Novel Graphene Biosensor Based on the Functionalization of Multifunctional Nano-bovine Serum Albumin for the Highly Sensitive Detection of Cancer Biomarkers

A simple,convenient,and highly sensitive bio-interface for graphene field-effect transistors(GFETs) based on multifunctional nano-denatured bovine serum albumin(nano-dBSA) functionalization was developed to target cancer bio-markers.The novel graphene–protein bioelectronic interface was constructed by heating to denature native BSA on the graphene substrate surface.The formed nano-d BSA film served as the cross-linker to immobilize monoclonal antibody against car-cinoembryonic antigen(anti-CEA mAb) on the graphene channel activated by EDC and Sulfo-NHS.The nano-dBSA film worked as a self-protecting layer of graphene to prevent surface contamination by lithographic processing.The improved GFETbiosensor exhibited good specificity and high sensitivity toward the target at an ultralow concentration of 337.58 fg mL-1.The electrical detection of the binding of CEA followed the Hill model for ligand–receptor interaction,indicating the negative binding cooperativity between CEA and anti-CEA mAb with a dissociation constant of 6.82×10-10M.The multifunctional nano-dBSA functionalization can confer a new function to graphene-like 2D nanomaterials and provide a promising bio-functionalization method for clinical application in biosensing,nanomedicine,and drug delivery.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer(PanCa)presents a major concern and health burden.The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics;however,they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting.Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures.The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians.Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages.In this review,we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

Leveraging electrochemical sensors to improve efficiency of cancer detection

Electrochemical biosensors have emerged as a promising technology for cancer detection due to their high sensitivity,rapid response,low cost,and capability for non-invasive detection.Recent advances in nanomaterials like nanoparticles,graphene,and nanowires have enhanced sensor performance to allow for cancer biomarker detection,like circulating tumor cells,nucleic acids,proteins and metabolites,at ultra-low concentrations.However,several challenges need to be addressed before electrochemical biosensors can be clinically implemented.These include improving sensor selectivity in complex biological media,device miniaturization for implantable applications,integration with data analytics,handling biomarker variability,and navigating regulatory approval.This editorial critically examines the prospects of electrochemical biosensors for efficient,low-cost and minimally invasive cancer screening.We discuss recent developments in nanotechnology,microfabrication,electronics integration,multiplexing,and machine learning that can help realize the potential of these sensors.However,significant interdisciplinary efforts among researchers,clinicians,regulators and the healthcare industry are still needed to tackle limitations in selectivity,size constraints,data interpretation,biomarker validation,toxicity and commercial translation.With committed resources and pragmatic strategies,electrochemical biosensors could enable routine early cancer detection and dramatically reduce the global cancer burden.

COL4A2 enhances thyroid cancer cell proliferation through the AKT pathway

Objectives:Thyroid cancer(THCA)is the most common malignant tumor in endocrine system and the incidence has been increasing worldwide.And the number of patients dying from THCA has also gradually risen because the incidence continues to increase,so the mechanisms related to effective targets is necessary to improve the survival.This study was to preliminarily investigate the effects of the COL4A2 gene on the regulation of thyroid cancer(THCA)cell proliferation and the associated pathways.Methods:Bioinformatics analysis revealed that COL4A2 was closely associated with cancer development.COL4A2 expression in THCA tissues was analyzed using immunohistochemistry,and survival information was determined via Kaplan-Meier curves.The expression of COL4A2 and AKT pathway-related genes were analyzed using qPCR and western blot analyses.Colony formation as well as CCK-8 assays exhibited the cell proliferation level and cell activity,respectively.Downstream of COL4A2 was identified by Gene set enrichment analysis(GSEA).The effects of the COL4A2 and AKT pathways on THCA tumor growth in vivo were determined using a mouse model.Results:Bioinformatics analysis exhibited that COL4A2 plays a significant role in cancer and that the AKT pathway is downstream of COL4A2.THCA patients with high COL4A2 expression had shorter recurrence-free survival.Upregulation of COL4A2 gene expression in 2 THCA cell lines promoted tumor cell growth and activity.The use of AKT pathway blockers also restrained the growth and activity of the 2 THCA cell lines.The use of AKT pathway blockers reduced tumor volume and mass and prolonged mouse survival.Conclusions:COL4A2 can promote the growth as well as development of THCA through the AKT pathway and COL4A2 could be used as a target for THCA.

