The application of single nucleotide polymorphism microarrays in cancer research

Molecular methods in cancer diagnostics: a short review

BACKGROUND

One of the ailments with the greatest fatality rates in the 21st century is cancer. Globally, molecular methods are widely employed to treat cancer-related disorders, and the body of research on this subject is growing yearly. A thorough and critical summary of the data supporting molecular methods for illnesses linked to cancer is required.

OBJECTIVE

In order to guide clinical practice and future research, it is important to examine and summarize the systematic reviews (SRs) that evaluate the efficacy and safety of molecular methods for disorders associated to cancer.

METHODS

We developed a comprehensive search strategy to find relevant articles from electronic databases like PubMed, Google Scholar, Web of Science (WoS), or Scopus. We looked through the literature and determined which diagnostic methods in cancer genetics were particularly reliable. We used phrases like 'cancer genetics', genetic susceptibility, Hereditary cancer, cancer risk assessment, 'cancer diagnostic tools', cancer screening', biomarkers, and molecular diagnostics, reviews and meta-analyses evaluating the efficacy and safety of molecular therapies for cancer-related disorders. Research that only consider treatment modalities that don't necessitate genetic or molecular diagnostics fall under the exclusion criteria.

RESULTS

The results of this comprehensive review clearly demonstrate the transformative impact of molecular methods in the realm of cancer genetics.This review underscores how these technologies have empowered researchers and clinicians to identify and understand key genetic alterations that drive malignancy, ranging from point mutations to structural variations. Such insights are instrumental in pinpointing critical oncogenic drivers and potential therapeutic targets, thus opening the door for methods in precision medicine that can significantly improve patient outcomes.

LIMITATION

The search does not specify a timeframe for publication inclusion, it may have missed recent advancements or changes in the field's landscape of molecular methods for cancer. As a result, it may not have included the most recent developments in the field.

CONCLUSION

After conducting an in-depth study on the molecular methods in cancer genetics, it is evident that these cutting-edge technologies have revolutionized the field of oncology, providing researchers and clinicians with powerful tools to unravel the complexities of cancer at the genetic level. The integration of molecular methods techniques has not only enhanced our understanding of cancer etiology, progression, and treatment response but has also opened new avenues for personalized medicine and targeted therapies, leading to improved patient outcomes.

Advancements and Applications of Preimplantation Genetic Testing in In Vitro Fertilization: A Comprehensive Review

Preimplantation genetic testing (PGT) has become an integral component of assisted reproductive technology (ART), offering couples the opportunity to screen embryos for genetic abnormalities before implantation during in vitro fertilization (IVF). This comprehensive review explores the advancements and applications of PGT in IVF, covering its various types, technological developments, clinical applications, efficacy, challenges, regulatory aspects, and future directions. The evolution of PGT techniques, including next-generation sequencing (NGS) and comparative genomic hybridization (CGH), has significantly enhanced the accuracy and reliability of genetic testing in embryos. PGT holds profound implications for the future of ART by improving IVF success rates, reducing the incidence of genetic disorders, and mitigating the emotional and financial burdens associated with failed pregnancies and genetic diseases. Recommendations for clinicians, researchers, and policymakers include staying updated on the latest PGT techniques and guidelines, exploring innovative technologies, establishing clear regulatory frameworks, and fostering collaboration to maximize the potential benefits of PGT in assisted reproduction. Overall, this review provides valuable insights into the current state of PGT and its implications for the field of reproductive medicine.

Primary mediastinal large B-cell lymphoma is characterized by large-scale copy-neutral loss of heterozygosity

Development of primary mediastinal B-cell lymphoma (PMBL) is driven by cumulative genomic aberrations. We discovered a unique copy-neutral loss of heterozygosity (CN-LOH) landscape of PMBL which distinguishes this tumour from other B-cell malignancies, including the biologically related diffuse large B-cell lymphoma. Using single nucleotide polymorphism array analysis we identified large-scale CN-LOH lesions in 91% (30/33) of diagnostic PMBLs and both investigated PMBL-derived cell lines. Altogether, the cohort showed 157 extra-large (25.3-248.4 Mb) CN-LOH lesions affecting up to 14 chromosomes per case (mean of 4.4) and resulting in a reduction of heterozygosity an average of 9.9% (range 1.3-51%) of the genome. Predominant involvement of terminal chromosomal segments suggests the implication of B-cell specific crossover events in the pathogenesis of PMBL. Notably, CN-LOH stretches non-randomly clustered on 6p (60%), 15 (37.2%) and 17q (40%), and frequently co-occurred with homozygous mutations in the MHC I (6p21), B2M (15q15) and GNA13 (17q23) genes, respectively, as shown by preliminary whole-exome/genome sequencing data. Altogether, our findings implicate CN-LOH as a novel and distinct mutational process contributing to the molecular pathogenesis of PMBL. The aberration acting as 'second hit' in the Knudson hypothesis, ranks as the major mechanism converting to homozygosity the PMBL-related driver genes. Screening of the cohort of 199 B cell leukamia/lymphoma whole-genomes revealed significant differences in the CN-LOH landscape of PMBL and other B-cell malignancies, including the biologically related diffuse large B-cell lymphoma.

