Biomarkers For Cancer Screening Research Articles

Portable Amperometric Biosensor Enhanced with Enzyme-Ternary Nanocomposites for Prostate Cancer Biomarker Detection

Enzyme-based portable amperometric biosensors are precise and low-cost medical devices used for rapid cancer biomarker screening. Sarcosine (Sar) is an ideal biomarker for prostate cancer (PCa). Because human serum and urine contain complex interfering substances that can directly oxidize at the electrode surface, rapid Sar screening biosensors are relatively challenging and have rarely been reported. Therefore, highly sensitive and selective amperometric biosensors that enable real-time measurements within <1.0 min are needed. To achieve this, a chitosan–polyaniline polymer nanocomposite (CS–PANI NC), a carrier for dispersing mesoporous carbon (MC), was synthesized and modified on a screen-printed carbon electrode (SPCE) to detect hydrogen peroxide (H2O2). The sarcosine oxidase (SOx) enzyme-immobilized CS–PANI–MC-2 ternary NCs were referred to as supramolecular architectures (SMAs). The excellent electron transfer ability of the SMA-modified SPCE (SMA/SPCE) sensor enabled highly sensitive H2O2 detection for immediate trace Sar biomarker detection. Therefore, the system included an SMA/SPCE coupled to a portable potentiostat linked to a smartphone for data acquisition. The high catalytic activity, porous architecture, and sufficient biocompatibility of CS–PANI–MC ternary NCs enabled bioactivity retention and immobilized SOx stability. The fabricated biosensor exhibited a detection limit of 0.077 μM and sensitivity of 8.09 μA mM−1 cm−2 toward Sar, demonstrating great potential for use in rapid PCa screening.

Triage performance of DNA methylation for women with high-risk human papillomavirus infection.

DNA methylation is a promising biomarker for cervical cancer screening. This study aimed to validate the triage performance of cytological DNA methylation for detecting cervical intraepithelial neoplasia of grade 3 or worse (CIN3+) in women with high-risk human papillomavirus (hrHPV) infection from a large prospective cohort undergoing opportunistic screening in China (METHY3). The triage performance for detecting CIN3+ lesions was compared between HPV16/18 genotyping, a liquid-based cytology (LBC) test, and the PAX1 and JAM3 methylation (PAX1m/JAM3m) test according to cervical pathologic outcomes. Among the 4394 women infected with hrHPV, 1105 had definitive cervical histological findings that were analyzed. For detecting CIN3+, the specificity of HPV16/18(+), the LBC result of ≥atypical squamous cells of undetermined significance (ASCUS), and PAX1m/JAM3m(+) was 66.4%, 23.9%, and 89.6%, respectively, with odds ratios of 4.24 (95% confidence interval [CI], 2.85-6.40), 4.44 (2.27-10.1), and 18.5 (12.1-28.7) (P < .001), respectively. PAX1m/JAM3m(+) had the highest area under the receiver operating characteristic curve (0.790, 95% CI, 0.747-0.832) in the whole cohort and in women of various ages. PAX1m/JAM3m (+) was detected in all patients with cancer (n = 28). Compared with HPV16/18 genotyping and the LBC test, PAX1m/JAM3m testing reduced referrals to colposcopy by 20.64 percentage points and 61.18 percentage points, respectively. PAX1 m /JAM3 m testing is highly specific for detecting CIN3+. As a triage biomarker, it is superior to HPV 16/18 genotyping and LBC testing for women with hrHPV infection.

Efficient Cancer Biomarker Screening and Multicancer Detection Enabled by a Multidimensional Serum Proteomic Strategy.

Biomarker discovery and application are paramount for the early diagnosis, treatment, and prognosis assessment of diseases. Novel proteomic strategies have been developed for high-efficiency biomarker screening. However, evaluating various strategies and applying them for the in-depth mining of biomarkers from blood need to be elucidated. Herein, we systematically evaluated the technical characteristics of three representative biomarker discovery strategies, including the most popular DIA proteomics, and two promising strategies targeting the cancer-secreted proteome or extracellular vesicle proteome, and integrated them into one multidimensional serum proteomic strategy. The results showed that the three strategies each have unique characteristics in terms of sensitivity, reproducibility, and protein coverage and are highly complementary in biomarker discovery. The integrated multidimensional serum proteomic strategy achieves deep and comprehensive coverage of the serum proteome, discovers more cancer markers, and helps achieve a more accurate multicancer (breast, lung, stomach, liver, and colorectum) diagnosis with 87.5% localization accuracy.

