Detection and localization of surgically resectable cancers with a multi-analyte blood test

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Functionalizing tetrahedral framework nucleic acids-based nanostructures for tumor in situ imaging and treatment

Timely in situ imaging and effective treatment are efficient strategies in improving the therapeutic effect and survival rate of tumor patients. In recent years, there has been rapid progress in the development of DNA nanomaterials for tumor in situ imaging and treatment, due to their unsurpassed structural stability, excellent material editability, excellent biocompatibility and individual endocytic pathway. Tetrahedral framework nucleic acids (tFNAs), are a typical example of DNA nanostructures demonstrating superior stability, biocompatibility, cell-entry performance, and flexible drug-loading ability. tFNAs have been shown to be effective in achieving timely tumor in situ imaging and precise treatment. Therefore, the progress in the fabrication, characterization, modification and cellular internalization pathway of tFNAs-based functional systems and their potential in tumor in situ imaging and treatment applications were systematically reviewed in this article. In addition, challenges and future prospects of tFNAs in tumor in situ imaging and treatment as well as potential clinical applications were discussed.

The molecular characteristics of recurrent/metastatic HPV-positive head and neck squamous cell carcinoma: A systematic review of the literature

OBJECTIVES

About 17% of patients with human papillomavirus (HPV)-positive head and neck squamous cell carcinoma (HNSCC), which is mainly comprised of oropharyngeal SCC (OPSCC), will experience disease recurrence, which is often considered incurable when manifested at a metastatic and/or recurrent stage. We conducted a critical qualitative systematic review. Our objectives were to provide an overview of the molecular landscape of recurrent/metastatic HPV-positive HNSCC as well as novel molecular biomarkers.

DESIGN

A literature review was conducted to identify studies reporting on the molecular characteristics of recurrent/metastatic HPV-positive HNSCC, novel molecular biomarkers and treatment options. The reviews of abstracts, full articles, and revision of the included studies, followed by data extraction and quality assessment were performed by three independent assessors. All primary literature, such as retrospective, prospective, and clinical trials as well as basic research studies were considered, and the final search was conducted at the end of February 2023. The level of evidence was rated using the guidelines published by the Oxford Centre for Evidence-based Medicine and quality was assessed using the Newcastle-Ottawa Scale criteria.

RESULTS AND CONCLUSIONS

The literature search resulted in the identification of 1991 articles. A total of 181 full articles were screened, and 66 articles were included in this analysis. Several studies reported that recurrent/metastatic HPV-positive HNSCC had higher rates of TP53 mutation and were genomically similar to HPV-negative HNSCC. The detection of circulating tumour tissue-modified HPV DNA (ctHPVDNA) as a specific biomarker has shown promising results for monitoring treatment response and recurrence in the subset of HPV-positive HNSCC. In addition, evidence for targeted therapy in recurrent/metastatic HPV-positive HNSCC has emerged, including agents that inhibit overexpressed EGFR. Studies of combination immunotherapy are also underway. Our review outlines the latest evidence on the distinct molecular profiles of recurrent/metastatic HPV-positive HNSCC as well as the clinical potential of ctHPVDNA testing in routine practice. More controlled and longitudinal studies are needed to identify additional molecular targets and to assess the performance and benefits of novel molecular biomarkers in clinical practice.

Circulating miRNA and circulating tumor DNA application as liquid biopsy markers in gastric cancer

Liquid biopsy has been investigated as a novel method to overcome the numerous challenges in gastric cancer (GC) management. This non-invasive, feasible, and easy-to-repeat method has been shown to be cost-effective and capable of increasing diagnostic sensitivity and prognostic assessment. Additionally, it is potentially accurate to aid decision-making and personalized treatment planning. MicroRNA (miRNA) and circulating tumor DNA (ctDNA) markers can enhance GC management in various aspects, including diagnosis (mainly earlier diagnosis and the ability to perform population-based screening), prognosis (more precise stratification of prognosis), and treatment (including more accurate prediction of treatment response and earlier detection of resistance to the treatment). Concerning the treatment-related application, miRNAs' mimics and antagonists (by using two main strategies of restoring tumor suppressor miRNAs and inhibiting oncogene miRNAs) have been shown to be effective therapeutic agents. However, these need to be further validated in clinical trials. Furthermore, novel delivery systems, such as lipid-based vectors, polymeric-based vectors, and exosome-based delivery, have been developed to enhance the performance of these agents. Moreover, this paper explores the current detection and measuring methods for these markers. These approaches are categorized into direct methods (e.g., Chem-NAT, HTG EdgeSeq, and Multiplex Circulating Fireplex) and indirect methods (e.g., Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), qPCR, microarray, and NGS) for miRNA detection. For ctDNA measurement, main core technologies like NGS, digital PCR, real-time PCR, and mass spectrometry are suggested.

Prostate cancer-derived extracellular vesicles metabolic biomarkers: Emerging roles for diagnosis and prognosis

Prostate cancer (PCa) is a global health concern, ranking as the most common cancer among men in Western countries. Traditional diagnostic methods are invasive with adverse effects on patients. Due to the heterogeneous nature of PCa and their multifocality, tissue biopsies often yield false-negative results. To address these challenges, researchers are exploring innovative approaches, particularly in the realms of proteomics and metabolomics, to identify more reliable biomarkers and improve PCa diagnosis. Liquid biopsy (LB) has emerged as a promising non-invasive strategy for PCa early detection, biopsy selection, active surveillance for low-risk cases, and post-treatment and progression monitoring. Extracellular vesicles (EVs) are lipid-bilayer nanovesicles released by all cell types and play an important role in intercellular communication. EVs have garnered attention as a valuable biomarker resource in LB for PCa-specific biomarkers, enhancing diagnosis, prognostication, and treatment guidance. Metabolomics provides insight into the body's metabolic response to both internal and external stimuli, offering quantitative measurements of biochemical alterations. It excels at detecting non-genetic influences, aiding in the discovery of more accurate cancer biomarkers for early detection and disease progression monitoring. This review delves into the potential of EVs as a resource for LB in PCa across various clinical applications. It also explores cancer-related metabolic biomarkers, both within and outside EVs in PCa, and summarises previous metabolomic findings in PCa diagnosis and risk assessment. Finally, the article addresses the challenges and future directions in the evolving field of EV-based metabolomic analysis, offering a comprehensive overview of its potential in advancing PCa management.

Colorectal cancer

Despite decreased incidence rates in average-age onset patients in high-income economies, colorectal cancer is the third most diagnosed cancer in the world, with increasing rates in emerging economies. Furthermore, early onset colorectal cancer (age ≤50 years) is of increasing concern globally. Over the past decade, research advances have increased biological knowledge, treatment options, and overall survival rates. The increase in life expectancy is attributed to an increase in effective systemic therapy, improved treatment selection, and expanded locoregional surgical options. Ongoing developments are focused on the role of sphincter preservation, precision oncology for molecular alterations, use of circulating tumour DNA, analysis of the gut microbiome, as well as the role of locoregional strategies for colorectal cancer liver metastases. This overview is to provide a general multidisciplinary perspective of clinical advances in colorectal cancer.

Use of ctDNA in early breast cancer: analytical validity and clinical potential

Circulating free tumor DNA (ctDNA) analysis is gaining popularity in precision oncology, particularly in metastatic breast cancer, as it provides non-invasive, real-time tumor information to complement tissue biopsies, allowing for tailored treatment strategies and improved patient selection in clinical trials. Its use in early breast cancer has been limited so far, due to the relatively low sensitivity of available techniques in a setting characterized by lower levels of ctDNA shedding. However, advances in sequencing and bioinformatics, as well as the use of methylome profiles, have led to an increasing interest in the application of ctDNA analysis in early breast cancer, from screening to curative treatment evaluation and minimal residual disease (MRD) detection. With multiple prospective clinical trials in this setting, ctDNA evaluation may become useful in clinical practice. This article reviews the data regarding the analytical validity of the currently available tests for ctDNA detection and the clinical potential of ctDNA analysis in early breast cancer.

