Genetic and epigenetic biomarkers in cancer diagnosis and identifying high risk populations

Polymerase Chain Reaction Chips for Biomarker Discovery and Validation in Drug Development

Polymerase chain reaction (PCR) chips are advanced, microfluidic platforms that have revolutionized biomarker discovery and validation because of their high sensitivity, specificity, and throughput levels. These chips miniaturize traditional PCR processes for the speed and precision of nucleic acid biomarker detection relevant to advancing drug development. Biomarkers, which are useful in helping to explain disease mechanisms, patient stratification, and therapeutic monitoring, are hard to identify and validate due to the complexity of biological systems and the limitations of traditional techniques. The challenges to which PCR chips respond include high-throughput capabilities coupled with real-time quantitative analysis, enabling researchers to identify novel biomarkers with greater accuracy and reproducibility. More recent design improvements of PCR chips have further expanded their functionality to also include digital and multiplex PCR technologies. Digital PCR chips are ideal for quantifying rare biomarkers, which is essential in oncology and infectious disease research. In contrast, multiplex PCR chips enable simultaneous analysis of multiple targets, therefore simplifying biomarker validation. Furthermore, single-cell PCR chips have made it possible to detect biomarkers at unprecedented resolution, hence revealing heterogeneity within cell populations. PCR chips are transforming drug development, enabling target identification, patient stratification, and therapeutic efficacy assessment. They play a major role in the development of companion diagnostics and, therefore, pave the way for personalized medicine, ensuring that the right patient receives the right treatment. While this tremendously promising technology has exhibited many challenges regarding its scalability, integration with other omics technologies, and conformity with regulatory requirements, many still prevail. Future breakthroughs in chip manufacturing, the integration of artificial intelligence, and multi-omics applications will further expand PCR chip capabilities. PCR chips will not only be important for the acceleration of drug discovery and development but also in raising the bar in improving patient outcomes and, hence, global health care as these technologies continue to mature.

Evaluation of the simultaneous effects of KRAS G12V and LCS6 alterations on the behavior of head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinomas are the seventh most common cancer accounting for 90 % of malignant neoplasia of the upper respiratory system. KRAS is a very important oncogene, leading to the suppression of apoptosis, and promoting the pathogenesis and development of tumors. MicroRNAs (miRNAs) are highly conserved, small noncoding RNA molecules aberrantly expressed in various pathologies including regulation of tumor and metastasis-associated genes. Variant (rs61764370) of the let-7 miRNA complementary site of KRAS 3'-untranslated region (KRAS-LCS6) has been shown to disrupt the ability of miRNAs to target genes resulting in differential target mRNA and protein expression.

METHODS

In this study, the effects of variant complementary site LCS6 of the let-7 miRNA in head and neck cancer were investigated in vitro using laryngeal carcinoma HEp-2 carrying G12V and LCS6 alterations in the KRAS gene. Non-cancer HEK-293 cells were also used as control cells.

RESULTS

G12V mutation in the KRAS gene increases invasion capacity and is specifically active on the ERK pathway associated with metastasis. Alteration in the LCS6 region of the KRAS gene did not show additional effects compared to cells only carrying G12V mutation. Our results also showed that the coexistence of G12V and LCS6 alterations is lethal to specific cell types, UM-SCC-17A laryngeal cancer cells in our case.

CONCLUSIONS

The LCS6 region alteration of the KRAS may play a key role in further cancer progression, and more research is needed to fully understand the mechanisms by which the LCS6 alterations promote cancer progression.

Cancer treatment approaches within the frame of hyperthermia, drug delivery systems, and biosensors: concepts and future potentials

This work presents a review of the therapeutic modalities and approaches for cancer treatment. A brief overview of the traditional treatment routes is presented in the introduction together with their reported side effects. A combination of the traditional approaches was reported to demonstrate an effective therapy until a few decades ago. With the improvement in the fabrication of nanomaterials, targeted therapy represents a novel therapeutic approach. This improvement established on nanoparticles is categorized into hyperthermia, drug delivery systems, and biosensors. Hyperthermia presents a personalized medicine-based approach in which targeted zones are heated up until the diseased tissue is destroyed by the thermal effect. The use of magnetic nanoparticles further improved the effectiveness of hyperthermia owing to the enhanced heating action, further increasing the accuracy of the targeting process. Nanoparticle-based biosensors present a smart nanodevice that can detect, monitor, and target tumor tissues by following the biomarkers in the body fluids. Magnetic nanoparticles offer a controlled thermo-responsive device that can be manipulated by changing the magnetic field, offering a more personalized and controlled hyperthermia therapeutic modality. Similarly, gold nanoparticles offer an effective aid in the hyperthermia treatment approach. Furthermore, carbon nanotubes and metal-organic frameworks present a cutting-edge approach to cancer treatment. A combination of functionalized nanoparticles offers a unique route for drug delivery systems, in which therapeutic agents carried by nanoparticles are guided into the human body and then released in the target spot.