Combining metabolomics and machine learning to discover biomarkers for early-stage breast cancer diagnosis.

There is an urgent need for better biomarkers for the detection of early-stage breast cancer. Utilizing untargeted metabolomics and lipidomics in conjunction with advanced data mining approaches for metabolism-centric biomarker discovery and validation may enhance the identification and validation of novel biomarkers for breast cancer screening. In this study, we employed a multimodal omics approach to identify and validate potential biomarkers capable of differentiating between patients with breast cancer and those with benign tumors. Our findings indicated that ether-linked phosphatidylcholine exhibited a significant difference between invasive ductal carcinoma and benign tumors, including cases with inconsistent mammography results. We observed alterations in numerous lipid species, including sphingomyelin, triacylglycerol, and free fatty acids, in the breast cancer group. Furthermore, we identified several dysregulated hydrophilic metabolites in breast cancer, such as glutamate, glycochenodeoxycholate, and dimethyluric acid. Through robust multivariate receiver operating characteristic analysis utilizing machine learning models, either linear support vector machines or random forest models, we successfully distinguished between cancerous and benign cases with promising outcomes. These results emphasize the potential of metabolic biomarkers to complement other criteria in breast cancer screening. Future studies are essential to further validate the metabolic biomarkers identified in our study and to develop assays for clinical applications.

COL25A1 and METAP1D DNA methylation are promising liquid biopsy epigenetic biomarkers of colorectal cancer using digital PCR

BackgroundColorectal cancer is a public health issue and was the third leading cause of cancer-related death worldwide in 2022. Early diagnosis can improve prognosis, making screening a central part of colorectal cancer management. Blood-based screening, diagnosis and follow-up of colorectal cancer patients are possible with the study of cell-free circulating tumor DNA. This study aimed to identify novel DNA methylation biomarkers of colorectal cancer that can be used for the follow-up of patients with colorectal cancer.MethodsA DNA methylation profile was established in the Gene Expression Omnibus (GEO) database (n = 507) using bioinformatics analysis and subsequently confirmed using The Cancer Genome Atlas (TCGA) database (n = 348). The in silico profile was then validated on local tissue and cell-free DNA samples using methylation-specific digital PCR in colorectal cancer patients (n = 35) and healthy donors (n = 35).ResultsThe DNA methylation of COL25A1 and METAP1D was predicted to be a colorectal cancer biomarker by bioinformatics analysis (ROC AUC = 1, 95% CI [0.999–1]). The two biomarkers were confirmed with tissue samples, and the combination of COL25A1 and METAP1D yielded 49% sensitivity and 100% specificity for cell-free DNA.ConclusionBioinformatics analysis of public databases revealed COL25A1 and METAP1D DNA methylation as clinically applicable liquid biopsies DNA methylation biomarkers. The specificity implies an excellent positive predictive value for follow-up, and the high sensitivity and relative noninvasiveness of a blood-based test make these biomarkers compatible with colorectal cancer screening. However, the clinical impact of these biomarkers in colorectal cancer screening and follow-up needs to be established in further prospective studies.