Genomics in medicine: A new era in medicine

The sequencing of complete human genome revolutionized the genomic medicine. However, the complex interplay of gene-environment-lifestyle and influence of non-coding genomic regions on human health remain largely unexplored. Genomic medicine has great potential for diagnoses or disease prediction, disease prevention and, targeted treatment. However, many of the promising tools of genomic medicine are still in their infancy and their application may be limited because of the limited knowledge we have that precludes its use in many clinical settings. In this review article, we have reviewed the evolution of genomic methodologies/tools, their limitations, and scope, for current and future clinical application.

Genetic variations analysis for complex brain disease diagnosis using machine learning techniques: opportunities and hurdles

BACKGROUND AND OBJECTIVES

This paper presents an in-depth review of the state-of-the-art genetic variations analysis to discover complex genes associated with the brain's genetic disorders. We first introduce the genetic analysis of complex brain diseases, genetic variation, and DNA microarrays. Then, the review focuses on available machine learning methods used for complex brain disease classification. Therein, we discuss the various datasets, preprocessing, feature selection and extraction, and classification strategies. In particular, we concentrate on studying single nucleotide polymorphisms (SNP) that support the highest resolution for genomic fingerprinting for tracking disease genes. Subsequently, the study provides an overview of the applications for some specific diseases, including autism spectrum disorder, brain cancer, and Alzheimer's disease (AD). The study argues that despite the significant recent developments in the analysis and treatment of genetic disorders, there are considerable challenges to elucidate causative mutations, especially from the viewpoint of implementing genetic analysis in clinical practice. The review finally provides a critical discussion on the applicability of genetic variations analysis for complex brain disease identification highlighting the future challenges.

METHODS

We used a methodology for literature surveys to obtain data from academic databases. Criteria were defined for inclusion and exclusion. The selection of articles was followed by three stages. In addition, the principal methods for machine learning to classify the disease were presented in each stage in more detail.

RESULTS

It was revealed that machine learning based on SNP was widely utilized to solve problems of genetic variation for complex diseases related to genes.

CONCLUSIONS

Despite significant developments in genetic diseases in the past two decades of the diagnosis and treatment, there is still a large percentage in which the causative mutation cannot be determined, and a final genetic diagnosis remains elusive. So, we need to detect the variations of the genes related to brain disorders in the early disease stages.

Association of XRCC3 rs1799794 polymorphism with survival of glioblastoma multiforme patients treated with combined radio-chemotherapy

This study reports the results of a monocentric prospective analysis conducted with the aim of evaluating the impact of XRCC1 rs25487, XRCC3 rs861539, XRCC3 rs1799794, RAD51 rs1801320 and GSTP-1 rs1695 single nucleotide polymorphisms (SNP) on patients with high-grade glioma treated with concomitant radio-chemotherapy. From October 2010 to August 2019, a total of 75 patients aged ≥18 years, with histological diagnosis of high-grade glioma, isocitrate dehydrogenase (IDH) 1/2 wild type and treated with radio-chemotherapy and sequential chemotherapy with temozolomide (TMZ) were prospectively recruited. The local ethic committee approved this study (Comitato Etico di Area Vasta Nord Ovest [CEAVNO]; protocol 3304/2011). After a median follow up of 25 months (range: 7-98 months), median progression-free survival (PFS) and overall survival (OS) were 11 months (CI95%: 8-14 months) and 18 months (CI95%: 15-21 months), respectively. In univariate and multivariate Cox regression analysis, a statistically significant association with PFS and OS was found with XRCC3 rs1799794 SNP. The study suggests that XRCC3 rs1799794 SNP can be associated with different PFS and OS in glioblastoma patients treated with radio-chemotherapy.

Application of Chromosome Microarray Analysis for the Differential Diagnosis of Low-grade Renal Cell Carcinoma With Clear Cell and Papillary Features

Clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC) are the 2 most common RCCs. However, some RCCs can have both clear cell and papillary features, including clear cell papillary RCC (ccpRCC). They can be a diagnostic challenge in daily practice. Accurate diagnosis of these tumors is important for both patient prognosis and appropriate treatment. Fourteen RCCs with papillary architecture, clear cytoplasm and low Fuhrman grade were analyzed by SNP-based chromosome microarray (CMA). Seven cases had pathologic features of ccpRCC, and all had normal genomic profiles except one that had copy neutral loss of heterozygosity (cnLOH) of chromosome 3 and loss of one copy of the X chromosome. The remaining 7 cases also had papillae and clear cytoplasm. Two of these cases showed losses of chromosome 3 which are typically found in ccRCC. One had a gain of chromosome 7, which is commonly seen in pRCC. The remaining 4 had no alterations of chromosome 3 or 7. However, 3 of these 4 had monosomy 8, which are consistent with RCC with monosomy 8. The remaining case had no copy number alterations. This study shows that low-grade RCC with papillae and clear cell phenotype represents a heterogeneous group, including ccpRCC, ccRCC, pRCC, and RCC with monosomy 8. CMA analysis can be useful for the differential diagnosis of these neoplasms.