Efficient enrichment of free target sequences in an integrated microfluidic device for point-of-care detection systems

Nucleic acid biomarker detection has great importance in the diagnosis of disease, the monitoring of disease progression and the classification of patients according to treatment decision making. Nucleic acid biomarkers found in the blood of patients have generated a lot of interest due to the possibility of being detected non-invasively which makes them ideal for monitoring and screening tests and particularly amenable to point-of-care (POC) or self-testing. A major challenge to POC molecular diagnostics is the need to enrich the target to optimise detection. In this work, we describe a microfabricated device for the enrichment of short dsDNA target sequences, which is especially valuable for potential detection methods, as it improves the probability of effectively detecting the target in downstream analyses. The device integrated a heating element and a temperature sensor with a microfluidic chamber to carry out the denaturation of the dsDNA combined with blocking-probes to enrich the target. This procedure was validated by fluorescence resonance energy transfer (FRET) technique, labelling DNA with a fluorophore and a quencher. As proof of concept, a 23-mer long dsDNA sequence corresponding to the L858R mutation of the EGFR gene was used. The qualitative results obtained determined that the most optimal blocking rate was obtained with the incorporation of 11/12-mer blocking-probes at a total concentration of 6 μM. This device is a powerful DNA preparation tool, which is an indispensable initial step for subsequent detection of sequences via nucleic acid hybridisation methods.

Exploring the potential of genetic analysis in historical blood spots for patients with iodine-deficient goiter and thyroid carcinomas in Switzerland and Germany (1929-1989)

Iodine deficiency-induced goiter continues to be a global public health concern, with varying manifestations based on geography, patient's age, and sex. To gain insights into clinical occurrences, a retrospective study analyzed medical records from patients with iodine deficiency-induced goiter or thyroid cancer who underwent surgery at the Community Hospital in Riehen, Switzerland, between 1929 and 1989. Despite today's adequate iodine supplementation, a significant risk for iodine-independent goiter remains in Switzerland, suggesting that genetic factors, among others, might be involved. Thus, a pilot study exploring the feasibility of genetic analysis of blood spots from these medical records was conducted to investigate and enhance the understanding of goiter development, potentially identify genetic variations, and explore the influence of dietary habits and other environmental stimuli on the disease.Blood prints from goiter patients' enlarged organs were collected per decade from medical records. These prints had been made by pressing, drawing, or tracing (i.e., pressed and drawn) the removed organs onto paper sheets. DNA analysis revealed that its yields varied more between the prints than between years. A considerable proportion of the samples exhibited substantial DNA degradation unrelated to sample collection time and DNA mixtures of different contributors. Thus, each goiter imprint must be individually evaluated and cannot be used to predict the success rate of genetic analysis in general. Collecting a large sample or the entire blood ablation for genetic analysis is recommended to mitigate potential insufficient DNA quantities. Researchers should also consider degradation and external biological compounds' impact on the genetic analysis of interest, with the dominant contributor anticipated to originate from the patient's blood.

Electrochemical biosensors for early diagnosis of glioblastoma

Glioblastoma (GBM) is a highly aggressive and life-threatening neurological malignancy of predominant astrocyte origin. This type of neoplasm can develop in either the brain or the spine and is also known as glioblastoma multiforme. Although current diagnostic methods such as magnetic resonance imaging (MRI) and positron emission tomography (PET) facilitate tumor location, these approaches are unable to assess disease severity. Furthermore, interpretation of imaging studies requires significant expertise which can have substantial inter-observer variability, thus challenging diagnosis and potentially delaying treatment. In contrast, biosensing systems offer a promising alternative to these traditional approaches. These technologies can continuously monitor specific molecules, providing valuable real-time data on treatment response, and could significantly improve patient outcomes. Among various types of biosensors, electrochemical systems are preferred over other types, as they do not require expensive or complex equipment or procedures and can be made with readily available materials and methods. Moreover, electrochemical biosensors can detect very small amounts of analytes with high accuracy and specificity by using various signal amplification strategies and recognition elements. Considering the advantages of electrochemical biosensors compared to other biosensing methods, we aim to highlight the potential application(s) of these sensors for GBM theranostics. The review's innovative insights are expected to antecede the development of novel biosensors and associated diagnostic platforms, ultimately restructuring GBM detection strategies.

