Blood-based liquid biopsy: Insights into early detection and clinical management of lung cancer

Circ_0006949 as a potential non-invasive diagnosis biomarker promotes the proliferation of NSCLC cells via miR-4673/GLUL axis

The 5-year survival for non-small cell lung cancer (NSCLC) remains <20 %, primarily due to the early symptoms of lung cancer are inconspicuous. Prompt identification and medical intervention could serve as effective strategies for mitigating the death rate. We therefore set out to identify biomarkers to help diagnose NSCLC. CircRNA microarray and qRT-PCR reveal that sputum circ_0006949 is a potential biomarker for the early diagnosis and therapy of NSCLC, which can enhance the proliferation and clone formation, regulate the cell cycle, and accelerate the migration and invasion of NSCLC cells. Circ_0006949 and miR-4673 are predominantly co-localized in the cytoplasm of NSCLC cell lines and tissues; it upregulates GLUL by adsorption of miR-4673 through competing endogenous RNAs mechanism. The circ_0006949/miR-4673/GLUL axis exerts pro-cancer effects in vitro and in vivo. Circ_0006949 can boost GLUL catalytic activity, and they are highly expressed in NSCLC tissues and correlate with poor prognosis. In summary, circ_0006949 is a potential biomarker for the early diagnosis and therapy of NSCLC. This novel sputum circRNA is statistically more predictive than conventional serum markers for NSCLC diagnosis. Non-invasive detection of patients with early-stage NSCLC using sputum has shown good potential for routine diagnosis and possible screening.

Deep volcanic residual U-Net for nodal metastasis (Nmet) identification from lung cancer

Lymph node metastasis detections are more clinically significant task associated with the presence and reappearance of lung cancer. The development of the computer-assisted diagnostic approach has greatly supported the diagnosis of human disorders in the field of medicine including lung cancer. Lung cancer treatment is possible if it is detected at the initial stage. Radiologists have great difficulty identifying and categorizing lung cancers in the initial phase. So, several methods were used to predict the lung cancer but does not provide accurate solutions with increased error rate. To overcome these issues, a Deep Volcanic Residual U-Net (DVR U-Net) for nodal metastasis is proposed in this manuscript which identifies the LC accurately in the early stage. Initially, the input images are taken from two datasets. After that, these input data are pre-processed using Anisotropic Diffusion Filter with a Fuzzy based Contrast-Limited Adaptive Histogram Equalization (ADFFCLAHE) method. Then the pre-processed images are given to the DVR U-Net to segment and extract the volume of interest for estimating the nodal stage of each volume of interest. Finally, DVR U-Net effectively detects and classifies the N + (nodal metastasis) or N- (non-nodal metastasis). The introduced method attains 99.9% higher accuracy as compared with the existing methods. Also, the statistical analysis of the Shapiro-Wilk test, Friedman test and Wilcoxon Signed-Rank test are executed to prove the statistical effectiveness of the implemented method.

Comparative study on genomic and epigenomic profiles of retinoblastoma or tuberous sclerosis complex via nanopore sequencing and a joint screening framework

Recurrence and extraocular metastasis in advanced intraocular retinoblastoma (RB) are still major obstacles for successful treatment of Chinese children. Tuberous sclerosis complex (TSC) is a very rare, multisystemic genetic disorder characterized by hamartomatous growth. In this study, we aimed to compare genomic and epigenomic profiles with human RB or TSC using recently developed nanopore sequencing, and to identify disease-associated variations or genes. Peripheral blood samples were collected from either RB or RB/TSC patients plus their normal siblings, followed by nanopore sequencing and identification of disease-specific structural variations (SVs) and differentially methylated regions (DMRs) by a systematic biology strategy named as multiomics-based joint screening framework. In total, 316 RB- and 1295 TSC-unique SVs were identified, as well as 1072 RB- and 1114 TSC-associated DMRs, respectively. We eventually identified 6 key genes for RB for further functional validation. Knockdown of CDK19 with specific siRNAs significantly inhibited Y79 cellular proliferation and increased sensitivity to carboplatin, whereas downregulation of AHNAK2 promoted the cell growth as well as drug resistance. Those two genes might serve as potential diagnostic markers or therapeutic targets of RB. The systematic biology strategy combined with functional validation might be an effective approach for rare pediatric malignances with limited samples and challenging collection process.

Epigenetic regulation of pulmonary inflammation

Pulmonary disease such as chronic obstructive pulmonary disease (COPD), asthma, pulmonary fibrosis and pulmonary hypertension are the leading cause of deaths. More importantly, lung diseases are on the rise and environmental factors induced epigenetic modifications are major players on this increased prevalence. It has been reported that dysregulation of genes involved in epigenetic regulation such as the histone deacetylase (HDACs) and histone acetyltransferase (HATs) play important role in lung health and pulmonary disease pathogenesis. Inflammation is an essential component of respiratory diseases. Injury and inflammation trigger release of extracellular vesicles that can act as epigenetic modifiers through transfer of epigenetic regulators such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), proteins and lipids, from one cell to another. The immune dysregulations caused by the cargo contents are important contributors of respiratory disease pathogenesis. N6 methylation of RNA is also emerging to be a critical mechanism of epigenetic alteration and upregulation of immune responses to environmental stressors. Epigenetic changes such as DNA methylation are stable and often long term and cause onset of chronic lung conditions. These epigenetic pathways are also being utilized for therapeutic intervention in several lung conditions.