The outpost against cancer:universal cancer only markers

Cancer is the leading cause of death worldwide.Early detection of cancer can lower the mortality of all types of cancer;however,effective early-detection biomarkers are lacking for most types of cancers.DNA methylation has always been a major target of interest because DNA methylation usually occurs before other detectable genetic changes.While investigating the common features of cancer using a novel guide positioning sequencing for DNA methylation,a series of universal cancer only markers(UCOMs)have emerged as strong candidates for effective and accurate early detection of cancer.While the clinical value of current cancer biomarkers is diminished by low sensitivity and/or low specificity,the unique characteristics of UCOMs ensure clinically meaningful results.Validation of the clinical potential of UCOMs in lung,cervical,endometrial,and urothelial cancers further supports the application of UCOMs in multiple cancer types and various clinical scenarios.In fact,the applications of UCOMs are currently under active investigation with further evaluation in the early detection of cancer,auxiliary diagnosis,treatment efficacy,and recurrence monitoring.The molecular mechanisms by which UCOMs detect cancers are the next important topics to be investigated.The application of UCOMs in real-world scenarios also requires implementation and refinement.

Application of microfluidic technology based on surface-enhanced Raman scattering in cancer biomarker detection:A review

With the continuous discovery and research of predictive cancer-related biomarkers,liquid biopsy shows great potential in cancer diagnosis.Surface-enhanced Raman scattering(SERS)and microfluidic technology have received much attention among the various cancer biomarker detection methods.The former has ultrahigh detection sensitivity and can provide a unique fingerprint.In contrast,the latter has the characteristics of miniaturization and integration,which can realize accurate control of the detection samples and high-throughput detection through design.Both have the potential for point-of-care testing(POCT),and their combination(lab-on-a-chip SERS(LoC-SERS))shows good compatibility.In this paper,the basic situation of circulating proteins,circulating tumor cells,exosomes,circulating tumor DNA(ctDNA),and microRNA(miRNA)in the diagnosis of various cancers is reviewed,and the detection research of these biomarkers by the LoC-SERS platform in recent years is described in detail.At the same time,the challenges and future development of the platform are discussed at the end of the review.Summarizing the current technology is expected to provide a reference for scholars engaged in related work and interested in this field.

PCA3 and TMPRSS2-ERG gene fusions as diagnostic biomarkers for prostate cancer

The incidence of prostate cancer （PCa） is rising steadily among males in many countries. Serum prostate-specific antigen （PSA） is widely applied to clinical diagnosis and screening of PCa. However, the so-called grey area of PSA levels 4.0-10.0 ng/mL has a low specificity of 25-40% resulting in a high rate of negative biopsy and overtreatment. So in order to treat PCa patients in early stage, there is an urgent need for new biomarkers in PCa diagnosis. The PCA3 gene, a non-coding RNA （ncRNA） that is highly expressed in prostate cancer （PCa） cells, has been identified as a molecular biomarkers to detect PCa, of which PCA3 has already under clinical application. PCA3 is strongly overexpressed in malignant prostate tissue compared to benign or normal adjacent one. Newly, PCA3 is considered to be a promising biomarker in clinical diagnosis and targeted therapy. The diagnostic significance of PCA3, however, is awaiting further researches. Moreover, it has been demonstrated recently that TMPRSS2-ERG gene fusion is identified as the predominant genetic change in patients diagnosed with PCa. Recent study revealed that combination of the PC43 and TMPRSS2-ERG gene fusion test optimizes PCa detection compared with that of single biomarker, which would lead to a considerable reduction of the number of prostate biopsies. In this review, we focused on the potential use of PCA3 and TMPRSS2-ERG gene fusion detection in the diagnosis of PCa.

