Human embryo live imaging reveals nuclear DNA shedding during blastocyst expansion and biopsy.

Proper preimplantation development is essential to assemble a blastocyst capable of implantation. Live imaging has uncovered major events driving early development in mouse embryos; yet, studies in humans have been limited by restrictions on genetic manipulation and lack of imaging approaches. We have overcome this barrier by combining fluorescent dyes with live imaging to reveal the dynamics of chromosome segregation, compaction, polarization, blastocyst formation, and hatching in the human embryo. We also show that blastocyst expansion mechanically constrains trophectoderm cells, causing nuclear budding and DNA shedding into the cytoplasm. Furthermore, cells with lower perinuclear keratin levels are more prone to undergo DNA loss. Moreover, applying trophectoderm biopsy, a mechanical procedure performed clinically for genetic testing, increases DNA shedding. Thus, our work reveals distinct processes underlying human development compared with mouse and suggests that aneuploidies in human embryos may not only originate from chromosome segregation errors during mitosis but also from nuclear DNA shedding.

Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo.

Single-cell analysis in living humans is essential for understanding disease mechanisms, but it is impractical in non-regenerative organs, such as the eye and brain, because tissue biopsies would cause serious damage. We resolve this problem by integrating proteomics of liquid biopsies with single-cell transcriptomics from all known ocular cell types to trace the cellular origin of 5,953 proteins detected in the aqueous humor. We identified hundreds of cell-specific protein markers, including for individual retinal cell types. Surprisingly, our results reveal that retinal degeneration occurs in Parkinson's disease, and the cells driving diabetic retinopathy switch with disease stage. Finally, we developed artificial intelligence (AI) models to assess individual cellular aging and found that many eye diseases not associated with chronological age undergo accelerated molecular aging of disease-specific cell types. Our approach, which can be applied to other organ systems, has the potential to transform molecular diagnostics and prognostics while uncovering new cellular disease and aging mechanisms.

Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions.

Cancer-microbe associations have been explored for centuries, but cancer-associated fungi have rarely been examined. Here, we comprehensively characterize the cancer mycobiome within 17,401 patient tissue, blood, and plasma samples across 35 cancer types in four independent cohorts. We report fungal DNA and cells at low abundances across many major human cancers, with differences in community compositions that differ among cancer types, even when accounting for technical background. Fungal histological staining of tissue microarrays supported intratumoral presence and frequent spatial association with cancer cells and macrophages. Comparing intratumoral fungal communities with matched bacteriomes and immunomes revealed co-occurring bi-domain ecologies, often with permissive, rather than competitive, microenvironments and distinct immune responses. Clinically focused assessments suggested prognostic and diagnostic capacities of the tissue and plasma mycobiomes, even in stage I cancers, and synergistic predictive performance with bacteriomes.

Noninvasive Early Identification of Therapeutic Benefit from Immune Checkpoint Inhibition.

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.

Extracellular Vesicle and Particle Biomarkers Define Multiple Human Cancers.

There is an unmet clinical need for improved tissue and liquid biopsy tools for cancer detection. We investigated the proteomic profile of extracellular vesicles and particles (EVPs) in 426 human samples from tissue explants (TEs), plasma, and other bodily fluids. Among traditional exosome markers, CD9, HSPA8, ALIX, and HSP90AB1 represent pan-EVP markers, while ACTB, MSN, and RAP1B are novel pan-EVP markers. To confirm that EVPs are ideal diagnostic tools, we analyzed proteomes of TE- (n = 151) and plasma-derived (n = 120) EVPs. Comparison of TE EVPs identified proteins (e.g., VCAN, TNC, and THBS2) that distinguish tumors from normal tissues with 90% sensitivity/94% specificity. Machine-learning classification of plasma-derived EVP cargo, including immunoglobulins, revealed 95% sensitivity/90% specificity in detecting cancer. Finally, we defined a panel of tumor-type-specific EVP proteins in TEs and plasma, which can classify tumors of unknown primary origin. Thus, EVP proteins can serve as reliable biomarkers for cancer detection and determining cancer type.

Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction.

Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to "win probability" models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient's course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demonstrate CIRI's broader utility in analogous models of chronic lymphocytic leukemia and breast adenocarcinoma and perform a proof-of-concept analysis demonstrating how CIRI could be used to develop predictive biomarkers for therapy selection. We envision that dynamic risk assessment will facilitate personalized medicine and enable innovative therapeutic paradigms.

Circulating tumor DNA in advanced solid tumors: Clinical relevance and future directions.