Radiomics and artificial intelligence for risk stratification of pulmonary nodules: Ready for primetime?

Pulmonary nodules are ubiquitously found on computed tomography (CT) imaging either incidentally or via lung cancer screening and require careful diagnostic evaluation and management to both diagnose malignancy when present and avoid unnecessary biopsy of benign lesions. To engage in this complex decision-making, clinicians must first risk stratify pulmonary nodules to determine what the best course of action should be. Recent developments in imaging technology, computer processing power, and artificial intelligence algorithms have yielded radiomics-based computer-aided diagnosis tools that use CT imaging data including features invisible to the naked human eye to predict pulmonary nodule malignancy risk and are designed to be used as a supplement to routine clinical risk assessment. These tools vary widely in their algorithm construction, internal and external validation populations, intended-use populations, and commercial availability. While several clinical validation studies have been published, robust clinical utility and clinical effectiveness data are not yet currently available. However, there is reason for optimism as ongoing and future studies aim to target this knowledge gap, in the hopes of improving the diagnostic process for patients with pulmonary nodules.

Construction of a risk stratification model integrating ctDNA to predict response and survival in neoadjuvant-treated breast cancer

BACKGROUND

The pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) of breast cancer is closely related to a better prognosis. However, there are no reliable indicators to accurately identify which patients will achieve pCR before surgery, and a model for predicting pCR to NAC is required.

METHODS

A total of 269 breast cancer patients in Shandong Cancer Hospital and Liaocheng People's Hospital receiving anthracycline and taxane-based NAC were prospectively enrolled. Expression profiling using a 457 cancer-related gene sequencing panel (DNA sequencing) covering genes recurrently mutated in breast cancer was carried out on 243 formalin-fixed paraffin-embedded tumor biopsies samples before NAC from 243 patients. The unique personalized panel of nine individual somatic mutation genes from the constructed model was used to detect and analyze ctDNA on 216 blood samples. Blood samples were collected at indicated time points including before chemotherapy initiation, after the 1st NAC and before the 2nd NAC cycle, during intermediate evaluation, and prior to surgery. In this study, we characterized the value of gene profile mutation and circulating tumor DNA (ctDNA) in combination with clinical characteristics in the prediction of pCR before surgery and investigated the prognostic prediction. The median follow-up time for survival analysis was 898 days.

RESULTS

Firstly, we constructed a predictive NAC response model including five single nucleotide variant (SNV) mutations (TP53, SETBP1, PIK3CA, NOTCH4 and MSH2) and four copy number variation (CNV) mutations (FOXP1-gain, EGFR-gain, IL7R-gain, and NFKB1A-gain) in the breast tumor, combined with three clinical factors (luminal A, Her2 and Ki67 status). The tumor prediction model showed good discrimination of chemotherapy sensitivity for pCR and non-pCR with an AUC of 0.871 (95% CI, 0.797-0.927) in the training set, 0.771 (95% CI, 0.649-0.883) in the test set, and 0.726 (95% CI, 0.556-0.865) in an extra test set. This tumor prediction model can also effectively predict the prognosis of disease-free survival (DFS) with an AUC of 0.749 at 1 year and 0.830 at 3 years. We further screened the genes from the tumor prediction model to establish a unique personalized panel consisting of 9 individual somatic mutation genes to detect and analyze ctDNA. It was found that ctDNA positivity decreased with the passage of time during NAC, and ctDNA status can predict NAC response and metastasis recurrence. Finally, we constructed the chemotherapy prediction model combined with the tumor prediction model and pretreatment ctDNA levels, which has a better prediction effect of pCR with the AUC value of 0.961.

CONCLUSIONS

In this study, we established a chemotherapy predictive model with a non-invasive tool that is built based on genomic features, ctDNA status, as well as clinical characteristics for predicting pCR to recognize the responders and non-responders to NAC, and also predicting prognosis for DFS in breast cancer. Adding pretreatment ctDNA levels to a model containing gene profile mutation and clinical characteristics significantly improves stratification over the clinical variables alone.

Hypoxia-induced circ-CDYL-EEF1A2 transcriptional complex drives lung metastasis of cancer stem cells from hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is often associated with poor outcomes due to lung metastasis. ICAM-1+ circulating tumor cells, termed circulating cancer stem cells (CCSCs), possess stem cell-like characteristics. However, it is still unexplored how their presence indicates lung metastasis tendency, and particularly, what mechanism drives their lung metastasis. Here, we demonstrated that a preoperative CCSC count in 5 mL of blood (CCSC5) of >3 was a risk factor for lung metastasis in clinical HCC patients. The CSCs overexpressed with circ-CDYL entered the bloodstream and developed lung metastases in mice. Mechanistically, circ-CDYL promoted COL14A1 expression and thus ERK signaling to facilitate epithelial-mesenchymal transition. Furthermore, we uncovered that an RNA-binding protein, EEF1A2, acted as a novel transcriptional (co-) factor to cooperate with circ-CDYL and initiate COL14A1 transcription. A high circ-CDYL level is caused by HIF-1⍺-mediated transcriptional upregulation of its parental gene CDYL and splicing factor EIF4A3 under a hypoxia microenvironment. Hence, the hypoxia microenvironment enables the high-tendency lung metastasis of ICAM-1+ CCSCs through the HIF-1⍺/circ-CDYL-EEF1A2/COL14A1 axis, potentially allowing clinicians to preoperatively detect ICAM-1+ CCSCs as a real-time biomarker for precisely deciding HCC treatment strategies.