Proteome-based biomarkers in pancreatic cancer

Pancreatic cancer,as a highly malignant cancer and the fourth cause of cancer-related death in world,is characterized by dismal prognosis,due to rapid disease progression,highly invasive tumour phenotype,and resistance to chemotherapy.Despite significant advances in treatment of the disease during the past decade,the survival rate is little improved.A contributory factor to the poor outcome is the lack of appropriate sensitive and specific biomarkers for early diagnosis.Furthermore,biomarkers for targeting,directing and assessing therapeutic intervention,as well as for detection of residual or recurrent cancer are also needed.Thus,the identification of adequate biomarkers in pancreatic cancer is of extreme importance.Recently,accompanying the development of proteomic technology and devices,more and more potential biomarkers have appeared and are being reported.In this review,we provide an overview of the role of proteome-based biomarkers in pancreatic cancer,including tissue,serum,juice,urine and cell lines.We also discuss the possible mechanism and prospects in the future.That information hopefully might be helpful for further research in the field.

Carcinogen-Macromolecular Adducts As Biomarkers in Human Cancer Risk Assessment

Substantial data have been generated during the past 5 years in both experimental systems and human populations which shed light on the potential role of carcinogen-macromolecular adducts in human cancer risk assessment. The use of DNA and protein adducts is based on the fundamental concept in chemical carcinogenesis that most genotoxins are metabolized to electrophilic 'ultimate' carcinogens that are capable of forming covalent adducts with cellular macromolecules. This report examines the relative usefulness and limitations of using DNA and protein adducts and related techniques for assessing human exposure to genotoxic carcinogens. Data discussed in this report clearly demonstrate that these biomarkers not only allow early detection of potential cancer hazard in humans, but they can also significantly increase the power of conventional cancer epidemiological studies in determining true causal relationships. In addition, such biomarkers can improve extrapolation of cancer risks from laboratory animals to humans or from one human population to another.

Early diagnosis of pancreatic cancer:What strategies to avoid a foretold catastrophe

While great strides in improving survival rates have been made for most cancers in recent years,pancreatic ductal adenocarcinoma(PDAC)remains one of the solid tumors with the worst prognosis.PDAC mortality often overlaps with incidence.Surgical resection is the only potentially curative treatment,but it can be performed in a very limited number of cases.In order to improve the prognosis of PDAC,there are ideally two possible ways:the discovery of new strategies or drugs that will make it possible to treat the tumor more successfully or an earlier diagnosis that will allow patients to be operated on at a less advanced stage.The aim of this review was to summarize all the possible strategies available today for the early diagnosis of PDAC and the paths that research needs to take to make this goal ever closer.All the most recent studies on risk factors and screening modalities,new laboratory tests including liquid biopsy,new imaging methods and possible applications of artificial intelligence and machine learning were reviewed and commented on.Unfortunately,in 2022 the results for this type of cancer still remain discouraging,while a catastrophic increase in cases is expected in the coming years.The article was also written with the aim of highlighting the urgency of devoting more attention and resources to this pathology in order to reach a solution that seems more and more unreachable every day.

Single-cell analysis of tumors:Creating new value for molecular biomarker discovery of cancer stem cells and tumor-infiltrating immune cells

Biomarker-driven individualized treatment in oncology has made tremendous progress through technological developments, new therapeutic modalities and a deeper understanding of the molecular biology for tumors, cancer stem cells and tumor-infltrating immune cells. Recent technical developments have led to the establi-shment of a variety of cancer-related diagnostic, progno-stic and predictive biomarkers. In this regard, different modern OMICs approaches were assessed in order to categorize and classify prognostically different forms of neoplasia. Despite those technical advancements, the extent of molecular heterogeneity at the individual cell level in human tumors remains largely uncharacterized.Each tumor consists of a mixture of heterogeneous cell types. Therefore, it is important to quantify the dynamic cellular variations in order to predict clinical parameters, such as a response to treatment and or potential for disease recurrence. Recently, single-cell based methods have been developed to characterize the heterogeneity in seemingly homogenous cancer cell populations prior to and during treatment. In this review, we highlight the recent advances for single-cell analysis and discuss the challenges and prospects for molecular characterization of cancer cells, cancer stem cells and tumor-infltrating immune cells.

