Photodynamic therapy (PDT) offers minimally invasive and repeatable cancer treatment options. Despite advancements in photosensitizer (PS) design, the optical control of PS activation remains unexplored. Here, we present the first photoswitchable PS based on a BOAHY-BODIPY dyad system. Inspired by BODIPY multimer structures and BOAHY's photoisomerization properties, we designed mono-(4 series) and bis-BOAHY-BODIPY (5 series) conjugates. These dyads primarily generate reactive oxygen species via a type-I process under white light. Notably, the 4 series compounds demonstrated effective photocytotoxicity and photoswitching properties in vitro. Building on these, we iodinated the monoconjugates to develop the highly efficient photoswitching PS, 6b, which exhibited enhanced intersystem crossing and type-II reactive oxygen species generation due to a reduced singlet-triplet energy gap. As the first demonstration of photoswitchable PDT agents, this strategy introduces a new approach with significant potential for selective cancer treatment and clinical applications.

This study demonstrates a novel biosensing platform utilizing a dielectric nanocavity to enhance fluorescence emission for the ultrasensitive detection of biomolecules. By coupling a silver (Ag) nanocube with a distributed Bragg reflector (DBR) mirror, we achieved a substantial fluorescence enhancement reaching a maximum enhancement factor of up to 855-fold and having quasi-single molecule sensitivity. The platform was successfully applied for multiplexed detection of four different miRNA biomarkers, showcasing its ability to detect multiple targets simultaneously with high sensitivity. The simplicity, rapid speed, and small detection volume (down to 0.5 μL) of this system make it suitable for high-throughput and large-area nanocavity imaging. Our findings offer a promising solution for ultrasensitive, multiplexed biosensing with potential applications in disease diagnosis, personalized medicine, and digital molecular diagnostics.

This review article explores the transformative potential of smart dust systems by examining how existing chemical sensing technologies can be adapted and advanced to realize their full capabilities. Smart dust, characterized by submillimeter-scale autonomous sensing platforms, offers unparalleled opportunities for real-time, spatiotemporal chemical mapping across diverse environments. This article introduces the technological advancements underpinning these systems, critically evaluates current limitations, and outlines new avenues for development. Key challenges, including multi-compound detection, system control, environmental impact, and cost, are discussed alongside potential solutions. By leveraging innovations in miniaturization, wireless communication, AI-driven data analysis, and sustainable materials, this review highlights the promise of smart dust to address critical challenges in environmental monitoring, healthcare, agriculture, and defense sectors. Through this lens, the article provides a strategic roadmap for advancing smart dust from concept to practical application, emphasizing its role in transforming the understanding and management of complex chemical systems.

Triple-negative breast cancer (TNBC) represents an aggressive subtype of breast cancer, characterized by early metastasis and a poor prognosis. Traditional imaging modalities often lack the sensitivity and molecular specificity required for the early detection of metastatic lesions. In this study, we developed a dual-modal imaging strategy that integrates surface-enhanced Raman scattering (SERS) and bioluminescence imaging probes, utilizing bioorthogonal labeling to track TNBC organ metastasis. The SERS probes were encapsulated with azide-labeled macrophage membranes to extend circulation time and enhance targeting efficiency. Additionally, bioorthogonal metabolic glycolengineering was employed to modify luciferase-labeled tumor cells (4T1-Luc) with bicyclo[6.1.0]nonyne (BCN) groups, facilitating precise binding between the probes and 4T1-Luc cells through click chemistry reactions. This dual-modal imaging approach enabled real-time monitoring of small metastatic lesions with high sensitivity, providing a non-invasive and accurate method for assessing tumor metastasis and therapeutic response in vivo. Our findings indicate that the dual-modal imaging technique, combining SERS and bioluminescence with bioorthogonal labeling, holds significant potential for advanced applications in oncology. STATEMENT OF SIGNIFICANCE: This study devised a surface-enhanced Raman scattering (SERS) and bioluminescence dual-modal imaging strategy integrated with a bioorthogonal label to address the challenge of tracking the metastasis of aggressive triple-negative breast cancer (TNBC). In contrast to conventional methods, this approach facilitated real-time, whole-body monitoring of tumor dissemination through bioluminescence. Simultaneously, it achieved the detection of micro-metastases in organs using SERS, thereby exceeding the sensitivity limitations of existing imaging techniques. Clinical validation with human samples further demonstrated its potential for non-invasive therapeutic assessment and early intervention. By bridging preclinical innovation and clinical requirements, this research offered a transformative tool for precision oncology. It is expected to attract the interest of researchers in the fields of biomedicine, nanotechnology, and cancer therapeutics.

Esophageal cancer is a major global health issue with a high mortality rate. Early diagnosis is crucial for improving patient outcomes, but traditional diagnostic methods are often invasive and costly. This study explores the potential of exhaled volatile organic compounds (VOCs) as a non-invasive diagnostic tool for esophageal cancer. Using gas chromatography-mass spectrometry (GC-MS), we analyzed the breath samples of 80 esophageal cancer patients and 60 healthy controls, identifying and quantifying over 100 VOCs. The results revealed significant differences in the concentrations of VOCs such as acetone, ethanol, and isoprene between the two groups. A multi-parameter regression diagnostic model based on a neural network algorithm achieved an accuracy of 90.3% in distinguishing esophageal cancer patients from healthy individuals. Further optimization incorporating physiological factors, including smoking, drinking, and dietary habits, improved the model's accuracy to 92.4%, with a specificity of 93.1%, representing a significant improvement over previous studies. These results suggest that VOCs analysis in exhaled breath holds great promise as a non-invasive, cost-effective, and accurate method for early detection of esophageal cancer.