Bio-Impedance Spectroscopy of Retained Cells Using a Micro-Perforated Sensing Membrane Filtrating Whole Blood Samples under High Flowrate

Blood filtration using micro-fabricated devices is an interdisciplinary topic of research and innovation driven by clinical applications in cytapheresis, cardiovascular disease monitoring, or liquid biopsy. In this paper, we demonstrate that a micro-perforated membrane can be equipped with sensing microelectrodes for detecting, in situ and in real-time, the capture of cellular material during ex vivo filtration of whole blood under high flow rates. This work describes the fabrication process of the sift and detection microdevice. We demonstrate that reliable electrical signals can be measured in whole blood samples flowing inside a fluidic system at typical flow rates, as large as 11.5 mL/min, hence allowing for large-volume sample processing. The in situ monitoring of the electrical impedance of the microelectrodes is shown to characterize the accumulation of living circulating cells retained by the filtrating membrane, opening interesting applications for monitoring blood filtration processes.

The Liquid Biopsy Consortium: Challenges and opportunities for early cancer detection and monitoring

The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.

A three-stage eccDNA based molecular profiling significantly improves the identification, prognosis assessment and recurrence prediction accuracy in patients with glioma

Glioblastoma (GBM) progression is influenced by intratumoral heterogeneity. Emerging evidence has emphasized the pivotal role of extrachromosomal circular DNA (eccDNA) in accelerating tumor heterogeneity, particularly in GBM. However, the eccDNA landscape of GBM has not yet been elucidated. In this study, we first identified the eccDNA profiles in GBM and adjacent tissues using circle- and RNA-sequencing data from the same samples. A three-stage model was established based on eccDNA-carried genes that exhibited consistent upregulation and downregulation trends at the mRNA level. Combinations of machine learning algorithms and stacked ensemble models were used to improve the performance and robustness of the three-stage model. In stage 1, a total of 113 combinations of machine learning algorithms were constructed and validated in multiple external cohorts to accurately distinguish between low-grade glioma (LGG) and GBM in patients with glioma. The model with the highest area under the curve (AUC) across all cohorts was selected for interpretability analysis. In stage 2, a total of 101 combinations of machine learning algorithms were established and validated for prognostic prediction in patients with glioma. This prognostic model performed well in multiple glioma cohorts. Recurrent GBM is invariably associated with aggressive and refractory disease. Therefore, accurate prediction of recurrence risk is crucial for developing individualized treatment strategies, monitoring patient status, and improving clinical management. In stage 3, a large-scale GBM cohort (including primary and recurrent GBM samples) was used to fit the GBM recurrence prediction model. Multiple machine learning and stacked ensemble models were fitted to select the model with the best performance. Finally, a web tool was developed to facilitate the clinical application of the three-stage model.

Optimal isolation of extracellular vesicles from pleural fluid and profiling of their microRNA cargo

Pleural effusion occurs in both benign and malignant pleural disease. In malignant pleural effusions, the diagnostic accuracy and sensitivity of pleural fluid cytology is less than perfect, particularly for the diagnosis of malignant pleural mesothelioma, but also in some cases for the diagnosis of metastatic pleural malignancy with primary cancer in the lung, breast or other sites. Extracellular vesicles (EVs) carry an enriched cargo of microRNAs (miRNAs) which are selectively packaged and differentially expressed in pleural disease states. To investigate the diagnostic potential of miRNA cargo in pleural fluid extracellular vesicles (PFEVs), we evaluated methods for isolating the extracellular vesicle (EV) fraction including combinations of ultracentrifugation, size-exclusion chromatography (SEC) and ultrafiltration (10 kDa filter unit). PFEVs were characterized by total and EV-associated protein, nanoparticle tracking analysis and visualisation by transmission electron microscopy. miRNA expression was analyzed by Nanostring nCounter® in separate EV fractions isolated from pleural fluid with or without additional RNA purification by ultrafiltration (3 kDa filter unit). Optimal PFEV yield, purity and miRNA expression were observed when PFEV were isolated from a larger volume of pleural fluid processed through combined ultracentrifugation and SEC techniques. Purification of total RNA by ultrafiltration further enhanced the detectability of PFEV miRNAs. This study demonstrates the feasibility of isolating PFEVs, and the potential to examine PFEV miRNA cargo using Nanostring technology to discover disease biomarkers.