Powerful quantifiers for cancer transcriptomics

Every day,investigators find a new link between a form of cancer and a particular alteration in the sequence or/and expression level of a key gene,awarding this gene the title of“biomarker”.The clinician may choose from numerous available panels to assess the type of cancer based on the mutation or expression regulation(“transcriptomic signature”)of“driver”genes.However,cancer is not a“onegene show”and,together with the alleged biomarker,hundreds other genes are found as mutated or/and regulated in cancer samples.Regardless of the platform,a well-designed transcriptomic study produces three independent features for each gene:Average expression level,expression variability and coordination with expression of each other gene.While the average expression level is used in all studies to identify what genes were up-/down-regulated or turn on/off,the other two features are unfairly ignored.We use all three features to quantify the transcriptomic change during the progression of the disease and recovery in response to a treatment.Data from our published microarray experiments on cancer nodules and surrounding normal tissue from surgically removed tumors prove that the transcriptomic topologies are not only different in histopathologically distinct regions of a tumor but also dynamic and unique for each human being.We show also that the most influential genes in cancer nodules[the Gene Master Regulators(GMRs)]are significantly less influential in the normal tissue.As such,“smart”manipulation of the cancer GMRs expression may selectively kill cancer cells with little consequences on the normal ones.Therefore,we strongly recommend a really personalized approach of cancer medicine and present the experimental procedure and the mathematical algorithm to identify the most legitimate targets(GMRs)for gene therapy.

Associations between Body Mass Index and Breast Cancer Markers

Body mass index(BMI)and breast cancer biomarkers(BCBs)such as resistin,leptin adiponectin,monocyte chemoattractant protein-1(MCP-1)and homeostasis model assessment of insulin resistance(HOMA-IR)are highly associated with each other.The report has focused the inter-relationship between BMI and BCBs based on probabilistic modeling.It has been shown that mean BMI is directly associated with leptin(P<0.0001)and MCP-1(P=0.0002),while it is inversely associated with adiponectin(P=0.0003),HOMA-IR(P<0.0001),and it is higher for healthy women(P=0.0116)than breast cancer women.In addition,variance of BMI is inversely associated with resistin(P=0.1450).On the other hand,mean MCP-1 is directly associated with BMI(P<0.0001).Mean resistin is directly associated with the interaction effect of BMI and leptin(BMI^*Leptin)(P=0.0415),while its variance is directly associated with BMI(P=0.0942),and it is inversely associated with BMI*Adiponectin(P=0.1518).Leptin is directly associated with BMI(P<0.0001).Also adiponectin is inversely associated with BMI(P<0.0001),BMI*Leptin(P=0.1729),while it is directly associated with Age^*BMI(P=0.0017)and BMI^*Resistin(P=0.0615).It can be concluded that BMI and BCBs are strongly associated with each other.Care should be taken on BMI for breast cancer women.

Osteopontin as potential biomarker and therapeutic target in gastric and liver cancers

Gastric cancer and liver cancer are among the most common malignancies and the leading causes of death worldwide,due to late detection and high recurrence rates.Today,these cancers have a heavy socioeconomic burden,for which a full understanding of their pathophysiological features is warranted to search for promising biomarkers and therapeutic targets.Osteopontin (OPN) is overexpressed in most patients with gastric and liver cancers.Over the past decade,emerging evidence has revealed a correlation of OPN level and clinicopathological features and prognosis in gastric and liver cancers,indicating its potential as an independent prognostic indicator in such patients.Functional studies have verified the potential of OPN knockdown as a therapeutic approach in vitro and in vivo .Furthermore,OPN mediates multifaceted roles in the interaction between cancer cells and the tumor microenvironment,in which many details need further exploration.OPN signaling results in various functions,including prevention of apoptosis,modulation of angiogenesis,malfunction of tumor-associated macrophages,degradation of extracellular matrix,activation of phosphoinositide 3-kinase-Akt and nuclear factor-κB pathways,which lead to tumor formation and progression,particularly in gastric and liver cancers.This editorial aims to review recent findings on alteration in OPN expression and its clinicopathological associations with tumor progression,its potential as a therapeutic target,and putative mechanisms in gastric and liver cancers.Better understanding of the implications of OPN in tumorigenesis might facilitate development of therapeutic regimens to benefit patients with these deadly malignancies.