Clonal relationship of synchronous head and neck cancer and esophageal cancer assessed by single nucleotide polymorphism-based loss of heterozygosity analysis

Background

The prognoses of head and neck squamous cell carcinoma (HNSCC) and esophageal squamous cell carcinoma (ESCC) are poor, especially when both tumors occur at the same time. We examined the clonal relatedness of HNSCCs with synchronous ESCCs to confirm whether the second tumors were metastasis or separate second primary malignancies (SPMs) using loss of heterozygosity (LOH) analysis.

Methods

Twenty-one pairs of formalin-fixed paraffin-embedded tissue from HNSCC patients with synchronous esophageal cancer were analyzed by single nucleotide polymorphism (SNP) array using the Illumina HumanCytoSNP FFPE-12 BeadChip (San Diego, CA), which contains approximately 300,000 probes. LOH was identified using Nexus Copy Number software (El Segundo, CA).

Results

Comparing the LOH pattern between HNSCC and paired ESCC, we found that 20 out of 21 paired tissues had a high number of discordant LOHs (LOH identified solely in the primary HNSCC but not in synchronous ESCC at the same genomic location) and a low number of concordant LOHs (LOH at the same genomic location in both HNSCC and ESCC). Only one case fell into the undetermined category. Therefore, these 20 ESCCs were classified as SPMs or second field tumors (SFTs). Moreover, the HNSCC patients with molecularly confirmed esophageal SPM had significantly poorer survival than the other patients.

Conclusions

We propose the use of a genome-wide SNP array as a tool to differentiate metastatic tumors from SPM/SFT. The SNP array offers genome-wide LOH information that earlier microsatellite analysis studies lack. The ability to accurately identify SPM should contribute to a better treatment plan and follow-up care of these patients.

Amplification of the EGFR and CCND1 Are Coordinated and Play Important Roles in the Progression of Oral Squamous Cell Carcinomas

Oral squamous cell carcinoma (OSCC) is a common cancer in Taiwan and worldwide. To provide some clues for clinical management of OSCC, 72 advanced-stage OSCCs were analyzed using two microarray platforms (26 cases with Affymetrix 500 K and 46 cases with Affymetrix SNP 6.0). Genomic identification of significant targets in cancer analyses were used to identify significant copy number alterations (CNAs) using a q-value cutoff of 0.25. Among the several significant regions, 12 CNAs were common between these two platforms. Two gain regions contained the well-known oncogenes EGFR (7p11.2) and CCND1 (11q13.3) and several known cancer suppressor genes, such as FHIT (3p14.2-p12.1), FAT1 (4q35.1), CDKN2A (9p21.3), and ATM (11q22.3-q24.3), reside within the 10 deletion regions. Copy number gains of EGFR and CCND1 were further confirmed by fluorescence in situ hybridization and TaqMan CN assay, respectively, in 257 OSCC cases. Our results indicate that EGFR and CCND1 CNAs are significantly associated with clinical stage, tumor differentiation, and lymph node metastasis. Furthermore, EGFR and CCND1 CNAs have an additive effect on OSCC tumor progression. Thus, current genome-wide CNA analysis provides clues for future characterization of important oncogenes and tumor suppressor genes associated with the behaviors of the disease.

Multiple primary lung cancer: a rising challenge

With the use of high-resolution chest imaging system and lung cancer screening program, patients with multiple primary lung cancers (MPLCs) are becoming a growing population in clinical practice worldwide. The diagnostic criteria for MPLCs has been established and modified by three major lung cancer research institutes. However, due to the fact that the differential diagnosis between MPLCs and a recurrence, metastatic, or satellite lesion arising from the original lesion remains ambiguous and confusing, there is still insufficient evidence to support a uniform guideline. Newly developed molecular and genomic methods have the potential to better define the relationship among multiple lesions and bring the possibility of targeted therapy. Surgical resection remains the first choice for the treatment of MPLCs and detailed strategy should be carefully planned taking characteristics of the tumor and status of patients into consideration. For those who are intolerant to surgery, a new technology called stereotactic body radiation therapy (SBRT) is now an optional therapeutic strategy. Furthermore, multiple GGOs are unique MPLCs that need special attentions in the clinical practice.