In contrast to conventional ensemble-average-based methods, opto-digital molecular analytic approaches digitize detection by physically partitioning individual detection events into discrete compartments or directly locating and analyzing the signals from single molecules. The sensitivity can be enhanced by signal amplification reactions, signal enhancement interactions, labelling by strong signal emitters, advanced optics, image processing, and machine learning, while specificity can be improved by designing target-selective probes and profiling molecular dynamics. With the capabilities to attain a limit of detection several orders lower than the conventional methods, reveal intrinsic molecular information, and achieve multiplexed analysis using a small-volume sample, the emerging opto-digital molecular analytics may be revolutionarily instrumental to clinical diagnosis, molecular chemistry and science, drug discovery, and environment monitoring. In this article, we provide a comprehensive review of the recent advances, offer insights into the underlying mechanisms, give comparative discussions on different strategies, and discuss the current challenges and future possibilities.

Breath biopsy is emerging as a rapid and non-invasive diagnostic tool that links exhaled chemical signatures with specific medical conditions. Despite its potential, clinical translation remains limited by the challenge of reliably detecting endogenous, disease-specific biomarkers in breath. Synthetic biomarkers represent an emerging paradigm for precision diagnostics such that they amplify activity-based biochemical signals associated with disease fingerprints. However, their adaptation to breath biopsy has been constrained by the limited availability of orthogonal volatile reporters that are detectable in exhaled breath. Here, we engineer multiplexed breath biomarkers that couple aberrant protease activities to exogenous volatile reporters. We designed novel intramolecular reactions that leverage protease-mediated aminolysis, enabling the sensing of a broad spectrum of proteases, and that each release a unique reporter in breath. This approach was validated in a mouse model of influenza to establish baseline sensitivity and specificity in a controlled inflammatory setting, and subsequently applied to diagnose lung cancer using an autochthonous Alk -mutant model. We show that combining multiplexed reporter signals with machine learning algorithms enables tumor progression tracking, treatment response monitoring, and detection of relapse after 30 minutes. Our multiplexed breath biopsy platform highlights a promising avenue for rapid, point-of-care diagnostics across diverse disease states.

Understanding dysregulated genes and pathways in cancer is critical for precision oncology. Integrating mass spectrometry-based proteomic data with transcriptomic data presents unique opportunities for systematic analyses of dysregulated genes and pathways in pan-cancer. Here, we compiled a comprehensive set of datasets, encompassing proteomic data from 2404 samples and transcriptomic data from 7752 samples across 13 cancer types. Comparisons between normal or adjacent normal tissues and tumor tissues identified several dysregulated pathways including mRNA splicing, interferon pathway, fatty acid metabolism, and complement coagulation cascade in pan-cancer. Additionally, pan-cancer upregulated and downregulated genes (PCUGs and PCDGs) were also identified. Notably, RRM2 and ADH1B, two genes which belong to PCUGs and PCDGs, respectively, were identified as robust pan-cancer diagnostic biomarkers. TNM stage-based comparisons revealed dysregulated genes and biological pathways involved in cancer progression, among which the dysregulation of complement coagulation cascade and epithelial-mesenchymal transition are frequent in multiple types of cancers. A group of pan-cancer continuously upregulated and downregulated proteins in different tumor stages (PCCUPs and PCCDPs) were identified. We further constructed prognostic risk stratification models for corresponding cancer types based on dysregulated genes, which effectively predict the prognosis for patients with these cancers. Drug prediction based on PCUGs and PCDGs as well as PCCUPs and PCCDPs revealed that small molecule inhibitors targeting CDK, HDAC, MEK, JAK, PI3K, and others might be effective treatments for pan-cancer, thereby supporting drug repurposing. We also developed web tools for cancer diagnosis, pathologic stage assessment, and risk evaluation. Overall, this study highlights the power of combining proteomic and transcriptomic data to identify valuable diagnostic and prognostic markers as well as drug targets and treatments for cancer.

The forward design of biosensors that implement Boolean logic to improve detection precision primarily relies on programming genetic components to control transcriptional responses. However, cell- and gene-free nanomaterials programmed with logical functions may present lower barriers for clinical translation. Here we report the design of activity-based nanosensors that implement AND-gate logic without genetic parts via bi-labile cyclic peptides. These actuate by releasing a reporter if and only if cleaved by a specific pair of proteases. AND-gated nanosensors that detect the concomitant activity of the granzyme B protease secreted by CD8 T cells and matrix metalloproteinases overexpressed by cancer cells identify the unique condition of cytotoxic T cell killing of tumour cells. In preclinical mouse models, AND-gated nanosensors discriminate tumours that are responsive to immune checkpoint blockade therapy from B2m-/- tumours that are resistant to it, minimize signals from tissues without co-localized protease expression including the lungs during acute influenza infection, and release a reporter locally in tissue or distally in the urine for facile detection.

Recent advances mean that innovations are emerging that enable better stratification of individuals based on their risk of cancer so that screening or diagnostic investigations can be targeted to those at greatest need. We explored the views of the public, from a societal perspective, of using such risk-based innovations to identify people's cancer risk and allocating healthcare accordingly.

We conducted three community juries, each with 7-9 participants. Participants were informed about the topic and potential novel risk-based innovations through a series of presentations from experts and discussions. Polygenic risk scores, geodemographic segmentation, continuous monitoring of biomarkers, minimally invasive tests, artificial intelligence analysis of medical records, and wearable devices were used as examples. The participants then deliberated over the research questions before reporting their verdicts on the acceptability of these novel data-based approaches in principle. Transcripts were analysed using codebook thematic analysis.

All juries found that the proposed risk-based approaches to cancer healthcare were, in general, acceptable. Primarily this was because the approaches would enable use of information in a positive and constructive way. However, there were a number of qualifiers or caveats. In particular, participants highlighted the necessity of using accurate and robust data with a well-evidenced association with cancer risk. They also expressed concerns about unintended consequences such as for insurance, scams or erosion of personal liberty, and the burden to participate in data collection across society. All agreed that opting-out must be straightforward.

Informed members of the public supported the concept of using innovations to estimate cancer risk and inform healthcare. Their priorities for accuracy, data security, participation burden, and personal liberty and choice tended to overlap with those of developers and policymakers. Work to ready these innovations for implementation should continue, with the public's priorities accounted for in their development and dissemination in order to address any unintended consequences upfront.

