Molecular Diagnosis Research Articles

Early-Onset Colorectal Cancer-A Retrospective Study from a Tertiary Referral Hospital in Romania.

Early-onset colorectal cancer emerges as a distinctive clinical and biological entity and is generally defined as the onset of colon or rectal neoplasia before the age of 50. Several reports describe an increasing incidence worldwide of colorectal cancers occurring in individuals younger than 50 years, along with particular histologic and molecular features. Although heredity may be an explanation in some cases with young-onset colorectal cancer, other driving factors remain partially unknown. The present study explores demographic, clinical, and pathological features within a group of patients diagnosed with colorectal cancer before the age of 50. It is a retrospective survey based on data collected between 2017 and 2023 within three surgical departments from a tertiary Romanian hospital. The clinical and pathological features we identified (later-stage disease, distal colon tumor localization, mucinous histology) are mainly superimposed with the existing data in the literature regarding this pathology. In order to lower the burden that colorectal neoplasia diagnosed in the young implies, a change of paradigm should be made in terms of establishing effective and targeted screening programs but also in the direction of enhancing complex clinical, pathological, and molecular diagnosis.

Sensitization to Food and Aero-Allergens in Children with Coeliac Disease Assessed with the Use of a Multiplex Molecular Diagnostic Technique

(1) Background. Coeliac disease (CD) often co-occurs with autoimmune conditions or genetic syndromes, but there are few studies on the co-existence of CD and immunoglobulin E (IgE)-mediated allergies. The purpose of this study was to assess sensitization to food and aero-allergens in pediatric patients with CD. (2) Methods. A multiplex ALEX®2 test was used to determine specific IgEs (sIgEs). (3) Results. The study included 108 children newly diagnosed with CD. Allergen extract- and/or allergen molecule-sIgEs were detected in 49.1% of children. Most children (41.5%) were sensitized to both inhalant and food allergens. The three most common aero-allergens (timothy pollen, ryegrass, silver birch) were molecules Phl p 1, Lol p 1, and Bet v 1. The most common food allergens (hazelnut, apple, and peanut) were Cor a 1, Mal d 1, and Ara h 8 molecules of the PR-10 subfamily. Patients were not sensitized to cereal allergens containing gluten. Spearman’s rank correlation analysis of sensitized patients showed a significant positive relationship (r = 0.31) between the patients’ age and the occurrence of positive sIgEs (≥0.3 kUA/L) for inhalant allergen molecules (p = 0.045). In sensitized patients, mainly symptoms of inhalant allergy were observed, such as hay fever, conjunctivitis, and bronchial asthma. (4) Conclusions. The current study indicates the co-occurrence of IgE sensitization to food and inhalant allergens in children with CD. The study highlights the need to take a closer look at the diagnosis of IgE-mediated allergy in patients with CD, which may help in their care and lead to a better understanding of the relationship between CD and IgE-mediated allergy.

Revisiting molecular diagnosis in a family with retinitis pigmentosa: integrating deep phenotyping and bioinformatic analysis

Revisiting molecular diagnosis in a family with retinitis pigmentosa: integrating deep phenotyping and bioinformatic analysis

Establishing a Standardized DNA Extraction Method Using NaCl from Oral Mucosa Cells for Its Application in Imprinting Diseases Such as Prader-Willi and Angelman Syndromes: A Preliminary Investigation.

Diagnosing imprinting defects in neonates and young children presents challenges, often necessitating molecular analysis for a conclusive diagnosis. The isolation of genetic material from oral swabs becomes crucial, especially in settings where blood sample collection is impractical or for vulnerable populations like newborns, who possess limited blood volumes and are often too fragile for invasive procedures. Oral swab samples emerge as an excellent source of DNA, effectively overcoming obstacles associated with rare diseases. In our study, we specifically addressed the determination of the quality and quantity of DNA extracted from oral swab samples using NaCl procedures. We compared these results with extractions performed using a commercial kit. Subsequently, the obtained material underwent MS-HRM analysis for loci associated with imprinting diseases such as Prader-Willi and Angelman syndromes. Our study emphasizes the significance of oral swab samples as a reliable source for obtaining DNA for MS-HRM analysis. NaCl extraction stands out as a practical and cost-effective method for genetic studies, contributing to a molecular diagnosis that proves particularly beneficial for patients facing delays in characterization, ultimately influencing their treatment.

Deciphering the progression of fine-needle aspiration: A bibliometric analysis of thyroid nodule research.