Genomic landscape of copy number variation and copy neutral loss of heterozygosity events in equine sarcoids reveals increased instability of the sarcoid genome

Although they are the most common neoplasms in equids, sarcoids are not fully characterized at the molecular level. Therefore, the objective of this study was to characterize the landscape of structural rearrangements, such as copy number variation (CNV) and copy neutral loss of heterozygosity (cnLOH), in the genomes of sarcoid tumor cells. This information will not only broaden our understanding of the characteristics of this genome but will also improve the general knowledge of this tumor and the mechanisms involved in its generation. To this end, Equine SNP64K Illumina microarrays were applied along with bioinformatics tools dedicated for signal intensity analysis. The analysis revealed increased instability of the genome of sarcoid cells compared with unaltered skin tissue samples, which was manifested by the prevalence of CNV and cnLOH events. Many of the identified CNVs overlapped with the other research results, but the simultaneously observed variability in the number and sizes of detected aberrations indicated a need for further studies and the development of more reliable bioinformatics algorithms. The functional analysis of genes co-localized with the identified aberrations revealed that these genes are engaged in vital cellular processes. In addition, a number of these genes directly contribute to neoplastic transformation. Furthermore, large numbers of cnLOH events identified in the sarcoids suggested that they may play no less significant roles than CNVs in the carcinogenesis of this tumor. Thus, our results indicate the importance of cnLOH and CNV in equine sarcoid oncogenesis and present a direction of future research.

The complexity of prostate cancer: genomic alterations and heterogeneity

Although prostate cancer is the most common malignancy to affect men in the Western world, the molecular mechanisms underlying its development and progression remain poorly understood. Like all cancers, prostate cancer is a genetic disease that is characterized by multiple genomic alterations, including point mutations, microsatellite variations, and chromosomal alterations such as translocations, insertions, duplications, and deletions. In prostate cancer, but not other carcinomas, these chromosome alterations result in a high frequency of gene fusion events. The development and application of novel high-resolution technologies has significantly accelerated the detection of genomic alterations, revealing the complex nature and heterogeneity of the disease. The clinical heterogeneity of prostate cancer can be partly explained by this underlying genetic heterogeneity, which has been observed between patients from different geographical and ethnic populations, different individuals within these populations, different tumour foci within the same patient, and different cells within the same tumour focus. The highly heterogeneous nature of prostate cancer provides a real challenge for clinical disease management and a detailed understanding of the genetic alterations in all cells, including small subpopulations, would be highly advantageous.

SNPs Array Karyotyping in Non-Hodgkin Lymphoma

The traditional methods for detection of chromosomal aberrations, which included cytogenetic or gene candidate solutions, suffered from low sensitivity or the need for previous knowledge of the target regions of the genome. With the advent of single nucleotide polymorphism (SNP) arrays, genome screening at global level in order to find chromosomal aberrations like copy number variants, DNA amplifications, deletions, and also loss of heterozygosity became feasible. In this review, we present an update of the knowledge, gained by SNPs arrays, of the genomic complexity of the most important subtypes of non-Hodgkin lymphomas.

An Efficient Genotyping Method in Chicken Based on Genome Reducing and Sequencing

Single nucleotide polymorphisms (SNPs) are essential for identifying the genetic mechanisms of complex traits. In the present study, we applied genotyping by genome reducing and sequencing (GGRS) method to construct a 252-plex sequencing library for SNP discovery and genotyping in chicken. The library was successfully sequenced on an Illumina HiSeq 2500 sequencer with a paired-end pattern; approximately 400 million raw reads were generated, and an average of approximately 1.4 million good reads per sample were generated. A total of 91,767 SNPs were identified after strict filtering, and all of the 252 samples and all of the chromosomes were well represented. Compared with the Illumina 60K chicken SNP chip data, approximately 34,131 more SNPs were identified using GGRS, and a higher SNP density was found using GGRS, which could be beneficial for downstream analysis. Using the GGRS method, more than 3528 samples can be sequenced simultaneously, and the cost is reduced to $18 per sample. To the best of our knowledge, this study describes the first report of such highly multiplexed sequencing in chicken, indicating potential applications for genome-wide association and genomic selection in chicken.

Understanding genetics in neuroimaging

Gene expression is a process of DNA sequence reading into protein synthesis. In cases of problems in DNA repair/apoptosis mechanisms, cells accumulate genomic abnormalities and pass them through generations of cells. The accumulation of mutations causes diseases and even tumors. In addition to cancer, many other neurologic conditions have been associated with genetic mutations. Some trials are testing patients with epigenetic treatments. Epigenetic therapy must be used with caution because epigenetic processes and changes happen constantly in normal cells, giving rise to drug off-target effects. Scientists are making progress in specifically targeting abnormal cells with minimal damage to normal ones.

Methods: for studying pharmacogenetic profiles of combination chemotherapeutic drugs

INTRODUCTION

Molecular and genetic analysis of tumors and individuals has led to patient-centered therapies, through the discovery and identification of genetic markers predictive of drug efficacy and tolerability. Present therapies often include a combination of synergic drugs, each of them directed against different targets. Therefore, the pharmacogenetic profiling of tumor masses and patients is becoming a challenge, and several questions may arise when planning a translational study.

