine differently scaled materials and devices that can enrich, measure and analyse specific circulating biomarkers, outlining their distinct detection challenges. Finally, we highlight emerging opportunities in biomarker and device integration and provide key future milestones for their clinical translation.

Liquid Plasticine-Based Electrokinetic Enrichment of Proteins

Protein analysis is an important approach for disease diagnosis, in which sample pretreatment is an essential step since protein samples are often complex and many protein biomarkers are of low abundance. Here, given the good openness and light transmission of liquid plasticine (LP), which is a liquid entity formed by SiO₂ nanoparticles and encapsulated aqueous solution, we developed a LP-based field-amplified sample stacking (FASS) system for protein enrichment. The system was composed of a LP container, a sample solution and a Tris-HCl solution containing hydroxyethyl cellulose (HEC). The system design, mechanism investigation, optimization of experimental parameters and characterization of LP-FASS performance for protein enrichment were well studied. Under the optimized experimental conditions of 1 % HEC, 100 mm Tris-HCl and 100 V in the LP-FASS system, a 40-80 times enrichment of proteins was obtained in 40 min using bovine hemoglobin (BHb) as the model protein using the constructed LP-FASS system. The simultaneous enrichment of multiple proteins (phycocyanin, BHb and cytochrome C) was also realized using the system. The LP-FASS system can serve as a new platform for protein enrichment which is easy to be combined with online and offline detections.

Precise profiling of exosomal biomarkers via programmable curved plasmonic nanoarchitecture-based biosensor for clinical diagnosis of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease of complex pathogenesis, with overt symptoms following disease progression. Early AD diagnosis is challenging due to the lack of robust biomarkers and limited patient access to diagnostics via neuroimaging and cerebrospinal fluid (CSF) tests. Exosomes present in body fluids are attracting attention as diagnostic biomarkers that directly reflect neuropathological features within the brain. In particular, exosomal miRNAs (exomiRs) signatures are involved in AD pathogenesis, showing a different expression between patients and the healthy controls (HCs). However, low yield and high homologous nature impede the accuracy and reproducibility of exosome blood-based AD diagnostics. Here, we developed a programmable curved plasmonic nanoarchitecture-based biosensor to analyze exomiRs in clinical serum samples for accurate AD diagnosis. To allow the detection of exomiRs in serum at attomolar levels, nanospaces (e.g., nanocrevice and nanocavity) were introduced into the nanostructures to dramatically increase the spectral sensitivity by adjusting the bending angle of the plasmonic nanostructure through sodium chloride concentration control. The developed biosensor classifies individuals into AD, mild cognitive impairment (MCI) patients, and HCs through profiling and quantifying exomiRs. Furthermore, integrating analysis expression patterns of multiple exosomal biomarkers improved serum-based diagnostic performance (average accuracy of 98.22%). Therefore, precise, highly sensitive serum-derived exosomal biomarker detection-based plasmonic biosensor has a robust capacity to predict the molecular pathologic of neurodegenerative disease, progression of cognitive decline, MCI/AD conversion, as well as early diagnosis and treatment.

Chemical isotope labeling for quantitative proteomics

Advancements in liquid chromatography and mass spectrometry over the last decades have led to a significant development in mass spectrometry-based proteome quantification approaches. An increasingly attractive strategy is multiplex isotope labeling, which significantly improves the accuracy, precision and throughput of quantitative proteomics in the data-dependent acquisition mode. Isotope labeling-based approaches can be classified into MS1-based and MS2-based quantification. In this review, we give an overview of approaches based on chemical isotope labeling and discuss their principles, benefits, and limitations with the goal to give insights into fundamental questions and provide a useful reference for choosing a method for quantitative proteomics. As a perspective, we discuss the current possibilities and limitations of multiplex, isotope labeling approaches for the data-independent acquisition mode, which is increasing in popularity.