Recent advances in label-free optical, electrochemical, and electronic biosensors for glioma biomarkers

Gliomas are the most commonly occurring primary brain tumor with poor prognosis and high mortality rate. Currently, the diagnostic and monitoring options for glioma mainly revolve around imaging techniques, which often provide limited information and require supervisory expertise. Liquid biopsy is a great alternative or complementary monitoring protocol that can be implemented along with other standard diagnosis protocols. However, standard detection schemes for sampling and monitoring biomarkers in different biological fluids lack the necessary sensitivity and ability for real-time analysis. Lately, biosensor-based diagnostic and monitoring technology has attracted significant attention due to several advantageous features, including high sensitivity and specificity, high-throughput analysis, minimally invasive, and multiplexing ability. In this review article, we have focused our attention on glioma and presented a literature survey summarizing the diagnostic, prognostic, and predictive biomarkers associated with glioma. Further, we discussed different biosensory approaches reported to date for the detection of specific glioma biomarkers. Current biosensors demonstrate high sensitivity and specificity, which can be used for point-of-care devices or liquid biopsies. However, for real clinical applications, these biosensors lack high-throughput and multiplexed analysis, which can be achieved via integration with microfluidic systems. We shared our perspective on the current state-of-the-art different biosensor-based diagnostic and monitoring technologies reported and the future research scopes. To the best of our knowledge, this is the first review focusing on biosensors for glioma detection, and it is anticipated that the review will offer a new pathway for the development of such biosensors and related diagnostic platforms.

Prognostic evaluation and immune infiltration analysis of five bioinformatic selected genes in hepatocellular carcinoma

Despite the development in hepatocellular carcinoma (HCC) treatment in recent years, the therapeutic outcome of HCC remains unfavourable. This study examines the prognosis of HCC from a genetic level using clinical databases and single‐cell data to identify genes with a high prognostic value. Three up‐regulated genes (UBE2S, PTTG1, and CDC20) and two down‐regulated genes (SOCS2 and DNASE1L3) in HCC tissues were identified. Various analyses confirmed its correlation with tumour stage (p < 0.01) and patient survival time (log‐rank p < 0.001). Immune analysis, single‐cell analysis, and gene set enrichment analysis (GSEA) were employed to provide insight on how they affect cancer progression, and we observed a close relation between these genes and tumour immune infiltration. Eventually, we constructed a risk score system that risk score = (0.0465) × UBE2S + (0.1851) × CDC20 + (−0.0461) × DNASE1L3 + (−0.2279) × SOCS2 (5‐year area under curve = 0.706). The risk score system may serve as an effective novel prognostic system for HCC patients. This study might provide novel ideas for prognostic or therapeutic biomarkers for HCC.

Hypermethylation of DHRS3 as a Novel Tumor Suppressor Involved in Tumor Growth and Prognosis in Gastric Cancer

Background/Aims

The role of DHRS3 in human cancer remains unclear. Our study explored the role of DHRS3 in gastric cancer (GC) and its clinicopathological significance and associated mechanisms.

Materials

Bisulfite-assisted genomic sequencing PCR and a Mass-Array system were used to evaluate and quantify the methylation levels of the promoter. The expression levels and biological function of DHRS3 was examined by both in vitro and in vivo assays. A two-way hierarchical cluster analysis was used to classify the methylation profiles, and the correlation between the methylation status of the DHRS3 promoter and the clinicopathological characteristics of GC were then assessed.

Results

The DHRS3 promoter was hypermethylated in GC samples, while the mRNA and protein levels of DHRS3 were significantly downregulated. Ectopic expression of DHRS3 in GC cells inhibited cell proliferation and migration in vitro, decreased tumor growth in vivo. DHRS3 methylation was correlated with histological type and poor differentiation of tumors. GC patients with high degrees of CpG 9.10 methylation had shorter survival times than those with lower methylation.

Conclusion

DHRS3 was hypermethylated and downregulated in GC patients. Reduced expression of DHRS3 is implicated in gastric carcinogenesis, which suggests DHRS3 is a tumor suppressor.

Exploring the Interdisciplinary Nature of Precision Medicine：Network Analysis and Visualization

Background

Interdisciplinary research is an important feature of precision medicine. However, the accurate cross-disciplinary status of precision medicine is still unclear.

Objective

The aim of this study is to present the nature of interdisciplinary collaboration in precision medicine based on co-occurrences and social network analysis.

Methods

A total of 7544 studies about precision medicine, published between 2010 and 2019, were collected from the Web of Science database. We analyzed interdisciplinarity with descriptive statistics, co-occurrence analysis, and social network analysis. An evolutionary graph and strategic diagram were created to clarify the development of streams and trends in disciplinary communities.