SEPT9: From pan-cancer to lung squamous cell carcinoma

BackgroundSEPT9 is a pivotal cytoskeletal GTPase that regulates diverse biological processes encompassing mitosis and cytokinesis. While previous studies have implicated SEPT9 in tumorigenesis and development; comprehensive pan-cancer analyses have not been performed. This study aims to systematically explore its role in cancer screening, prognosis, and treatment, addressing this critical gap.MethodsGene and protein expression data containing clinical information were obtained from public databases for pan-cancer analyses. Additionally, clinical samples from 90 patients with lung squamous cell carcinoma (LUSC) were used to further experimentally validate the clinical significance of SEPT9. In addition, the molecular docking tool was used to analyze the affinities between SEPT9 protein and drugs.ResultsSEPT9 is highly expressed in various cancers, and its aberrant expression correlates with genetic alternations and epigenetic modifications, leading to adverse clinical outcomes. Take LUSC as an example, additional dataset analyses and immunohistochemical experiments further confirm the diagnostic and prognostic values as well as the clinical relevance of the SEPT9 gene and protein. Functional enrichment, single-cell expression, and immune infiltration analyses revealed that SEPT9 promotes malignant tumor progression and modulates the immune microenvironments, enabling patients to benefit from immunotherapy. Moreover, drug sensitivity and molecular docking analyses showed that SEPT9 is associated with the sensitivity and resistance of multiple drugs and has stable binding activity with them, including Vorinostat and OTS-964. To harness its prognostic and therapeutic potential in LUSC, a mitotic spindle-associated prognostic model including SEPT9, HSF1, ARAP3, KIF20B, FAM83D, TUBB8, and several clinical characteristics, was developed. This model not only improves clinical outcome predictions but also reshapes the immune microenvironment, making immunotherapy more effective for LUSC patients.ConclusionThis is the first study to systematically analyze the role of SEPT9 in cancers and innovatively apply the mitotic spindle-associated model to LUSC, fully demonstrating its potential as a valuable biomarker for cancer screening and prognosis, and highlighting its application value in promoting immunotherapy and chemotherapy, particularly for LUSC.

The level of expression of HPV16 early transcripts is not associated with the natural history of cervical lesions.

The natural history of cervical cancer is closely linked to that of high-risk human papillomaviruses (HPV) infection. It is recognized that upon HPV DNA integration, partial or complete loss of the E2 open reading frame precludes expression of the corresponding protein, resulting in upregulation of the E6 and E7 viral oncoproteins. To better characterize HPV16 infection at the cervical level, viral load, viral DNA integration, and viral early transcript expression (E2, E5, and E6) were analyzed in a series of 158 cervical specimens representative of the full spectrum of cervical disease. Overall, the frequency of early transcript detection varied from 45% to 90% and tended to increase with lesion severity. In addition, the levels of E2, E5, and E6 transcript expression were slightly higher in high-grade lesions than in cervical specimens without abnormalities. Notably, early transcript expression was clearly associated with viral load, and no inverse correlation was found between the expression of E2 and E6 transcripts. No clear association was found between early transcript expression and HPV16 DNA integration, with the exception that samples with a fully integrated HPV16 genome did not harbor E2 or E5 transcripts. In conclusion, early HPV16 transcript expression appears to be associated with viral load rather than lesion grade. From a practical point of view, quantification of HPV16 early transcripts is difficult to translate into a relevant biomarker for cervical cancer screening.

The diagnostic performance of the Mindray system in detecting CA125 and HE4 for patients with ovarian cancer.

Cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) are the most commonly used tumor biomarkers for ovarian cancer (OC) screening and diagnosis. The risk of ovarian malignancy algorithm (ROMA) score uses these markers, as detected by the Roche system, to predict the risk of OC. This study sought to assess the performance of the Mindray system in detecting CA125 and HE4 for ROMA score calculation in clinical settings. Consecutive OC patients and patients with benign pelvic masses were screened and enrolled in this study. The CA125 and HE4 levels of these patients were measured using both the Mindray and Roche systems. The ROMA score for each patient was calculated. Diagnostic performance was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. The HE4 and CA125 levels were significantly higher in the patients with OC than the patients with benign ovarian masses. Both detection systems showed high efficiency in detecting ovarian cancer. For the premenopausal OC patients, the AUC values for the ROMA score, HE4, and CA125 were 0.866, 0.852, and 0.879, respectively, using the Roche system, and 0.911, 0.902, and 0.883, respectively, using the Mindray system. For the postmenopausal OC patients, the AUC values for the ROMA score, HE4, and CA125 were 0.962, 0.920, and 0.953, respectively, using Roche system, and 0.966, 0.924, and 0.959, respectively, using the Mindray system. The correlation analysis showed strong agreement between the two systems. Among the patients who experienced recurrence, we observed a significant increase in both HE4 and CA125 levels compared to baseline using the Mindray system. The Mindray and Roche systems provide consistent results. The Mindray system can be used to detect HE4 and CA125 for ROMA score calculation.