Derivation and comprehensive analysis of ageing-related genes in intervertebral disc degeneration for prediction and immunology

Intervertebral disc degeneration (IDD) is triggered primarily by ageing, a process characterized by intrinsic, multifaceted and progressive characteristics. Regarding the crucial senescence genes and underlying regulatory mechanisms leading to the etiology of IDD, there is still some uncertainty. In this study, we used gene expression patterns from the GEO database to create a diagnostic model of IDD using differential ageing-related genes (DARG). We examine the relative dynamics of immune cells by single-sample gene set. On the basis of transcription factor (TF) miRNA and miRNA-mRNA pairs, the regulatory network for transcription and post-transcriptional processes was built. The active therapeutic components and Chinese herbal remedies of the main ageing genes were investigated using a network pharmacology approach. 20 DARGs were combined to create a diagnostic model, and both the training and validation sets had an area under the ROC curve of 1. We found alterations in many cell types in IDD tissue, but mainly in activated dendritic cells, type 17 T helper cells, and mast cells. We identified a regulatory axis for STAT1/miR-4306/PPARA based on the correlations between gene expression and targeting. Active substances (Naringenin and Quercetin) and herbs (Aurantii fructus and Eucommiae cortex) targeting PPARA for the treatment of IDD were discovered through network pharmacology. These results provide a theoretical framework for identifying and treating IDD. For the first time, we were able to diagnose IDD patients using 20 ageing-related indicators. At the same time, TF-miRNA-mRNA in conjunction with network pharmacology enabled the identification of prospective therapeutic targets and pharmacological processes.

The development of microfluidic-based western blotting: Technical advances and future perspectives

Over the past two decades significant technical advancement in the field of western blotting has been made possible through the utilization of microfluidic technologies. In this review we provide a critical overview of these advancements, highlighting the advantages and disadvantages of each approach. Particular attention is paid to the development of now commercially available systems, including those for single cell analysis. This review also discusses more recent developments, including algorithms for automation and/or improved quantitation, the utilization of different materials/chemistries, use of projection electrophoresis, and the development of triBlots. Finally, the review includes commentary on future advances in the field based on current developments, and the potential of these systems for use as point-of-care devices in healthcare.

Liquid Chromatography-Mass Spectrometry Analysis of Frataxin Proteoforms in Whole Blood as Biomarkers of the Genetic Disease Friedreich's Ataxia

Friedreich's ataxia (FRDA) is caused primarily by expanded GAA repeats in intron 1 of both alleles of the FXN gene, which causes transcriptional silencing and reduced expression of frataxin mRNA and protein. FRDA is characterized by slowly progressive ataxia and cardiomyopathy. Symptoms generally appear during adolescence, and patients slowly progress to wheelchair dependency usually in the late teens or early twenties with death on average in the 4th decade. There are two known mature proteoforms of frataxin. Mitochondrial frataxin (frataxin-M) is a 130-amino acid protein with a molecular weight of 14,268 Da, and there is an alternatively spliced N-terminally acetylated 135-amino acid form (frataxin-E) with a molecular weight of 14,953 Da found in erythrocytes. There is reduced expression of frataxin in the heart and brain, but frataxin is not secreted into the systemic circulation, so it cannot be analyzed in serum or plasma. Blood is a readily accessible biofluid that contains numerous different cell types that express frataxin. We have found that pig blood can serve as an excellent surrogate matrix to validate an assay for frataxin proteoforms because pig frataxin is lost during the immunoprecipitation step used to isolate human frataxin. Frataxin-M is expressed in blood cells that contain mitochondria, whereas extra-mitochondrial frataxin-E is found in erythrocytes. This means that the analysis of frataxin in whole blood provides information on the concentration of both proteoforms without having to isolate the individual cell types. In the current study, we observed that the distributions of frataxin levels for a sample of 25 healthy controls and 50 FRDA patients were completely separated from each other, suggesting 100% specificity and 100% sensitivity for distinguishing healthy controls from FRDA cases, a very unusual finding for a biomarker assay. Additionally, frataxin levels were significantly correlated with the GAA repeat length and age of onset with higher correlations for extra-mitochondrial frataxin-E than those for mitochondrial frataxin-M. These findings auger well for using frataxin levels measured by the validated stable isotope dilution ultrahigh-performance liquid chromatography-multiple reaction monitoring/mass spectrometry assay to monitor therapeutic interventions and the natural history of FRDA. Our study also illustrates the utility of using whole blood for protein disease biomarker discovery and validation.

Molecular Diagnosis and Cancer Prognosis-A Concise Review

Cancer is a complicated disease. Globally, it is one of the major causes for morbidity and mortality. A critical challenge associated with it is the difficulty to accurately diagnose it at an early stage. The malignancy due to multistage and heterogeneity that result from genetic and epigenetic modifications poses critical challenge to diagnose and monitor the progress at an early stage. Current diagnostic techniques normally suggest invasive biopsy procedure that can cause further infections and bleeding. Therefore, noninvasive diagnostic methods with high accuracy, safety and earliest detection are the needs of the hour. Herein, we provide a detailed review on the advanced methodologies and protocols developed for the detection of cancer biomarkers based on proteins, nucleic acids and extracellular vesicles. Furthermore, existing challenges and the improvements essential for the rapid, sensitive and noninvasive detection have also been discussed.