Results

The results indicate that 105 disciplines are involved in precision medicine research and cover a wide range. However, the disciplinary distribution is unbalanced. Current cross-disciplinary collaboration in precision medicine mainly focuses on clinical application and technology-associated disciplines. The characteristics of the disciplinary collaboration network are as follows: (1) disciplinary cooperation in precision medicine is not mature or centralized; (2) the leading disciplines are absent; (3) the pattern of disciplinary cooperation is mostly indirect rather than direct. There are 7 interdisciplinary communities in the precision medicine collaboration network; however, their positions in the network differ. Community 4, with disciplines such as genetics and heredity in the core position, is the most central and cooperative discipline in the interdisciplinary network. This indicates that Community 4 represents a relatively mature direction in interdisciplinary cooperation in precision medicine. Finally, according to the evolution graph, we clearly present the development streams of disciplinary collaborations in precision medicine. We describe the scale and the time frame for development trends and distributions in detail. Importantly, we use evolution graphs to accurately estimate the developmental trend of precision medicine, such as biological big data processing, molecular imaging, and widespread clinical applications.

Conclusions

This study can help researchers, clinicians, and policymakers comprehensively understand the overall network of interdisciplinary cooperation in precision medicine. More importantly, we quantitatively and precisely present the history of interdisciplinary cooperation and accurately predict the developing trends of interdisciplinary cooperation in precision medicine.

Integrative Analysis of DNA Methylation and Gene Expression Identified Follicular Thyroid Cancer-Specific Diagnostic Biomarkers

The diagnosis of follicular thyroid carcinoma (FTC) prior surgical resection remains a challenge, as routine screening methods, such as ultrasound or even FNAB, could not diagnose FTC preoperatively. Here, we performed an integrative analysis of DNA methylation and RNA array data from our own cohort (14 Follicular thyroid carcinoma vs 16 Benign thyroid lesion) to identify thyroid cancer-specific DNA methylation markers. We first identified differentially methylated and expressed genes and examined their correlations. Candidate DNA methylation sites were selected and further verified in validation set. Among all candidate methylation sites, cg06928209 was the most promising site as a molecular marker for early diagnosis, with a sensitivity of 90%, a specificity of 80% and an AUC of 0.77. Overall, our study demonstrates the potential use of methylation markers in FTC diagnosis and may boost the development of new epigenetic therapies.

Elevated exposure to polycyclic aromatic hydrocarbons (PAHs) may trigger cancers in Pakistan: an environmental, occupational, and genetic perspective

Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic compounds which are emitted through incomplete combustion of organic materials, fossil fuels, consumption of processed meat, smoked food, and from various industrial activities. High molecular mass and mobility make PAHs widespread and lethal for human health. A cellular system in human detoxifies these toxicants through specialized enzymatic machinery called xenobiotic-metabolizing (CYP450) and phase-II (GSTs) enzymes (XMEs). These metabolizing enzymes include cytochromes P450 family (CYP1, CYP2), glutathione s-transferases, and ALDHs. Gene polymorphisms in XMEs encoding genes can compromise their metabolizing capacity to detoxify ingested carcinogens (PAHs etc.) that may lead to prolong and elevated exposure to ingested toxicants and may consequently lead to cancer. Moreover, PAHs can induce cancer through reprograming XMEs' gene functions by altering their epigenetic markers. This review article discusses possible interplay between individual's gene polymorphism in XMEs' genes, their altered epigenetic markers, and exposure to PAHs in cancer susceptibility in Pakistan.

Biosensor-based diagnostic approaches for various cellular biomarkers of breast cancer: A comprehensive review

Breast cancer is the most commonly occurring cancer among women which leads to thousands of deaths worldwide. The chances of survival are more if the breast cancer is diagnosed at early stage. At present, mammography, magnetic resonance imaging, ultrasound and tissue biopsies are the main diagnostic techniques available for the detection of breast cancer. However, despite of offering promising results, requirement of expensive setup, skilled supervision, expert analysis, invasive procedure (biopsy) and low capacity of multiplexing are the main limitations of these diagnostic techniques. Due to high cost, these screening tests are out of reach of people belonging to low socioeconomic groups and this poses serious health burden to the society. Recently, biosensor-based diagnostic technology for early detection of various types of cancers and other non-oncological disorders have gained considerable attention because of their several advantageous features over existing diagnostic technologies such as high throughput, noninvasive nature, cost effectiveness, easy interpretable results and capacity for multiplexing. Further, biosensors can be designed for biomarkers which are confined to particular type of cancer. In this review, we have discussed about various genomic, transcriptomic, proteomic and metabolomic biomarkers associated with breast cancer, various biosensors-based diagnostic approaches designed for detection of specific biomarkers associated with breast cancer are also described. Further, this review throws insight on various biomarkers linked with breast cancer which can be effectively exploited to develop new diagnostic technology. The assessment of these biomarkers associated with BC using biosensors in large population are cost-effective, non-invasive and high throughput. They help in risk assessment of disease at very initial stage even in backward areas and also help to lower the disease burden of society and economic cost of treatment for a common man. This review would provide new avenues for the development of biosensor based diagnostic technology for the detection of biomarkers associated with breast cancer.