Early detection and precise tumor localization are critical for improving treatment outcomes and enabling more targeted and minimally invasive therapies as biotechnology evolves. However, endogenous biomarkers from early lesions face significant challenges, such as short circulation times and blood dilution, which hinder early diagnostic efforts. In this study, we present a multimodal nanosensor specifically engineered to target cancer by responding to CD44 and tumor-associated enzymes within the microenvironment. Following systemic administration, the nanosensor selectively accumulates at the disease site, delivering hexaminolevulinate (HAL) to produce protoporphyrin IX (PpIX) as a synthetic biomarker, thus amplifying disease signals for analysis via a microfluidics-based device. Concurrently, embedded Gd2O3 nanoclusters facilitate tumor visualization through magnetic resonance imaging (MRI). Beyond tumor diagnosis, this innovative methodology supports the multimodal monitoring of drug response through the assessment of blood reporter signals and MRI imaging. This multifunctional system addresses critical limitations in traditional cancer diagnostics, which typically rely on sequential blood biomarker tests, followed by imaging. Our approach enhances diagnostic efficiency, minimizes the need for invasive procedures, and promotes more accurate and personalized cancer care.

Urinalysis, as a non-invasive and efficient diagnostic method, is very important but faces great challenges due to the complex compositions of urine and limited naturally occurring biomarkers for diseases. Herein, by leveraging the intrinsic absence of endogenous fluorinated interference, a strategy with the enzymatically activated assembly of synthetic fluorinated peptide for cholestatic liver injury (CLI) diagnosis and treatment through 19F nuclear magnetic resonance (NMR) urinalysis and efficient drug retention is developed. Specifically, alkaline phosphatase (ALP), overexpressed in the liver of CLI mice, triggers the assembly of fluorinated peptide, thus, directing the traffic and dynamic distribution of the synthetic biomarkers after administration, whereas CLI mice display much slower clearance of peptides through urine as compared with healthy counterparts. As such, it enables to transform pathophysiological information into exogenous signals via noninvasive urinary monitoring. Moreover, as a proof-of-concept, by grafting different functional groups to peptides, the theranostic platforms can be established to provide a new paradigm for the design of multifunctional peptides.

Understanding transcription profiles of living tissues is critical for biology and medicine. However, measurement of the transcript levels is typically done in homogenized tissues post-mortem. Here, we present a new platform that enables non-invasive monitoring of specific mRNA levels in vivo , without tissue destruction. We achieved this by combining two cutting-edge tools - synthetic serum markers, called Released Markers of Activity ( RMAs ), and RNA-based sensors of transcription. We call this platform IN-vivo Tracking of ACtive Transcription, or INTACT . In INTACT, when the target mRNA is expressed, the RNA sensor detects it and triggers the production and release of RMA reporters into the blood. Once in blood, the RMAs can be easily measured through a simple blood draw. Our data shows that INTACT can measure transcription of transgenes, as well as endogenous transcripts, such as c-Fos or Arc , both in vivo in the brain and in tissue culture. INTACT enables simple measurement of transcript level histories in genetically-targetable cell populations of living animals.

A biofunctional immunosensor combining photoelectrochemical (PEC) and electrochemical (EC) was proposed for the quantitative detection of the liver cancer marker alpha-fetoprotein (AFP) in human blood. BiVO4/BiOI-MWCNTs photoactive materials were first prepared on conductive glass FTO, and the photoelectrode was functionalized by chitosan and glutaraldehyde. Then, the AFP capture antibody (Ab1) was successfully modified on the photoelectrode, and the label-free rapid detection of AFP antigen was achieved by PEC. In addition, Au@PdPt nanospheres were also used as a marker for binding to AFP detection antibody (Ab2). Due to the excellent catalytic properties of Au@PdPt in EC reaction, a signal increase in the EC response can be achieved when Ab2 binds to the AFP antigen, which ensures high sensitivity for the detection of AFP. The detection limits of PEC and EC are 0.050 pg/mL and 0.014 pg/mL, respectively. The sensor also possesses good specificity, stability and reproducibility, shows excellent performance in the detection of clinical samples and has good clinical applicability.

Biosensors are capable of diagnosing tumors through imaging in vivoor liquid biopsy, but they face the challenges of inefficient delivery into tumor sites and the lack of reliable tumor-associated biomarkers. Herein, we constructed a dual-mode biosensor based on a multifunctional peptide nucleic acid (PNA)/peptide copolymer and DNA tetrahedron for tumor imaging and urinalysis. The biosensor could enter the cancer cells to initiate a microRNA-21-specific catalytic hairpin assembly reaction after cleavage by matrix-metalloprotease (MMP) in the tumor microenvironment, and the MMP cleavage product was released into the bloodstream and then was filtered out by the kidney. As PNA was a synthetic DNA analogue that could not be degraded by nucleases and proteases, it could serve as a reliable synthetic biomarker and be easily detected by high-performance liquid chromatography in urine. Importantly, the biosensor was hitchhiked on the macrophage membrane to realize efficient delivery in the depth of tumor utilizing the macrophage ability of actively homing to the tumor site and infiltrating into the tumor. The results indicated that the signal output of the biosensor was improved remarkably and mice with a tumor volume as little as 30-40 mm3 could be reliably discriminated through urine assay. This innovative macrophage-hitchhiking dual-mode biosensor holds a great potential as a non-invasive and convenient tool for tumor diagnosis and tumor progression evaluation.

Simultaneous detection of different biomarkers related to the spatiotemporally dynamic immune events is of particular importance for the accurate evaluation of antitumor immune effects. Here, we have developed an AND-gate logic dual resonance energy transfer nanoprobe (named DRET) for dynamic monitoring of programmed CD8+ T cell activation and tumor cell apoptosis. Immunotherapy-induced granzyme B secretion from CD8+ T cells and the subsequent caspase-3 release from apoptotic tumor cells individually activate one of the tiers of the "AND-gate" logic DRET. The resulting fluorescence recovery and magnetic resonance T1 enhancement can be used for precise immunomodulatory drug screening, early efficacy prediction, and immune stratification. Particularly, not only "Responders" can be distinguished from "Non-responders", but also "Acquired resistance" can be identified from "Maintain responders", providing a novel approach to put forward the accurate evaluation of antitumor immunity.