This study aims to dissect the evolution and pivotal shifts in Fine-Needle Aspiration (FNA) research for thyroid nodules over the past 2 decades, focusing on delineating key technological advancements and their impact on clinical practice. A comprehensive bibliometric analysis was conducted on 5418 publications from the Web of Science Core Collection database (2000-2023). Publications were rigorously selected based on their contributions to the advancement of FNA techniques and their influence on thyroid nodule management practices. Our analysis uncovered significant breakthroughs, most notably the incorporation of ultrasound and molecular diagnostics in FNA, which have markedly elevated diagnostic accuracy. A pivotal shift was identified towards minimally invasive post-FNA treatments, such as Radiofrequency Ablation, attributable to these diagnostic advancements. Additionally, the emergence of AI-assisted cytology represents a frontier in precision diagnostics, promising enhanced disease identification. The geographical analysis pinpointed the United States, Italy, and China as key contributors, with the United States leading in both publication volume and citation impact. This bibliometric analysis sheds light on the transformative progression in FNA practices for thyroid nodules, characterized by innovative diagnostic technologies and a trend towards patient-centric treatment approaches. The findings underscore the need for further research into AI integration and global practice standardization. Future explorations should focus on the practical application of these advancements in diverse healthcare settings and their implications for global thyroid nodule management.

Unravelling the clinical heterogeneity of undefined recurrent fever over time in the European registries on Autoinflammation

BackgroundSystemic autoinflammatory disorders (SAIDs) represent a growing spectrum of diseases characterized by dysregulation of the innate immune system. The most common pediatric autoinflammatory fever syndrome, Periodic Fever, Aphthous Stomatitis, Pharyngitis, Adenitis (PFAPA), has well defined clinical diagnostic criteria, but there is a subset of patients who do not meet these criteria and are classified as undefined autoinflammatory diseases (uAID). This project, endorsed by PRES, supported by the EMERGE fellowship program, aimed to analyze the evolution of symptoms in recurrent fevers without molecular diagnosis in the context of undifferentiated AIDs, focusing on PFAPA and syndrome of undifferentiated recurrent fever (SURF), using data from European AID registries.MethodsData of patients with PFAPA, SURF and uSAID were collected from 3 registries including detailed epidemiological, demographic and clinical data, results of the genetic testing and additional laboratory investigations with retrospective application of the modified Marshall and PRINTO/Eurofever classification criteria on the cohort of PFAPA patients and preliminary SURF criteria on uSAID/SURF patients.ResultsClinical presentation of PFAPA is variable and some patients did not fit the conventional PFAPA criteria and exhibit different symptoms. Some patients did not meet the criteria for either PFAPA or SURF, highlighting the heterogeneity within these groups. The study also explored potential overlaps between PFAPA and SURF/uAID, revealing that some patients exhibited symptoms characteristic of both conditions, emphasizing the need for more precise classification criteria.ConclusionsPatients with recurrent fevers without molecular diagnoses represent a clinically heterogeneous group. Improved classification criteria are needed for both PFAPA and SURF/uAID to accurately identify and manage these patients, ultimately improving clinical outcomes.

Abstract IA002: Molecular subtypes of NMIBC

Abstract Non-muscle-invasive bladder cancers (NMIBCs) show large variation in disease aggressiveness which is not fully explained by differences in clinical and pathological factors. It is therefore essential to increase our understanding of the molecular landscape of NMIBC to improve risk assessment and identify potential therapeutic targets. In 2021, we published the four transcriptomic UROMOL2021 classes of NMIBC: class 1, class 2a, class 2b and class 3 (Lindskrog et al., Nature Communications, 2021). Multiple other subtyping schemes for NMIBC have been published, including, among others, the Lund taxonomy (Marzouka et al., The Journal of Molecular Diagnostics, 2022), the stage-stratified subtypes from Leeds (Hurst et al., Cell Reports Medicine, 2021) and BRS1-3 from Rotterdam (de Jong et al., Science Translational Medicine, 2023). In my presentation, I will give an overview of the development and status of NMIBC subtypes and discuss clinical utility. Furthermore, I will present novel data from the UROMOL cohort, where we have now performed a comprehensive genomic characterization of tumors using whole exome sequencing (n=438) and shallow whole genome sequencing (n=362). Overall, we observe a large genomic variation within NMIBC that is associated with different gene expression profiles (UROMOL2021 classes). We performed integrative clustering analysis of somatic mutations, copy number alterations and gene expression data for 230 tumors and identified four “iClusters”, which were highly prognostic and went beyond the single-layer stratifications of tumors. Multi-omics subtyping may improve our understanding of differences in disease aggressiveness within NMIBC further, which could ultimately be used to improve risk assessment of patients and identify potential therapeutic targets. Citation Format: Sia V. Lindskrog. Molecular subtypes of NMIBC [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr IA002.

