Biomarkers For Early Cancer Detection Research Articles

Unraveling the Connection: Extracellular Vesicles and Non-Small Cell Lung Cancer.

Extracellular vesicles (EVs) are nanoscale lipid bilayer vesicles released during cell activation, cellular damage, or apoptosis. They carry nucleic acids, proteins, and lipids facilitating intercellular communication and activate signaling pathways in target cells. In non-small cell lung cancer (NSCLC), EVs may contribute to tumor growth and metastasis by modulating immune responses, facilitating epithelial-mesenchymal transition, and promoting angiogenesis, while potentially contributing to resistance to chemotherapy drugs. EVs in liquid biopsies serve as non-invasive biomarkers for early cancer detection and diagnosis. Due to their small size, inherent molecular transport properties, and excellent biocompatibility, EVs also act as natural drug delivery vehicles in NSCLC therapy.

Plasma cell-free DNA methylome-based liquid biopsy for accurate gastric cancer detection.

Early detection plays a critical role in mitigating mortality rates linked to gastric cancer. However, current clinical screening methods exhibit suboptimal efficacy. Methylation alterations identified from cell-free DNA (cfDNA) present a promising biomarker for early cancer detection. Our study focused on identifying gastric cancer-specific markers from cfDNA methylation to facilitate early detection. We enrolled 150 gastric cancer patients and 100 healthy controls in this study, and undertook genome-wide methylation profiling of cfDNA using cell-free methylated DNA immunoprecipitation and high-throughput sequencing. We identified 21 differentially methylated regions (DMRs) between the gastric tumor and nontumor groups using multiple algorithms. Subsequently, using the 21 DMRs, we developed a gastric cancer detection model by random forest algorithm in the discovery set, and validated the model in an independent set. The model was able to accurately discriminate gastric cancer with a sensitivity and specificity of 93.90% and 95.15% in the discovery set, respectively, and 88.38% and 94.23% in the validation set, respectively. These results underscore the efficacy and accuracy of cfDNA-derived methylation markers in distinguishing early stage gastric cancer. This study highlighted the significance of cfDNA methylation alterations in early gastric cancer detection.

Extracellular Vesicles, Circadian Rhythms, and Cancer: A Comprehensive Review with Emphasis on Hepatocellular Carcinoma.

This review comprehensively explores the complex interplay between extracellular vesicles (ECVs)/exosomes and circadian rhythms, with a focus on the role of this interaction in hepatocellular carcinoma (HCC). Exosomes are nanovesicles derived from cells that facilitate intercellular communication by transporting bioactive molecules such as proteins, lipids, and RNA/DNA species. ECVs are implicated in a range of diseases, where they play crucial roles in signaling between cells and their surrounding environment. In the setting of cancer, ECVs are known to influence cancer initiation and progression. The scope of this review extends to all cancer types, synthesizing existing knowledge on the various roles of ECVs. A unique aspect of this review is the emphasis on the circadian-controlled release and composition of exosomes, highlighting their potential as biomarkers for early cancer detection and monitoring metastasis. We also discuss how circadian rhythms affect multiple cancer-related pathways, proposing that disruptions in the circadian clock can alter tumor development and treatment response. Additionally, this review delves into the influence of circadian clock components on ECV biogenesis and their impact on reshaping the tumor microenvironment, a key component driving HCC progression. Finally, we address the potential clinical applications of ECVs, particularly their use as diagnostic tools and drug delivery vehicles, while considering the challenges associated with clinical implementation.

Rapid enzyme-free detection of miRNA-21 in human ovarian cancerous cells using a fluorescent nanobiosensor designed based on hairpin DNA-templated silver nanoclusters