Extranodal lymphoma: pathogenesis, diagnosis and treatment

Approximately 30% of lymphomas occur outside the lymph nodes, spleen, or bone marrow, and the incidence of extranodal lymphoma has been rising in the past decade. While traditional chemotherapy and radiation therapy can improve survival outcomes for certain patients, the prognosis for extranodal lymphoma patients remains unsatisfactory. Extranodal lymphomas in different anatomical sites often have distinct cellular origins, pathogenic mechanisms, and clinical manifestations, significantly influencing their diagnosis and treatment. Therefore, it is necessary to provide a comprehensive summary of the pathogenesis, diagnosis, and treatment progress of extranodal lymphoma overall and specifically for different anatomical sites. This review summarizes the current progress in the common key signaling pathways in the development of extranodal lymphomas and intervention therapy. Furthermore, it provides insights into the pathogenesis, diagnosis, and treatment strategies of common extranodal lymphomas, including gastric mucosa-associated lymphoid tissue (MALT) lymphoma, mycosis fungoides (MF), natural killer/T-cell lymphoma (nasal type, NKTCL-NT), and primary central nervous system lymphoma (PCNSL). Additionally, as PCNSL is one of the extranodal lymphomas with the worst prognosis, this review specifically summarizes prognostic indicators and discusses the challenges and opportunities related to its clinical applications. The aim of this review is to assist clinical physicians and researchers in understanding the current status of extranodal lymphomas, enabling them to make informed clinical decisions that contribute to improving patient prognosis.

Advances in novel strategies for isolation, characterization, and analysis of CTCs and ctDNA

Over the past decade, the detection and analysis of liquid biopsy biomarkers such as circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) have advanced significantly. They have received recognition for their clinical usefulness in detecting cancer at an early stage, monitoring disease, and evaluating treatment response. The emergence of liquid biopsy has been a helpful development, as it offers a minimally invasive, rapid, real-time monitoring, and possible alternative to traditional tissue biopsies. In resource-limited settings, the ideal platform for liquid biopsy should not only extract more CTCs or ctDNA from a minimal sample volume but also accurately represent the molecular heterogeneity of the patient's disease. This review covers novel strategies and advancements in CTC and ctDNA-based liquid biopsy platforms, including microfluidic applications and comprehensive analysis of molecular complexity. We discuss these systems' operational principles and performance efficiencies, as well as future opportunities and challenges for their implementation in clinical settings. In addition, we emphasize the importance of integrated platforms that incorporate machine learning and artificial intelligence in accurate liquid biopsy detection systems, which can greatly improve cancer management and enable precision diagnostics.

Longitudinal detection of subcategorized CD44v6+ CTCs and circulating tumor endothelial cells (CTECs) enables novel clinical stratification and improves prognostic prediction of small cell lung cancer: A prospective, multi-center study

Current management of small cell lung cancer (SCLC) remains challenging. Effective biomarkers are needed to subdivide patients presenting distinct treatment response and clinical outcomes. An understanding of heterogeneous phenotypes of aneuploid CD31- circulating tumor cells (CTCs) and CD31+ circulating tumor endothelial cells (CTECs) may provide novel insights in the clinical management of SCLC. In the present translational and prospective study, increased cancer metastasis-related cell proliferation and motility, accompanied with up-regulated mesenchymal marker vimentin but down-regulated epithelial marker E-cadherin, were observed in both lentivirus infected SCLC and NSCLC cells overexpressing the stemness marker CD44v6. Aneuploid CTCs and CTECs expressing CD44v6 were longitudinally detected by SE-iFISH in 120 SCLC patients. Positive detection of baseline CD44v6+ CTCs and CD44v6+ CTECs was significantly associated with enhanced hepatic metastasis. Karyotype analysis revealed that chromosome 8 (Chr8) in CD44v6+ CTCs shifted from trisomy 8 towards multiploidy in post-therapeutic patients compared to pre-treatment subjects. Furthermore, the burden of baseline CD44v6+ CTCs (t0) or amid the therapy (t1-2), the ratio of baseline CD31+ CTEC/CD31- CTC (t0), and CTC-WBC clusters (t0) were correlated with treatment response and distant metastases, particularly brain metastasis, in subjects with limited disease (LD-SCLC) but not in those with extensive disease (ED-SCLC). Multivariate survival analysis validated that longitudinally detected CD44v6+/CD31- CTCs was an independent prognostic factor for inferior survival in SCLC patients. Our study provides evidence for the first time that comprehensive analyses of CTCs, CTECs, and their respective CD44v6+ subtypes enable clinical stratification and improve prognostic prediction of SCLC, particularly for potentially curable LD-SCLC.

Testing the generalizability of cfDNA fragmentomic features across different studies for cancer early detection

cfDNA fragmentomic features have been used in cancer detection models; however, the generalizability of the models needs to be tested. We proposed a type of cfDNA fragmentomic feature named chromosomal arm-level fragment size distribution (ARM-FSD), evaluated and compared its performance and generalizability for lung cancer and pan-cancer detection with existing cfDNA fragmentomic features (as reference) by using cohorts from different institutions. The ARM-FSD lung cancer model outperformed the reference model by ∼10% when being tested by two external cohorts (AUC: 0.97 vs. 0.86; 0.87 vs. 0.76). For pan-cancer detection, the performance of the ARM-FSD based model is consistently higher than the reference (AUC: 0.88 vs. 0.75, 0.98 vs. 0.63) in a pan-cancer and a lung cancer external validation cohort, indicating that ARM-FSD model produces stable performance across multiple cohorts. Our study reveals ARM-FSD based models have a higher generalizability, and highlights the necessity of cross-study validation for predictive model development.