AREAS COVERED

The review presents the different techniques used to stratify oncology patients and to tailor antineoplastic treatments according to individual pharmacogenetic profiling. The advantages of these methodologies are discussed as well as current limits.

EXPERT OPINION

Facing the rapid technological evolution for genetic analyses, the most pressing issues are the choice of appropriate strategies (i.e., from gene candidate up to next-generation sequencing) and the possibility to replicate study results for their final validation. It is likely that the latter will be the major obstacle in the future. However, the present landscape is opening up new possibilities, overcoming those hurdles that have limited result translation into clinical settings for years.

Identification of ZDHHC14 as a novel human tumour suppressor gene

Genomic changes affecting tumour suppressor genes are fundamental to cancer. We applied SNP array analysis to a panel of testicular germ cell tumours to search for novel tumour suppressor genes and identified a frequent small deletion on 6q25.3 affecting just one gene, ZDHHC14. The expression of ZDHHC14, a putative protein palmitoyltransferase with unknown cellular function, was decreased at both RNA and protein levels in testicular germ cell tumours. ZDHHC14 expression was also significantly decreased in a panel of prostate cancer samples and cell lines. In addition to our findings of genetic and protein expression changes in clinical samples, inducible overexpression of ZDHHC14 led to reduced cell viability and increased apoptosis through the classic caspase-dependent apoptotic pathway and heterozygous knockout of ZDHHC14 increased [CORRECTED] cell colony formation ability. Finally, we confirmed our in vitro findings of the tumour suppressor role of ZDHHC14 in a mouse xenograft model, showing that overexpression of ZDHHC14 inhibits tumourigenesis. Thus, we have identified a novel tumour suppressor gene that is commonly down-regulated in testicular germ cell tumours and prostate cancer, as well as given insight into the cellular functional role of ZDHHC14, a potential protein palmitoyltransferase that may play a key protective role in cancer.

Analysis of boutique arrays: a universal method for the selection of the optimal data normalization procedure

DNA microarrays, which are among the most popular genomic tools, are widely applied in biology and medicine. Boutique arrays, which are small, spotted, dedicated microarrays, constitute an inexpensive alternative to whole-genome screening methods. The data extracted from each microarray-based experiment must be transformed and processed prior to further analysis to eliminate any technical bias. The normalization of the data is the most crucial step of microarray data pre-processing and this process must be carefully considered as it has a profound effect on the results of the analysis. Several normalization algorithms have been developed and implemented in data analysis software packages. However, most of these methods were designed for whole-genome analysis. In this study, we tested 13 normalization strategies (ten for double-channel data and three for single-channel data) available on R Bioconductor and compared their effectiveness in the normalization of four boutique array datasets. The results revealed that boutique arrays can be successfully normalized using standard methods, but not every method is suitable for each dataset. We also suggest a universal seven-step workflow that can be applied for the selection of the optimal normalization procedure for any boutique array dataset. The described workflow enables the evaluation of the investigated normalization methods based on the bias and variance values for the control probes, a differential expression analysis and a receiver operating characteristic curve analysis. The analysis of each component results in a separate ranking of the normalization methods. A combination of the ranks obtained from all the normalization procedures facilitates the selection of the most appropriate normalization method for the studied dataset and determines which methods can be used interchangeably.

Individualized therapy for metastatic colorectal cancer

Systemic therapeutic efficacy is central to determining the outcome of patients with metastatic colorectal cancer (CRC). In these patients, there is a critical need for predictive biomarkers to optimize efficacy whilst minimizing toxicity. The integration of a new generation of molecularly targeted drugs into the treatment of CRC, coupled with the development of sophisticated technologies for individual tumours as well as patient molecular profiling, underlines the potential for personalized medicine. In this review, we focus on the latest progress made within the genomic and proteomic fields, concerning predictive biomarkers for individualized therapy in metastatic CRC.

Toll-like receptors and human disease: lessons from single nucleotide polymorphisms

Toll-like receptors (TLRs), a large group of proteins which recognize various pathogen-associated molecular patterns, are critical for the normal function of the innate immune system. Following their discovery many single nucleotide polymorphisms within TLRs and components of their signaling machinery have been discovered and subsequently implicated in a wide range of human diseases including atherosclerosis, sepsis, asthma, and immunodeficiency. This review discusses the effect of genetic variation on TLR function and how they may precipitate disease.

Clinically relevant cancer biomarkers and pharmacogenetic assays

BACKGROUND

The number of pharmacogenetic assays available is continuously expanding as more molecularly targeted anticancer drugs are under clinical development. While the literature regarding drug-gene associations and therapeutic implications is often robust, reviews regarding clinical assay availability and profiling methodologies of commonly used cancer biomarkers are often lacking.

OBJECTIVE

To concisely identify and describe cancer biomarkers and their respective pharmacogenetic assays currently available in clinical practice.