BackgroundCancer is known as one of the main non-communicable diseases and the leading cause of death in the new era. Early diagnosis of cancer requires the identification of special biomarkers. Currently, microRNAs (miRNAs) have attracted the attention of researchers as useful biomarkers for cancer early detection. Hence, various methods have been recently developed for detecting and monitoring miRNAs. Among all miRNAs, detection of miRNA-21 (miR-21) is important because it is abnormally overexpressed in most cancers. Here, a new biosensor based on silver nanoclusters (AgNCs) is introduced for detecting miR-21. ResultsAs a fluorescent probe, a rationally designed hairpin sequence containing a poly-cytosine motif was used to facilitate the formation of AgNCs. A guanine-rich sequence was also employed to enhance the sensing signal. It was found that in the absence of miR-21, adding a guanine-rich sequence to the detecting probe caused only a slight change in the fluorescence emission intensity of AgNCs. While in the presence of miR-21, the emission signal enhanced. A direct correlation was observed between the increase in the fluorescence of AgNCs and the concentration of miR-21. The performance of the proposed biosensor was characterized thoroughly and confirmed. The biosensor detected miR-21 in an applicable linear range from 9 pM to 1.55 nM (LOD: 2 pM). SignificanceThe designed biosensor was successfully applied for detecting miR-21 in human plasma samples and also in human normal and lung and ovarian cancer cells. This biosensing strategy can be used as a model for detecting other miRNAs. The designed nanobiosensor can measure miR-21 without using any enzymes, with fewer experimental steps, and at a low cost compared to the reported biosensors in this field.

Optimization of ultracentrifugation-based method to enhance the purity and proteomic profiling depth of plasma-derived extracellular vesicles and particles.

Circulating extracellular vesicles and particles (EVPs) are being investigated as potential biomarkers for early cancer detection, prognosis, and disease monitoring. However, the suboptimal purity of EVPs isolated from peripheral blood plasma has posed a challenge of in-depth analysis of the EVP proteome. Here, we compared the effectiveness of different methods for isolating EVPs from healthy donor plasma, including ultracentrifugation (UC)-based protocols, phosphatidylserine-Tim4 interaction-based affinity capture (referred to as "PS"), and several commercial kits. Modified UC methods with an additional UC washing or size exclusion chromatography step substantially improved EVP purity and enabled the detection of additional proteins via proteomic mass spectrometry, including many plasma membrane and cytoplasmic proteins involved in vesicular regulation pathways. This improved performance was reproduced in cancer patient plasma specimens, resulting in the identification of a greater number of differentially expressed EVP proteins, thus expanding the range of potential biomarker candidates. However, PS and other commercial kits did not outperform UC-based methods in improving plasma EVP purity. PS yielded abundant contaminating proteins and a biased enrichment for specific EVP subsets, thus unsuitable for proteomic profiling of plasma EVPs. Therefore, we have optimized UC-based protocols for circulating EVP isolation, which enable further in-depth proteomic analysis for biomarker discovery.

Serum miR‐215‐5p, miR‐192‐5p and miR-378a-5p as novel diagnostic biomarkers for periampullary adenocarcinoma

ObjectiveMicroRNAs (miRNAs) are present in human serum in a stable form. Circulating miRNAs are increasingly recognized as promising biomarkers for early cancer detection. The aim of this study was to identify serum miRNAs as biomarkers for periampullary adenocarcinoma (PAC). Patients and methods68 patients with PAC and 50 healthy controls (HCs) subjects were recruited in this study. The expression levels of 11 selected miRNAs were determined in serum samples using the SYBR-green quantitative reverse transcription polymerase chain reaction (qRT-PCR) method. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic potential of serum miRNAs. ResultsThe expression levels of three miRNAs (miR‐215‐5p, miR‐192‐5p, and miR-378a-5p) were significantly upregulated in the serum samples derived from the PAC patients compared with those from the HC (p < 0.001). The ROC analysis showed that all three significantly altered miRNAs (miR‐215‐5p, miR‐192‐5p, and miR-378a-5p) could potentially discriminate patients with PAC from HC with AUC value of 0.771 (95% CI: 0.684–0.843), 0.877 (95% CI: 0.799–0.927) and 0.768 (95% CI: 0.674–0.853) respectively. Further comparisons showed that these three serum miRNAs (miR‐215‐5p, miR‐192‐5p, and miR-378a-5p) can strongly discriminate early-stage PAC patients from HC with an AUC value of 0.802 (95% CI: 0.719–0.886), 0.870 (95% CI: 0.793–0.974) and 0.793 (95% CI: 0.706–0.880) respectively, may aid in early detection of PAC. ConclusionsTaken together, our findings demonstrated that these three serum miRNAs (miR‐215‐5p, miR‐192‐5p, and miR-378a-5p) may serve as noninvasive biomarkers for the early detection of PAC.

Triple-Negative Breast Cancer EVs Modulate Growth and Migration of Normal Epithelial Lung Cells.