Preoperative Mutational Analysis of Circulating Tumor Cells (CTCs) and Plasma-cfDNA Provides Complementary Information for Early Prediction of Relapse: A Pilot Study in Early-Stage Non-Small Cell Lung Cancer

PURPOSE

We assessed whether preoperativemutational analyses of circulating tumor cells (CTCs) and plasma-cfDNA could be used as minimally invasive biomarkers and as complimentary tools for early prediction of relapse in early-stage non-small -cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

Using ddPCR assays, hotspot mutations of BRAF, KRAS, EGFR and PIK3CA were identified in plasma-cfDNA samples and size-based enriched CTCs isolated from the same blood samples of 49 early-stage NSCLC patients before surgery and in a control group of healthy blood donors (n= 22). Direct concordance of the mutational spectrum was further evaluated in 27 patient-matched plasma-cfDNA and CTC-derived DNA in comparison to tissue-derived DNA.

RESULTS

The prevalence of detectable mutations of the four tested genes was higher in CTC-derived DNA than in the corresponding plasma-cfDNA (38.8% and 24.5%, respectively).The most commonly mutated gene was PIK3CA, in both CTCs and plasma-cfDNA at baseline and at the time of relapse. Direct comparison of the mutation status of selected drug-responsive genes in CTC-derived DNA, corresponding plasma-cfDNA and paired primary FFPE tissues clearly showed the impact of heterogeneity both within a sample type, as well as between different sample components. The incidence of relapse was higher when at least one mutation was detected in CTC-derived DNA or plasma-cfDNA compared with patients in whom no mutation was detected (p =0.023). Univariate analysis showed a significantly higher risk of progression (HR: 2.716; 95% CI, 1.030-7.165; p =0.043) in patients with detectable mutations in plasma-cfDNA compared with patients with undetectable mutations, whereas the hazard ratio was higher when at least one mutation was detected in CTC-derived DNA or plasma-cfDNA (HR: 3.375; 95% CI, 1.098-10.375; p =0.034).

CONCLUSIONS

Simultaneous mutational analyses of plasma-cfDNA and CTC-derived DNA provided complementary molecular information from the same blood sample and greater diversity in genomic information for cancer treatment and prognosis. The detection of specific mutations in ctDNA and CTCs in patients with early-stage NSCLC before surgery was independently associated with disease recurrence, which represents an important stratification factor for future trials.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

The critical role of serum thymidine kinase 1(STK1) in predicting prognosis for immunotherapy in T4 stage lung squamous cell carcinoma

Purpose

The role of serum thymidine kinase 1 (STK1) in predicting the prognosis of T4-stage lung squamous cell carcinoma (LUSC) with immunotherapy is the focus of our work.

Methods

A total of 180 LUSC patients were enrolled. In this study, according to the T stage, the patients were divided into two groups: the T1-T2 stage and the T3-T4 stage. Receiver operating characteristic (ROC) curves were used to determine the best cutoff value for predicting overall survival (OS) outcomes. The next step is to use this cutoff value to introduce univariate and multivariate Cox regression models to screen the prognostic factors in different T stages of LUSC. The association of STK1 with other clinicopathological factors was also determined. Finally, to further explore the link between STK1 and the staging of LUSC patients, we have further divided the staging into T1-3 and T4 stages. We identified factors influencing the prognosis of patients who received immunotherapy in T4 stage LUSC.

Results

First, we determined that the optimal cutoff for STK1 for predicting OS outcome was 1.165 pmol/L. Correlation analysis revealed that STK1 was over-expressed in LUSC patients at the T3-4 stage. Univariate and multivariate analysis showed that immunotherapy was an independent prognostic factor in patients with T4 stage LUSC. In the group of patients who received immunotherapy or not, the STK1 expression level was found to be an independent prognostic factor in T4 LUSC patients receiving PD-1/PD-L1 inhibitor treatment; patients with high levels of STK1 had an increased risk of death (95%CI = 1.028-2.04).

Conclusion

STK1 is associated with a higher T stage and may be an effective prognostic marker for advanced LUSC immunotherapy patients.

Clinical Scores, Biomarkers and IT Tools in Lung Cancer Screening-Can an Integrated Approach Overcome Current Challenges?