DISCUSSION

Analysis of germ-line DNA mutations can often help to predict pharmacokinetic and pharmacodynamic responses, whereas somatic DNA mutations are particularly useful in predicting tumor response. Molecular profiling and pre-emptive identification of cancer biomarkers can help to predict disease prognosis as well as response to anticancer therapy. Dozens of pharmacogenetic assays, utilizing several common methodologies, are currently available in clinical practice. It is essential for clinicians to understand the molecular pathways for anticancer drugs, the therapeutic implications of mutations within these pathways, the clinical assay(s) available to test for pharmacogenetic differences, and the common profiling methodology employed.

CONCLUSION

As research continues to unveil more drug-gene and disease-gene associations, it is critical that clinicians understand which pharmacogenetic assays are available to identify inter-individual differences that predict safety and efficacy of anticancer drugs as we move toward the concept of personalized medicine.

Genomic profiling of mantle cell lymphoma

Genomic profiling of mantle cell lymphoma (MCL) cells has enabled a better understanding of the complex mechanisms underlying the pathogenesis of disease. Besides the t(11;14)(q13;q32) leading to cyclin D1 overexpression, MCL exhibits a characteristic pattern of DNA copy number aberrations that differs from those detected in other B-cell lymphomas. These genomic changes disrupt selected oncogenes and suppressor genes that are required for lymphoma development and progression, many of which are components of cell cycle, DNA damage response and repair, apoptosis, and cell-signaling pathways. Additionally, some of them may represent effective therapeutic targets. A number of genomic and molecular abnormalities have been correlated with the clinical outcome of patients with MCL and are considered prognostic factors. However, only a few genomic markers have been shown to predict the response to current or novel targeted therapies. One representative example is the high-level amplification of the BCL2 gene, which predicts a good response to pro-apoptotic BH3 mimetic drugs. In summary, genomic analyses have contributed to the substantial advances made in the comprehension of the pathogenesis of MCL, providing a solid basis for the identification of optimal therapeutic targets and for the design of new molecular therapies aiming to cure this fatal disease.

Profiling of ileal carcinoids

Identification of common molecular mechanisms is needed to facilitate the development of new treatment options for patients with ileal carcinoids.

PURPOSE OF REVIEW

Recent profiling studies on ileal carcinoids were examined to obtain a comprehensive view of risk factors, genetic aberrations, and transcriptional alterations. Special attention was paid to mechanisms that could provide novel targets for therapy.

RESULTS

Genome-wide association studies have shown that single nucleotide polymorphisms (SNPs) at IL12A and DAD1 are associated with an increased risk of ileal carcinoids. Genomic profiling revealed distinct patterns of copy-number alterations in ileal carcinoids. Two groups of carcinoids could be identified by hierarchical clustering. A major group of tumors was characterized by loss on chromosome 18 followed by additional losses on chromosomes 3p, 11q, and 13. Three minimal common regions of deletions were identified at 18q21.1-q21.31, 18q22.1-q22.2, and 18q22.3-q23. A minor group of tumors was characterized by clustered gains on chromosomes 4, 5, 7, 14, and 20. Expression profiling identified three groups of ileal carcinoids by principal component analysis. Tumor progression was associated with changes in gene expression including downregulation of MIR133A. Candidate genes for targeted therapy included ERBB2/HER2, DAD1, PRKCA, RYBP, CASP1, CASP4, CASP5, VMAT1, RET, APLP1, OR51E1, GPR112, SPOCK1, RUNX1, and MIR133A.

CONCLUSION

Profiling of ileal carcinoids has revealed recurrent genetic alterations and distinct patterns of gene expression. Frequent alterations in cellular pathways and genes were identified, suggesting novel targets for therapy. Translational studies are needed to validate suggested molecular targets.

A genome-wide single-nucleotide polymorphism-array can improve the prognostic stratification of the core binding factor acute myeloid leukemia

Core binding factor (CBF) AML with the D816 C-KIT gene mutation demonstrate inferior treatment outcomes. However, the remaining cases without the D816 C-KIT mutation imply a requirement of more sophisticated dissection of the patients according to their prognosis. In this study, we analyzed the prognostic value of a single nucleotide polymorphism array (SNP-A) based karyotyping combined with metaphase cytogenetics (MC) to facilitate further stratification of CBF AML patients. A total of 98 CBF AML patients were included and genome-wide Human SNP 6.0 Arrays (Affymetrix) were performed using marrow samples taken at diagnosis. Overall, 40 abnormal lesions were identified in 25 patients (26%). Survival of the patients with the abnormal lesion(s) detected by SNP-A and/or MC was worse than those without lesions in terms of the 2-year overall survival (OS; 57.5% vs. 76.4%, P = 0.028), event-free (EFS; 45.7% vs. 66.2%, P = 0.072), and leukemia-free survival (LFS; 49.0% vs. 77.4%, P = 0.015), specially in the subgroup with inv(16)/t(16;16) (40.9% vs. 80.2% OS, P = 0.040) and in the subgroup without the D816 C-KIT mutation (61.6% vs. 82.7% OS, P = 0.038). Multivariate analysis confirmed the prognostic impact of the abnormal SNP-A and/or MC lesion on EFS (HR 2.011, P = 0.047), and LFS (HR 3.231, P = 0.005) in the overall CBF AML. This study suggests that the combined use of SNP-A with MC in the CBF AML can provide important prognostic value, especially in the inv(16)/t(16;16) subgroup or in the patients without the D816 C-KIT mutation.