Breast cancer is the most common cancer amongst women worldwide. Recently, owing to screening programs and new technologies, the survival rate has increased significantly. Breast cancer can potentially develop metastases, and, despite them, lung metastases generally occur within five years of breast cancer diagnosis. In this study, the objective was to analyze the effect of breast cancer-derived EVs on a lung epithelial cell line. BEAS-2B cells were treated with extracellular vesicles (EVs) derived from triple-negative breast cancer cells (TNBCs), e.g., MDA-MB-231 and HS578T, separated using differential ultracentrifugation. We observed an increased growth, migration, and invasiveness of normal epithelial lung cells over time in the presence of TNBC EVs compared to the control. Therefore, these data suggest that EVs released by tumor cells contain biological molecules capable of influencing the pro-tumorigenic activity of normal cells. Exploring the role of EVs in oncology research and their potential cargo may be novel biomarkers for early cancer detection and further diagnosis.

Electrochemical Sensor for the Detection and Accurate Early Diagnosis of Ovarian Cancer.

Ovarian cancer (OC) has the highest mortality rate among malignant tumors, primarily because it is difficult to diagnose early. Exosomes, a type of extracellular vesicle rich in parental information, have garnered significant attention in the field of cancer diagnosis and treatment. They play an important regulatory role in the occurrence, development, and metastasis of OC. Consequently, exosomes have emerged as noninvasive biomarkers for early cancer detection. Therefore, identifying cancer-derived exosomes may offer a novel biomarker for the early detection of OC. In this study, we developed a metal-organic frameworks assembled "double hook"-type aptamer electrochemical sensor, which enables accurate early diagnosis of OC. Under optimal experimental conditions, electrochemical impedance spectroscopy technology demonstrated a good linear relationship within the concentration range of 31-3.1 × 106 particles per microliter, with a detection limit as low as 12 particles per microliter. The universal exosome detection platform is constructed, and this platform can not only differentiate between high-grade serous ovarian cancer (HGSOC) patients and healthy individuals but also distinguish between HGSOC patients and nonhigh-grade serous OC (non-HGSOC). Consequently, it provides a novel strategy for the early diagnosis of OC and holds great significance in clinical differential diagnosis.

Role of MicroRNA in Hypoxic Tumours and their Potential as Biomarkers for Early Detection of Cancer.

Hypoxia is a pathophysiological condition characterized by oxygen deficiency in tissues, which negatively affects normal biological functions. It is a typical microenvironment character of almost all solid tumours. Noncoding RNA are small functional RNA molecules that regulate gene expression at chromatin and posttranscriptional levels. Micro-RNAs (miRNAs) are a type of noncoding RNA and are ~12-22 nucleotides long that are crucial in regulating gene expression by partnering with the mRNAs of protein-coding genes. It is widely reported that miRs play an important role in various key processes and pathways during tumour formation, as well as advancement in hypoxic tumors by influencing the HIF pathway. The role of miRNAs in hypoxic tumours, namely in pancreatic, kidney, breast, lung and colorectal, are described. These miRNAs have immense potential as diagnostic and prognostic biomarkers for early cancer detection.

Circulating tumor DNA: from discovery to clinical application in breast cancer.

Breast cancer (BC) stands out as the cancer with the highest incidence of morbidity and mortality among women worldwide, and its incidence rate is currently trending upwards. Improving the efficiency of breast cancer diagnosis and treatment is crucial, as it can effectively reduce the disease burden. Circulating tumor DNA (ctDNA) originates from the release of tumor cells and plays a pivotal role in the occurrence, development, and metastasis of breast cancer. In recent years, the widespread application of high-throughput analytical technology has made ctDNA a promising biomarker for early cancer detection, monitoring minimal residual disease, early recurrence monitoring, and predicting treatment outcomes. ctDNA-based approaches can effectively compensate for the shortcomings of traditional screening and monitoring methods, which fail to provide real-time information and prospective guidance for breast cancer diagnosis and treatment. This review summarizes the applications of ctDNA in various aspects of breast cancer, including screening, diagnosis, prognosis, treatment, and follow-up. It highlights the current research status in this field and emphasizes the potential for future large-scale clinical applications of ctDNA-based approaches.