As most lung cancer (LC) cases are still detected at advanced and incurable stages, there are increasing efforts to foster detection at earlier stages by low dose computed tomography (LDCT) based LC screening. In this scoping review, we describe current advances in candidate selection for screening (selection phase), technical aspects (screening), and probability evaluation of malignancy of CT-detected pulmonary nodules (PN management). Literature was non-systematically assessed and reviewed for suitability by the authors. For the selection phase, we describe current eligibility criteria for screening, along with their limitations and potential refinements through advanced clinical scores and biomarker assessments. For LC screening, we discuss how the accuracy of computerized tomography (CT) scan reading might be augmented by IT tools, helping radiologists to cope with increasing workloads. For PN management, we evaluate the precision of follow-up scans by semi-automatic volume measurements of CT-detected PN. Moreover, we present an integrative approach to evaluate the probability of PN malignancy to enable safe decisions on further management. As a clear limitation, additional validation studies are required for most innovative diagnostic approaches presented in this article, but the integration of clinical risk models, current imaging techniques, and advancing biomarker research has the potential to improve the LC screening performance generally.

Secreted proteins MDK, WFDC2, and CXCL14 as candidate biomarkers for early diagnosis of lung adenocarcinoma

BACKGROUND

Early diagnosis of lung adenocarcinoma (LUAD), one of the most common types of lung cancer, is very important to improve the prognosis of patients. The current methods can't meet the requirements of early diagnosis. There is a pressing need to identify novel diagnostic biomarkers. Secretory proteins are the richest source for biomarker research. This study aimed to identify candidate secretory protein biomarkers for early diagnosis of LUAD by integrated bioinformatics analysis and clinical validation.

METHODS

Differentially expressed genes (DEGs) of GSE31210, gene expression data of early stage of LUAD, were analyzed by GEO2R. Upregulated DEGs predicted to encode secreted proteins were obtained by taking the intersection of the DEGs list with the list of genes encoding secreted proteins predicted by the majority decision-based method (MDSEC). The expressions of the identified secreted proteins in the lung tissues of early-stage LUAD patients were further compared with the healthy control group in mRNA and protein levels by using the UALCAN database (TCGA and CPTAC). The selected proteins expressed in plasma were further validated by using Luminex technology. The diagnostic value of the screened proteins was evaluated by receiver operating characteristic (ROC) analysis. Cell counting kit-8 assay was carried out to investigate the proliferative effects of these screened proteins.

RESULTS

A total of 2183 DEGs, including 1240 downregulated genes and 943 upregulated genes, were identified in the GSE31210. Of the upregulated genes, 199 genes were predicted to encode secreted proteins. After analysis using the UALCAN database, 16 molecules were selected for further clinical validation. Plasma concentrations of three proteins, Midkine (MDK), WAP four-disulfide core domain 2 (WFDC2), and C-X-C motif chemokine ligand 14 (CXCL14), were significantly higher in LUAD patients than in healthy donors. The area under the curve values was 0.944, 0.881, and 0.809 for MDK, WFDC2, and CXCL14, 0.962 when combined them. Overexpression of the three proteins enhanced the proliferation activity of A549 cells.

CONCLUSIONS

MDK, WFDC2, and CXCL14 were identified as candidate diagnostic biomarkers for early-stage LUAD and might also play vital roles in tumorigenesis.

Chemical Cyclic Amplification: Hydroxylamine Boosts the Fenton Reaction for Versatile and Scalable Biosensing

Nucleic acid detection is undoubtedly one of the most important research fields to meet the medical needs of genetic disease diagnosis, cancer treatment, and infectious disease prevention. However, the practical detection methods based on biological amplification are complex and time-consuming and require highly trained operators. Herein, we report a simple, rapid, and sensitive method for the nucleic acid assay by fluorescence or naked eye using chemical cyclic amplification. The addition of hydroxylamine (HA) during the Fenton reaction can continuously generate hydroxyl radicals (^•OH) via Fe³⁺/Fe²⁺ cycle, termed as "hydroxylamine boosts the Fenton reaction (Fenton-HA system)". Meanwhile, the reducing substances, such as terephthalic acid or o-phenylenediamine, react with ^•OH to generate oxidized substances that can be recognized by the naked eye or detected by fluorescence so as to realize the detection of Fe³⁺. The concentration of Fe³⁺ has a good linear relationship with fluorescence intensity in the range of 0.1 to 100 nM, and the limit of detection is calculated to be 0.03 nM (S/N = 3). Subsequently, Fe was introduced into the nucleic acid hybridization system after the Fe source was transformed into Fe³⁺, and the nucleic acids were indirectly determined by this method. This Fenton-HA system was used for sensing HIV-DNA and miRNA-21 to verify the validity of this method in nucleic acid detection. The detection limits were as low as 2.5 pM for HIV-DNA and 3 pM for miRNA-21. We believe that our work has unlocked an efficient signal amplification strategy, which is expected to develop a new generation of highly sensitive chemical biosensors.