Endometrial cancer (EC) is the most common gynecological malignancy, with rising incidence and mortality rates. Key risk factors, including obesity, prolonged estrogen exposure, and metabolic disorders, underscore the urgent need for non-invasive, early diagnostic tools. This review focuses on the role of DNA methylation as a potential biomarker for early EC detection. Aberrant DNA methylation in the promoter regions of tumor suppressor genes can lead to gene silencing and cancer progression. We examine recent studies utilizing minimally invasive samples, such as urine, cervicovaginal, and cervical scrapes, to detect early-stage EC through DNA methylation patterns. Markers such as RASSF1A, HIST1H4F, GHSR, SST, and ZIC1 have demonstrated high diagnostic accuracy, with AUC values up to 0.95, effectively distinguishing EC from non-cancerous conditions. This review highlights the potential of DNA methylation-based testing as a non-invasive alternative to traditional diagnostic methods, offering earlier detection, better risk stratification, and more personalized treatment plans. These innovations hold the promise of transforming clinical practice by enabling more timely and effective management of endometrial cancer.

Circular RNAs (circRNAs) have been confirmed to be an important modulator and therapeutic target of cervical cancer (CC). The aim of this study is to explore the role and mechanism of circ_0081723 in CC progression. Circ_0081723, microRNA-545-3p (miR-545-3p), and CREB3 regulatory factor (CREBRF) levels were detected using quantitative real-time PCR (qRT-PCR) assay. CREBRF, ki-67, Bcl-2 related X protein (Bax), and E-cadherin expression levels were determined using western blot (WB) and immunohistochemistry (IHC) assays. Cell proliferation was assessed using Cell Counting Kit-8 (CCK-8), cell colony formation, and 5-ethynyl-2'-deoxyuridine (EdU) assays. Flow cytometry was used to measure cell apoptosis.  Cell migration and invasion were examined using Transwell assay. Interaction between miR-545-3p and circ_0081723 or CREBRF was verified using dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assays. The biological role of circ_0081723 on CC growth was examined using the xenograft tumor model in vivo. Circ_0081723 and CREBRF were increased, and miR-545-3p was decreased in CC tissues and cells. Circ_0081723 silencing suppressed CC cell growth and motility whereas boosted CC cell apoptosis. Besides, circ_0081723 acted as a molecular sponge for miR-545-3p, and circ_0081723 knockdown-induced effects were largely reversed by miR-545-3p downregulation in CC cells. Moreover, miR-545-3p repressed CC progression by targeting CREBRF.  Circ_0081723 absence blocked xenograft tumor growth in vivo. Circ_0081723 stimulated CC cell malignant behaviors by regulating the miR-545-3p/CREBRF pathway, providing a possible circRNA-targeted therapy for CC.

Quantitative analysis of cell-free RNA (cfRNA) in plasma sample can be used for screening, diagnosing, and prognosticating of multiple diseases. Here, we report a quantitative CRISPR/Cas digital imaging platform (qCasdip) for the detection of various cfRNAs, including circular RNAs and miRNAs, in clinical samples at the attomolar (aM) level without the need for preamplification. Digital counting strategy provides qCasdip quantitative ability with a linear detection range of 102-106 aM. Meanwhile, qCasdip demonstrated cfRNA profiling in clinical plasma samples, improving the diagnosis of breast cancer. These data highlight the potential of qCasdip to quantitatively assess the molecular patterns of specific cfRNA panels in plasma, thereby providing a novel liquid biopsy solution to enhance disease diagnosis.

Accurate tumor detection is crucial for the early discovery and subsequent treatment of small neoplastic foci. Molecular imaging, which combines non-invasiveness, high specificity, and strong sensitivity, excels in diagnosing early tumors and stands out among tumor diagnosis methods. Here, we introduced a dual-modal imaging probe capable of actively targeting tumor cells, suitable for both near-infrared (NIR) fluorescence and magnetic resonance imaging (MRI). Dendritic mesoporous silica was used as a carrier for the probe, encapsulating Ag2S quantum dots (QDs) for NIR fluorescence imaging. Additionally, the probe conjugated the MRI contrast agent Gd-DOTA and cetuximab, which targeted EGFR on the tumor cell membrane surface, to achieve dual-modal imaging in the tumor area. This strategy provided a methodology for the accurate diagnosis of early-stage tumor lesions and guides precise lesion resection during surgery, offering significant potential for clinical application.

Lung cancer remains a global health concern, demanding the development of noninvasive, prompt, selective, and point-of-care diagnostic tools. Correspondingly, breath analysis using nanobiosensors has emerged as a promising noninvasive nose-on-chip technique for the early detection of lung cancer through monitoring diversified biomarkers such as volatile organic compounds/gases in exhaled breath. This comprehensive review summarizes the state-of-the-art breath-based lung cancer diagnosis employing chemiresistive-module nanobiosensors supported by theoretical findings. It unveils the fundamental mechanisms and biological basis of breath biomarker generation associated with lung cancer, technological advancements, and clinical implementation of nanobiosensor-based breath analysis. It explores the merits, challenges, and potential alternate solutions in implementing these nanobiosensors in clinical settings, including standardization, biocompatibility/toxicity analysis, green and sustainable technologies, life-cycle assessment, and scheming regulatory modalities. It highlights nanobiosensors' role in facilitating precise, real-time, and on-site detection of lung cancer through breath analysis, leading to improved patient outcomes, enhanced clinical management, and remote personalized monitoring. Additionally, integrating these biosensors with artificial intelligence, machine learning, Internet-of-things, bioinformatics, and omics technologies is discussed, providing insights into the prospects of intelligent nose-on-chip lung cancer sniffing nanobiosensors. Overall, this review consolidates knowledge on breathomic biosensor-based lung cancer screening, shedding light on its significance and potential applications in advancing state-of-the-art medical diagnostics to reduce the burden on hospitals and save human lives.