Abstract LB102: Triaging oral premalignant lesions: Plasma ultrashort cell-free DNA-based liquid biopsy approach

Abstract Background: Rapid advancements in cell-free DNA (cfDNA) based liquid biopsy (LB), has opened avenues of critical clinical importance. Recent discovery of a novel class of cell-free DNA 40-70 bps in length, ultrashort cfDNA (uscfDNA) is demonstrating immense potential as a cancer early detection biomarker. Globally, oral cavity squamous cell carcinomas (OCSCC) make up a significant proportion of head and neck squamous cell cancers. OCSCC commonly arises after the occurrence of oral premalignant lesions (OPLs), making it an ideal target for plasma-based LB screening initiatives. Methods: Current work focuses on preferential extraction of low molecular weight nucleic acids and single-stranded library preparation and sequencing, Broad Range cell-free DNA- Sequencing (BRcfDNA-Seq), to obtain uscf- &amp; 167 bps mononucleosomal cfDNA (mncfDNA), for disease detection. Sequencing data was bioinformatically processed: paired-end reads merged (BBmerge), aligned with BWA-mem, deduplicated using SRSLY UMI, and blacklisted portions removed. This was followed by analysis for non-mutational features like fragmentomics, occurrence of G-Quad structures, 4-mer Motif sequences at the end of cfDNA sequences, functional genomic element peak formation by uscfDNA. These features have been recently described non-mutation metrics which have demonstrated evidence of clinical relevance. With non-mutational multi-modal analysis of uscfDNA, obtained using BRcfDNA-Seq, we were able to categorize oral premalignant disorders into two cohorts: one which progressed into OCSCC (PG-OPL) (n=19) &amp; one which did not (nPG-OPL) (n=19). Results: Bioinformatic processing for fragmentomics, of the relative proportion of 40-53bps fragments to 54-70bps fragments in the uscfDNA population demonstrated a significant difference across 1700 chromosomal bins between PG &amp; nPG-OPL (multiple t test, FDR 10%, p value = 0.044, AUROC = 0.7258). The occurrence of G-quadruplex structures in uscfDNA was also significantly different between the two groups (student t test, p= 0.02, AUROC= 0.6953). Examination of the end-motifs profiles of uscfDNA between PG-OPL &amp; nPG-OPL samples showed the randomness of the motifs as revealed by the Shannon entropy score is significant between the two groups (p = 0.046, AUROC = 0.6482). We further evaluated individual motifs that could discriminate between the two groups and identified CCCC, CCCT, TGGG, etc. are highly discriminatory. uscfDNA contained a substantially higher proportion of functional genomic element sequences in the PG-OPL group than the nPG-OPL group like exon (p = 0.00067, AUROC = 0.7147) &amp; 5’ UTR (p= 0.000006, AUROC= 0.7673) are different between the groups. Conclusion: Results demonstrated clinical relevance of BRcfDNA-Seq for plasma-derived cfDNA in assessment of malignancy progression of OPLs. These non-mutational multi-modal features of cfDNA maybe indicative of local and systemic factors associated with disease affecting cfDNA. Citation Format: Neeti Swarup, Jordan C. Cheng, Irene Choi, Mohammad Arshad Aziz, Kelly Y. Liu, Fang Wei, Feng Li, Yong Kim, Catherine Poh, David T. Wong. Triaging oral premalignant lesions: Plasma ultrashort cell-free DNA-based liquid biopsy approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB102.

ZnO Nanocages Decorated with Au@AgAu Yolk-Shell Nanomaterials for SERS-Based Detection of Hyperuricemia.

Surface-enhanced Raman scattering (SERS) is widely recognized as a highly sensitive technology for chemical detection and biological sensing. In SERS-based biomedical applications, developing highly efficient sensing platforms based on SERS plays a pivotal role in monitoring disease biomarker levels and facilitating the early detection of cancer biomarkers. Hyperuricemia, characterized by abnormally high concentrations of uric acid (UA) in the blood, was associated with a range of diseases, such as gouty arthritis, heart disease, and acute kidney injury. Recent reports have demonstrated the correlation between UA concentrations in blood and tears. In this work, we report the fabrication of SERS substrates utilizing ZnO nanocages and yolk-shell-structured plasmonic nanomaterials for the noninvasive detection of UA in tears. This innovative SERS substrate enables noninvasive and sensitive detection of UA to prevent hyperuricemia-related diseases.