A Review on CNTs-Based Electrochemical Sensors and Biosensors: Unique Properties and Potential Applications

Carbon nanotubes (CNTs), are safe, biocompatible, bioactive, and biodegradable materials, and have sparked a lot of attention due to their unique characteristics in a variety of applications, including medical and dye industries, paper manufacturing and water purification. CNTs also have a strong film-forming potential, permitting them to be widely employed in constructing sensors and biosensors. This review concentrates on the application of CNT-based nanocomposites in the production of electrochemical sensors and biosensors. It emphasizes the synthesis and optimization of CNT-based sensors for a range of applications and outlines the benefits of using CNTs for biomolecule immobilization. In addition, the use of molecularly imprinted polymer (MIP)-CNTs in the production of electrochemical sensors is also discussed. The challenges faced by the current CNTs-based sensors, along with some the future perspectives and their future opportunities, are also briefly explained in this paper.

Artificial intelligence aids in development of nanomedicines for cancer management

Over the last decade, the nanomedicine has experienced unprecedented development in diagnosis and management of diseases. A number of nanomedicines have been approved in clinical use, which has demonstrated the potential value of clinical transition of nanotechnology-modified medicines from bench to bedside. The application of artificial intelligence (AI) in development of nanotechnology-based products could transform the healthcare sector by realizing acquisition and analysis of large datasets, and tailoring precision nanomedicines for cancer management. AI-enabled nanotechnology could improve the accuracy of molecular profiling and early diagnosis of patients, and optimize the design pipeline of nanomedicines by tuning the properties of nanomedicines, achieving effective drug synergy, and decreasing the nanotoxicity, thereby, enhancing the targetability, personalized dosing and treatment potency of nanomedicines. Herein, the advances in AI-enabled nanomedicines in cancer management are elaborated and their application in diagnosis, monitoring and therapy as well in precision medicine development is discussed.

Advances in the Molecular Landscape of Lung Cancer Brain Metastasis

Lung cancer is one of the most frequent tumors that metastasize to the brain. Brain metastasis (BM) is common in advanced cases, being the major cause of patient morbidity and mortality. BMs are thought to arise via the seeding of circulating tumor cells into the brain microvasculature. In brain tissue, the interaction with immune cells promotes a microenvironment favorable to the growth of cancer cells. Despite multimodal treatments and advances in systemic therapies, lung cancer patients still have poor prognoses. Therefore, there is an urgent need to identify the molecular drivers of BM and clinically applicable biomarkers in order to improve disease outcomes and patient survival. The goal of this review is to summarize the current state of knowledge on the mechanisms of the metastatic spread of lung cancer to the brain and how the metastatic spread is influenced by the brain microenvironment, and to elucidate the molecular determinants of brain metastasis regarding the role of genomic and transcriptomic changes, including coding and non-coding RNAs. We also present an overview of the current therapeutics and novel treatment strategies for patients diagnosed with BM from NSCLC.

A biocatalytic peptidobiosensing molecular bridge for detecting osteosarcoma marker protein

A biosensing scheme requiring only one-step sample incubation before signal collection, and using a compact "three-in-one" probe of target-binding, signal conversion, and amplification, may greatly simplify the design of biosensors. Therefore, sparing the multi-step addition of enzymes, protein, and nanomaterial, as well as the associated complexity and non-specific interactions. In this work, a peptide probe aimed at such compact features has been designed, based on protein-triggered, conformation-driven, and Cu (II) facilitated side-chain di-tyrosine cyclization. This design can use target-probe recognition to induce discriminated cross-linking and self-cleavage of the probe, resulting in retention or dissociation of a signal amplification motif from the search and consequently quantitative detection performance. The method has also been tested preliminarily in fractioned osteosarcoma clinical samples, showing an acceptable coherence between signal readout and clinical diagnosis. On the basis of these early findings, it is reasonable to assume that the proposed probe will be beneficial for the next development of tumor screening and prognosis sensors.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Combination of automated sample preparation and micro-flow LC-MS for high-throughput plasma proteomics

BACKGROUND

Non-invasive detection of blood-based markers is a critical clinical need. Plasma has become the main sample type for clinical proteomics research because it is easy to obtain and contains measurable protein biomarkers that can reveal disease-related physiological and pathological changes. Many efforts have been made to improve the depth of its identification, while there is an increasing need to improve the throughput and reproducibility of plasma proteomics analysis in order to adapt to the clinical large-scale sample analysis.