A dual-targeted electrochemical aptasensor for neuroblastoma-related microRNAs detection

Neuroblastoma (NB) is a significant pediatric cancer associated with high mortality rates, demanding innovative and appropriate approaches for its accurate detection. This paper described the design of a dual-target electrochemical aptasensor capable of simultaneously detecting neuroblastoma-associated microRNAs (miRNA-181 and miRNA-184) with exceptional sensitivity. Screen-printed carbon electrodes (SPCEs) were utilized with gold nanorods (AuNRs), and aptamers functionalized gold nanoparticles (AuNPs) to improve sensitivity, specificity, and portable detection ability. The detection method employed in this study includes differential pulse voltammetry (DPV) and cyclic voltammetry (CV). Our aptasensor exhibited remarkable limits of detections (LODs) of 5.10 aM for miRNA-181 and 9.39 aM for miRNA-184, respectively, along with a broad linear range spanning from 0.1 fM to 100 pM for both miRNAs. The practical significance of neuroblastoma diagnosis was shown through the validation of serum samples and comparison with quantitative polymerase chain reaction (qPCR). Our electrochemical aptasensor is user-friendly, easy to engineer, and offers a promising approach for accurately and selectively detecting important miRNA biomarkers in cancer screening and diagnosis, showing potential application in various clinical scenarios.

MetDecode: methylation-based deconvolution of cell-free DNA for noninvasive multi-cancer typing.

Circulating-cell free DNA (cfDNA) is widely explored as a noninvasive biomarker for cancer screening and diagnosis. The ability to decode the cells of origin in cfDNA would provide biological insights into pathophysiological mechanisms, aiding in cancer characterization and directing clinical management and follow-up. We developed a DNA methylation signature-based deconvolution algorithm, MetDecode, for cancer tissue origin identification. We built a reference atlas exploiting de novo and published whole-genome methylation sequencing data for colorectal, breast, ovarian, and cervical cancer, and blood-cell-derived entities. MetDecode models the contributors absent in the atlas with methylation patterns learnt on-the-fly from the input cfDNA methylation profiles. In addition, our model accounts for the coverage of each marker region to alleviate potential sources of noise. In-silico experiments showed a limit of detection down to 2.88% of tumor tissue contribution in cfDNA. MetDecode produced Pearson correlation coefficients above 0.95 and outperformed other methods in simulations (P < 0.001; T-test; one-sided). In plasma cfDNA profiles from cancer patients, MetDecode assigned the correct tissue-of-origin in 84.2% of cases. In conclusion, MetDecode can unravel alterations in the cfDNA pool components by accurately estimating the contribution of multiple tissues, while supplied with an imperfect reference atlas. MetDecode is available at https://github.com/JorisVermeeschLab/MetDecode.

Programmable Framework Nucleic Acid-Modified Nanomagnetic Beads for Efficient Isolation of Exosomes and Exosomal Proteomics Analysis.

Exosomes are increasingly being regarded as emerging and promising biomarkers for cancer screening, diagnosis, and therapy. The downstream molecular analyses of exosomes were greatly affected by the isolation efficiency from biosamples. Among the current exosome isolation strategies, affinity nanomaterials performed comparably better with selectivity and specificity. However, these techniques did not take the structure and size of exosomes into account, which may lead to a loss of isolation efficiency. In this article, a framework nucleic acid was employed to prepare a well-designed nanosized bead Fe3O4@pGMA@DNA TET@Ti4+ for enrichment of exosomes. The abundant phosphate groups in the framework nucleic acid provide binding sites to immobilize Ti4+, and its rigid three-dimensional skeleton makes them act as roadblocks to barricade exosomes and provide affinity interactions on a three-dimensional scale, resulting in the improvement of isolation efficiency. The model exosomes can be effectively isolated with 92% recovery in 5 min. From 100 μL of HeLa cell culture supernatant, 34 proteins out of the top 100 commonly identified exosomal proteins were identified from the isolated exosomes by the novel beads, which is obviously more than that by TiO2 (19 proteins), indicating higher isolation efficiency and exosome purity by Fe3O4@pGMA@DNA TET@Ti4+ beads. The nanobeads were finally applied for comparing exosomal proteomics analysis from real clinical serum samples. Twenty-five upregulated and 10 downregulated proteins were identified in the lung cancer patients group compared to the health donors group, indicating that the novel nanobeads have great potential in isolation of exosomes for exosomal proteomics analysis in cancer screening and diagnosis.

Expression and hypermethylation of JAM and EPB41L3 in cervical squamous cell carcinoma: Clinical significance and applications.