Downregulation of praja2 restrains endocytosis and boosts tyrosine kinase receptors in kidney cancer

Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer in the adult population. Late diagnosis, resistance to therapeutics and recurrence of metastatic lesions account for the highest mortality rate among kidney cancer patients. Identifying novel biomarkers for early cancer detection and elucidating the mechanisms underlying ccRCC will provide clues to treat this aggressive malignant tumor. Here, we report that the ubiquitin ligase praja2 forms a complex with-and ubiquitylates the AP2 adapter complex, contributing to receptor endocytosis and clearance. In human RCC tissues and cells, downregulation of praja2 by oncogenic miRNAs (oncomiRs) and the proteasome markedly impairs endocytosis and clearance of the epidermal growth factor receptor (EGFR), and amplifies downstream mitogenic and proliferative signaling. Restoring praja2 levels in RCC cells downregulates EGFR, rewires cancer cell metabolism and ultimately inhibits tumor cell growth and metastasis. Accordingly, genetic ablation of praja2 in mice upregulates RTKs (i.e. EGFR and VEGFR) and induces epithelial and vascular alterations in the kidney tissue.In summary, our findings identify a regulatory loop between oncomiRs and the ubiquitin proteasome system that finely controls RTKs endocytosis and clearance, positively impacting mitogenic signaling and kidney cancer growth.

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers.

Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcomes, thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of malignancy to decisions on treatment and subsequent monitoring. A large variety of molecular, histologic, radiographic, or physiological entities or features are among the common types of cancer biomarkers. Sizeable recent methodological progress and insights have promoted significant developments in the field of early cancer detection biomarkers. Here we provide an overview of recent advances in the knowledge related to biomolecules and cellular entities used for early cancer detection. We examine data from the CAS Content Collection, the largest human-curated collection of published scientific information, as well as from the biomarker datasets at Excelra, and analyze the publication landscape of recent research. We also discuss the evolution of key concepts and cancer biomarkers development pipelines, with a particular focus on pancreatic and liver cancers, which are known to be remarkably difficult to detect early and to have particularly high morbidity and mortality. The objective of the paper is to provide a broad overview of the evolving landscape of current knowledge on cancer biomarkers and to outline challenges and evaluate growth opportunities, in order to further efforts in solving the problems that remain. The merit of this review stems from the extensive, wide-ranging coverage of the most up-to-date scientific information, allowing unique, unmatched breadth of landscape analysis and in-depth insights.

Anti-BIRC5 autoantibody serves as a valuable biomarker for diagnosing AFP-negative hepatocellular carcinoma.

Autoantibodies targeting tumor-associated antigens (TAAbs) have emerged as promising biomarkers for early cancer detection. This research aimed to assess the diagnostic capacity of anti-BIRC5 autoantibody in detecting AFP-negative hepatocellular carcinoma (ANHCC). This research was carried out in three stages (discovery phase, validation phase, and evaluation phase) and included a total of 744 participants. Firstly, the anti-BIRC5 autoantibody was discovered using protein microarray, exhibiting a higher positive rate in ANHCC samples (ANHCCs) compared to normal control samples (NCs). Secondly, the anti-BIRC5 autoantibody was validated through enzyme-linked immunosorbent assay (ELISA) in 85 ANHCCs and 85 NCs from two clinical centers (Zhengzhou and Nanchang). Lastly, the diagnostic usefulness of the anti-BIRC5 autoantibody for hepatocellular carcinoma (HCC) was evaluated by ELISA in a cohort consisting of an additional 149 AFP-positive hepatocellular carcinoma samples (APHCCs), 95 ANHCCs and 244 NCs. The association of elevated autoantibody to high expression of BIRC5 in HCC was further explored by the database from prognosis, immune infiltration, DNA methylation, and gene mutation level. In the validation phase, the area under the ROC curve (AUC) of anti-BIRC5 autoantibody to distinguish ANHCCs from NCs in Zhengzhou and Nanchang centers was 0.733 and 0.745, respectively. In the evaluation phase, the AUCs of anti-BIRC5 autoantibody for identifying ANHCCs and HCCs from NCs were 0.738 and 0.726, respectively. Furthermore, when combined with AFP, the AUC for identifying HCCs from NCs increased to 0.914 with a sensitivity of 77.5% and specificity of 91.8%. High expression of BIRC5 gene is not only correlated with poor prognosis of HCCs, but also significantly associated with infiltration of immune cells, DNA methylation, and gene mutation. The findings suggest that the anti-BIRC5 autoantibody could serve as a potential biomarker for ANHCC, in addition to its supplementary role alongside AFP in the diagnosis of HCC. Next, we can carry out specific verification and explore the function of anti-BIRC5 autoantibody in the occurrence and development of HCC.