Cancer Biomarker-Triggered Disintegrable DNA Nanogels for Intelligent Drug Delivery

Even though various techniques have been developed thus far for targeted delivery of therapeutics, design and fabrication of cancer biomarker-triggered disintegrable nanogels, which are exclusively composed of nucleic acid macromolecules, are still challenging nowadays. Here, we describe for the first time our creation of intelligent DNA nanogels whose backbones are sorely disintegrable by flap endonuclease 1 (FEN1), an enzymatic biomarker that is highly overexpressed in most cancer cells but not in their normal counterparts. It is the catalytic actions of intracellular FEN1 on bifurcated DNA structures that lead to the cancer-specific disintegration of our DNA nanogels and controlled release of drugs in target cancer cells. Consequently, the brand-new strategies introduced in the current report could break new ground in designing drug carriers for eliminating unwanted side effects of chemotherapeutic agents and live-cell probes for cancer risk assessment, diagnosis, and prognosis.

Host-dependent variables: The missing link to personalized medicine

Individualized medicine has the potential to tailor anticancer therapy with the best response and highest safety margin to provide better patient care. However, modern targeted therapies are still being tested through clinical trials comparing preselected patient cohorts and assessed upon behaviour of group averages. Clinically manifesting malignant disease requires identification of host- and tumour-dependent variables such as biological characteristics of the tumour and its microenvironment including immune response features, and overall capacity of the host to receive, tolerate and efficiently utilize treatment. Contemporary medical oncology including clinical trial design need to refocus from assessing group averages to individuality taking into consideration time dependent host-associated characteristics and reinventing outliers to be appreciated as naturally occurring variables collectively determining the ultimate outcome of malignant disease.

Potential prognostic biomarkers in pancreatic juice of resectable pancreatic ductal adenocarcinoma

Despite potentially curative surgery pancreatic cancer has a dismal prognosis. Serum cancer antigen 19-9 (CA 19-9) correlates with tumor burden, resectability and survival in patients with pancreatic ductal adenocarcinoma. Identification of novel biomarkers may facilitate early diagnosis of pancreatic cancer and improve survival. Pancreatic juice is a rich source of cancer-specific proteins rendering it a promising tool for identifying biomarkers. Recent proteomic and microRNA expression analyses have identified several biomarkers of potential diagnostic and prognostic value. Tumor markers CA 19-9 and carcinoembryonic antigen (CEA) are widely used in the characterization of premalignant and malignant lesions of the pancreas. Elevated level of CEA in bile is a marker for malignancy and a predictor of hepatic recurrence. The potential value of CA 19-9, CEA and lactate dehydrogenase as prognostic biomarkers in pancreatic juice and bile is unknown. Specimens of pancreatic juice and bile can be readily collected during surgical resection of the tumor. Profiling of pancreatic juice and bile to identify novel prognostic biomarkers may improve selection of patients for adjuvant therapy with a favorable impact on overall survival in patients diagnosed with pancreatic cancer.

Genome-wide copy number analysis reveals candidate gene loci that confer susceptibility to high-grade prostate cancer

BACKGROUND

Two key issues in prostate cancer (PCa) that demand attention currently are the need for a more precise and minimally invasive screening test owing to the inaccuracy of prostate-specific antigen and differential diagnosis to distinguish advanced vs. indolent cancers. This continues to pose a tremendous challenge in diagnosis and prognosis of PCa and could potentially lead to overdiagnosis and overtreatment complications. Copy number variations (CNVs) in the human genome have been linked to various carcinomas including PCa. Detection of these variants may improve clinical treatment as well as an understanding of the pathobiology underlying this complex disease.

METHODS

To this end, we undertook a pilot genome-wide CNV analysis approach in 36 subjects (18 patients with high-grade PCa and 18 controls that were matched by age and ethnicity) in search of more accurate biomarkers that could potentially explain susceptibility toward high-grade PCa. We conducted this study using the array comparative genomic hybridization technique. Array results were validated in 92 independent samples (46 high-grade PCa, 23 benign prostatic hyperplasia, and 23 healthy controls) using polymerase chain reaction-based copy number counting method.

RESULTS

A total of 314 CNV regions were found to be unique to PCa subjects in this cohort (P<0.05). A log₂ ratio-based copy number analysis revealed 5 putative rare or novel CNV loci or both associated with susceptibility to PCa. The CNV gain regions were 1q21.3, 15q15, 7p12.1, and a novel CNV in PCa 12q23.1, harboring ARNT, THBS1, SLC5A8, and DDC genes that are crucial in the p53 and cancer pathways. A CNV loss and deletion event was observed at 8p11.21, which contains the SFRP1 gene from the Wnt signaling pathway. Cross-comparison analysis with genes associated to PCa revealed significant CNVs involved in biological processes that elicit cancer pathogenesis via cytokine production and endothelial cell proliferation.