Abnormal DNA methylation as a cell-free circulating DNA biomarker for colorectal cancer detection:A review of literature

Colorectal cancer(CRC) is one of the most prevalent malignancies in the world. CRC-associated morbidity and mortality is continuously increasing, in part due to a lack of early detection. The existing screening tools such as colonoscopy, are invasive and yet high cost, affecting the willingness of patients to participate in screening programs. In recent years, evidence is accumulating that the interaction of aberrant genetic and epigenetic modifications is the cornerstone for the CRC development and progression by alternating the function of tumor suppressor genes, DNA repair genes and oncogenes of colonic cells. Apart from the understanding of the underlying mechanism(s) of carcinogenesis, the aforementioned interaction has also allowed identification of clinical biomarkers, especially epigenetic, for the early detection and prognosis of cancer patients. One of the ways to detect these epigenetic biomarkers is the cell-free circulating DNA(circ DNA), a blood-based cancer diagnostic test, mainly focusing in the molecular alterations found in tumor cells, such as DNA mutations and DNA methylation.In this brief review, we epitomize the current knowledge on the research in circ DNA biomarkers-mainly focusing on DNA methylation-as potential blood-based tests for early detection of colorectal cancer and the challenges for validation and globally implementation of this emergent technology.

Development and optimization of an antibody array method for potential cancer biomarker detection

Biomarkers play an important role in the detection at an early stage of pancreatic cancer. The aim of the present study was to optimize the conditions of antibody arrays for detecting Hippocalcin-like 1 （HPCAL1）, phosphatidylethanolamine binding protein 1 （PEBP1）, lectin galactoside-binding soluble 7 （LGALS7）, and serpin peptidase inhibitor clade E member 2 （SERPINE2） as biomarkers for pancreatic cancer detection in a single assay and to investigate antibodies’ specificity and cross-reactivity. Capture antibodies against HPCAL1, PEBP1, LGALS7 and SERPINE2 were printed on nitrocellulose coated glass slides. HPCAL1, PEBP1, LGALS7 and SERPINE2 proteins with different concentrations were incubated with the capture antibodies at different temperatures for different time periods. Biotinylated detection antibodies recognizing a different epitope on the captured proteins and a secondary detection molecule （Streptavidin-PE） were used to detect fluorescent signals. The arrays showed the strongest signals when the concentration of the capture antibodies was at 500 μg/mL in PBST0.05 （PBS with 0.05% Tween-20）, and the slides were incubated overnight at 4°C. The lowest protein concentration for detection was 2 ng/mL. Each antibody demonstrated high specificity to the corresponding antigen in detecting a mixture of 4 proteins without significant cross-reactivity. The fluorescence and biomarker concentration displayed a linear correlation. The antibody microarray system could be a useful tool for potential biomarker detection for pancreatic cancer.

The potential for liquid biopsies in the precision medical treatment of breast cancer

Currently the clinical management of breast cancer relies on relatively few prognostic/predictive clinical markers(estrogen receptor, progesterone receptor, HER2), based on primary tumor biology. Circulating biomarkers, such as circulating tumor DNA(ctDNA) or circulating tumor cells(CTCs) may enhance our treatment options by focusing on the very cells that are the direct precursors of distant metastatic disease, and probably inherently different than the primary tumor's biology. To shift the current clinical paradigm, assessing tumor biology in real time by molecularly profiling CTCs or ctDNA may serve to discover therapeutic targets, detect minimal residual disease and predict response to treatment. This review serves to elucidate the detection,characterization, and clinical application of CTCs and ctDNA with the goal of precision treatment of breast cancer.