Advances and Challenges in Nanomaterial-Based Electrochemical Immunosensors for Small Cell Lung Cancer Biomarker Neuron-Specific Enolase.

Early and rapid detection of neuron-specific enolase (NSE) is highly significant, as it is putative biomarker for small-cell lung cancer as well as COVID-19. Electrochemical techniques have attracted substantial attention for the early detection of cancer biomarkers due to the important properties of simplicity, high sensitivity, specificity, low cost, and point-of-care detection. This work reviews the clinically relevant labeled and label-free electrochemical immunosensors developed so far for the analysis of NSE. The prevailing role of nanostructured materials as electrode matrices is thoroughly discussed. Subsequently, the key performances of various immunoassays are critically evaluated in terms of limit of detection, linear ranges, and incubation time for clinical translation. Electrochemical techniques coupled with screen-printed electrodes developing market level commercialization of NSE sensors is also discussed. Finally, the review concludes with the current challenges associated with available methods and provides a future outlook toward commercialization opportunities for easy detection of NSE.

CRISPR/Cas13a-mediated dual-modal biosensing platform based on the Zn0.5Cd0.5S/Ti3C2 Schottky heterojunction for the sensitive detection of miRNAs-21

MicroRNAs-21 (miRNAs-21), which promote tumor development and invasion by facilitating tumor cell proliferation and inhibiting apoptosis, is identified as a reliable biomarker for early cancer detection and prognosis. Herein, a CRISPR/Cas13a-mediated dual-modal biosensing platform was designed based on the Zn0.5Cd0.5S/Ti3C2 (ZCS/TC) Schottky heterojunction and implemented for monitoring miRNAs-21. Specifically, two-dimensional TC nanosheets with a large surface-to-volume ratio produced ample growth sites for the ZCS nanosphere. Moreover, the formation of Schottky heterojunctions at the ZCS/TC interface, validated by density functional theory calculations, can enhance their photoelectric conversion efficiency, providing a satisfactory initial signal for the subsequent implementation of a photoelectrochemical (PEC) biosensor. Furthermore, with the assistance of the MnO2-mediated CRISPR-Cas13a strategy, the dual-mode detection of miRNAs-21 was initiated via visualization and the use of the PEC biosensor. Under the optimized conditions, the linear range of the biosensor for detecting miRNAs-21 was 0.5 fM-1.0 nM and the detection limit was 0.21 fM. The developed platform can be used for the early detection and monitoring of various diseases, specifically cancer, and help create more research opportunities in this field.

Ultra-short cell-free DNA fragments enhance cancer early detection in a multi-analyte blood test combining mutation, protein and fragmentomics.

Cancer morbidity and mortality can be reduced if the cancer is detected early. Cell-free DNA (cfDNA) fragmentomics emerged as a novel epigenetic biomarker for early cancer detection, however, it is still at its infancy and requires technical improvement. We sought to apply a single-strand DNA sequencing technology, for measuring genetic and fragmentomic features of cfDNA and evaluate the performance in detecting multiple cancers. Blood samples of 364 patients from six cancer types (colorectal, esophageal, gastric, liver, lung, and ovarian cancers) and 675 healthy individuals were included in this study. Circulating tumor DNA mutations, cfDNA fragmentomic features and a set of protein biomarkers were assayed. Sensitivity and specificity were reported by cancer types and stages. Circular Ligation Amplification and sequencing (CLAmp-seq), a single-strand DNA sequencing technology, yielded a population of ultra-short fragments (<100 bp) than double-strand DNA preparation protocols and reveals a more significant size difference between cancer and healthy cfDNA fragments (25.84 bp vs. 16.05 bp). Analysis of the subnucleosomal peaks in ultra-short cfDNA fragments indicates that these peaks are regulatory element "footprints" and correlates with gene expression and cancer stages. At 98 % specificity, a prediction model using ctDNA mutations alone showed an overall sensitivity of 46 %; sensitivity reaches 60 % when protein is added, sensitivity further increases to 66 % when fragmentomics is also integrated. More improvements observed for samples representing earlier cancer stages than later ones. These results suggest synergistic properties of protein, genetic and fragmentomics features in the identification of early-stage cancers.