Finding the needle in the haystack: a review of microarray gene expression research into schizophrenia

BACKGROUND

With an estimated 80% heritability, molecular genetic research into schizophrenia has remained inconclusive. Recent large-scale, genome-wide association studies only identified a small number of susceptibility genes with individually very small effect sizes. However, the variable expression of the phenotype is not well captured in diagnosis-based research as well as when assuming a 'heterogenic risk model' (as apposed to a monogenic or polygenic model). Hence, the expression of susceptibility genes in response to environmental factors in concert with other disease-promoting or protecting genes has increasingly attracted attention.

METHOD

The current review summarises findings of microarray gene expression research with relevance to schizophrenia as they emerged over the past decade.

RESULTS

Most findings from post mortem, peripheral tissues and animal models to date have linked altered gene expression in schizophrenia to presynaptic function, signalling, myelination, neural migration, cellular immune mechanisms, and response to oxidative stress consistent with multiple small effects of many individual genes. However, the majority of results are difficult to interpret due to small sample sizes (i.e. potential type-2 errors), confounding factors (i.e. medication effects) or lack of plausible neurobiological theory.

CONCLUSION

Nevertheless, microarray gene expression research is likely to play an important role in the future when investigating gene/gene and gene/environment interactions by adopting a neurobiologically sound theoretical framework.

A new frontier in personalized cancer therapy: mapping molecular changes

Mutations in the genome of a normal cell can affect the function of its many genes and pathways. These alterations could eventually transform the cell from a normal to a malignant state by allowing an uncontrolled proliferation of the cell and formation of a cancer tumor. Each tumor in an individual patient can have hundreds of mutated genes and perturbed pathways. Cancers clinically presenting as the same type or subtype could potentially be very different at the molecular level and thus behave differently in response to therapy. The challenge is to distinguish the key mutations driving the cancer from the background of mutational noise and find ways to effectively target them. The promise is that such a molecular approach to classifying cancer will lead to better diagnostic, prognostic and personalized treatment strategies. This article provides an overview of advances in the molecular characterization of cancers and their applications in therapy.

Genome-wide high density single-nucleotide polymorphism array-based karyotyping improves detection of clonal aberrations including der(9) deletion, but does not predict treatment outcomes after imatinib therapy in chronic myeloid leukemia

The current study investigated molecular cytogenetic characteristics of chronic myeloid leukemia (CML) using genome-wide, single nucleotide polymorphism arrays (SNP-A) capable of detecting cryptic submicroscopic genomic aberrations. Genome-Wide Human SNP 6.0 Array (Affymetrix, CA, USA) was performed in 118 patients having CML, chronic phase. Thirty-nine clonal aberrations (CAs) were identified (35 losses, two gains, two copy neutral loss of heterozygosity) that were not detected by metaphase cytogenetics in 25 patients (21%). The 9q34 deletions were found in 10% of cases, while 22q11.2 deletions were observed in 12% of cases. Seven patients (6%) harbored both 5'-ABL and 3'-BCR deletions adjacent to the t(9;22) breakpoint. Copy number gains were identified at 8p and 9p, and losses at 2q, 7q, 8q, 9q, 11q, 13q, 16p, and 22q. When we compared the treatment outcome of imatinib therapy between patients with and without CAs identified by SNP-A, treatment failure and progression to advanced disease were not significantly different (p > 0.05). In addition, according to the presence of deletions of 9q34 and/or 22q11.2 identified by SNP-A, the treatment outcome did not show any significant differences (p > 0.05). Our data suggests that SNP-A analysis is a useful tool for detection of clonal aberrations including deletions adjacent to the t(9;22) breakpoint in the CML cancer genome. However, clonal aberrations detected by SNP-A could not improve a prognostic stratification in CML patients with chronic phase.

Array-based karyotyping for prognostic assessment in chronic lymphocytic leukemia: performance comparison of Affymetrix 10K2.0, 250K Nsp, and SNP6.0 arrays

Specific chromosomal alterations are recognized as important prognostic factors in chronic lymphocytic leukemia (CLL). Array-based karyotyping is gaining acceptance as an alternative to the standard fluorescence in situ hybridization (FISH) panel for detecting these aberrations. This study explores the optimum single nucleotide polymorphism (SNP) array probe density for routine clinical use, presents clinical validation results for the 250K Nsp Affymetrix SNP array, and highlights clinically actionable genetic lesions missed by FISH and conventional cytogenetics. CLL samples were processed on low (10K2.0), medium (250K Nsp), and high (SNP6.0) probe density Affymetrix SNP arrays. Break point definition and detection rates for clinically relevant genetic lesions were compared. The 250K Nsp array was subsequently validated for routine clinical use and demonstrated 98.5% concordance with the standard CLL FISH panel. SNP array karyotyping detected genomic complexity and/or acquired uniparental disomy not detected by the FISH panel. In particular, a region of acquired uniparental disomy on 17p was shown to harbor two mutated copies of TP53 that would have gone undetected by FISH, conventional cytogenetics, or array comparative genomic hybridization. SNP array karyotyping allows genome-wide, high resolution detection of copy number and uniparental disomy at genomic regions with established prognostic significance in CLL, detects lesions missed by FISH, and provides insight into gene dosage at these loci.