This study aimed to explore the expression and hypermethylation of EPB41L3 and JAM3 in cervical squamous cell carcinoma (CSCC) and to investigate their clinical significance. JAM3 and EPB41L3 mRNA expression was analyzed using a public database, and protein expression was detected using immunohistochemistry. The methylation status of JAM3 and EPB41L3 was detected in CSCC tissues and cervical cytological specimens using a quantitative methylation-specific PCR (qMSP). JAM3 and EPB41L3 mRNA were downregulated in CSCC. The JAM3 protein was positively detected in 39.4% of CSCC tissues and frequently expressed in those with lower FIGO stage and no lymph node metastasis. EPB41L3 was expressed in 18.9% of CSCC tissues. The hypermethylation of JAM3 was detected in 52.3% of CSCC tissues and related to higher FIGO stage and lymph node metastasis. EPB41L3 hypermethylation was detected in 72.7% of CSCC tissues and related to older ages and lymph node metastasis. In cervical cytological specimens, no methylation of JAM3 and EPB41L3 was found in normal or inflamed cervical epithelial cells. The methylation of JAM3 was detected in 0%, 8.3%, and 6.3% of ASCUS, LSIL, and HSIL samples, while EPB41L3 was detected in 12.5%, 42.9%, and 71.4%, respectively. The sensitivity of the combination of JAM3 and EPB41L3 methylation detection in ASCUS, LSIL, and HSIL was 8.3%, 15.6%, and 85.7%, respectively. The specificity of the combination of JAM3 and EPB41L3 methylation detection was 100%. Downregulation of JAM3 and EPB41L3 by hypermethylation was detected in CSCC. JAM3 and EPB41L3 hypermethylation are potential biomarkers for cervical cancer screening.

Exosomal Thomsen-Friedenreich Glycoantigen: A New Liquid Biopsy Biomarker for Lung and Breast Cancer Diagnoses.

Exosomes or small extracellular vesicles have emerged as potent biomarkers of cancer liquid biopsy. We discovered a new exosomal carbohydrate marker, TF-Ag-α (Galβ1-3GalNAc-α), and showed that exosomal TF-Ag-α detected both lung and breast cancers with >95% accuracy. Our findings demonstrated that exosomal TF-Ag-α is a promising liquid biopsy biomarker for cancer screening and early detection.

Evaluation of mtDNA common deletion in esophageal squamous cell carcinoma.

Mitochondrial defects are thought to play a role in cancer initiation and progression for a long time. Because of the absence of protective histones and an inefficiency in the DNA repair process, mitochondrial DNA is known to be prone to mutations. The deletion of 4977bp is one of the most common mutations in human cancers. This study aimed to investigate the relationship between 4977bp common deletion and Esophageal Squamous Cell Carcinoma Disease (SCC) to provide prognostic information. By using a PCR protocol, this study identified the 4977bp deletion of mtDNA. A PCR method was used on tumor samples from 41 squamous cell carcinoma patients and blood samples from 50 healthy individuals to detect DNA. Among the 41 tumor samples (80.5%), 33 were found to have the 4977bp deletion, while none of the blood samples from healthy individuals contained it. It is shown that the deletion of 4977bp of mtDNA correlates significantly with SCC in this study. A 4977bp deletion could be used as an effective cancer screening indicator and biomarker for early diagnosis and prevention of cancer.

Identification and validation of screening models for breast cancer with 3 serum miRNAs in an 11,349 samples mixed cohort.

The study focuses on enhancing breast cancer (BC) prognosis through early detection, aiming to establish a non-invasive, clinically viable BC screening method using specific serum miRNA levels. Involving 11,349 participants across BC, 11 other cancer types, and control groups, the study identified serum biomarkers through feature selection and developed two BC screening models using six machine learning algorithms. These models underwent evaluation across test, internal, and external validation sets, assessing performance metrics like accuracy, sensitivity, specificity, and the area under the curve (AUC). Subgroup analysis was conducted to test model stability. Based on the three serum miRNA biomarkers (miR-1307-3p, miR-5100, and miR-4745-5p), a BC screening model, SM4BC3miR model, was developed. This model achieved AUC performances of 0.986, 0.986, and 0.939 on the test, internal, and external sets, respectively. Furthermore, the SSM4BC model, utilizing ratio scores of miR-1307-3p/miR-5100 and miR-4745-5p/miR-5100, showed AUCs of 0.973, 0.980, and 0.953, respectively. Subgroup analyses underscored both models' robustness and stability. This research introduced the SM4BC3miR and SSM4BC models, leveraging three specific serum miRNA biomarkers for breast cancer screening. Demonstrating high accuracy and stability, these models present a promising approach for early detection of breast cancer. However, their practical application and effectiveness in clinical settings remain to be further validated.