Negligible effects of read trimming on the accuracy of germline short variant calling in the human genome

Background Next generation sequencing (NGS) has become a standard tool in the molecular diagnostics of Mendelian disease, and the precision of such diagnostics is greatly affected by the accuracy of variant calling from sequencing data. Recently, we have comprehensively evaluated the performance of multiple variant calling pipelines. However, no systematic analysis of the effects of read trimming on variant discovery with modern variant calling software has yet been performed. Methods In this work, we systematically evaluated the effects of adapters on the performance of 8 variant calling and filtering methods using 14 standard reference Genome-in-a-Bottle (GIAB) samples. Variant calls were compared to the ground truth variant sets, and the effect of adapter trimming with different tools was assessed using major performance metrics (precision, recall, and F1 score). Results We show that adapter trimming has no effect on the accuracy of the best-performing variant callers (e.g., DeepVariant) on whole-genome sequencing (WGS) data. For whole-exome sequencing (WES) datasets subtle improvement of accuracy was observed in some of the samples. In high-coverage WES data (~200x mean coverage), adapter removal allowed for discovery of 2-4 additional true positive variants in only two out of seven datasets tested. Moreover, this effect was not dependent on the median insert size and proportion of adapter sequences in reads. Surprisingly, the effect of trimming on variant calling was reversed when moderate coverage (~80-100x) WES data was used. Finally, we show that some of the recently developed machine learning-based variant callers demonstrate greater dependence on the presence of adapters in reads. Conclusions Taken together, our results indicate that adapter removal is unnecessary when calling germline variants, but suggest that preprocessing methods should be carefully chosen when developing and using machine learning-based variant analysis methods.

Liquid profiling for patients with advanced cancer is ready for clinical integration

SummaryMolecular profiling of circulating tumor DNA (ctDNA) to guide treatment decisions has found its way into routine management of patients with advanced cancer. This represents a pivotal advancement in precision oncology, offering a non-invasive and fast-tracked method to detecting clinically relevant biomarkers. With the backing of international oncology guidelines, ctDNA analysis is now a standard approach to consider in molecular diagnostics. Despite the promise of ctDNA in refining treatment strategies through the detection of genomic alterations and treatment-relevant biomarkers with high concordance to tissue biopsies, challenges persist. These include the interpretation of discordances due to tumor heterogeneity, sampling biases, and technical limitations, alongside the differentiation of tumor-derived mutations from clonal hematopoiesis. The current consensus supports the utility of comprehensive genomic profiling (CGP) panels for a broad spectrum of actionable targets, while acknowledging the limitations and advocating for a balanced application of “tissue-first” and “plasma-first” approaches tailored to individual patient scenarios. The essential role of molecular tumor boards (MTBs) is in navigating the complexities of ctDNA data interpretation, thereby ensuring the effective incorporation of liquid biopsy into personalized cancer treatment regimens.

Droplet microfluidics for single‐molecule and single‐cell analysis in research, diagnosis, and therapy

AbstractDuring the last decade, molecular diagnostics has become increasingly important, especially during the SARS‐CoV‐2 pandemic. Advances in droplet‐based microfluidics, which divides samples into thousands of microdroplets, are responsible for high‐throughput data provision, increased analysis sensitivity, and improved performance to overcome challenges in controlling diseases and early diagnosis. Different targets, such as nucleic acids, proteins, or single cells, can be detected and analyzed in terms of their characteristics in a much more extensive and precise manner with the integration of droplet microfluidics into various molecular diagnostic techniques. In this review, we explore recent advances in the development of droplet microfluidics‐based molecular diagnostic techniques and future perspectives in the field.