The more the messier：centrosome amplification as a novel biomarker for personalized treatment of colorectal cancers

Colon cancer is currently the third most common cancer and second most fatal cancer in the United States,resulting in approximately 600,000 deaths annually.Though colorectal cancer death rates are decreasing by about 3%every year,disease outcomes could be substantially improved with more research into the drivers of colon carcinogenesis,the determinants of aggressiveness in colorectal cancer and the identification of biomarkers that could enable choice of more optimal treatments.Colon carcinogenesis is notably a slow process that can take decades.Known factors that contribute to the development of colon cancer are mutational,epigenetic and environmental,and risk factors include age,history of polyps and family history of colon cancer.Colorectal cancers exhibit heterogeneity in their features and are often characterized by the presence of chromosomal instability,microscopic satellite instability,or CpG island methylator phenotype.In this review,we propose that centrosome amplification may be a widespread occurrence in colorectal cancers and could potently influence tumor biology.Moreover,the quantitation of this cancer-specific anomaly could offer valuable prognostic information and pave the way for further customization of treatment based on the organellar profile of patients.Patient stratification models that take into account centrosomal status could thus potentially reduce adverse side effects and result in improved outcomes for colorectal cancer patients.

Overexpression of the M2 isoform of pyruvate kinase is an adverse prognostic factor for signet ring cell gastric cancer

AIM:To investigate M2 isoform of pyruvate kinase(PKM2) expression in gastric cancers and evaluate its potential as a prognostic biomarker and an anticancer target.METHODS:All tissue samples were derived from gastric cancer patients underwent curative gastrectomy as a primary treatment.Clinical and pathological information were obtained from the medical records.Gene expression microarray data from 60 cancer and 19 noncancer gastric tissues were analyzed to evaluate the expression level of PKM2 mRNA.Tissue microarrays were constructed from 368 gastric cancer patients.Immunohistochemistry was used to measure PKM2 expression and PKM2 positivity of cancer was determined by proportion of PKM2-positive tumor cells and staining intensity.Association between PKM2 expression and the clinicopathological factors was evaluated and the correlation between PKM2 and cancer prognosis was evaluated.RESULTS:PKM2 mRNA levels were increased more than 2-fold in primary gastric cancers compared to adjacent normal tissues from the same patients(log transformed expression level:7.6 ± 0.65 vs 6.3 ± 0.51,P < 0.001).Moreover,differentiated type cancers had significantly higher PKM2 mRNA compared to undifferentiated type cancers(log transformed expression level:7.8 ± 0.70 vs 6.7 ± 0.71,P < 0.001).PKM2 protein was mainly localized in the cytoplasm of primary cancer cells and detected in 144 of 368(39.1%) human gastric cancer cases.PKM2 expression was not related with stage(P = 0.811),but strongly correlated with gastric cancer differentiation(P < 0.001).Differentiated type cancers expressed more PKM2 protein than did the undifferentiated ones.Well differentiated adenocarcinoma showed 63.6% PKM2-positive cells;in contrast,signet-ring cell cancers showed only 17.7% PKM2-positive cells.Importantly,PKM2 expression was correlated with shorter overall survival(P < 0.05) independent of stage only in signet-ring cell cancers.CONCLUSION:PKM2 expression might be an adverse prognostic factor for signet-ring cell carcinomas.Its function and potential as a prognostic marker should be further verified in gastric cancer.

The Composition of Colonic Commensal Bacteria According to Anatomical Localization in Colorectal Cancer

Colorectal cancer （CRC） is a multistage disease resulting from complex factors, including genetic mutations, epigenetic changes, chronic inflammation, diet, and lifestyle. Recent accumulating evidence suggests that the gut microbiota is a new and important player in the development of CRC. Imbalance of the gut microbiota, especially dysregulated gut bacteria, contributes to colon cancer through mechanisms of inflammation, host defense modulations, oxidative stress, and alterations in bacterial-derived metabolism. Gut commensal bacteria are anatomically defined as four populations： luminal commensal bacteria, mucus-resident bacteria, epithelium-resident bacteria, and lymphoid tissue-resident commensal bacteria. The bacterial flora that are harbored in the gastrointestinal （GI） tract vary both longitudinally and cross-sectionally by different anatomical localization. It is notable that the translocation of colonic commensal bacteria is closely related to CRC progression. CRC-associated bacteria can serve as a noninvasive and accurate biomarker for CRC diagnosis. In this review, we summarize recent findings on the oncogenic roles of gut bacteria with different anatomical localization in CRC progression.