The associations between dysregulation of human blood metabolites and lung cancer risk: evidence from genetic data

BackgroundMetabolic dysregulation is recognized as a significant hallmark of cancer progression. Although numerous studies have linked specific metabolic pathways to cancer incidence, the causal relationship between blood metabolites and lung cancer risk remains unclear.MethodsGenomic data from 29,266 lung cancer patients and 56,450 control individuals from the Transdisciplinary Research in Cancer of the Lung and the International Lung Cancer Consortium (TRICL-ILCCO) were utilized, and findings were replicated using additional data from the FinnGen consortium. The analysis focused on the associations between 486 blood metabolites and the susceptibility to overall lung cancer and its three major clinical subtypes. Various Mendelian randomization methods, including inverse-variance weighting, weighted median estimation, and MR-Egger regression, were employed to ensure the robustness of our findings.ResultsA total of 19 blood metabolites were identified with significant associations with lung cancer risk. Specifically, oleate (OR per SD = 2.56, 95% CI: 1.51 to 4.36), 1-arachidonoylglyceropholine (OR = 1.79, 95% CI: 1.22 to 2.65), and arachidonate (OR = 1.67, 95% CI: 1.16 to 2.40) were associated with a higher risk of lung cancer. Conversely, 1-linoleoylglycerophosphoethanolamine (OR = 0.57, 95% CI: 0.40 to 0.82), ADpSGEGDFXAEGGGVR, a fibrinogen cleavage peptide (OR = 0.60, 95% CI: 0.47 to 0.77), and isovalerylcarnitine (OR = 0.62, 95% CI: 0.49 to 0.78) were associated with a lower risk of lung cancer. Notably, isoleucine (OR = 9.64, 95% CI: 2.55 to 36.38) was associated with a significantly higher risk of lung squamous cell cancer, while acetyl phosphate (OR = 0.11, 95% CI: 0.01 to 0.89) was associated with a significantly lower risk of small cell lung cancer.ConclusionThis study reveals the complex relationships between specific blood metabolites and lung cancer risk, highlighting their potential as biomarkers for lung cancer prevention, screening, and treatment. The findings not only deepen our understanding of the metabolic mechanisms of lung cancer but also provide new insights for future treatment strategies.

MiRNAs as potential biomarkers in early breast cancer detection: a systematic review.

Breast cancer remains a significant global health challenge, with high incidence and mortality rates. While mammography has contributed to declining mortality, its limitations in sensitivity and specificity for early detection, particularly in distinguishing between pure atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC), highlight the need for more precise tools. Even with core needle biopsy (CNB), conclusive diagnoses often require surgical excision. This underscores the urgency for non-invasive biomarkers to improve early detection and differentiation, potentially reducing invasive procedures. Recent research has shifted focus from mRNA to microRNAs (miRNAs) as promising biomarkers for breast cancer screening. These small non-coding RNAs, which exhibit abnormal expression patterns in breast cancer patients' tissue and serum/plasma, play crucial roles in early breast cancer development by modulating proto-oncogenes or tumor suppressor genes at the post-transcriptional level. Notably, miRNAs such as miR-21, miR-155, and miR-200c are key regulators of cell proliferation and apoptosis, with the potential to distinguish between normal tissue and various stages of breast lesions, including ADH, DCIS, and IDC. Additionally, miRNAs in serum and plasma offer a non-invasive method to differentiate breast cancer stages. This review aims to consolidate current knowledge on early breast lesions and explore the potential of miRNAs as biomarkers for early breast cancer detection, which could enhance risk prediction and reduce reliance on invasive diagnostic procedures.

A Four-Gene Panel in Rectal Swab Samples as a Biomarker for Colorectal Cancer Screening.