CONCLUSION

In conclusion, we postulated that the CNVs identified in this study could provide an insight into the development of advanced PCa.

Computational Analysis of Specific MicroRNA Biomarkers for Noninvasive Early Cancer Detection

Cancer is a complex disease residing in various tissues of human body, accompanied with many abnormalities and mutations in genomes, transcriptome, and epigenome. Early detection plays a crucial role in extending survival time of all major cancer types. Recent advances in microarray and sequencing techniques have given more support to identifying effective biomarkers for early detection of cancer. MicroRNAs (miRNAs) are more and more frequently used as candidates for biomarkers in cancer related studies due to their regulation of target gene expression. In this paper, the comparative analysis is used to discover miRNA expression patterns in cancer versus normal samples on early stage of eight prevalent cancer types. Our work focuses on the specific miRNAs biomarkers identification and function analysis. Several identified miRNA biomarkers in this paper are matched well with those reported in existing researches, and most of them could serve as potential candidate indicators for clinical early diagnosis applications.

The Role of Epigenomics in the Study of Cancer Biomarkers and in the Development of Diagnostic Tools

Epigenetics plays a key role in cancer development. Genetics alone cannot explain sporadic cancer and cancer development in individuals with no family history or a weak family history of cancer. Epigenetics provides a mechanism to explain the development of cancer in such situations. Alterations in epigenetic profiling may provide important insights into the etiology and natural history of cancer. Because several epigenetic changes occur before histopathological changes, they can serve as biomarkers for cancer diagnosis and risk assessment. Many cancers may remain asymptomatic until relatively late stages; in managing the disease, efforts should be focused on early detection, accurate prediction of disease progression, and frequent monitoring. This chapter describes epigenetic biomarkers as they are expressed during cancer development and their potential use in cancer diagnosis and prognosis. Based on epigenomic information, biomarkers have been identified that may serve as diagnostic tools; some such biomarkers also may be useful in identifying individuals who will respond to therapy and survive longer. The importance of analytical and clinical validation of biomarkers is discussed, along with challenges and opportunities in this field.

Epigenetic biomarkers in liver cancer

Liver cancer (hepatocellular carcinoma or HCC) is a major cancer worldwide. Research in this field is needed to identify biomarkers that can be used for early detection of the disease as well as new approaches to its treatment. Epigenetic biomarkers provide an opportunity to understand liver cancer etiology and evaluate novel epigenetic inhibitors for treatment. Traditionally, liver cirrhosis, proteomic biomarkers, and the presence of hepatitis viruses have been used for the detection and diagnosis of liver cancer. Promising results from microRNA (miRNA) profiling and hypermethylation of selected genes have raised hopes of identifying new biomarkers. Some of these epigenetic biomarkers may be useful in risk assessment and for screening populations to identify who is likely to develop cancer. Challenges and opportunities in the field are discussed in this chapter.

DNA methylation biomarkers: cancer and beyond

Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient's response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.

Biomarkers of HIV-associated Cancer

Cancer biomarkers have provided great opportunities for improving the management of cancer patients by enhancing the efficiency of early detection, diagnosis, and efficacy of treatment. Every cell type has a unique molecular signature, referred to as biomarkers, which are identifiable characteristics such as levels or activities of a myriad of genes, proteins, or other molecular features. Biomarkers can facilitate the molecular definition of cancer, provide information about the course of cancer, and predict response to chemotherapy. They offer the hope of early detection as well as tracking disease progression and recurrence. Current progress in the characterization of molecular genetics of HIV-associated cancers may form the basis for improved patient stratification and future targeted or individualized therapies. Biomarker use for cancer staging and personalization of therapy at the time of diagnosis could improve patient care. This review focuses on the relevance of biomarkers in the most common HIV-associated malignancies, namely, Kaposi sarcoma, non-Hodgkin’s lymphoma, and invasive cervical cancer.

Prognostic significance of serum beta-2 microglobulin in patients with non-Hodgkin lymphoma

BACKGROUND AND OBJECTIVE

Elevated serum beta-2 microglobulin (β2-M) has previously been reported in non-Hodgkin lymphoma (NHL) patients. This study examined the association between serum β2-M and the prognosis of NHL and analyzed its predictive value.

METHOD

A total of 287 NHL patients from Taiyuan, Shanxi, China, participated in a prospective cohort study between 2008 and 2011. Overall survival (OS) was compared between NHL patients with high and normal β2-M levels using the log-rank test. Three standard Cox regression models including the International Prognostic Index (IPI) score, β2-M or IPI score+β2-M as independent variables were constructed. The time-dependent receiver operating characteristic curves method and C index were used to examine the tendency of the models' predictive accuracy over time.