Influencing factors of LDCT recommendation by physicians in Sichuan Province, China

The study aimed to investigate the influencing factors of physicians in recommending low-dose computed tomography (LDCT) for lung cancer screening to high-risk groups. A total of 1767 participants with good knowledge of LDCT were included in a cross-sectional study. Data about physicians' demographics, perception of barriers on LDCT screening, medical conditions for practicing medicine and the behavior of recommending LDCT were collected by a questionnaire. Physicians who care about the transportation convenience of patients were less likely to recommend LDCT (OR 0.568, 95% CI (0.423 to 0.763), p < 0.05). The physicians who considered LDCT expensive, recommended LDCT less than others (OR 0.308, 95% CI (0.186 to 0.510), p < 0.05). The false positive rate of LDCT can decrease the possibility of physicians' recommending (OR 0.542, 95% CI (0.387 to 0.758), p < 0.05). The physicians in oncology department and health management center were more likely to recommend LDCT (OR 2.282, 95% CI (1.557 to 3.345); OR 2.476, 95% CI (1.618 to 3.791)). The convenience of transportation, the price, and the\ false positive rate may be the main concerns among physicians on recommending LDCT to high-risk groups. The influencing factors of physicians' recommending on LDCT was various. Information technology, government support in price and self-improvement of LDCT should be gathered together to break the barriers on physicians' recommending on LDCT.

Natural flavonoids exhibit potent anticancer activity by targeting microRNAs in cancer: A signature step hinting towards clinical perfection

Cancer prevalence and its rate of incidence are constantly rising since the past few decades. Owing to the toxicity of present-day antineoplastic drugs, it is imperative to explore safer and more effective molecules to combat and/or prevent this dreaded disease. Flavonoids, a class of polyphenols, have exhibited multifaceted implications against several diseases including cancer, without showing significant toxicity towards the normal cells. Shredded pieces of evidence suggest that flavonoids can enhance drug sensitivity and suppress proliferation, metastasis, and angiogenesis of cancer cells by modulating several oncogenic or oncosuppressor microRNAs (miRNAs, miRs). They play pivotal roles in regulation of various biological and pathological processes, including various cancers. In the present review, the structure, chemistry and miR targeting efficacy of quercetin, luteolin, silibinin, genistein, epigallocatechin gallate, and cyanidin against several cancer types are comprehensively discussed. miRs are considered as next-generation medicine of recent times, and their targeting by naturally occurring flavonoids in cancer cells could be deemed as a signature step. We anticipate that our compilations related to miRNA-mediated regulation of cancer cells by flavonoids might catapult the clinical investigations and affirmation in the future.

The Prognostic Value of the Circulating Tumor Cell-Based Four mRNA Scoring System: A New Non-Invasive Setting for the Management of Bladder Cancer

Bladder cancer (BC) is one of the most expensive lifetime cancers to treat because of the high recurrence rate, repeated surgeries, and long-term cystoscopy monitoring and treatment. The lack of an accurate classification system predicting the risk of recurrence or progression leads to the search for new biomarkers and strategies. Our pilot study aimed to identify a prognostic gene signature in circulating tumor cells (CTCs) isolated by ScreenCell devices from muscle invasive and non-muscle invasive BC patients. Through the PubMed database and Cancer Genome Atlas dataset, a panel of 15 genes modulated in BC with respect to normal tissues was selected. Their expression was evaluated in CTCs and thanks to the univariate and multivariate Cox regression analysis, EGFR, TRPM4, TWIST1, and ZEB1 were recognized as prognostic biomarkers. Thereafter, by using the risk score model, we demonstrated that this 4-gene signature significantly grouped patients into high- and low-risk in terms of recurrence free survival (HR = 2.704, 95% CI = 1.010−7.313, Log-rank p < 0.050). Overall, we identified a new prognostic signature that directly impacted the prediction of recurrence, improving the choice of the best treatment for BC patients.

Rapid Capturing and Chemiluminescent Sensing of Programmed Death Ligand-1 Expressing Extracellular Vesicles

Cancer specific extracellular vesicles (EVs) are of significant clinical relevance, for instance programmed death ligand-1 (PD-L1) expressing EVs (PD-L1@EVs) have been shown to be ideal biomarker for non-invasive diagnosis of cancer and can predate the response of cancer patients to anti-PD-1/PD-L-1 immunotherapy. The development of sensitive and straightforward methods for detecting PD-L1@EVs can be a vital tool for non-invasive diagnosis of cancer. Most of the contemporary methods for EVs detection have limitations such as involvement of long and EV’s loss prone isolation methods prior to detection or they have employed expensive antibodies and instruments to accomplish detection. Therefore, we designed an ultracentrifugation-free and antibody-free sensing assay for PD-L1@EV by integrating Titanium oxide (TiO2) coated magnetic beads (Fe3O4@TiO2) rapid capturing of EVs from undiluted serum with aptamers specificity and chemiluminescence (CL) sensitivity. To accomplish this we used Fe3O4@TiO2 beads to rapidly capture EVs from the undiluted patient serum and added biotin labelled PD-L1 aptamer to specifically recognize PD-L1@EVs. Later, added streptavidin-modified Alkaline phosphates (ALP) taking advantage of biotin-streptavidin strong binding. Addition of CDP-star, a chemiluminescent substrate of ALP, initiates the chemiluminiscense that was recorded using spectrophotometer. The sensing assay showed high sensitivity with limit of detection (LOD) as low as 2.584×105 EVs/mL and a wider linear correlation of CL intensity (a.u.) with the concentration of PD-L1@EVs from 105 to 108 EVs/mL. To examine the clinical utility of sensing assay we used undiluted serum samples from lung cancer patients and healthy individuals and successfully discern between healthy individuals and lung cancer patients. We are optimistic that the sensing assay can ameliorate our ability to be able to diagnose lung cancer non-invasively and can be helpful to predate the patient’s response to anti-PD-1/PD-L1 immunotherapy.