The application of genomic profiling assays using plasma circulating tumor DNA (ctDNA) is rapidly evolving in the management of patients with advanced solid tumors. Diverse plasma ctDNA technologies in both commercial and academic laboratories are in routine or emerging use. The increasing integration of such testing to inform treatment decision making by oncology clinicians has complexities and challenges but holds significant potential to substantially improve patient outcomes. In this review, the authors discuss the current role of plasma ctDNA assays in oncology care and provide an overview of ongoing research that may inform real-world clinical applications in the near future.

Circulating Biomarkers Instead of Genotyping to Establish Metabolizer Phenotypes.

Pharmacogenomics (PGx) enables personalized treatment for the prediction of drug response and to avoid adverse drug reactions. Currently, PGx mainly relies on the genetic information of absorption, distribution, metabolism, and excretion (ADME) targets such as drug-metabolizing enzymes or transporters to predict differences in the patient's phenotype. However, there is evidence that the phenotype-genotype concordance is limited. Thus, we discuss different phenotyping strategies using exogenous xenobiotics (e.g., drug cocktails) or endogenous compounds for phenotype prediction. In particular, minimally invasive approaches focusing on liquid biopsies offer great potential to preemptively determine metabolic and transport capacities. Early studies indicate that ADME phenotyping using exosomes released from the liver is reliable. In addition, pharmacometric modeling and artificial intelligence improve phenotype prediction. However, further prospective studies are needed to demonstrate the clinical utility of individualized treatment based on phenotyping strategies, not only relying on genetics. The present review summarizes current knowledge and limitations.

Multi-Cancer Early Detection: The New Frontier in Cancer Early Detection.

The new generation of cancer early detection tests holds remarkable promise for revolutionizing and changing the paradigm of cancer early detection. Dozens of cancer early detection tests are being developed and evaluated. Some are already commercialized and available for use, most as a complement to and not in place of existing recommended cancer screening tests. This review evaluates existing single- and multi-cancer early detection tests (MCEDs), discussing their performance characteristics including sensitivity, specificity, positive and negative predictive values, and accuracy. It also critically looks at the potential harms that could result from these tests, including false positive and negative results, the risk of overdiagnosis and overtreatment, psychological and economic harms, and the risk of widening cancer inequities. We also review the large-scale, population-based studies that are being launched in the United States and United Kingdom to determine the impact of MCEDs on clinically relevant outcomes and implications for current practice.

Current and new frontiers in hereditary cancer surveillance: Opportunities for liquid biopsy.

At least 5% of cancer diagnoses are attributed to a causal pathogenic or likely pathogenic germline genetic variant (hereditary cancer syndrome-HCS). These individuals are burdened with lifelong surveillance monitoring organs for a wide spectrum of cancers. This is associated with substantial uncertainty and anxiety in the time between screening tests and while the individuals are awaiting results. Cell-free DNA (cfDNA) sequencing has recently shown potential as a non-invasive strategy for monitoring cancer. There is an opportunity for high-yield cancer early detection in HCS. To assess clinical validity of cfDNA in individuals with HCS, representatives from eight genetics centers from across Canada founded the CHARM (cfDNA in Hereditary and High-Risk Malignancies) Consortium in 2017. In this perspective, we discuss operationalization of this consortium and early data emerging from the most common and well-characterized HCSs: hereditary breast and ovarian cancer, Lynch syndrome, Li-Fraumeni syndrome, and Neurofibromatosis type 1. We identify opportunities for the incorporation of cfDNA sequencing into surveillance protocols; these opportunities are backed by examples of earlier cancer detection efficacy in HCSs from the CHARM Consortium. We seek to establish a paradigm shift in early cancer surveillance in individuals with HCSs, away from highly centralized, regimented medical screening visits and toward more accessible, frequent, and proactive care for these high-risk individuals.

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges.

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

Epigenetic liquid biopsies: a novel putative biomarker in immunology and inflammation.

Immune and inflammatory processes occurring within tissues are often undetectable by blood cell counts, standard circulating biomarkers, or imaging, representing an unmet biomedical need. Here, we outline recent advances indicating that liquid biopsies can broadly inform human immune system dynamics. Nucleosome-size fragments of cell-free DNA (cfDNA) released from dying cells into blood contain rich epigenetic information such as methylation, fragmentation, and histone mark patterns. This information allows to infer the cfDNA cell of origin, as well as pre-cell death gene expression patterns. We propose that the analysis of epigenetic features of immune cell-derived cfDNA can shed light on immune cell turnover dynamics in healthy people, and inform the study and diagnosis of cancer, local inflammation, infectious or autoimmune diseases, as well as responses to vaccination.

Clinical Characteristics and Mechanisms of Acute Myocarditis.

REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05335928.

Fragmentation landscape of cell-free DNA revealed by deconvolutional analysis of end motifs.