Glycan Profiling in Small Extracellular Vesicles with a SERS Microfluidic Biosensor Identifies Early Malignant Development in Lung Cancer

Glycosylation is the most common post-translational modification of proteins and regulates a myriad of fundamental biological processes under normal, and pathological conditions. Altered protein glycosylation is linked to malignant transformation, showing distinct glycopatterns that are associated with cancer initiation and progression by regulating tumor proliferation, invasion, metastasis, and therapeutic resistance. The glycopatterns of small extracellular vesicles (sEVs) released by cancer cells are promising candidates for cancer monitoring since they exhibit glycopatterns similar to their cell-of-origin. However, the clinical application of sEV glycans is challenging due to the limitations of current analytical technologies in tracking the trace amounts of sEVs specifically derived from tumors in circulation. Herein, a sEV GLYcan PHenotype (EV-GLYPH) assay that utilizes a microfluidic platform integrated with surface-enhanced Raman scattering for multiplex profiling of sEV glycans in non-small cell lung cancer is clinically validated. For the first time, the EV-GLYPH assay effectively identifies distinct sEV glycan signatures between non-transformed and malignantly transformed lung cells. In a clinical study evaluated on 40 patients, the EV-GLYPH assay successfully differentiates patients with early-stage malignant lung nodules from benign lung nodules. These results reveal the potential to profile sEV glycans for noninvasive diagnostics and prognostics, opening up promising avenues for clinical applications and understanding the role of sEV glycosylation in lung cancer.

Improving platelet-RNA-based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification

Liquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community on which methods are the most effective or how to process the data. To circumvent this, we performed a large-scale study using various machine-learning techniques. First, we took a closer look at existing datasets and filtered out some patients to assert data collection quality. The final data collection included platelet RNA samples acquired from 1397 cancer patients (17 types of cancer) and 354 asymptomatic, presumed healthy, donors. Then, we assessed an array of different machine-learning models and techniques (e.g., feature selection of RNA transcripts) in pan-cancer detection and multiclass classification. Our results show that simple logistic regression performs the best, reaching a 68% cancer detection rate at a 99% specificity level, and multiclass classification accuracy of 79.38% when distinguishing between five cancer types. In summary, by revisiting classical machine-learning models, we have exceeded the previously used method by 5% and 9.65% in cancer detection and multiclass classification, respectively. To ease further research, we open-source our code and data processing pipelines (https://gitlab.com/jopekmaksym/improving-platelet-rna-based-diagnostics), which we hope will serve the community as a strong baseline.

Alteration in DNA methylation patterns: Epigenetic signatures in gastrointestinal cancers

Abnormalities in epigenetic modifications can cause malignant transformations in cells, leading to cancers of the gastrointestinal (GI) tract, which accounts for 20% of all cancers worldwide. Among the epigenetic alterations, DNA hypomethylation is associated with genomic instability. In addition, CpG methylation and promoter hypermethylation have been recognized as biomarkers for different malignancies. In GI cancers, epigenetic alterations affect genes responsible for cell cycle control, DNA repair, apoptosis, and tumorigenic-specific signaling pathways. Understanding the pattern of alterations in DNA methylation in GI cancers could help scientists discover new molecular-based pharmaceutical treatments. This study highlights alterations in DNA methylation in GI cancers. Understanding epigenetic differences among GI cancers may improve targeted therapies and lead to the discovery of new diagnostic biomarkers.

Circulating Tumor DNA-Guided De-Escalation Targeted Therapy for Advanced Non-Small Cell Lung Cancer: A Nonrandomized Clinical Trial

Importance

Uninterrupted targeted therapy until disease progression or intolerable toxic effects is currently the routine therapy for advanced non-small cell lung cancer (NSCLC) involving driver gene variations. However, drug resistance is inevitable.

Objective

To assess the clinical feasibility of adaptive de-escalation tyrosine kinase inhibitor (TKI) treatment guided by circulating tumor DNA (ctDNA) for achieving complete remission after local consolidative therapy (LCT) in patients with advanced NSCLC.

Design, Setting, and Participants

This prospective nonrandomized trial was conducted at a single center from June 3, 2020, to July 19, 2022, and included 60 patients with advanced NSCLC with driver variations without radiologically detectable disease after TKI and LCT. The median (range) follow-up time was 19.2 (3.8-29.7) months. Data analysis was conducted from December 15, 2022, to May 10, 2023.

Intervention

Cessation of TKI treatment and follow-up every 3 months. Treatment was restarted in patients with progressive disease (defined by the Response Evaluation Criteria in Solid Tumors 1.1 criteria), detectable ctDNA, or elevated carcinoembryonic antigen (CEA) levels, whichever manifested first, and treatment ceased if all indicators were negative during follow-up surveillance.

Main Outcomes and Measures

Progression-free survival (PFS). Secondary end points were objective response rate, time to next treatment, and overall survival.

Results

Among the total study sample of 60 participants (median [range] age, 55 [21-75] years; 33 [55%] were female), the median PFS was 18.4 (95% CI, 12.6-24.2) months and the median (range) total treatment break duration was 9.1 (1.5-28.1) months. Fourteen patients (group A) remained in TKI cessation with a median (range) treatment break duration of 20.3 (6.8-28.1) months; 31 patients (group B) received retreatment owing to detectable ctDNA and/or CEA and had a median PFS of 20.2 (95% CI, 12.9-27.4) months with a median (range) total treatment break duration of 8.8 (1.5-20.6) months; and 15 patients (group C) who underwent retreatment with TKIs due to progressive disease had a median PFS of 5.5 (95% CI, 1.5-7.2) months. For all participants, the TKI retreatment response rate was 96%, the median time to next treatment was 29.3 (95% CI, 25.3-35.2) months, and the data for overall survival were immature.

Conclusions and Relevance

The findings of this nonrandomized trial suggest that this adaptive de-escalation TKI strategy for patients with NSCLC is feasible in those with no lesions after LCT and a negative ctDNA test result. This might provide a de-escalation treatment strategy guided by ctDNA for the subset of patients with advanced NSCLC.

Trial Registration

ClinicalTrials.gov Identifier: NCT03046316.

The use of platelets as a clinical tool in oncology: opportunities and challenges

Platelets are small circulating anucleated cells mainly involved in thrombosis and hemostasis processes. Moreover, platelets play an active role in tumorigenesis and cancer progression, stimulating angiogenesis and vascular remodelling, and protecting circulating cancer cells from shear forces and immune surveillance. Several reports indicate that platelet number in the blood circulation of cancer patients is associated with prognosis and response to treatment. However, the mechanisms of platelets "education" by cancer cells and the crosstalk between platelets and tumor are still unclear, and the role of "tumor educated platelets" (TEPs) is achieving growing interest in cancer research. TEPs are a biological source of cancer-derived biomarkers, especially RNAs that are protected by platelets membrane from circulating RNases, and could serve as a non-invasive tool for tumor detection, molecular profiling and evolution during therapy in clinical practice. Moreover, short platelet lifespan offers the possibility to get a snapshot assessment of cancer molecular profile, providing a real-time tool. We review and discuss the potential and the clinical utility, in terms of cancer diagnosis and monitoring, of platelet count together with other morphological parameters and of the more recent and innovative TEP profiling.