Chronic kidney disease (CKD) is a progressive condition characterized by a gradual loss of kidney function, leading to significant health complications and an increased risk of cardiovascular events. Early detection and effective management are crucial for slowing disease progression and improving patient outcomes. Biomarkers are valuable tools in CKD diagnosis, prognosis, and treatment. Traditional biomarkers, such as serum creatinine and urine protein, are widely used, but emerging biomarkers like cystatin C, kidney injury molecule-1 (KIM-1), and neutrophil gelatinase-associated lipocalin (NGAL) offer enhanced diagnostic precision and insights into disease severity. These advanced biomarkers are particularly important in older adults, who may present with age-related physiological changes and comorbid conditions that complicate CKD management. This review explores the current state of biomarker research in CKD, focusing on their application in older populations. It highlights the role of traditional and emerging biomarkers, discusses their relevance for early detection and prognosis, and examines future directions in biomarker research, including technological innovations and personalized medicine approaches. By integrating biomarkers into clinical practice, healthcare providers can achieve more accurate diagnoses, tailor treatments to individual patient needs, and potentially improve the overall management of CKD. Continued research and development in this field are essential for addressing the complexities of CKD and advancing patient care.

A label-free optical sandwich immunoassay sensor, utilizing weak value amplification and total internal reflection, was devised for real-time, high-sensitivity analysis and detection of low-concentration targets. 3D printed channels and sodium chloride solution were employed to ensure reproducibility, reliability, and stability of the measurements for calibration. The sandwich structure demonstrated enhanced responsiveness in the proposed optical biosensor through a comparative analysis of the direct assay and sandwich assay for detecting alpha-fetoprotein (AFP) at the same concentration. By optimizing the binding sequences of the coating antibody, target, and detection antibody in the sandwich method, a more suitable sandwich sensing approach based on weak value amplification was achieved. With this approach, the limit of detection (LOD) of 6.29 ng/mL (pM level) for AFP in PBS solution was achieved. AFP testing and regeneration experiments in human serum have proved the feasibility of our methods in detecting complex samples and the reusability of sensing chips. Additionally, the method demonstrated excellent selectivity for unpaired antigens. The efficacy of this methodology was evaluated by simultaneously detecting AFP, carcinoembryonic antigen (CEA), and CA15-3 on a singular sensor chip. In conclusion, the label-free sandwich immunoassay sensing scheme holds promise for advancing the proposed optical sensors based on weak value amplification in early diagnosis and prevention applications. Compared to other biomarker detection methods, it will be easier to promote in practical applications.

Over the past decade, circular RNA (circRNA) research has evolved into a bona fide research field shedding light on the functional consequence of this unique family of RNA molecules in cancer. Although the method of formation and the abundance of circRNAs can differ from their cognate linear mRNA, the spectrum of interacting partners and their resultant cellular functions in oncogenesis are analogous. However, with 10 times more diversity in circRNA variants compared with linear RNA variants, combined with their hyperstability in the cell, circRNAs are equipped to influence every stage of oncogenesis. This is an opportune time to address the breadth of circRNA in cancer focused on their spatiotemporal expression, mutations in biogenesis factors and contemporary functions through each stage of cancer. In this Review, we highlight examples of functional circRNAs in specific cancers, which satisfy critical criteria, including their physical co-association with the target and circRNA abundance at stoichiometrically valid quantities. These considerations are essential to develop strategies for the therapeutic exploitation of circRNAs as biomarkers and targeted anticancer agents.

Immune cell therapies are an emerging class of living drugs that rely on the delivery of therapeutic transgenes to enhance, modulate, or restore cell function, such as those that encode for tumor-targeting receptors or replacement proteins. However, many cellular immunotherapies are autologous treatments that are limited by high manufacturing costs, typical vein-to-vein time of 3-4 weeks, and severe immune-related adverse effects. To address these issues, different classes of gene delivery vehicles are being developed to target specific immune cell subsets in vivo to address the limitations of ex vivo manufacturing, modulate therapeutic responses in situ, and reduce on- and off-target toxicity. The success of in vivo gene delivery to immune cells - which is being tested at the preclinical and clinical stages of development for the treatment of cancer, infectious diseases, and autoimmunity - is paramount for the democratization of cellular immunotherapies.

Colorimetric sensing offers instant reporting via visible signals. Versus labor-intensive and instrument-dependent detection methods, colorimetric sensors present advantages including short acquisition time, high throughput screening, low cost, portability, and a user-friendly approach. These advantages have driven substantial growth in colorimetric sensors, particularly in point-of-care (POC) diagnostics. Rapid progress in nanotechnology, materials science, microfluidics technology, biomarker discovery, digital technology, and signal pattern analysis has led to a variety of colorimetric reagents and detection mechanisms, which are fundamental to advance colorimetric sensing applications. This review first summarizes the basic components (e.g., color reagents, recognition interactions, and sampling procedures) in the design of a colorimetric sensing system. It then presents the rationale design and typical examples of POC devices, e.g., lateral flow devices, microfluidic paper-based analytical devices, and wearable sensing devices. Two highlighted colorimetric formats are discussed: combinational and activatable systems based on the sensor-array and lock-and-key mechanisms, respectively. Case discussions in colorimetric assays are organized by the analyte identities. Finally, the review presents challenges and perspectives for the design and development of colorimetric detection schemes as well as applications. The goal of this review is to provide a foundational resource for developing colorimetric systems and underscoring the colorants and mechanisms that facilitate the continuing evolution of POC sensors.

Timely detection of early-stage cancer holds immense potential in enhancing prognostic outcomes. There is an increasing desire for versatile tools to enable simple, sensitive, and cost-effective cancer detection. By exploiting the extraintestinal metabolic inertness and efficiency renal clearance of sucrose, we designed a liposome nanosensor using sucrose as a messenger to convert tumor-specific esterase activity into glucose meter readout, enabling economical and sensitive urinalysis for cancer detection in point-of-care testing (POCT). Our results demonstrate that the nanosensors exhibited significant signal differences between tumor-bearing and healthy mice in both orthotopic and metastatic tumor models. Additionally, efficient elimination of the nanosensors through the hepatobiliary pathway was observed with no significant toxicity. Such a non-invasive diagnostic modality significantly assists in personalized pharmacological treatment and follow-up efficacy assessment. We envision that this modular liposome nanosensor platform might be applied for economically detecting diverse diseases via a simple urinary test.