Cell-free DNA (cfDNA) fragmentation is nonrandom, at least partially mediated by various DNA nucleases, forming characteristic cfDNA end motifs. However, there is a paucity of tools for deciphering the relative contributions of cfDNA cleavage patterns related to underlying fragmentation factors. In this study, through non-negative matrix factorization algorithm, we used 256 5' 4-mer end motifs to identify distinct types of cfDNA cleavage patterns, referred to as "founder" end-motif profiles (F-profiles). F-profiles were associated with different DNA nucleases based on whether such patterns were disrupted in nuclease-knockout mouse models. Contributions of individual F-profiles in a cfDNA sample could be determined by deconvolutional analysis. We analyzed 93 murine cfDNA samples of different nuclease-deficient mice and identified six types of F-profiles. F-profiles I, II, and III were linked to deoxyribonuclease 1 like 3 (DNASE1L3), deoxyribonuclease 1 (DNASE1), and DNA fragmentation factor subunit beta (DFFB), respectively. We revealed that 42.9% of plasma cfDNA molecules were attributed to DNASE1L3-mediated fragmentation, whereas 43.4% of urinary cfDNA molecules involved DNASE1-mediated fragmentation. We further demonstrated that the relative contributions of F-profiles were useful to inform pathological states, such as autoimmune disorders and cancer. Among the six F-profiles, the use of F-profile I could inform the human patients with systemic lupus erythematosus. F-profile VI could be used to detect individuals with hepatocellular carcinoma, with an area under the receiver operating characteristic curve of 0.97. F-profile VI was more prominent in patients with nasopharyngeal carcinoma undergoing chemoradiotherapy. We proposed that this profile might be related to oxidative stress.

Revisiting Extracellular RNA Release, Processing, and Function.

It is assumed that RNAs enriched in extracellular samples were selected for release by their parental cells. However, recent descriptions of extracellular RNA (exRNA) biogenesis and their differential stabilities question this assumption, as they could produce identical outcomes. Here, we share our opinion about the importance of considering both selective and nonselective mechanisms for RNA release into the extracellular environment. In doing so, we provide new perspectives on RNA-mediated intercellular communication, including an analogy to communication through social media. We also argue that technical limitations have restricted the study of some of the most abundant exRNAs, both inside and outside extracellular vesicles (EVs). These RNAs may be better positioned to induce a response in recipient cells compared with low abundance miRNAs.

Extracellular vesicles in glioblastoma: Biomarkers and therapeutic tools.

Glioblastoma (GBM) is the most aggressive tumor among the gliomas and intracranial tumors and to date prognosis for GBM patients remains poor, with a median survival typically measured in months to a few years depending on various factors. Although standardized therapies are routinely employed, it is clear that these strategies are unable to cope with heterogeneity and invasiveness of GBM. Furthermore, diagnosis and monitoring of responses to therapies are directly dependent on tissue biopsies or magnetic resonance imaging (MRI) techniques. From this point of view, liquid biopsies are arising as key sources of a variety of biomarkers with the advantage of being easily accessible and monitorable. In this context, extracellular vesicles (EVs), physiologically shed into body fluids by virtually all cells, are gaining increasing interest both as natural carriers of biomarkers and as specific signatures even for GBM. What makes these vesicles particularly attractive is they are also emerging as therapeutical vehicles to treat GBM given their native ability to cross the blood-brain barrier (BBB). Here, we reviewed recent advances on the use of EVs as biomarker for liquid biopsy and nanocarriers for targeted delivery of anticancer drugs in glioblastoma.

Celiac Disease Affects 1% of Global Population: Who Will Manage All These Patients?

Celiac disease is a common gastrointestinal condition with an estimated global prevalence of up to 1%. Adequate long-term surveillance of patients is imperative to ensure strict adherence to treatment with a gluten-free diet and the ensuing clinical and histologic recovery. Traditionally, this has been accomplished by means of regular on-site attendance at specialist health care facilities, accompanied for most patients by follow-up endoscopic and laboratory tests. However, the rapidly increasing prevalence of celiac disease and the limited health care resources challenge the current centralized and nonindividualized follow-up strategies. The improved noninvasive surveillance tools and online health care services are further changing the landscape of celiac disease management. There is a clear need for more personalized and on-demand follow-up based on early treatment response and patient-related factors associated with long-term prognosis. Additional scientific evidence on the optimal implementation of follow-up for pediatric and adulthood celiac disease is nevertheless called for.

Opportunities for Improving Biopsy and Non-Biopsy-Based Diagnosis of Celiac Disease.