Frameshift mutations in peripheral blood as a biomarker for surveillance of Lynch syndrome

BACKGROUND

Lynch syndrome is a hereditary cancer predisposition syndrome caused by germline mutations in DNA mismatch repair genes, which lead to high microsatellite instability and frameshift mutations at coding mononucleotide repeats in the genome. Recurrent frameshift mutations in these regions are thought to play a central role in the increased risk of various cancers, but no biomarkers are currently available for the surveillance of high microsatellite instability-associated cancers.

METHODS

A frameshift mutation-based biomarker panel was developed and validated by targeted next-generation sequencing of supernatant DNA from cultured high microsatellite instability colorectal cancer cells. This panel supported selection of 122 frameshift mutation targets as potential biomarkers. This biomarker panel was then tested using matched tumor, adjacent normal tissue, and buffy coat samples (53 samples) and blood-derived cell-free DNA (cfDNA) (38 samples) obtained from 45 high microsatellite instability and mismatch repair-deficient patients. We also sequenced cfDNA from 84 healthy participants to assess background noise.

RESULTS

Recurrent frameshift mutations at coding mononucleotide repeats were detectable not only in tumors but also in cfDNA from high microsatellite instability and mismatch repair-deficient patients, including a Lynch syndrome carrier, with a varying range of target detection (up to 85.2%), whereas they were virtually undetectable in healthy participants. Receiver operating characteristic curve analysis showed high sensitivity and specificity (area under the curve = 0.94) of the investigated panel.

CONCLUSIONS

We demonstrated that frameshift mutations can be detected in cfDNA from high microsatellite instability and mismatch repair-deficient patients and asymptomatic carriers. The 122-target frameshift mutation panel described here has promise as a tool for improved surveillance of high microsatellite instability and mismatch repair-deficient patients, with the potential to reduce the frequency of invasive screening methods for this high-cancer-risk cohort.

Prediagnostic evaluation of multicancer detection tests: design and analysis considerations

There is growing interest in multicancer detection tests, which identify molecular signals in the blood that indicate a potential preclinical cancer. A key stage in evaluating these tests is a prediagnostic performance study, in which investigators store specimens from asymptomatic individuals and later test stored specimens from patients with cancer and a random sample of controls to determine predictive performance. Performance metrics include rates of cancer-specific true-positive and false-positive findings and a cancer-specific positive predictive value, with the latter compared with a decision-analytic threshold. The sample size trade-off method, which trades imprecise targeting of the true-positive rate for precise targeting of a zero-false-positive rate can substantially reduce sample size while increasing the lower bound of the positive predictive value. For a 1-year follow-up, with ovarian cancer as the rarest cancer considered, the sample size trade-off method yields a sample size of 163 000 compared with a sample size of 720 000, based on standard calculations. These design and analysis recommendations should be considered in planning a specimen repository and in the prediagnostic evaluation of multicancer detection tests.

Colorimetric sensing for translational applications: from colorants to mechanisms

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.

Social Media Promotion of Health Tests With Potential for Overdiagnosis or Overuse: Protocol for a Content Analysis

BACKGROUND

In recent years, social media have emerged as important spaces for commercial marketing of health tests, which can be used for the screening and diagnosis of otherwise generally healthy people. However, little is known about how health tests are promoted on social media, whether the information provided is accurate and balanced, and if there is transparency around conflicts of interest.

OBJECTIVE

This study aims to understand and quantify how social media is being used to discuss or promote health tests with the potential for overdiagnosis or overuse to generally healthy people.

METHODS

Content analysis of social media posts on the anti-Mullerian hormone test, whole-body magnetic resonance imaging scan, multicancer early detection, testosterone test, and gut microbe test from influential international social media accounts on Instagram and TikTok. The 5 tests have been identified as having the following criteria: (1) there are evidence-based concerns about overdiagnosis or overuse, (2) there is evidence or concerns that the results of tests do not lead to improved health outcomes for generally healthy people and may cause harm or waste, and (3) the tests are being promoted on social media to generally healthy people. English language text-only posts, images, infographics, articles, recorded videos including reels, and audio-only posts are included. Posts from accounts with <1000 followers as well as stories, live videos, and non-English posts are excluded. Using keywords related to the test, the top posts were searched and screened until there were 100 eligible posts from each platform for each test (total of 1000 posts). Data from the caption, video, and on-screen text are being summarized and extracted into a Microsoft Excel (Microsoft Corporation) spreadsheet and included in the analysis. The analysis will take a combined inductive approach when generating key themes and a deductive approach using a prespecified framework. Quantitative data will be analyzed in Stata SE (version 18.0; Stata Corp).

RESULTS

Data on Instagram and TikTok have been searched and screened. Analysis has now commenced. The findings will be disseminated via publications in peer-reviewed international medical journals and will also be presented at national and international conferences in late 2024 and 2025.

CONCLUSIONS

This study will contribute to the limited evidence base on the nature of the relationship between social media and the problems of overdiagnosis and overuse of health care services. This understanding is essential to develop strategies to mitigate potential harm and plan solutions, with the aim of helping to protect members of the public from being marketed low-value tests, becoming patients unnecessarily, and taking resources away from genuine needs within the health system.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/56899.

The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood

T cells recognize tumor antigens and initiate an anticancer immune response in the very early stages of tumor development, and the antigen specificity of T cells is determined by the T-cell receptor (TCR). Therefore, monitoring changes in the TCR repertoire in peripheral blood may offer a strategy to detect various cancers at a relatively early stage. Here, we developed the deep learning framework iCanTCR to identify patients with cancer based on the TCR repertoire. The iCanTCR framework uses TCRβ sequences from an individual as an input and outputs the predicted cancer probability. The model was trained on over 2,000 publicly available TCR repertoires from 11 types of cancer and healthy controls. Analysis of several additional publicly available datasets validated the ability of iCanTCR to distinguish patients with cancer from noncancer individuals and demonstrated the capability of iCanTCR for the accurate classification of multiple cancers. Importantly, iCanTCR precisely identified individuals with early-stage cancer with an AUC of 86%. Altogether, this work provides a liquid biopsy approach to capture immune signals from peripheral blood for noninvasive cancer diagnosis.

SIGNIFICANCE

Development of a deep learning-based method for multicancer detection using the TCR repertoire in the peripheral blood establishes the potential of evaluating circulating immune signals for noninvasive early cancer detection.

Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling

BACKGROUND

Downstaging-reduction in late-stage incidence-has been proposed as an endpoint in randomized trials of multi-cancer early detection (MCED) tests. How downstaging depends on test performance and follow-up has been studied for some cancers but is understudied for cancers without existing screening and for MCED tests that include these cancer types.

METHODS

We develop a model for cancer natural history that can be fit to registry incidence patterns under minimal inputs and can be estimated for solid cancers without existing screening. Fitted models are combined to project downstaging in MCED trials given sensitivity for early- and late-stage cancers. We fit models for 12 cancers using incidence data from the Surveillance, Epidemiology, and End Results program and project downstaging in a simulated trial under variable preclinical latencies and test sensitivities.

RESULTS

A proof-of-principle lung cancer model approximated downstaging in the National Lung Screening Trial. Given published stage-specific sensitivities for 12 cancers, we projected downstaging ranging from 21% to 43% across plausible preclinical latencies in a hypothetical 3-screen MCED trial. Late-stage incidence reductions manifest soon after screening begins. Downstaging increases with longer early-stage latency or higher early-stage test sensitivity.

CONCLUSIONS

Even short-term MCED trials could produce substantial downstaging given adequate early-stage test sensitivity.

IMPACT

Modeling the natural histories of cancers without existing screening facilitates analysis of novel MCED products and trial designs. The framework informs expectations of MCED impact on disease stage at diagnosis and could serve as a building block for designing trials with late-stage incidence as the primary endpoint.