RESULTS

NHL patients with elevated β2-M values had worse OS (p<0.001) and higher mortality risk (HR=1.93, 95% CI 1.37-2.77, p<0.001) than patients with normal β2-M values. There were statistically significant differences between the C indexes for the models with IPI+β2-M, IPI or β2-M alone (p<0.001).

CONCLUSION

Our results demonstrated an association between serum β2-M and NHL prognosis. Combining β2-M with IPI may help to improve the prognostic accuracy of NHL.

Serum-based protein biomarkers for detection of lung cancer

Lung cancer is one of the most common cancers in terms of both incidence and mortality.The major reasons for the increasing number of deaths from lung cancer are late detection and lack of effective therapies. To improve our understanding of lung cancer biology, there is urgent need for blood-based, non-invasive molecular tests to assist in its detection in a cost-effective manner at an early stage when curative interventions are still possible. Recent advances in proteomic technology have provided extensive, high throughput analytical tools for identification, characterization and functional studies of proteomes. Changes in protein expression patterns in response to stimuli can serve as indicators or biomarkers of biological and pathological processes as well as physiological and pharmacological responses to drug treatment, thus aiding in early diagnosis and prognosis of disease. However, only a few biomarkers have been approved by the FDA to date for screening and diagnostic purposes. This review provides a brief overview of currently available proteomic techniques, their applications and limitations and the current state of knowledge about important serum biomarkers in lung cancer and their potential value as prognostic and diagnostic tools.

Aberrant promoter methylation of beta-1,4 galactosyltransferase 1 as potential cancer-specific biomarker of colorectal tumors

Epigenetic alterations, such as CpG islands methylation and histone modifications, are recognized key characteristics of cancer. Glycogenes are a group of genes which epigenetic status was found to be changed in several tumors. In this study, we determined promoter methylation status of the glycogene beta-1,4-galactosyltransferase 1 (B4GALT1) in colorectal cancer patients. Methylation status of B4GALT1 was assessed in 130 colorectal adenocarcinomas, 13 adenomas, and in paired normal tissue using quantitative methylation specific PCR (QMSP). B4GALT1 mRNA expression was evaluated in methylated/unmethylated tumor and normal specimens. We also investigated microsatellite stability and microsatellite instability status and KRAS/BRAF mutations. Discriminatory power of QMSP was assessed by receiving operating curve (ROC) analysis on a training set of 24 colorectal cancers and paired mucosa. The area under the ROC curve (AUC) was 0.737 (95% confidence interval [CI]:0.591-0.881, P = 0.005) with an optimal cutoff value of 2.07 yielding a 54% sensitivity (95% CI: 35.1%-72.1%) and a specificity of 91.7% (95% CI: 74.1%-97.7%). These results were confirmed in an independent validation set where B4GALT1 methylation was detected in 52/106 patients. An inverse correlation was observed between methylation and B4GALT1 mRNA expression levels (r = -0.482, P = 0.037). Significant differences in methylation levels and frequencies was demonstrated in invasive lesions as compared with normal mucosa (P = 0.0001) and in carcinoma samples as compared with adenoma (P = 0.009). B4GALT1 methylation is a frequent and specific event in colorectal cancer and correlates with downregulation of mRNA expression. These results suggest that the glycogene B4GALT1 represent a valuable candidate biomarker of invasive phenotype of colorectal cancer.

Potential molecular approaches for the early diagnosis of lung cancer (review)

Lung cancer is the leading cause of mortality from cancer among men and women worldwide. More individuals die each year of lung cancer than of colon, breast and prostate cancer combined. Despite new diagnostic techniques, the overall 5-year survival rate remains at approximately 15% and the majority of patients still present with advanced disease. Therefore, lung cancer is the most lethal cancer at present. Diagnosing and treating cancer at its early stages, ideally during the precancerous stages, could increase the 5-year survival rate by 3-4‑fold, with the possibility of cure. To date, no screening method has been shown to decrease the disease-specific mortality rate. This review describes issues related to early lung cancer screening and their rationale, the management of primary cancers detected by screening and the different approaches that have been tested for cancer screening; these include imaging techniques, bronchoscopies and molecular screening, such as analysis of epigenomics using different noninvasive or invasive sources, such as blood, sputum, bronchoscopic samples and exhaled breath.

Epigenetic biomarkers in cancer epidemiology

Biochemical, epigenetic, genetic, and imaging biomarkers are used to identify people at high risk for developing cancer. In cancer epidemiology, epigenetic biomarkers offer advantages over other types of biomarkers because they are expressed against a person's genetic background and environmental exposure, and because epigenetic events occur early in cancer development. This chapter describes epigenetic biomarkers that are being used to study the epidemiology of different types of cancer. Because epigenetic alterations can be reversed by chemicals and activate gene expression, epigenetic biomarkers potentially have numerous clinical applications in cancer intervention and treatment and significant implications in public health. This review discusses cancer biomarkers, the characteristics of an ideal biomarker for cancer, and technologies for biomarker detection.