The accumulating data regarding a non-biopsy diagnosis of celiac disease has led to its adoption in certain scenarios, although debate on whether and when to use non-biopsy criteria in clinical practice is ongoing. Despite the growing popularity and evidence basis for a biopsy-free approach to diagnosis in the context of highly elevated serologies, there will continue to be a role for a biopsy in some groups. This review summarizes the current evidence supporting a non-biopsy approach and arguments supporting continued reliance on biopsy, and focuses on opportunities to improve both approaches.

Accuracy of the No-Biopsy Approach for the Diagnosis of Celiac Disease in Adults: A Systematic Review and Meta-Analysis.

BACKGROUND & AIMS: Current international guidelines recommend duodenal biopsies to confirm the diagnosis of celiac disease in adult patients. However, growing evidence suggests that immunoglobulin A (IgA) anti-tissue transglutaminase (tTg) antibody levels ≥10 times the upper limit of normal (ULN) can accurately predict celiac disease, eliminating the need for biopsy. We performed a systematic review and meta-analysis to evaluate the accuracy of the no-biopsy approach to confirm the diagnosis of celiac disease in adults. METHODS: We systematically searched MEDLINE, EMBASE, Cochrane Library, and Web of Science from January 1998 to October 2023 for studies reporting the sensitivity and specificity of IgA-tTG ≥10×ULN against duodenal biopsies (Marsh grade ≥2) in adults with suspected celiac disease. We used a bivariate random effects model to calculate the summary estimates of sensitivity, specificity, and positive and negative likelihood ratios. The positive and negative likelihood ratios were used to calculate the positive predictive value of the no-biopsy approach across different pretest probabilities of celiac disease. The methodological quality of the included studies was evaluated using the QUADAS-2 tool. This study was registered with PROSPERO, number CRD42023398812. RESULTS: A total of 18 studies comprising 12,103 participants from 15 countries were included. The pooled prevalence of biopsy-proven celiac disease in the included studies was 62% (95% confidence interval [CI], 40%-83%). The proportion of patients with IgA-tTG ≥10×ULN was 32% (95% CI, 24%-40%). The summary sensitivity of IgA-tTG ≥10×ULN was 51% (95% CI, 42%-60%), and the summary specificity was 100% (95% CI, 98%-100%). The area under the summary receiver operating characteristic curve was 0.83 (95% CI, 0.77 - 0.89). The positive predictive value of the no-biopsy approach to identify patients with celiac disease was 65%, 88%, 95%, and 99% if celiac disease prevalence was 1%, 4%, 10%, and 40%, respectively. Between-study heterogeneity was moderate (I2 =30.3%), and additional sensitivity analyses did not significantly alter our findings. Only 1 study had a low risk of bias across all domains. CONCLUSION: The results of this meta-analysis suggest that selected adult patients with IgA-tTG ≥10×ULN and a moderate to high pretest probability of celiac disease could be diagnosed without undergoing invasive endoscopy and duodenal biopsy.

A Circulating Panel of circRNA Biomarkers for the Noninvasive and Early Detection of Pancreatic Ductal Adenocarcinoma.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies. Delayed manifestation of symptoms and lack of specific diagnostic markers lead patients being diagnosed with PDAC at advanced stages. This study aimed to develop a circular RNA (circRNA)-based biomarker panel to facilitate noninvasive and early detection of PDAC. METHODS: A systematic genome-wide discovery of circRNAs overexpressed in patients with PDAC was conducted. Subsequently, validation of the candidate markers in the primary tumors from patients with PDAC was performed, followed by their translation into a plasma-based liquid biopsy assay by analyzing 2 independent clinical cohorts of patients with PDAC and nondisease controls. The performance of the circRNA panel was assessed in conjunction with the plasma levels of cancer antigen 19-9 for the early detection of PDAC. RESULTS: Initially, a panel of 10 circRNA candidates was identified during the discovery phase. Subsequently, the panel was reduced to 5 circRNAs in the liquid biopsy-based assay, which robustly identified patients with PDAC and distinguished between early-stage (stage I/II) and late-stage (stage III/IV) disease. The areas under the curve of this diagnostic panel for the detection of early-stage PDAC were 0.83 and 0.81 in the training and validation cohorts, respectively. Moreover, when this panel was combined with cancer antigen 19-9 levels, the diagnostic performance for identifying patients with PDAC improved remarkably (area under the curve, 0.94) for patients in the validation cohort. Furthermore, the circRNA panel could also efficiently identify patients with PDAC (area under the curve, 0.85) who were otherwise deemed clinically cancer antigen 19-9-negative (<37 U/mL). CONCLUSIONS: A circRNA-based biomarker panel with a robust noninvasive diagnostic potential for identifying patients with early-stage PDAC was developed.