Proteomics, pathway array and signaling network-based medicine in cancer

Cancer is a multifaceted disease that results from dysregulated normal cellular signaling networks caused by genetic, genomic and epigenetic alterations at cell or tissue levels. Uncovering the underlying protein signaling network changes, including cell cycle gene networks in cancer, aids in understanding the molecular mechanism of carcinogenesis and identifies the characteristic signaling network signatures unique for different cancers and specific cancer subtypes. The identified signatures can be used for cancer diagnosis, prognosis, and personalized treatment. During the past several decades, the available technology to study signaling networks has significantly evolved to include such platforms as genomic microarray (expression array, SNP array, CGH array, etc.) and proteomic analysis, which globally assesses genetic, epigenetic, and proteomic alterations in cancer. In this review, we compared Pathway Array analysis with other proteomic approaches in analyzing protein network involved in cancer and its utility serving as cancer biomarkers in diagnosis, prognosis and therapeutic target identification. With the advent of bioinformatics, constructing high complexity signaling networks is possible. As the use of signaling network-based cancer diagnosis, prognosis and treatment is anticipated in the near future, medical and scientific communities should be prepared to apply these techniques to further enhance personalized medicine.

Use of SNPs in cancer predisposition analysis, diagnosis and prognosis: tools and prospects

BACKGROUND

The development of cancer is accompanied by several genetic alterations. Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation found in the human population. SNP arrays offer a high-resolution, high-throughput technology for genome-wide analysis, allowing the simultaneous detection of genotype and copy number changes. The power of SNP arrays as a research tool has accelerated our understanding of the genetic alterations in cancer, providing potential clinical applications.

OBJECTIVE

This manuscript reviews the use of SNPs in cancer research and discusses the potential clinical application of analysing SNPs for cancer predisposition analysis, diagnosis and prognosis. We also discuss potential future applications for the analysis of SNPs.

METHODS

In writing this review, we have reflected on our own extensive experience in the field of cancer genomics and have surveyed peer-reviewed articles focussing on the application of SNPs in cancer research. In addition, we have referred to product websites.

CONCLUSION

Since its development, SNP array technology has been extensively applied in cancer research. Information generated from SNP array analysis has been providing valuable information. With the full understanding of the rich resources of SNPs and their effects on influencing cellular function, SNP arrays will revolutionise the clinical practice in cancer risk assessment, diagnosis and prognosis making the concept of personalised medicine a reality.

Genetic variations in esophageal cancer risk and prognosis

Investigations into inherited genetic variations in the DNA code (known as polymorphisms) in the field of oncology have provided preliminary support for an association with cancer risks and outcomes. Early studies have highlighted several genes with this potential predictive and prognostic power. However, these studies have had methodological limitations and have produced inconsistent results, making impractical as yet the routine evaluation of such genetic polymorphisms in general clinical practice. Continued research in this area is essential if we are to be able to soon use genetic polymorphisms to better select patients for targeted anticancer interventions. This review discusses the role of genetic polymorphisms and their association with esophageal cancer risk and prognosis. The article also highlights future directions in this new, emerging field of molecular epidemiology.

Basic molecular techniques for the detection of single nucleotide polymorphisms: genome-wide applications in search for endocrine tumor related genes

The necessity of genotyping high number of variations in extended sample sets has become apparent in the era of large genomic studies of common complex disorders, in cancer and in pharmacogenomics. The single nucleotide polymorphisms' (SNPs) apparent advantages over other genetic markers such as high frequency, relative stability, and statistically random distribution across the genome have made them a method of choice for most of these genome-wide oriented applications. The requirement for simultaneous genotyping of high number of SNPs, keeping at the same time reasonable price and reliable accuracy, triggered the rise of the genotyping throughput, and led to the development of the array-based technologies. The present chapter briefly reviews the methodological and historical aspect of the basic SNP detecting techniques that lie in the basis of the modern high-throughput technologies, providing at the same time detailed guide on the application of one of the most advanced SNP microarray platform on the market: the genome-wide SNP Array 6.0 recently developed by Affymetrix, which we have used to study families with Catney complex and Micronodular adrenocortical hyperplasia. In addition, we discuss practical clues and tips aiming at extending applications and improving performance.