Genomic alterations and transcriptional phenotypes in circulating tumor DNA and matched metastatic tumor

Background

Profiling circulating cell-free DNA (cfDNA) has become a fundamental practice in cancer medicine, but the effectiveness of cfDNA at elucidating tumor-derived molecular features has not been systematically compared to standard single-lesion tumor biopsies in prospective cohorts of patients. The use of plasma instead of tissue to guide therapy is particularly attractive for patients with small cell lung cancer (SCLC), a cancer whose aggressive clinical course making it exceedingly challenging to obtain tumor biopsies.

Methods

Here, a prospective cohort of 49 plasma samples obtained before, during, and after treatment from 20 patients with recurrent SCLC, we study cfDNA low pass whole genome (0.1X coverage) and exome (130X) sequencing in comparison with time-point matched tumor, characterized using exome and transcriptome sequencing.

Results

Direct comparison of cfDNA versus tumor biopsy reveals that cfDNA not only mirrors the mutation and copy number landscape of the corresponding tumor but also identifies clinically relevant resistance mechanisms and cancer driver alterations not found in matched tumor biopsies. Longitudinal cfDNA analysis reliably tracks tumor response, progression, and clonal evolution. Genomic sequencing coverage of plasma DNA fragments around transcription start sites shows distinct treatment-related changes and captures the expression of key transcription factors such as NEUROD1 and REST in the corresponding SCLC tumors, allowing prediction of SCLC neuroendocrine phenotypes and treatment responses.

Conclusions

These findings have important implications for non-invasive stratification and subtype-specific therapies for patients with SCLC, now treated as a single disease.

Unlocking the future of cancer diagnosis - promises and challenges of ctDNA-based liquid biopsies in non-small cell lung cancer

The advent of liquid biopsies has brought significant changes to the diagnosis and monitoring of non-small cell lung cancer (NSCLC), presenting both promise and challenges. Molecularly targeted drugs, capable of enhancing survival rates, are now available to around a quarter of NSCLC patients. However, to ensure their effectiveness, precision diagnosis is essential. Circulating tumor DNA (ctDNA) analysis as the most advanced liquid biopsy modality to date offers a non-invasive method for tracking genomic changes in NSCLC. The potential of ctDNA is particularly rooted in its ability to furnish comprehensive (epi-)genetic insights into the tumor, thereby aiding personalized treatment strategies. One of the key advantages of ctDNA-based liquid biopsies in NSCLC is their ability to capture tumor heterogeneity. This capability ensures a more precise depiction of the tumor's (epi-)genomic landscape compared to conventional tissue biopsies. Consequently, it facilitates the identification of (epi-)genetic alterations, enabling informed treatment decisions, disease progression monitoring, and early detection of resistance-causing mutations for timely therapeutic interventions. Here we review the current state-of-the-art in ctDNA-based liquid biopsy technologies for NSCLC, exploring their potential to revolutionize clinical practice. Key advancements in ctDNA detection methods, including PCR-based assays, next-generation sequencing (NGS), and digital PCR (dPCR), are discussed, along with their respective strengths and limitations. Additionally, the clinical utility of ctDNA analysis in guiding treatment decisions, monitoring treatment response, detecting minimal residual disease, and identifying emerging resistance mechanisms is examined. Liquid biopsy analysis bears the potential of transforming NSCLC management by enabling non-invasive monitoring of Minimal Residual Disease and providing early indicators for response to targeted treatments including immunotherapy. Furthermore, considerations regarding sample collection, processing, and data interpretation are highlighted as crucial factors influencing the reliability and reproducibility of ctDNA-based assays. Addressing these challenges will be essential for the widespread adoption of ctDNA-based liquid biopsies in routine clinical practice, ultimately paving the way toward personalized medicine and improved outcomes for patients with NSCLC.

Liquid biopsy: An arsenal for tumour screening and early diagnosis

Cancer has become the second leading cause of death in the world, and more than 50% of cancer patients are diagnosed at an advanced stage. Early diagnosis of tumours is the key to improving patient quality of life and survival time and reducing the socioeconomic burden. However, there is still a lack of reliable early diagnosis methods in clinical practice. In recent years, liquid biopsy technology has developed rapidly. It has the advantages of noninvasiveness, easy access to sample sources, and reproducibility. It has become the main focus of research on the early diagnosis methods of tumours. This review summarises the research progress of existing liquid biopsy markers, such as circulating tumour DNA, circulating viral DNA, DNA methylation, circulating tumour cells, circulating RNA, exosomes, and tumour education platelets in early diagnosis of tumours, and analyses the current advantages and limitations of various markers, providing a direction for the application and transformation of liquid biopsy research in early diagnosis of clinical tumours.

Effective enrichment of trace exosomes for the label-free SERS detection via low-cost thermophoretic profiling

Exosome-based liquid biopsies possess great potential in monitoring cancer development However, current exosome detection biosensors require large exosome volumes, showing the weak detection sensitivity. Besides, these methods pay little attention to in situ analysis of exosomes, hence limiting the provision of more accurate clinically-relevant information. Herein, we develop an innovative label-free biosensor combining the low-cost thermophoretic enrichment method with the surface-enhanced Raman spectroscopy (SERS) detection. Based on the thermophoretic enrichment strategy, exosomes and gold nanoparticles can be enriched together into a small area with a scale of 500 μm within 10 min. The Raman signals of various exosomes derived from normal, cancerous cell lines and human serum are dynamically monitored in situ, with the limit of detection of 102-103 particles per microliter, presenting higher sensitivity compared with the similar label-free SERS detection. The spectral data set of different exosomes is applied to train for multivariate classification of cell types and to estimate how the normal exosome data resemble cancer cell exosome. The reliable classification and identification of different exosomes can be realized. The current biosensor is convenient, low-cost and requires small exosome volumes (∼3 μL), and if validated in larger cohorts may contribute to the tumor prediction and diagnosis.

Immune-related gene methylation prognostic instrument for stratification and targeted treatment of ovarian cancer patients toward advanced 3PM approach

Background

DNA methylation is an important mechanism in epigenetics, which can change the transcription ability of genes and is closely related to the pathogenesis of ovarian cancer (OC). We hypothesize that DNA methylation is significantly different in OCs compared to controls. Specific DNA methylation status can be used as a biomarker of OC, and targeted drugs targeting these methylation patterns and DNA methyltransferase may have better therapeutic effects. Studying the key DNA methylation sites of immune-related genes (IRGs) in OC patients and studying the effects of these methylation sites on the immune microenvironment may provide a new method for further exploring the pathogenesis of OC, realizing early detection and effective monitoring of OC, identifying effective biomarkers of DNA methylation subtypes and drug targets, improving the efficacy of targeted drugs or overcoming drug resistance, and better applying it to predictive diagnosis, prevention, and personalized medicine (PPPM; 3PM) of OC.

Method

Hypermethylated subtypes (cluster 1) and hypomethylated subtypes (cluster 2) were established in OCs based on the abundance of different methylation sites in IRGs. The differences in immune score, immune checkpoints, immune cells, and overall survival were analyzed between different methylation subtypes in OC samples. The significant pathways, gene ontology (GO), and protein-protein interaction (PPI) network of the identified methylation sites in IRGs were enriched. In addition, the immune-related methylation signature was constructed with multiple regression analysis. A methylation site model based on IRGs was constructed and verified.