Increasing the diagnostic yield of childhood glaucoma cases recruited into the 100,000 Genomes Project

Childhood glaucoma (CG) encompasses a heterogeneous group of genetic eye disorders that is responsible for approximately 5% of childhood blindness worldwide. Understanding the molecular aetiology is key to improving diagnosis, prognosis and unlocking the potential for optimising clinical management. In this study, we investigated 86 CG cases from 78 unrelated families of diverse ethnic backgrounds, recruited into the Genomics England 100,000 Genomes Project (GE100KGP) rare disease cohort, to improve the genetic diagnostic yield. Using the Genomics England/Genomic Medicine Centres (GE/GMC) diagnostic pipeline, 13 unrelated families were solved (13/78, 17%). Further interrogation using an expanded gene panel yielded a molecular diagnosis in 7 more unrelated families (7/78, 9%). This analysis effectively raises the total number of solved CG families in the GE100KGP to 26% (20/78 families). Twenty-five percent (5/20) of the solved families had primary congenital glaucoma (PCG), while 75% (15/20) had secondary CG; 53% of this group had non-acquired ocular anomalies (including iris hypoplasia, megalocornea, ectopia pupillae, retinal dystrophy, and refractive errors) and 47% had non-acquired systemic diseases such as cardiac abnormalities, hearing impairment, and developmental delay. CYP1B1 was the most frequently implicated gene, accounting for 55% (11/20) of the solved families. We identified two novel likely pathogenic variants in the TEK gene, in addition to one novel pathogenic copy number variant (CNV) in FOXC1. Variants that passed undetected in the GE100KGP diagnostic pipeline were likely due to limitations of the tiering process, the use of smaller gene panels during analysis, and the prioritisation of coding SNVs and indels over larger structural variants, CNVs, and non-coding variants.

A novel variant in the FLNB gene associated with spondylocarpotarsal synostosis syndrome.

Genetic disorders involved in skeleton system arise due to the disturbance in skeletal development, growth and homeostasis. Filamin B is an actin binding protein which is large dimeric protein which cross link actin cytoskeleton filaments into dynamic structure. A single nucleotide changes in the FLNB gene causes spondylocarpotarsal synostosis syndrome, a rare bone disorder due to which the fusion of carpels and tarsals synostosis occurred along with fused vertebrae. In the current study we investigated a family residing in north-western areas of Pakistan. The whole exome sequencing of proband was performed followed by Sanger sequencing of all family members of the subject to validate the variant segregation within the family. Bioinformatics tools were utilized to assess the pathogenicity of the variant. Whole Exome Sequencing revealed a novel variant (NM_001457: c.209C>T and p.Pro70Leu) in the FLNB gene which was homozygous missense mutation in the FLNB gene. The variant was further validated and visualized by Sanger sequencing and protein structure studies respectively as mentioned before. The findings have highlighted the importance of the molecular diagnosis in SCT (spondylocarpotarsal synostosis syndrome) for genetic risk counselling in consanguineous families.

Optical genome mapping unveils hidden structural variants in neurodevelopmental disorders

While short-read sequencing currently dominates genetic research and diagnostics, it frequently falls short of capturing certain structural variants (SVs), which are often implicated in the etiology of neurodevelopmental disorders (NDDs). Optical genome mapping (OGM) is an innovative technique capable of capturing SVs that are undetectable or challenging-to-detect via short-read methods. This study aimed to investigate NDDs using OGM, specifically focusing on cases that remained unsolved after standard exome sequencing. OGM was performed in 47 families using ultra-high molecular weight DNA. Single-molecule maps were assembled de novo, followed by SV and copy number variant calling. We identified 7 variants of interest, of which 5 (10.6%) were classified as likely pathogenic or pathogenic, located in BCL11A, OPHN1, PHF8, SON, and NFIA. We also identified an inversion disrupting NAALADL2, a gene which previously was found to harbor complex rearrangements in two NDD cases. Variants in known NDD genes or candidate variants of interest missed by exome sequencing mainly consisted of larger insertions (> 1kbp), inversions, and deletions/duplications of a low number of exons (1–4 exons). In conclusion, in addition to improving molecular diagnosis in NDDs, this technique may also reveal novel NDD genes which may harbor complex SVs often missed by standard sequencing techniques.

Sample-to-result molecular diagnostic platforms and their suitability for infectious disease testing in low- and middle-income countries.