Pancreatic cancer biomarkers and their implication in cancer diagnosis and epidemiology

Pancreatic cancer is the fourth most common cause of cancer-related mortality in the United States. Biomarkers are needed to detect this cancer early during the disease development and for screening populations to identify those who are at risk. In cancer, “biomarker” refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker might be either a molecule secreted by a tumor or it can be a specific response of the body to the presence of cancer. Genetic, epigenetic, proteomic, glycomic, and imaging biomarkers can be used for cancer diagnosis, prognosis, and epidemiology. A number of potential biomarkers have been identified for pancreatic cancer. These markers can be assayed in non-invasively collected biofluids. These biomarkers need analytical and clinical validation so that they can be used for the purpose of screening and diagnosing pancreatic cancer and determining disease prognosis. In this article, the latest developments in pancreatic cancer biomarkers are discussed.

Epigenetic mechanisms in cancer

After the completion of the human genome, a need was identified by scientists to look for a functional map of the human genome. Epigenomics provided functional characteristics of genes identified in the genome. Epigenetics is the alteration in gene expression (function) without changing the nucleotide sequence. Both activation and inactivation of cancer-associated genes can occur by epigenetic mechanisms. The major players in epigenetic mechanisms of gene regulation are DNA methylation, histone deacetylation, chromatin remodeling, small noncoding RNA expression and gene imprinting. In the last few years, epigenetic mechanisms have been studied in a number of tumor types and epigenetic markers have been identified that are suitable for cancer detection, diagnosis, follow-up of treatment and screening high-risk populations. One interesting aspect of epigenetics is the reactivation of genes by successful reversion of some epigenetic changes using chemicals. The reversibility of epigenetic aberrations has made them attractive targets for cancer treatment with modulators that demethylate DNA and inhibit histone deacetylases, leading to the reactivation of silenced genes. In this article, we have described the current status of this powerful science and discussed the challenges in the clinical fields where epigenetic approaches in cancer are applied.

Cancer biomarkers: are we ready for the prime time?

A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. In cancer, a biomarker refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker might be either a molecule secreted by a tumor or it can be a specific response of the body to the presence of cancer. Genetic, epigenetic, proteomic, glycomic, and imaging biomarkers can be used for cancer diagnosis, prognosis and epidemiology. These markers can be assayed in non-invasively collected biofluids. However, few cancer biomarkers are highly sensitive and specific for cancer detection at the present time. Consequently, biomarkers are not yet ready for routine use due to challenges in their clinical validation for early disease detection, diagnosis and monitoring to improve long-term survival of patients.

DNA methylation based biomarkers in non-invasive cancer screening

DNA methylation plays a critical role in the regulation of gene expression, differentiation and in the development of cancer and other diseases. Hypermethylation of CpG islands located in the promoter regions of tumor suppressor genes is now firmly established as the most frequent mechanism for gene inactivation in cancers. Feasibility of using DNA methylation based biomarkers for early detection of cancer has been shown. Potential of using DNA methylation for prediction of therapeutic outcome and patient survival has also been shown. DNA originated from cancer cells has been routinely detected in clinical specimens (ex. Plasma/serum, sputum, urine etc.) from cancer patients. Presence of methylated DNA sequences in clinical specimens and potential of using them as biomarkers have been recognized. Novel methylation based biomarkers that can be used in clinical specimens, obtained non-invasively from cancer patients, offer significant practical advantages. More resources need to be committed to this area of biomarker research. Thus, we review recent findings on DNA methylation based cancer biomarkers with particular focus on these applicable to the clinical specimens obtained non-invasively from cancer patients.

Epigenetic targets in cancer epidemiology

Recently, it has been shown that epigenetic changes are involved in early stages of tumorigenesis, and they may trigger the genetic events leading to tumor development. In cancer epidemiology, there are several epigenetic alterations involved, such as DNA hypermethylation, DNA hypomethylation, and chromatin modifications with critical roles in the initiation and progression of human neoplasms. This chapter discusses the hypermethylation profiles of several tumor types, including bladder, brain, breast, colorectal, ovarian, prostate, and other cancers as well as DNA hypomethylation phenomena together with the chromatin modifications and their role in the complex mechanism of epigenetic silencing. Moreover, the involvement of environmental exposures in cancer susceptibility is addressed. In conclusion, these epigenetic changes are important characteristics of human neoplasia, and a better understanding of these modifications and the link between these changes for each tumor type will be important in early diagnosis of cancer and cancer prevention.