Breast cancer: miRNAs monitoring chemoresistance and systemic therapy.

With a high mortality rate that accounts for millions of cancer-related deaths each year, breast cancer is the second most common malignancy in women. Chemotherapy has significant potential in the prevention and spreading of breast cancer; however, drug resistance often hinders therapy in breast cancer patients. The identification and the use of novel molecular biomarkers, which can predict response to chemotherapy, might lead to tailoring breast cancer treatment. In this context, accumulating research has reported microRNAs (miRNAs) as potential biomarkers for early cancer detection, and are conducive to designing a more specific treatment plan by helping analyze drug resistance and sensitivity in breast cancer treatment. In this review, miRNAs are discussed in two alternative ways-as tumor suppressors to be used in miRNA replacement therapy to reduce oncogenesis and as oncomirs to lessen the translation of the target miRNA. Different miRNAs like miR-638, miR-17, miR-20b, miR-342, miR-484, miR-21, miR-24, miR-27, miR-23 and miR-200 are involved in the regulation of chemoresistance through diverse genetic targets. For instance, tumor-suppressing miRNAs like miR-342, miR-16, miR-214, and miR-128 and tumor-promoting miRNAs like miR101 and miR-106-25 cluster regulate the cell cycle, apoptosis, epithelial to mesenchymal transition and other pathways to impart breast cancer drug resistance. Hence, in this review, we have discussed the significance of miRNA biomarkers that could assist in providing novel therapeutic targets to overcome potential chemotherapy resistance to systemic therapy and further facilitate the design of tailored therapy for enhanced efficacy against breast cancer.

Pan-cancer detection and tissue-of-origin identification by whole-genome sequencing of plasma cell-free DNA.

3055 Background: Despite notable advances in cancer therapeutics, much of the mortality of human cancers results from late diagnosis. The early detection of cancer remains an unmet need that can benefit the effective treatments and better prognosis. Cell-free DNA (cfDNA) in the circulation provides an emerging diagnostic method for non-invasive cancer screening. The fragmentation signatures of cfDNA originating from different cell types or malignancies display distinct patterns, suggesting the potential as cancer biomarkers. This study aims to investigate the fragmentation profiles of cfDNA in several cancer types, and to develop a new approach for pan-cancer detection and tissue-of-origin identification. Methods: Plasma samples from 739 patients with lung (N=577), colorectal (N=98), breast (N=51) and liver (N=13) cancers, as well as 716 healthy individuals were collected in this study. Cell-free DNA was isolated and used to generate the whole-genome sequencing data. We developed an approach called PatternWGS (Pan-cancer detection and tissue-of-origin identification by whole-genome sequencing) to analyze the DNA fragmentation patterns comprehensively. Fragmentation features integrating cfDNA fragment size distribution, frequency of end motif sequence, and copy number variation were utilized to construct the optimal prediction model. We presented a multi-cancer detection model for distinguishing individuals with and without cancer using Generalized Linear Models (glmnet), and further built a cancer-origin model to predict cancer types using Random Forest algorithm. Training and testing occurred on randomly selected sampling splits of 60% and 40% of the data, respectively. Features selection and model construction were performed by only training cohort, and the test set was solely used for performance evaluation. Results: A larger proportion of shorter cfDNA fragments in cancers was observed. We proposed a fragment score indicating the degree of short fragmentation, and this fragment score was significantly higher in cancers (p&lt;0.001). Several end motifs were identified to be specifically enriched in cancer patients. The multi-cancer detection model reached an area under the curve (AUC) of 0.98, with the sensitivity of 93% at 95% specificity. The sensitivity of detecting lung, colorectal, breast, and liver cancers reached 94.2%, 87%, 100% and 100% respectively, at 95% specificity. The cancer-origin model demonstrated an overall accuracy of 81.7% for the identification of tissue of origin. Conclusions: Our prediction model demonstrated a superior performance for multi-cancer detection and cancer origin prediction, suggesting the potential of plasma cfDNA fragmentation signatures as non-invasive biomarkers for early cancer detection in clinical. The distinct fragmentation patterns in cancer provide new insight to understand the mechanism of tumorigenesis.