In accordance with the World Health Organization data, cancer remains at the forefront of fatal diseases. An upward trend in cancer incidence and mortality has been observed globally, emphasizing that efforts in developing detection and treatment methods should continue. The diagnostic path typically begins with learning the medical history of a patient; this is followed by basic blood tests and imaging tests to indicate where cancer may be located to schedule a needle biopsy. Prompt initiation of diagnosis is crucial since delayed cancer detection entails higher costs of treatment and hospitalization. Thus, there is a need for novel cancer detection methods such as liquid biopsy, elastography, synthetic biosensors, fluorescence imaging, and reflectance confocal microscopy. Conventional therapeutic methods, although still common in clinical practice, pose many limitations and are unsatisfactory. Nowadays, there is a dynamic advancement of clinical research and the development of more precise and effective methods such as oncolytic virotherapy, exosome-based therapy, nanotechnology, dendritic cells, chimeric antigen receptors, immune checkpoint inhibitors, natural product-based therapy, tumor-treating fields, and photodynamic therapy. The present paper compares available data on conventional and modern methods of cancer detection and therapy to facilitate an understanding of this rapidly advancing field and its future directions. As evidenced, modern methods are not without drawbacks; there is still a need to develop new detection strategies and therapeutic approaches to improve sensitivity, specificity, safety, and efficacy. Nevertheless, an appropriate route has been taken, as confirmed by the approval of some modern methods by the Food and Drug Administration.

Fluorescence imaging in the second near-infrared window (NIR-II) is burgeoning because of its higher imaging fidelity in monitoring physiological and pathological processes than clinical visible/the second near-infrared window fluorescence imaging. Notably, the imaging fidelity is heavily dependent on fluorescence agents. So far, indocyanine green, one of the polymethine dyes, with good biocompatibility and renal clearance is the only dye approved by the Food and Drug Administration, but it shows relatively low NIR-II brightness. Importantly, tremendous efforts are devoted to synthesizing polymethine dyes for imaging preclinically and clinically. They have shown feasibility in the customization of structure and properties to fulfill various needs in imaging and therapy. Herein, a timely update on NIR-II polymethine dyes, with a special focus on molecular design strategies for fluorescent, photoacoustic, and multimodal imaging, is offered. Furthermore, the progress of polymethine dyes in sensing pathological biomarkers and even reporting drug release is illustrated. Moreover, the NIR-II fluorescence imaging-guided therapies with polymethine dyes are summarized regarding chemo-, photothermal, photodynamic, and multimodal approaches. In addition, artificial intelligence is pointed out for its potential to expedite dye development. This comprehensive review will inspire interest among a wide audience and offer a handbook for people with an interest in NIR-II polymethine dyes.

The early diagnosis of cancer is vital for effective treatment and improved prognosis. Tumor biomarkers, which can be used for the early diagnosis, treatment, and prognostic evaluation of cancer, have emerged as a topic of intense research interest in recent years. Nucleic acid, as a type of tumor biomarker, contains vital genetic information, which is of great significance for the occurrence and development of cancer. Currently, living cell nucleic acid probes, which enable the in situ imaging and dynamic monitoring of nucleic acids, have become a rapidly developing field. This review focuses on living cell nucleic acid probes that can be used for the early diagnosis of tumors. We describe the fundamental design of the probe in terms of three units and focus on the roles of different nanomaterials in probe delivery.

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Determining whether multi-cancer early detection (MCED) tests are cost effective is important in deciding whether they should be included in the clinical path of cancer care, especially for cancers where screening tools do not exist.

The main objective of this study is to determine the cost effectiveness of including a MCED screening regimen together with existing provincial screening protocols for selected cancers that are prevalent in Ontario, Canada, among average risk persons aged 50-75 years. The selected cancers include breast, colorectal, lung, esophageal, liver, pancreatic, stomach, and ovarian.

Cost effectiveness was estimated from a provincial Ministry of Health perspective. A state-transition Markov model representing the decision path of both the proposed and existing screening strategies along the natural history of the selected types of cancers was implemented. The incremental cost-effectiveness ratio (ICER) was calculated using data from available literature and the guidelines published by the Canadian Agency for Drugs and Technologies in Health (CADTH) for conducting a cost-effectiveness analysis, which included a discount rate of 1.5% applied to all costs and outcomes. Costs were also converted to 2022 Canadian dollars. To test the robustness of the model, both univariate and probabilistic sensitivity analyses were conducted.

MCED screening resulted in more diagnosed cases of each type of cancer, even at an earlier stage of disease. This was also associated with fewer related deaths compared with standard of care. Notwithstanding, the analysis revealed that the MCED intervention was not cost effective [ICER: CAD$143,369 per quality-adjusted life year (QALY)], given a willingness to pay (WTP) threshold of $100,000 per QALY. The probabilistic sensitivity analyses revealed that the MCED intervention strategy was preferred to standard of care no more than 2% of the time at this WTP for both males and females. The model was most sensitive to the cost of MCED screening, and the levels of specificity of the MCED and colorectal cancer screening tests.

The main contribution of the study is to present and execute a methodological approach that can be adopted to test the cost effectiveness of an MCED tool in the Canadian setting. The model is also sufficiently generic that it could be adapted to other jurisdictions, and with consideration for increasing the WTP threshold beyond the common $100,000 per QALY limit, given the life-threatening nature of cancer, to ensure that MCED interventions are cost-effective.