METHODS

We have developed and optimized a robust plasma analysis workflow that combines an automated sample preparation platform with a micro-flow LC-MS-based detection method. The stability and reproducibility of the workflow were systematically evaluated and the workflow was applied to a proof-of-concept plasma proteome study of 30 colon cancer patients from three age groups.

RESULTS

This workflow can analyze dozens of samples simultaneously with high reproducibility. Without protein depletion and prefractionation, more than 300 protein groups can be identified in a single analysis with micro-flow LC-MS system on a Orbitrap Exploris 240 mass spectrometer, including quantification of 35 FDA approved disease markers. The quantitative precision of the entire workflow was acceptable with median CV of 9%. The preliminary proteomic analysis of colon cancer plasma from different age groups could be well separated with identification of potential colon cancer-related biomarkers.

CONCLUSIONS

This workflow is suitable for the analysis of large-scale clinical plasma samples with its simple and time-saving operation, and the results demonstrate the feasibility of discovering significantly changed plasma proteins and distinguishing different patient groups.

Engineering At-Home Dilution and Filtration Methods to Enable Paper-Based Colorimetric Biosensing in Human Blood with Cell-Free Protein Synthesis

Diagnostic blood tests can guide the administration of healthcare to save and improve lives. Most clinical biosensing blood tests require a trained technician and specialized equipment to process samples and interpret results, which greatly limits test accessibility. Colorimetric paper-based diagnostics have an equipment-free readout, but raw blood obscures a colorimetric response which has motivated diverse efforts to develop blood sample processing techniques. This work uses inexpensive readily-available materials to engineer user-friendly dilution and filtration methods for blood sample collection and processing to enable a proof-of-concept colorimetric biosensor that is responsive to glutamine in 50 µL blood drop samples in less than 30 min. Paper-based user-friendly blood sample collection and processing combined with CFPS biosensing technology represents important progress towards the development of at-home biosensors that could be broadly applicable to personalized healthcare.

Development and Validation of Tumor Marker Indices in Advanced Gastric Cancer Patients

BACKGROUND

Tumor markers (TMs) are important for the prognosis of gastric cancer (GC). However, the prognostic importance of the tumor marker index (TMI) based on GC-specific TMs for advanced gastric cancer (AGC) still needs to be further explored.

METHODS

We retrospectively examined patients who underwent radical gastric cancer surgery between February 2014 and June 2016 at the Department of Gastroenterological Surgery, Affiliated Cancer Hospital, Harbin Medical University. The patients were divided into training and validation groups. TMI was determined as the geometric mean of the standard cancer antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) levels. Patient overall survival was assessed using the Kaplan-Meier method. Independent prognosis-associated risk factors were identified using Cox hazard regression models. A nomogram model incorporating TMI and clinicopathological factors was developed, and its performance was evaluated using a decision curve analysis, concordance index, and calibration plots.

RESULTS

In the TMI training cohort, the cutoff value was set at .439, categorizing patients into TMI-High and TMI-Low groups. The 5-year survival rate in the TMI-Low group significantly surpassed that in the TMI-High group (78.2% vs 58.1% and 49.7 vs 41.6, P < .001). TMI emerged as an independent prognostic factor. The nomogram accurately predicted patient prognosis by using TMI and clinicopathological characteristics. Validation of the TMI in the independent cohort yielded satisfactory results.

CONCLUSION

The TMI constructed based on specific TMs associated with gastric cancer can offer a precise prognostic prediction for patients.

Tailored point-of-care biosensors for liquid biopsy in the field of oncology

In the field of cancer detection, technologies to analyze tumors using biomarkers circulating in fluids such as blood have developed rapidly based on liquid biopsy. A proactive approach to early cancer detection can lead to more effective treatments with minimal side effects and better long-term patient survival. However, early detection of cancer is hindered by the existing limitations of conventional cancer diagnostic methods. To enable early diagnosis and regular monitoring and improve automation, the development of integrated point-of-care (POC) and biosensors is needed. This is expected to fundamentally change the diagnosis, management, and monitoring of response to treatment of cancer. POC-based techniques will provide a way to avoid complications that occur after invasive tissue biopsy, such as bleeding, infection, and pain. The aim of this study is to provide a comprehensive view of biosensors and their clinical relevance in oncology for the detection of biomarkers with liquid biopsies of proteins, miRNA, ctDNA, exosomes, and cancer cells. The preceding discussion also illustrates the changing landscape of liquid biopsy-based cancer diagnosis through nanomaterials, machine learning, artificial intelligence, wearable devices, and sensors, many of which apply POC design principles. With the advent of sensitive, selective, and timely detection of cancer, we see the field of POC technology for cancer detection and treatment undergoing a positive paradigm shift in the foreseeable future.