Results

A total of 120 IRGs with 142 differentially methylated sites (DMSs) were identified. The DMSs were clustered into a high-level methylation group (cluster 1) and a low-level methylation group (cluster 2). The significant pathways and GO analysis showed many immune-related and cancer-associated enrichments. A methylation site signature based on IRGs was constructed, including RORC|cg25112191, S100A13|cg14467840, TNF|cg04425624, RLN2|cg03679581, and IL1RL2|cg22797169. The methylation sites of all five genes showed hypomethylation in OC, and there were statistically significant differences among RORC|cg25112191, S100A13|cg14467840, and TNF|cg04425624 (p < 0.05). This prognostic model based on low-level methylation and high-level methylation groups was significantly linked to the immune microenvironment as well as overall survival in OC.

Conclusions

This study provided different methylation subtypes for OC patients according to the methylation sites of IRGs. In addition, it helps establish a relationship between methylation and the immune microenvironment, which showed specific differences in biological signaling pathways, genomic changes, and immune mechanisms within the two subgroups. These data provide ones to deeply understand the mechanism of immune-related methylation genes on the occurrence and development of OC. The methylation-site signature is also to establish new possibilities for OC therapy. These data are a precious resource for stratification and targeted treatment of OC patients toward an advanced 3PM approach.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00359-3.

Multi-cancer risk stratification based on national health data: a retrospective modelling and validation study

BACKGROUND

Health care is experiencing a drive towards digitisation, and many countries are implementing national health data resources. Although a range of cancer risk models exists, the utility on a population level for risk stratification across cancer types has not been fully explored. We aimed to close this gap by evaluating pan-cancer risk models built on electronic health records across the Danish population with validation in the UK Biobank.

METHODS

In this retrospective modelling and validation study, data for model development and internal validation were derived from the following Danish health registries: the Central Person Registry, the Danish National Patient Registry, the death registry, the cancer registry, and full-text medical records from secondary care records in the capital region. The development data included adults aged 16-86 years without previous malignant cancers in the time period from Jan 1, 1995, to Dec 31, 2014. The internal validation period was from Jan 1, 2015, to April 10, 2018, and the data included all adults without a previous indication of cancer aged 16-75 years on Dec 31, 2014. The external validation cohort from the UK Biobank included all adults without a previous indication of cancer aged 50-75 years. We used time-dependent Bayesian Cox hazard models built on the combined medical history of Danish individuals. A set of 1392 covariates from available clinical disease trajectories, text-mined basic health factors, and family histories were used to train predictive models of 20 major cancer types. The models were validated on cancer incidence between 2015 and 2018 across Denmark and on individuals in the UK Biobank. The primary outcomes were discrimination and calibration performance.

FINDINGS

From the Danish registries, we included 6 732 553 individuals covering 60 million hospital visits, 90 million diagnoses, and a total of 193 million life-years between Jan 1, 1978, and April 10, 2018. Danish registry data covering the period from Jan 1, 2015, to April 10, 2018, were used to internally validate risk models, containing a total of 4 248 491 individuals who remained at risk of a primary malignant cancer diagnosis and 67 401 cancer cases recorded. For the external validation, we evaluated the same time period in the UK Biobank covering 377 004 individuals with 11 486 cancer cases. The predictive performance of the models on Danish data showed good discrimination (concordance index 0·81 [SD 0·08], ranging from 0·66 [95% CI 0·65-0·67] for cervix uteri cancer to 0·91 [0·90-0·92] for liver cancer). Performance was similar on the UK Biobank in a direct transfer when controlling for shifts in the age distribution (concordance index 0·66 [SD 0·08], ranging from 0·55 [95% CI 0·44-0·66] for cervix uteri cancer to 0·78 [0·77-0·79] for lung cancer). Cancer risks were associated, in addition to heritable components, with a broad range of preceding diagnoses and health factors. The best overall performance was seen for cancers of the digestive system (oesophageal, stomach, colorectal, liver, and pancreatic) but also thyroid, kidney, and uterine cancers.

INTERPRETATION

Data available in national electronic health databases can be used to approximate cancer risk factors and enable risk predictions in most cancer types. Model predictions generalise between the Danish and UK health-care systems. With the emergence of multi-cancer early detection tests, electronic health record-based risk models could supplement screening efforts.

FUNDING

Novo Nordisk Foundation and the Danish Innovation Foundation.

Perspectives on Clinical Adoption Barriers to Blood-Based Multi-Cancer Early Detection Tests across Stakeholders

Current United States Preventive Services Task Force (USPSTF) recommendations include routine screening for breast, cervical, colorectal, and lung cancer; however, two out of every three cancer cases occur in other indications, leading to diagnoses in advanced stages of the disease and a higher likelihood of mortality. Blood-based multi-cancer early detection (MCED) tests can impact cancer screening and early detection by monitoring for multiple different cancer types at once, including indications where screening is not performed routinely today. We conducted a survey amongst healthcare providers (HCPs), payers, and patients within the U.S. health system to understand the current utilization of cancer screening tests and the anticipated barriers to widespread adoption of blood-based MCED tests. The results indicated that the community favors the adoption of blood-based MCED tests and that there is broad agreement on the value proposition. Despite this recognition, the survey highlighted that there is limited use today due to the perceived lack of clinical accuracy and utility data, high out-of-pocket patient costs, and lack of payer coverage. To overcome the hurdles for future widespread adoption of blood-based MCED tests, increased investment in data generation, education, and implementation of logistical support for HCPs will be critical.

Circulating tumor DNA (ctDNA): can it be used as a pan-cancer early detection test?

Circulating tumor DNA (ctDNA, DNA shed by cancer cells) is emerging as one of the most transformative cancer biomarkers discovered to-date. Although potentially useful at all the phases of cancer detection and patient management, one of its most exciting possibilities is as a relatively noninvasive pan-cancer screening test. Preliminary findings with ctDNA tests such as Galleri or CancerSEEK suggest that they have high specificity (> 99.0%) for malignancy. Their sensitivity varies depending on the type of cancer and stage of disease but it is generally low in patients with stage I disease. A major advantage of ctDNA over existing screening strategies is the potential ability to detect multiple cancer types in a single test. A limitation of most studies published to-date is that they are predominantly case-control investigations that were carried out in patients with a previous diagnosis of malignancy and that used apparently healthy subjects as controls. Consequently, the reported sensitivities, specificities and positive predictive values might be lower if the tests are used for screening in asymptomatic populations, that is, in the population where these tests are likely be employed. To demonstrate clinical utility in an asymptomatic population, these tests must be shown to reduce cancer mortality without causing excessive overdiagnosis in a large randomized prospective randomized trial. Such trials are currently ongoing for Galleri and CancerSEEK.

Association of the immediate perioperative dynamics of circulating DNA levels and neutrophil extracellular traps formation in cancer patients

Objectives

Elevated circulating DNA (cirDNA) concentrations were found to be associated with trauma or tissue damage which suggests involvement of inflammation or cell death in post-operative cirDNA release. We carried out the first prospective, multicenter study of the dynamics of cirDNA and neutrophil extracellular trap (NETs) markers during the perioperative period from 24 h before surgery up to 72 h after curative surgery in cancer patients.

Methods

We examined the plasma levels of two NETs protein markers [myeloperoxidase (MPO) and neutrophil elastase (NE)], as well as levels of cirDNA of nuclear (cir-nDNA) and mitochondrial (cir-mtDNA) origin in 29 colon, prostate, and breast cancer patients and in 114 healthy individuals (HI).

Results

The synergistic analytical information provided by these markers revealed that: (i) NETs formation contributes to post-surgery conditions; (ii) post-surgery cir-nDNA levels were highly associated with NE and MPO in colon cancer [r = 0.60 (P < 0.001) and r = 0.53 (P < 0.01), respectively], but not in prostate and breast cancer; (iii) each tumor type shows a specific pattern of cir-nDNA and NETs marker dynamics, but overall the pre- and post-surgery median values of cir-nDNA, NE, and MPO were significantly higher in cancer patients than in HI.