Diagnostics are an essential, undervalued part of the health-care system. For many diseases, molecular diagnostics are the gold standard, but are not easy to implement in Low- and Middle-Income Countries (LMIC). Sample-to-result (S2R) platforms combining all procedures in a closed system could offer a solution. In this paper, we investigated their suitability for implementation in LMIC. A scorecard was used to evaluate different platforms on a range of parameters. Most platforms scored fairly on the platform itself, ease-of-use and test consumables; however, shortcomings were identified in cost, distribution and test panels tailored to LMIC needs. The diagnostic coverage for common infectious diseases was found to have a wider coverage in high-income countries (HIC) than LMIC. A literature study showed that in LMIC, these platforms are mainly used as diagnostic tools or evaluation of diagnostic performance, with a minority assessing the operational characteristics or the clinical utility. In this narrative review, we identified various points for adaptation of S2R platforms to LMIC conditions. For S2R platforms to be suitable for implementation in LMIC some modifications by the manufacturers could be considered. Furthermore, strengthening health systems and digitalization are vital; as are smaller, cheaper, faster, and sustainable technologies.

A prospective study on Rickettsia infections in Central India

Rickettsial infections are under-reported in India. The actual disease burden has been underestimated as non-specific serological tests are mostly used to diagnose these infections. The aim of this study was the detection of Rickettsia infections in clinical specimens by Real-time Polymerase Chain Reaction.A study was established to analyse blood samples taken from pyrexia of unknown origin (PUO) or undifferentiated fever cases. A total of 69 such patients, were referred/walked-in to our diagnostic centre, Indore, India between October 2021 and May 2023. The blood samples were collected in EDTA lavender (purple) top tube.Of the tested samples, 14 patients (20.3%) were positive for Rickettsia infection.Gender wise distribution revealed higher incidence (57%) of Rickettsial infections in male patients. Children were majorly infected (50% of cases); multiple infection was also noted in them, though severity was not high. Severe clinical manifestation including hospitalization was also noted in some patients. Few reports are available from India on molecular diagnosis of Rickettsia infection. Early-stage molecular diagnosis will help to stave off and prevent serious complications.

Viral Meningitis (Enterovirus) Outbreak in The Pediatric Population of Sulaymaniyah Governorate, Iraq: A Multi-Center Experience

Introduction Viral meningitis, often caused by enteroviruses in children, is prevalent globally but is difficult to distinguish from bacterial forms. Molecular testing like PCR is vital; however. This study investigates the characteristics of viral meningitis in pediatric patients during an outbreak in Sulaymaniyah Governorate, Iraq. Methods This is a multicentered prospective study that included children with a confirmed diagnosis of viral meningitis who have visited pediatric clinics throughout Sulaimani, Halabja, Kalar, and Ranya cities during the period from May 2023 to June 2023. Results In total, 116 cases were included, of whom 75 (64.7%) were male and had a mean age of 6.5 ± 3.2. Most were between the ages of 4-6 (38, 32.8%) and 7-12 years (55, 47.4%). Only 53.4% had contact with another patient. Common symptoms included fever (63.8%) and headache (62.1%). Lymphocyte predominance was observed in 46.6% of CSF samples. Upon molecular diagnosis, the inflammation in all of the cases was due to enterovirus infection. Most of the patients (75%) received empirical antibiotics. The average hospital stay was 10 days. While 95.7% of patients had no complications during recovery, a few experienced issues like weakness and malaise. All had good clinical outcomes. Conclusion The viral meningitis outbreak in Sulaymaniyah Governorate is caused by enterovirus, with epidemiological, clinical, and laboratory findings similar to that of the literature. The condition has resulted in a high prescription rate of empirical antibiotics due to late diagnosis.

Rapid and sensitive diagnosis of live Mycobacterium tuberculosis using clustered regularly interspaced short palindromic repeat‐Cas13a point‐of‐care RNA testing

AbstractMycobacterium tuberculosis (MTB) is the causal pathogen of tuberculosis (TB). Rapid and accurate detection of live MTB is important for transmission control and patient treatment. Here, we described a clustered regularly interspaced short palindromic repeat (CRISPR)‐Cas13a‐based molecular diagnosis approach for rapid and specific detection of live MTB. This detection method, which we termed CRISPR‐Live‐MTB, contained two consecutive reactions including nuclear acid sequence‐based amplification (NASBA) and CRISPR‐Cas13a collateral cleavage reaction. CRISPR‐Live‐MTB could efficiently detect MTB single‐stranded RNA (ssRNA) in 2 hours with high specificity over double‐stranded DNA (dsDNA). Importantly, CRISPR‐Live‐MTB exhibited a limit of detection of 2.4 copies for MTB ssRNA, which was 1000 times lower than that of the clinically used NASBA method. Moreover, lateral flow was integrated into the CRISPR‐Live‐MTB method to enable point‐of‐care testing application with a sensitivity of 95% and a specificity of 100%. Overall, our study demonstrated the feasibility of CRISPR‐Live‐MTB as a rapid, sensitive, and specific approach for live MTB detection.