Advanced diagnostic and therapeutic strategies in nanotechnology for lung cancer

As a highly invasive thoracic malignancy with increasing prevalence, lung cancer is also the most lethal cancer worldwide due to the failure of effective early detection and the limitations of conventional therapeutic strategies for advanced-stage patients. Over the past few decades, nanotechnology has emerged as an important technique to obtain desired features by modifying and manipulating different objects on a molecular level and gained a lot of attention in many fields of medical applications. Studies have shown that in lung cancer, nanotechnology may be more effective and specific than traditional methods for detecting extracellular cancer biomarkers and cancer cells in vitro, as well as imaging cancer in vivo; Nanoscale drug delivery systems have developed rapidly to overcome various forms of multi-drug resistance and reduce detrimental side effects to normal tissues by targeting cancerous tissue precisely. There is no doubt that nanotechnology has the potential to enhance healthcare systems by simplifying and improving cancer diagnostics and treatment. Throughout this review, we summarize and highlight recent developments in nanotechnology applications for lung cancer in diagnosis and therapy. Moreover, the prospects and challenges in the translation of nanotechnology-based diagnostic and therapeutic methods into clinical applications are also discussed.

Progress with Metabolomic Blood Tests for Gastrointestinal Cancer Diagnosis-An Assessment of Biomarker Translation

There is an urgent need for cost-effective, non-invasive tools to detect early stages of gastrointestinal cancer (colorectal, gastric, and esophageal cancers). Despite many publications suggesting circulating metabolites acting as accurate cancer biomarkers, few have reached the clinic. In upper gastrointestinal cancer this is critically important, as there is no test to complement gold-standard endoscopic evaluation in patients with mild symptoms that do not meet referral criteria. Therefore, this study aimed to describe and solve this translational gap. Studies reporting diagnostic accuracy of metabolomic blood-based gastrointestinal cancer biomarkers from 2007 to 2020 were systematically reviewed and progress of each biomarker along the discovery-validation-adoption pathway was mapped. Successful biomarker translation was defined as a composite endpoint, including patent protection/FDA approval/recommendation in national guidelines. The review found 77 biomarker panels of gastrointestinal cancer, including 25 with an AUROC >0.9. All but one was stalled at the discovery phase, 9.09% were patented and none were clinically approved, confirming the extent of biomarker translational gap. In addition, there were numerous "re-discoveries," including histidine, discovered in 7 colorectal studies. Finally, this study quantitatively supports the presence of a translational gap between discovery and clinical adoption, despite clear evidence of highly performing biomarkers with significant potential clinical value.

Diagnostic role of plasma ORM2 in differentiating prostate cancer from benign prostatic hyperplasia

PURPOSE

Markers are needed to increase the diagnostic accuracy of prostate-specific antigen (PSA) in prostate cancer (PCa) screening. Mounting evidence has shown that plasma proteins can be hopeful biomarkers for cancer diagnosis.

METHODS

Tandem mass tag (TMT)-based proteomics and parallel reaction monitoring (PRM) analysis were used to screen the differential proteins and further validated in other independent studies (n = 539). Receiver-operating characteristic (ROC), decision curves and nomograms were applied to assess the diagnostic accuracy of biomarkers.

RESULTS

Three candidate proteins (DBP, LCAT and ORM2) were preliminarily screened. Subsequent validation studies revealed significant upregulation of ORM2 in PCa patients across other independent cohorts. ORM2 yielded excellent discriminative power for PCa from benign prostatic hyperplasia (BPH) patients (AUC = 0.861 and 0.814 in validation phases 2a and 2b, respectively). Importantly, the combination of ORM2 and PSA gave better predictive accuracy than PSA alone. We incorporated age, PSA and ORM2 into a nomogram, which yielded C-index of 0.883 in validation phase 2a. A similar C-index of 0.879 was obtained in external validation phase 2b.

CONCLUSIONS

In summary, our study suggests that ORM2 could be treated as a complementary biomarker for PSA in distinguishing PCa from BPH.