Optical imaging has played an indispensable role in clinical diagnostics and fundamental biomedical research due to its high sensitivity, high spatiotemporal resolution, cost-effectiveness, and easy accessibility. However, the issues of light scattering and low tissue penetration make them effective only for superficial imaging. To overcome these issues, renal-clearable optical nanoprobes have recently emerged, which are activated by abnormal disease-associated biomarkers and initiate a pharmacokinetic switch by undergoing degradation and eventually releasing signal reporters into urine, for simple imaging and sensitive optical in vitro urinalysis. In this review, we focus on the advancements of renal-clearable organic nanoprobes for optical imaging and remote urinalysis. The versatile design strategies of these nanoprobes are discussed along with their sensing mechanisms toward biomolecules of interest as well as their unique biological applications. Finally, challenges and perspectives are discussed to further advance the next-generation renal-clearable nanoprobes for in vivo imaging and in vitro urinalysis.

Lung cancer is associated with the greatest cancer mortality as it typically presents with incurable distributed disease. Biomarkers relevant to risk assessment for the detection of lung cancer continue to be a challenge because they are often not detectable during the asymptomatic curable stage of the disease. A solution to population-scale testing for lung cancer will require a combination of performance, scalability, cost-effectiveness, and simplicity.

One solution is to measure the activity of serum available enzymes that contribute to the transformation process rather than counting biomarkers. Protease enzymes modify the environment during tumor growth and present an attractive target for detection. An activity based sensor platform sensitive to active protease enzymes is presented. A panel of 18 sensors was used to measure 750 sera samples from participants at increased risk for lung cancer with or without the disease.

A machine learning approach is applied to generate algorithms that detect 90% of cancer patients overall with a specificity of 82% including 90% sensitivity in Stage I when disease intervention is most effective and detection more challenging.

This approach is promising as a scalable, clinically useful platform to help detect patients who have lung cancer using a simple blood sample. The performance and cost profile is being pursued in studies as a platform for population wide screening.

Prefoldin Subunit 5 (PFDN5) plays a critical role as a member of the prefoldins (PFDNs) in maintaining a finely tuned equilibrium between protein production and degradation. However, there has been no comprehensive analysis specifically focused on PFDN5 thus far. Here, a comprehensive multi-omics (transcriptomics, genomics, and proteomics) analysis, systematic molecular biology experiments (in vitro and in vivo), transcriptome sequencing and PCR Array were performed for identifying the value of PFDN5 in pan-cancer, especially in Gastric Cancer (GC). We found PFDN5 had the potential to serve as a prognostic and therapeutic biomarker in GC. And PFDN5 could promote the proliferation of GC cells, primarily by affecting the cell cycle, cell death and immune process etc. These findings provide novel insights into the molecular mechanisms and precise treatments of in GC.

Disease-modifying drugs have transformed the treatment options for many systemic autoimmune diseases. However, an evolving understanding of disease mechanisms, which might vary between individuals, is paving the way for the development of novel agents that operate in a patient-tailored manner through immunophenotypic regulation of disease-relevant cells and the microenvironment of affected tissue domains. Immunoengineering is a field that is focused on the application of engineering principles to the modulation of the immune system, and it could enable future personalized and immunoregulatory therapies for rheumatic diseases. An important aspect of immunoengineering is the harnessing of material chemistries to design technologies that span immunologically relevant length scales, to enhance or suppress immune responses by re-balancing effector and regulatory mechanisms in innate or adaptive immunity and rescue abnormalities underlying pathogenic inflammation. These materials are endowed with physicochemical properties that enable features such as localization in immune cells and organs, sustained delivery of immunoregulatory agents, and mimicry of key functions of lymphoid tissue. Immunoengineering applications already exist for disease management, and there is potential for this new discipline to improve disease modification in rheumatology.

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.

About 94% of oral cancers are squamous cell carcinomas (OSCCs). Its occurrence is age-related due to some factors. Salivary biomarkers have good susceptibility to OSCC's early diagnosis. Moreover, since the clinical diagnosis of advanced stages of OSCC is feasible, its prognosis is very poor.

According to inclusion and exclusion criteria, 40 OSCC patients and 40 healthy people were selected, and 5 mL of saliva were prepared from each person. The quantity of saline transferrin was computed. After that, the data were analyzed.

Our study results demonstrated that the mean and standard deviation of the salivary transferrin in the control group were 1.234 mL and 0.374, respectively, and in the case group, it was equal to 2.512 mL for the mean and 0.463 for the standard deviation. There was a statistically substantial difference between the mean of the salivary transferrin variable in the two study groups.

In conclusion, the mean concentration of salivary transferrin in the case group was higher than in the control group.

Addressing the critical requirement for real-time monitoring of tumor progression in cancer care, this study introduces an innovative wearable platform. This platform employs a thermoplastic polyurethane (TPU) film embedded with hafnium oxide nanoparticles (HfO2 NPs) to facilitate dynamic tracking of tumor growth and regression in real time. Significantly, the synthesized HfO2 NPs exhibit promising characteristics as effective sonosensitizers, holding the potential to efficiently eliminate cancer cells through ultrasound irradiation. The TPU-HfO2 film, acting as a dielectric elastomer (DE) strain sensor, undergoes proportional deformation in response to changes in the tumor volume, thereby influencing its electrical impedance. This distinctive behavior empowers the DE strain sensor to continuously and accurately monitor alterations in tumor volume, determining the optimal timing for initiating HfO2 NP treatment, optimizing dosages, and assessing treatment effectiveness. Seamless integration with a wireless system allows instant transmission of detected electrical impedances to a smartphone for real-time data processing and visualization, enabling immediate patient monitoring and timely intervention by remote medical staff. By combining the dynamic tumor monitoring capabilities of the TPU-HfO2 film with the sonosensitizer potential of HfO2 NPs, this approach propels cancer care into the realm of telemedicine, representing a significant advancement in patient treatment.

This work reports the development of a novel microfluidic biosensor using a graphene field-effect transistor (GFET) design for the parallel label-free analysis of multiple biomarkers. Overcoming the persistent challenge of constructing μm2-sized FET sensitive interfaces that incorporate multiple receptors, we implement a split-float-gate structure that enables the manipulation of multiplexed biochemical functionalization using microfluidic channels. Immunoaffinity biosensing experiments are conducted using the mixture samples containing three liver cancer biomarkers, carcinoembryonic antigen (CEA), α-fetoprotein (AFP), and parathyroid hormone (PTH). The results demonstrate the capability of our label-free biochip to quantitatively detect multiple target biomarkers simultaneously by observing the kinetics in 10 minutes, with the detection limit levels in the nanomolar range. This microfluidic biosensor provides a valuable analytical tool for rapid multi-target biosensing, which can be potentially utilized for domiciliary tests of cancer screening and prognosis, obviating the need for sophisticated instruments and professional operations in hospitals.