Microfluidic Approaches and Methods Enabling Extracellular Vesicle Isolation for Cancer Diagnostics

Advances in cancer research over the past half-century have clearly determined the molecular origins of the disease. Central to the use of molecular signatures for continued progress, including rapid, reliable, and early diagnosis is the use of biomarkers. Specifically, extracellular vesicles as biomarker cargo holders have generated significant interest. However, the isolation, purification, and subsequent analysis of these extracellular vesicles remain a challenge. Technological advances driven by microfluidics-enabled devices have made the challenges for isolation of extracellular vesicles an emerging area of research with significant possibilities for use in clinical settings enabling point-of-care diagnostics for cancer. In this article, we present a tutorial review of the existing microfluidic technologies for cancer diagnostics with a focus on extracellular vesicle isolation methods.

Mendelian Randomization Study of Causal Relationship between Omega-3 Fatty Acids and Risk of Lung Cancer

Objective

Evidence suggests that omega-3 fatty acid intake exerts a protective effect on lung cancer, but its causal association with risk of lung cancer remains uncertain. This study attempts to clarify the causal effect of omega-3 fatty acids on lung cancer utilizing genome-wide association study (GWAS) data with Mendelian randomization (MR) approach.

Methods

This study acquired omega-3 fatty acid data from the UK Biobank and data of lung cancer patients from the Consortium and International Lung Cancer Consortium (ILCCO). Single-nucleotide polymorphisms (SNPs) associated with omega-3 fatty acids were screened as instrumental variables (IVs) in line with the criteria of p < 5E - 8, linkage disequilibrium R ² > 0.001 and distance < 10000 kb. Through inverse variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode, causal association between omega-3 fatty acids and risk of lung cancer was evaluated. Cochran's Q test was applied for a heterogeneity test. The pleiotropy and horizontal pleiotropy among IVs were evaluated via MR-Egger regression intercept analysis.

Results

Totally, 42 SNPs associated with omega-3 fatty acids were identified as IVs. According to the results of IVW (OR (95% CI): 0.899 (0.817, 0.990), p = 0.03), MR-Egger (OR (95% CI): 0.856 (0.750, 0.977), p = 0.026), weighted median (OR (95% CI): 0.899 (0.817, 0.990), p = 0.001), simple mode (OR (95% CI): 0.901 (-0.678, 1.199), p = 0.478), and weighted mode (OR (95% CI): 0.859 (0.782, 0.944), p = 0.003), omega-3 fatty acids showed a causal association with low risk of lung cancer. No genetic pleiotropy or horizontal pleiotropy was found according to MR-Egger regression intercept analysis.

Conclusion

Our findings provide sufficient evidence that omega-3 fatty acids are causal protective factors of lung cancer. Despite this, further work is required for elucidating the potential mechanisms.

Serum fingerprinting by slippery liquid-infused porous SERS for non-invasive lung cancer detection

Direct and label-free analysis of clinical serum samples using slippery liquid-infused porous-enhanced Raman spectroscopy (SLIPSERS) enables the rapid non-invasive identification of lung cancer.

Simple Electric Device to Isolate Nucleic Acids from Whole Blood Optimized for Point of Care Testing of Brain Damage

BACKGROUND

Detection or monitoring of brain damage is a clinically crucial issue. Nucleic acids in the whole blood can be used as biomarkers for brain injury. Polymerase chain reaction (PCR) which is one of the most commonly used molecular diagnostic assays requires isolated nucleic acids to initiate amplification. Currently used nucleic acid isolation procedures are complicated and require laboratory equipments.

OBJECTIVE

In this study, we tried to develop a simple and convenient method to isolate nucleic acids from the whole blood sample using a tiny battery-powered electric device. The quality of the isolated nucleic acids should be suitable for PCR assay without extra preparation.

METHODS

A plastic device with separation chamber was designed and printed with a 3D printer. Two platinum electrodes were placed on both sides and a battery was used to supply the electricity. To choose the optimal nucleic acid isolation condition, diverse lysis buffers and separation buffers were evaluated, and the duration and voltage of the electricity were tested. Western blot analysis and PCR assay were used to determine the quality of the separated nucleic acids.

RESULTS

2ul of whole blood was applied to the cathode side of the separation chamber containing 78 ul of normal saline. When the electricity at 5 V was applied for 5 min, nucleic acids were separated from segment 1 to 3 of the separation chamber. The concentration of nucleic acids peaked around 7~8 mm from cathode side. PCR assay using the separation buffer as the template was performed successfully both in conventional and realtime PCR methods. The hemoglobin in the whole blood did not show the inhibitory effect in our separation system and it may be due to structural modification of hemoglobin during electric separation.

CONCLUSION

Our simple electric device can separate nucleic acids from the whole blood sample by applying electricity at 5 V for 5 min. The separation buffer solution taken from the device can be used for PCR assay successfully.