Conclusion

Taken as a whole, our work reveals the association of NETs formation with the elevated cir-nDNA release during a cancer patient's perioperative period, depending on surgical procedure or cancer type. By contrast, cir-mtDNA is poorly associated with NETs formation in the studied perioperative period, which would appear to indicate a different mechanism of release or suggest mitochondrial dysfunction.

del Hierro A, H-Vázquez J, Cuesta-Sancho S, Bernardo D. State-of-the-art cytometry in the search of novel biomarkers in digestive cancers

Despite that colorectal and liver cancer are among the most prevalent tumours in the world, the identification of non-invasive biomarkers to aid on their diagnose and subsequent prognosis is a current unmet need that would diminish both their incidence and mortality rates. In this context, conventional flow cytometry has been widely used in the screening of biomarkers with clinical utility in other malignant processes like leukaemia or lymphoma. Therefore, in this review, we will focus on how advanced cytometry panels covering over 40 parameters can be applied on the study of the immune system from patients with colorectal and hepatocellular carcinoma and how that can be used on the search of novel biomarkers to aid or diagnose, prognosis, and even predict clinical response to different treatments. In addition, these multiparametric and unbiased approaches can also provide novel insights into the specific immunopathogenic mechanisms governing these malignant diseases, hence potentially unravelling novel targets to perform immunotherapy or identify novel mechanisms, rendering the development of novel treatments. As a consequence, computational cytometry approaches are an emerging methodology for the early detection and predicting therapies for gastrointestinal cancers.

Genetic screening of liver cancer: State of the art

Liver cancer, primarily hepatocellular carcinoma, remains a global health challenge with rising incidence and limited therapeutic options. Genetic factors play a pivotal role in the development and progression of liver cancer. This state-of-the-art paper provides a comprehensive review of the current landscape of genetic screening strategies for liver cancer. We discuss the genetic underpinnings of liver cancer, emphasizing the critical role of risk-associated genetic variants, somatic mutations, and epigenetic alterations. We also explore the intricate interplay between environmental factors and genetics, highlighting how genetic screening can aid in risk stratification and early detection via using liquid biopsy, and advancements in high-throughput sequencing technologies. By synthesizing the latest research findings, we aim to provide a comprehensive overview of the state-of-the-art genetic screening methods for liver cancer, shedding light on their potential to revolutionize early detection, risk assessment, and targeted therapies in the fight against this devastating disease.

Biomarkers in Cancer Screening: Promises and Challenges in Cancer Early Detection

Cancer continues to be one the leading causes of death worldwide, primarily due to the late detection of the disease. Cancers detected at early stages may enable more effective intervention of the disease. However, most cancers lack well-established screening procedures except for cancers with an established early asymptomatic phase and clinically validated screening tests. There is a critical need to identify and develop assays/tools in conjunction with imaging approaches for precise screening and detection of the aggressive disease at an early stage. New developments in molecular cancer screening and early detection include germline testing, synthetic biomarkers, and liquid biopsy approaches.

Fragmentomics features of ovarian cancer

Ovarian cancer (OC) is a major cause of cancer mortality in women worldwide. Due to the occult onset of OC, its nonspecific clinical symptoms in the early phase, and a lack of effective early diagnostic tools, most OC patients are diagnosed at an advanced stage. In this study, shallow whole-genome sequencing was utilized to characterize fragmentomics features of circulating tumor DNA (ctDNA) in OC patients. By applying a machine learning model, multiclass fragmentomics data achieved a mean area under the curve (AUC) of 0.97 (95% CI 0.962-0.976) for diagnosing OC. OC scores derived from this model strongly correlated with the disease stage. Further comparative analysis of OC scores illustrated that the fragmentomics-based technology provided additional clinical benefits over the traditional serum biomarkers cancer antigen 125 (CA125) and the Risk of Ovarian Malignancy Algorithm (ROMA) index. In conclusion, fragmentomics features in ctDNA are potential biomarkers for the accurate diagnosis of OC.

Early-stage lung cancer is driven by a transitional cell state dependent on a KRAS-ITGA3-SRC axis

Glycine-12 mutations in the GTPase KRAS (KRASG12) are an initiating event for development of lung adenocarcinoma (LUAD). KRASG12 mutations promote cell-intrinsic rewiring of alveolar type-II progenitor (AT2) cells, but to what extent such changes interplay with lung homeostasis and cell fate pathways is unclear. Here, we generated single-cell RNA-seq (scRNA-seq) profiles from AT2-mesenchyme organoid co-cultures, mice, and stage-IA LUAD patients, identifying conserved regulators of AT2 transcriptional dynamics and defining the impact of KRASG12D mutation with temporal resolution. In AT2WT organoids, we found a transient injury/plasticity state preceding AT2 self-renewal and AT1 differentiation. Early-stage AT2KRAS cells exhibited perturbed gene expression dynamics, most notably retention of the injury/plasticity state. The injury state in AT2KRAS cells of patients, mice, and organoids was distinguishable from AT2WT states via altered receptor expression, including co-expression of ITGA3 and SRC. The combination of clinically relevant KRASG12D and SRC inhibitors impaired AT2KRAS organoid growth. Together, our data show that an injury/plasticity state essential for lung repair is co-opted during AT2 self-renewal and LUAD initiation, suggesting that early-stage LUAD may be susceptible to interventions that target specifically the oncogenic nature of this cell state.

Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-Specific Transcriptome and Molecular Subtype

Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predicted consensus molecular subtypes in patients with metastatic colorectal cancer. Analysis of plasma evRNA also enabled monitoring of changes in transcriptomic subtype under treatment selection pressure and identification of molecular pathways associated with recurrence. This approach also revealed expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of using transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to the identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling.

SIGNIFICANCE

The development of an approach to interrogate molecular subtypes, cancer-associated pathways, and differentially expressed genes through RNA sequencing of plasma extracellular vesicles lays the foundation for liquid biopsy-based longitudinal monitoring of patient tumor transcriptomes.

Increased blood draws for ultrasensitive ctDNA and CTCs detection in early breast cancer patients

Early breast cancer patients often experience relapse due to residual disease after treatment. Liquid biopsy is a methodology capable of detecting tumor components in blood, but low concentrations at early stages pose challenges. To detect them, next-generation sequencing has promise but entails complex processes. Exploring larger blood volumes could overcome detection limitations. Herein, a total of 282 high-volume plasma and blood-cell samples were collected for dual ctDNA/CTCs detection using a single droplet-digital PCR assay per patient. ctDNA and/or CTCs were detected in 100% of pre-treatment samples. On the other hand, post-treatment positive samples exhibited a minimum variant allele frequency of 0.003% for ctDNA and minimum cell number of 0.069 CTCs/mL of blood, surpassing previous investigations. Accurate prediction of residual disease before surgery was achieved in patients without a complete pathological response. A model utilizing ctDNA dynamics achieved an area under the ROC curve of 0.92 for predicting response. We detected disease recurrence in blood in the three patients who experienced a relapse, anticipating clinical relapse by 34.61, 9.10, and 7.59 months. This methodology provides an easily implemented alternative for ultrasensitive residual disease detection in early breast cancer patients.

Cell-free DNA methylation in the clinical management of lung cancer

The clinical use of cell-free DNA (cfDNA) methylation in managing lung cancer depends on its ability to differentiate between malignant and healthy cells, assign methylation changes to specific tissue sources, and elucidate opportunities for targeted therapy. From a technical standpoint, cfDNA methylation analysis is primed as a potential clinical tool for lung cancer screening, early diagnosis, prognostication, and treatment, pending the outcome of elaborate validation studies. Here, we discuss the current state of the art in cfDNA methylation analysis, examine the unique features and limitations of these new methods in a clinical context, propose two models for applying cfDNA methylation data for lung cancer screening, and discuss future research directions.