The dysregulation of gene expression is one of the key molecular features of colorectal cancer (CRC) development. This study aimed to investigate whether such dysregulation is reflected in rectal swab specimens of CRC patients and to evaluate its potential as a non-invasive approach for screening. We compared the expression level of 14 CRC-associated genes in tumor and adjacent non-tumor tissue of CRC patients and examined the correlation of their levels in tissue with paired rectal swab specimens. The level of these 14 genes in rectal swab specimens was compared among patients with CRC or polyp and control subjects, and the diagnostic potential of each dysregulated gene and the gene panel were evaluated. The expression of CXCR2, SAA, COX1, PPARδ, PPARγ, Groγ, IL8, p21, c-myc, CD44 and CSF1 was significantly higher in CRC, and there was a significant correlation in the levels of most of them between the CRC and rectal swab specimens. In the training study, we showed that CD44, IL8, CXCR2 and c-myc levels were significantly higher in the rectal swab specimens of the CRC patients. Such result was confirmed in the validation study. A panel of these four genes was developed, and ROC analysis showed that this four-gene panel could identify CRC patients with an AUC value of 0.83 and identify overall polyp and precancerous adenoma patients with AUC values of 0.6522 and 0.7322, respectively. Finally, the predictive study showed that the four-gene panel demonstrated sensitivities of 63.6%, 76.9% and 88.9% in identifying overall polyp, precancerous adenoma and CRC patients, respectively, whereas the specificity for normal subjects was 72.2%. The expression of CRC-associated genes in rectal swab specimens reflects the dysregulation status in colorectal tissue, and the four-gene panel is a potential non-invasive biomarker for early precancerous adenoma and CRC screening.

The Role of Biomarkers in Lung Cancer Screening.

Lung Cancer Screening (LCS) is an evolving field with variations in its implementation in various countries. There are only scarce data from National LCS programs. We aim to provide an up-to-date overview of the current evidence regarding the use of biomarkers in LCS. A multidisciplinary Task Force experts' panel collaborated and conducted a systematic literature search, followed by screening, review and synthesis of available evidence. Biomarkers in LCS could be used to improve risk stratification in high-risk participants, improve clarification regarding indeterminate lung nodules and avoid overdiagnosis in suspicious lung findings. Currently, there seem to be promising biomarkers (blood/serum/breath) that have been studied in various trials; however, there is still a lack of solid evidence in clinical validation that would pave the way for their integration into LCS programs. Biomarkers are the next logical step in improving the LCS pathway and its efficiency by playing an adjuvant role in a minimally invasive way. National LCS programs and pilot studies should integrate biomarkers to validate their accuracy in real-life LCS participants.

Circulating MiR-1185¸ MiR-3183, and MiR-584 Levels in Plasma as Diagnostic Non-invasive Biomarkers for Early Detection of Breast Cancer

Introduction: MicroRNAs (miRNAs) are non-coding RNA molecules with short sequences that function as main post-transcriptional gene regulators of different biological pathways via negative regulation of gene expression, thereby leading to either mRNA degradation or translational blockade. Dysregulated expression of these miRNAs has been related etiologically to many human diseases, including breast cancer. Various cellular processes of breast cancer progression, including cell proliferation, apoptosis, metastasis, recurrence and chemodrug resistance, are modulated by oncogenic miRNA (oncomiR). Objective: The objective of this investigation was to study the expression level and potential diagnostic/ prognostic roles of circulating microRNAs (miR-3183, miR-1185, and miR-584) as novel breast cancer biomarkers. Method: The current study was conducted on 99 breast cancer (BC) female patients, aged between 20-63 years old, as the case group and 50 age-matched healthy females as control (HC). After microRNA extraction from the serum samples, real-time PCR was carried out for relative expression quantification of miR-1185, miR-3183a, and miR-584. The ROC curve analysis was performed to investigate the diagnostic value of miRNAs. Result: It was demonstrated that miRNA-1185, miRNA-584, and miRNA-3183 were significantly up-regulated (p-values &lt;0.0001) in female BC cases compared to the control group. Besides, based on the ROC analysis for BC versus HC, it was revealed that the AUC for miRNA-584 was 0.844 (95% confidence interval (CI) and could be proposed as a diagnostic biomarker for breast cancer screening and follow-up. Conclusion: MiRNAs expression profiling using blood-based samples demonstrated their upregulation in the serum and plasma and revealed the concept that circulating miRNAs have high potential as novel noninvasive biomarkers for cancer diagnosis and screening.