Application of whole exome sequencing in the diagnosis of muscular disorders: a study of Taiwanese pediatric patients

BackgroundMuscular dystrophies and congenital myopathies encompass various inherited muscular disorders that present diagnostic challenges due to clinical complexity and genetic heterogeneity.MethodsThis study aimed to investigate the use of whole exome sequencing (WES) in diagnosing muscular disorders in pediatric patients in Taiwan. Out of 161 pediatric patients suspected to have genetic/inherited myopathies, 115 received a molecular diagnosis through conventional tests, single gene testing, and gene panels. The remaining 46 patients were divided into three groups: Group 1 (multiplex ligation-dependent probe amplification–negative Duchenne muscular dystrophy) with three patients (6.5%), Group 2 (various forms of muscular dystrophies) with 21 patients (45.7%), and Group 3 (congenital myopathies) with 22 patients (47.8%).ResultsWES analysis of these groups found pathogenic variants in 100.0% (3/3), 57.1% (12/21), and 68.2% (15/22) of patients in Groups 1 to 3, respectively. WES had a diagnostic yield of 65.2% (30 patients out of 46), detecting 30 pathogenic or potentially pathogenic variants across 28 genes.ConclusionWES enables the diagnosis of rare diseases with symptoms and characteristics similar to congenital myopathies and muscular dystrophies, such as muscle weakness. Consequently, this approach facilitates targeted therapy implementation and appropriate genetic counseling.

Identification of Gene Expression in Different Stages of Breast Cancer with Machine Learning.

Determining the tumor origin in humans is vital in clinical applications of molecular diagnostics. Metastatic cancer is usually a very aggressive disease with limited diagnostic procedures, despite the fact that many protocols have been evaluated for their effectiveness in prognostication. Research has shown that dysregulation in miRNAs (a class of non-coding, regulatory RNAs) is remarkably involved in oncogenic conditions. This research paper aims to develop a machine learning model that processes an array of miRNAs in 1097 metastatic tissue samples from patients who suffered from various stages of breast cancer. The suggested machine learning model is fed with miRNA quantitative read count data taken from The Cancer Genome Atlas Data Repository. Two main feature-selection techniques have been used, mainly Neighborhood Component Analysis and Minimum Redundancy Maximum Relevance, to identify the most discriminant and relevant miRNAs for their up-regulated and down-regulated states. These miRNAs are then validated as biological identifiers for each of the four cancer stages in breast tumors. Both machine learning algorithms yield performance scores that are significantly higher than the traditional fold-change approach, particularly in earlier stages of cancer, with Neighborhood Component Analysis and Minimum Redundancy Maximum Relevance achieving accuracy scores of up to 0.983 and 0.931, respectively, compared to 0.920 for the FC method. This study underscores the potential of advanced feature-selection methods in enhancing the accuracy of cancer stage identification, paving the way for improved diagnostic and therapeutic strategies in oncology.

Molecular Stratification and Treatment Monitoring of Lung Cancer Using a Small Extracellular Vesicle-Activated Nanocavity Architecture.

Development of molecular diagnostics for lung cancer stratification and monitoring is crucial for the rational planning and timely adjustment of treatments to improve clinical outcomes. In this regard, we propose a nanocavity architecture to sensitively profile the protein signature on small extracellular vesicles (sEVs) to enable accurate, noninvasive staging and treatment monitoring of lung cancer. The nanocavity architecture is formed by molecular recognition through the binding of sEVs with the nanobox-based core-shell surface-enhanced Raman scattering (SERS) barcodes and mirrorlike, asymmetric gold microelectrodes. By imposing an alternating current on the gold microelectrodes, a nanofluidic shear force was stimulated that supported the binding of sEVs and the efficient assembly of the nanoboxes. The binding of sEVs further induced a nanocavity between the nanobox and the gold microelectrode that significantly amplified the electromagnetic field to enable the simultaneous enhancement of Raman signals from four SERS barcodes and generate patient-specific molecular sEV signatures. Importantly, evaluated on a cohort of clinical samples (n = 76) on the nanocavity architecture, the acquired patient-specific sEV molecular signatures achieved accurate identification, stratification, and treatment monitoring of lung cancer patients, highlighting its potential for transition to clinical utility.