Bridging horizons beyond CIRCULATE-Japan: a new paradigm in molecular residual disease detection via whole genome sequencing-based circulating tumor DNA assay

Circulating tumor DNA (ctDNA) is the fraction of cell-free DNA in patient blood that originates from a tumor. Advances in DNA sequencing technologies and our understanding of the molecular biology of tumors have increased interest in exploiting ctDNA to facilitate detection of molecular residual disease (MRD). Analysis of ctDNA as a promising MRD biomarker of solid malignancies has a central role in precision medicine initiatives exemplified by our CIRCULATE-Japan project involving patients with resectable colorectal cancer. Notably, the project underscores the prognostic significance of the ctDNA status at 4 weeks post-surgery and its correlation to adjuvant therapy efficacy at interim analysis. This substantiates the hypothesis that MRD is a critical prognostic indicator of relapse in patients with colorectal cancer. Despite remarkable advancements, challenges endure, primarily attributable to the exceedingly low ctDNA concentration in peripheral blood, particularly in scenarios involving low tumor shedding and the intrinsic error rates of current sequencing technologies. These complications necessitate more sensitive and sophisticated assays to verify the clinical utility of MRD across all solid tumors. Whole genome sequencing (WGS)-based tumor-informed MRD assays have recently demonstrated the ability to detect ctDNA in the parts-per-million range. This review delineates the current landscape of MRD assays, highlighting WGS-based approaches as the forefront technique in ctDNA analysis. Additionally, it introduces our upcoming endeavor, WGS-based pan-cancer MRD detection via ctDNA, in our forthcoming project, SCRUM-Japan MONSTAR-SCREEN-3.

Noninvasive Blood-Based Cancer Detection in Veterinary Medicine

The past decade has seen incredible advances in blood-based cancer detection in people and in dogs - yet this represents only a glimpse of the benefits these tests can provide to patients. The clinical uses of this technology range from screening asymptomatic individuals for early detection to use as an aid in diagnosis when cancer is suspected, to cancer monitoring both during and after treatment. This article summarizes the benefits of early cancer detection and examines use cases and methods of blood-based cancer detection in dogs, including quantitative, qualitative, and alternative approaches.

New roles of tumor-derived exosomes in tumor microenvironment

Throughout tumorigenesis, the co-evolution of tumor cells and their surrounding microenvironment leads to the development of malignant phenotypes. Cellular communication within the tumor microenvironment (TME) plays a critical role in influencing various aspects of tumor progression, including invasion and metastasis. The release of exosomes, a type of extracellular vesicle, by most cell types in the body, is an essential mediator of intercellular communication. A growing body of research indicates that tumor-derived exosomes (TDEs) significantly expedite tumor progression through multiple mechanisms, inducing epithelial-mesenchymal transition and macrophage polarization, enhancing angiogenesis, and aiding in the immune evasion of tumor cells. Herein, we describe the formation and characteristics of the TME, and summarize the contents of TDEs and their diverse functions in modulating tumor development. Furthermore, we explore potential applications of TDEs in tumor diagnosis and treatment.

Decoding bioactive signals of the RNA secretome: the cell-free messenger RNA catalogue

Despite gene-expression profiling being one of the most common methods to evaluate molecular dysregulation in tissues, the utilization of cell-free messenger RNA (cf-mRNA) as a blood-based non-invasive biomarker analyte has been limited compared to other RNA classes. Recent advancements in low-input RNA-sequencing and normalization techniques, however, have enabled characterization as well as accurate quantification of cf-mRNAs allowing direct pathological insights. The molecular profile of the cell-free transcriptome in multiple diseases has subsequently been characterized including, prenatal diseases, neurological disorders, liver diseases and cancers suggesting this biological compartment may serve as a disease agnostic platform. With mRNAs packaged in a myriad of extracellular vesicles and particles, these signals may be used to develop clinically actionable, non-invasive disease biomarkers. Here, we summarize the recent scientific developments of extracellular mRNA, biology of extracellular mRNA carriers, clinical utility of cf-mRNA as disease biomarkers, as well as proposed functions in cell and tissue pathophysiology.

Circulating tumor DNA in liquid biopsy: Current diagnostic limitation

With the rapid development of science and technology, cell-free DNA (cfDNA) is rapidly becoming an important biomarker for tumor diagnosis, monitoring and prognosis, and this cfDNA-based liquid biopsy technology has great potential to become an important part of precision medicine. cfDNA is the total amount of free DNA in the systemic circulation, including DNA fragments derived from tumor cells and all other somatic cells. Tumor cells release fragments of DNA into the bloodstream, and this source of cfDNA is called circulating tumor DNA (ctDNA). cfDNA detection has become a major focus in the field of tumor research in recent years, which provides a new opportunity for non-invasive diagnosis and prognosis of cancer. In this paper, we discuss the limitations of the study on the origin and dynamics analysis of ctDNA, and how to solve these problems in the future. Although the future faces major challenges, it also contains great potential.

Circulating tumor DNA in liquid biopsy: Current diagnostic limitation

With the rapid development of science and technology, cell-free DNA (cfDNA) is rapidly becoming an important biomarker for tumor diagnosis, monitoring and prognosis, and this cfDNA-based liquid biopsy technology has great potential to become an important part of precision medicine. cfDNA is the total amount of free DNA in the systemic circulation, including DNA fragments derived from tumor cells and all other somatic cells. Tumor cells release fragments of DNA into the bloodstream, and this source of cfDNA is called circulating tumor DNA (ctDNA). cfDNA detection has become a major focus in the field of tumor research in recent years, which provides a new opportunity for non-invasive diagnosis and prognosis of cancer. In this paper, we discuss the limitations of the study on the origin and dynamics analysis of ctDNA, and how to solve these problems in the future. Although the future faces major challenges, it also contains great potential.

An in vitro CRISPR screen of cell-free DNA identifies apoptosis as the primary mediator of cell-free DNA release

ABTRACT

Clinical circulating cell-free DNA (cfDNA) testing is now routine, however test accuracy remains limited. By understanding the life-cycle of cfDNA, we might identify opportunities to increase test performance. Here, we profile cfDNA release across a 24-cell line panel and utilize a cell-free CRISPR screen (cfCRISPR) to identify mediators of cfDNA release. Our panel outlines two distinct groups of cell lines: one which releases cfDNA fragmented similarly to clinical samples and purported as characteristic of apoptosis, and another which releases larger fragments associated with vesicular or necrotic DNA. Our cfCRISPR screens reveal that genes mediating cfDNA release are primarily involved with apoptosis, but also identify other subsets of genes such as RNA binding proteins as potential regulators of cfDNA release. We observe that both groups of cells lines identified primarily produce cfDNA through apoptosis. These results establish the utility of cfCRISPR, genetically validate apoptosis as a major mediator of DNA release in vitro, and implicate ways to improve cfDNA assays.

High-Fidelity Sensitive Tracing Circulating Tumor Cell Telomerase Activity

Dynamic tracing of intracellular telomerase activity plays a crucial role in cancer cell recognition and correspondingly in earlier cancer diagnosis and personalized precision therapy. However, due to the complexity of the required reaction system and insufficient loading of reaction components into cells, achieving a high-fidelity determination of telomerase activity is still a challenge. Herein, an Aptamer-Liposome mediated Telomerase activated poly-Molecular beacon Arborescent Nanoassembly(ALTMAN) approach was described for direct high-fidelity visualization of telomerase activity. Briefly, intracellular telomerase activates molecular beacons, causing their hairpin structures to unfold and produce fluorescent signals. Furthermore, multiple molecular beacons can self-assemble, forming arborescent nanostructures and leading to exponential amplification of fluorescent signals. Integrating the enzyme-free isothermal signal amplification successfully increased the sensitivity and reduced interference by leveraging the skillful design of the molecular beacon and the extension of the telomerase-activated TTAGGG repeat sequence. The proposed approach enabled ultrasensitive visualization of activated telomerase exclusively with a prominent detection limit of 2 cells·μL-1 and realized real-time imaging of telomerase activity in living cancer cells including blood samples from breast cancer patients and urine samples from bladder cancer patients. This approach opens an avenue for establishing a telomerase activity determination and in situ monitoring technique that can facilitate both telomerase fundamental biological studies and cancer diagnostics.