Cancer is a dynamic process and thus requires highly informative and reliable biomarkers to help guide patient care. Liquid-based biopsies have emerged as a clinical tool for tracking cancer dynamics. Extracellular vesicles (EVs), lipid bilayer delimited particles secreted by cells, are a new class of liquid-based biomarkers. EVs are rich in selectively sorted biomolecule cargos, which provide a spatiotemporal fingerprint of the cell of origin, including cancer cells.

This review summarizes the performance characteristics of EV-based biomarkers at different stages of cancer progression, from early malignancy to recurrence, while emphasizing their potential as diagnostic, prognostic, and screening biomarkers. We discuss the characteristics of effective biomarkers, consider challenges associated with the EV biomarker field, and report guidelines based on the biomarker discovery pipeline.

Basic science and clinical trial studies have shown the potential of EVs as precision-based biomarkers for tracking cancer status, with promising applications for diagnosing disease, predicting response to therapy, and tracking disease burden. The multi-analyte cargos of EVs enhance the performance characteristics of biomarkers. Recent technological advances in ultrasensitive detection of EVs have shown promise with high specificity and sensitivity to differentiate early-cancer cases vs healthy individuals, potentially outperforming current gold-standard imaging-based cancer diagnosis. Ultimately, clinical translation will be dictated by how these new EV biomarker-based platforms perform in larger sample cohorts. Applying ultrasensitive, scalable, and reproducible EV detection platforms with better design considerations based upon the biomarker discovery pipeline should guide the field towards clinically useful liquid biopsy biomarkers.

Creating synthetic biomarkers for the development of precision diagnostics has enabled detection of disease through pathways beyond those used for traditional biofluid measurements. Synthetic biomarkers generally make use of reporters that provide readable signals in the biofluid to reflect the biochemical alterations in the local disease microenvironment during disease incidence and progression. The pharmacokinetic concentration of the reporters and biochemical amplification of the disease signal are paramount to achieving high sensitivity and specificity in a diagnostic test. Here, a cancer diagnostic platform is built using one format of synthetic biomarkers: activity-based nanosensors carrying chemically stabilized DNA reporters that can be liberated by aberrant proteolytic signatures in the tumor microenvironment. Synthetic DNA as a disease reporter affords multiplexing capability through its use as a barcode, allowing for the readout of multiple proteolytic signatures at once. DNA reporters released into the urine are detected using CRISPR nucleases via hybridization with CRISPR RNAs, which in turn produce a fluorescent or colorimetric signal upon enzyme activation. In this protocol, DNA-barcoded, activity-based nanosensors are constructed and their application is exemplified in a preclinical mouse model of metastatic colorectal cancer. This system is highly modifiable according to disease biology and generates multiple disease signals simultaneously, affording a comprehensive understanding of the disease characteristics through a minimally invasive process requiring only nanosensor administration, urine collection, and a paper test which enables point-of-care diagnostics.

Cytotoxic T-lymphocyte associated antigen-4 (CTLA-4) is an immunosuppressive checkpoint that is involved in the development and metastasis of cancers. Several studies revealed that CTLA-4 rs231775A/G polymorphism may be associated with the risk of cancer in some populations, but the conclusions of these studies are not consistent.

We conducted a pooled analysis with eligible studies to explore the association between the CTLA-4 rs231775 variant and cancer risk. Additionally, we used in silico tools to evaluated the expression of CTLA-4 on urinary system cancer. Moreover, we adopted the enzyme-linked immunosorbent assay (ELISA), and Gene Set Enrichment Analysis (GSEA) to investigate the effects of CTLA-4 on bladder cancer (BLCA).

In total, 92 case-control studies involving 29,987 patients with cancer and 36,484 healthy individuals (controls) were included in the pooled analysis. In the stratified analysis based on cancer type, the rs231775 A/G polymorphism was associated with increased bladder cancer risk in the heterozygote contrast model (OR = 1.23, 95% CI = 1.01-1.51, P = 0.040). The race-stratified analysis revealed that East Asians with the GG genotype had a 12% lower risk of developing cancer than those with the GA + AA genotype (95% CI = 0.81-0.95, P = 0.001). The in silico analysis showed that CTLA-4 expression was augmented in patients with BLCA. The ELISA results revealed that CTLA-4 expression was reduced in patients with BLCA carrying the AA genotype. Several signaling pathways, including cytokine-cytokine receptor interactions and T-cell receptor signaling, were associated with CTLA-4 expression.

The CTLA-4 rs231775 A/G polymorphism is associated with cancer risk in East Asian population. This polymorphism is especially associated with BLCA.

Biomarkers are biomolecules used to identify or predict the presence of a specific disease or condition. They play an important role in early diagnosis and may be crucial for treatment. MicroRNAs (miRNAs), a group of small non-coding RNAs, are more and more regarded as promising biomarkers for several reasons. Dysregulation of miRNAs has been linked with development of several diseases, including many different types of cancer, and abnormal levels can be present in early stages of tumor development. Because miRNAs are stable molecules secreted and freely circulating in blood and urine, they can be sampled with little or no invasion. Here, we present an overview of the current literature, focusing on the types of cancers for which dysregulation of miR-665 has been associated with disease progression, recurrence, and/or prognosis. It needs to be emphasized that the role of miR-665 sometimes seems ambiguous, in the sense that it can be upregulated in one cancer type and downregulated in another and can even change during the progression of the same cancer. Caution is thus needed before using miR-665 as a biomarker, and extrapolation between different cancer types is not advisable. Moreover, more detailed understanding of the different roles of miR-665 will help in determining its potential as a diagnostic and prognostic biomarker.