Pushing the Boundaries of Liquid Biopsies for Early Precision Intervention

Liquid biopsies are emerging as powerful minimally invasive approaches that have the potential to solve several long-standing problems spanning the continuum of cancer care: early detection of cancer, minimal residual disease tracking, and refinement of the heterogeneity of clinical responses together with therapeutic response monitoring in the metastatic setting. Existing challenges driven by technical limitations and establishment of the clinical value of liquid biopsies represent fields of active research that call for convergence science approaches to bridge scientific discovery with clinical care.

Early screening of colorectal cancer using feature engineering with artificial intelligence-enhanced analysis of nanoscale chromatin modifications

Colonoscopy is accurate but inefficient for colorectal cancer (CRC) prevention due to the low (~ 7 to 8%) prevalence of target lesions, advanced adenomas. We leveraged rectal mucosa to identify patients who harbor CRC field carcinogenesis by evaluating chromatin 3D architecture. Supranucleosomal disordered chromatin chains (~ 5 to 20 nm, ~1 kbp) fold into chromatin packing domains (~ 100 to 200 nm, ~ 100 to 1000 kbp). In turn, the fractal-like conformation of DNA within chromatin domains and the folding of the genome into packing domains has been shown to influence multiple facets of gene transcription, including the transcriptional plasticity of cancer cells. We deployed an optical spectroscopic nanosensing technique, chromatin-sensitive partial wave spectroscopic microscopy (csPWS), to evaluate the packing density scaling D of the chromatin chain conformation within packing domains from rectal mucosa in 256 patients with varying degrees of progression to colorectal cancer. We found average packing scaling D of chromatin domains was elevated in tumor cells, histologically normal-appearing cells 4 cm proximal to the tumor, and histologically normal-appearing rectal mucosa compared to cells from control patients (p < 0.001). Nuclear D had a robust correlation with the model of 5-year risk of CRC with r2 = 0.94. Furthermore, rectal D was evaluated as a screening biomarker for patients with advanced adenomas presenting an AUC of 0.85 and 85% sensitivity and specificity. artificial intelligence-enhanced csPWS improved diagnostic performance with AUC = 0.90. Considering the low sensitivity of existing CRC tests, including liquid biopsies, to early-stage cancers our work highlights the potential of chromatin biomarkers of field carcinogenesis in detecting early, significant precancerous colon lesions.

NCI Resources for Cancer Immunoprevention Research

Cancer prevention and early detection, the first two of the eight primary goals of the National Cancer Plan released in April 2023, are at the forefront of the nation's strategic efforts to reduce cancer incidence and mortality. The Division of Cancer Prevention (DCP) of the NCI is the federal government's principal component devoted to promoting and supporting innovative cancer prevention research. Recent advances in tumor immunology, cancer immunotherapy, and vaccinology strongly suggest that the host immune system can be effectively harnessed to elicit protective immunity against the development of cancer, that is, cancer immunoprevention. Cancer immunoprevention may be most effective if the intervention is given before or early in the carcinogenic process while the immune system remains relatively uncompromised. DCP has increased the emphasis on immunoprevention research in recent years and continues to expand program resources and interagency collaborations designed to facilitate research in the immunoprevention field. These resources support a wide array of basic, translational, and clinical research activities, including discovery, development, and validation of biomarkers for cancer risk assessment and early detection (Early Detection Research Network), elucidation of biological and pathophysiological mechanistic determinants of precancer growth and its control (Translational and Basic Science Research in Early Lesions), spatiotemporal multiomics characterization of precancerous lesions (Human Tumor Atlas Network/Pre-Cancer Atlas), discovery of immunoprevention pathways and immune targets (Cancer Immunoprevention Network), and preclinical and clinical development of novel agents for immunoprevention and interception (Cancer Prevention-Interception Targeted Agent Discovery Program, PREVENT Cancer Preclinical Drug Development Program, and Cancer Prevention Clinical Trials Network).

STK11/LKB1 alterations worsen the poor prognosis of KRAS mutated early-stage non-squamous non-small cell lung carcinoma, results based on the phase 2 IFCT TASTE trial

BACKGROUND

STK11/LKB1 mutations have been associated with primary resistance to PD-1 axis inhibitors and poor prognosis in advanced KRAS-mutant lung adenocarcinoma. This study aimed to assess the prognostic significance of STK11/LKB1 alterations in localized non-squamous non-small cell lung carcinoma (non-sq NSCLC).

PATIENTS AND METHODS

Surgical samples from patients undergoing complete resection for stage IIa, IIb, or IIIa (N2 excluded) non-sq NSCLC in the randomized adjuvant phase II trial (NCT00775385 IFCT-1801 TASTE trial) were examined. Patients received either standard chemotherapy (Pemetrexed Cisplatin) or personalized treatment based on EGFR mutation (Erlotinib) and ERCC1 expression. Tumor molecular profiles were analyzed using targeted NGS and correlated with overall survival (OS) and disease-free survival (DFS), adjusting for relevant clinical variables. Additionally, interactions between treatment groups and molecular alterations on OS, PD-L1 expression, and tumor-circulating DNA in post-operative plasma samples were evaluated.

RESULTS

Among 134 patients (predominantly male smokers with adenocarcinoma), KRAS mutations were associated with shorter DFS (HR: 1.95, 95 % CI: 1.1-3.4, p = 0.02) and OS (HR: 2.32, 95 % CI: 1.2-4.6, p = 0.014). Isolated STK11/LKB1 mutations (n = 18) did not significantly impact DFS or OS. However, within KRAS-mutated samples (n = 53), patients with concurrent STK11/LKB1 mutations (n = 10) exhibited significantly shorter DFS (HR: 3.85, CI: 1.5-10.2, p = 0.006) and a trend towards shorter OS (HR: 1.80, CI: 0.6-5.3, p = 0.28). No associations were found between PD-L1 expression, other gene mutations, progression-free survival (PFS), or OS.

CONCLUSION

This analysis reinforces KRAS mutations as predictive factors for relapse and poor survival in localized non-sq NSCLC. Furthermore, the presence of concomitant STK11/LKB1 mutations exacerbated the prognosis within the KRAS-mutated subset. These findings emphasize the clinical relevance of these molecular markers and their potential impact on treatment strategies in non-sq NSCLC.

Principles of digital sequencing using unique molecular identifiers

Massively parallel sequencing technologies have long been used in both basic research and clinical routine. The recent introduction of digital sequencing has made previously challenging applications possible by significantly improving sensitivity and specificity to now allow detection of rare sequence variants, even at single molecule level. Digital sequencing utilizes unique molecular identifiers (UMIs) to minimize sequencing-induced errors and quantification biases. Here, we discuss the principles of UMIs and how they are used in digital sequencing. We outline the properties of different UMI types and the consequences of various UMI approaches in relation to experimental protocols and bioinformatics. Finally, we describe how digital sequencing can be applied in specific research fields, focusing on cancer management where it can be used in screening of asymptomatic individuals, diagnosis, treatment prediction, prognostication, monitoring treatment efficacy and early detection of treatment resistance as well as relapse.