Petra Hudler

Genetic Aspects of Gastric Cancer Instability

Unravelling the molecular mechanisms underlying gastric carcinogenesis is one of the major challenges in cancer genomics. Gastric cancer is a very complex and heterogeneous disease, and although much has been learned about the different genetic changes that eventually lead to its development, the detailed mechanisms still remain unclear. Malignant transformation of gastric cells is the consequence of a multistep process involving different genetic and epigenetic changes in numerous genes in combination with host genetic background and environmental factors. The majority of gastric adenocarcinomas are characterized by genetic instability, either microsatellite instability (MSI) or chromosomal instability (CIN). It is believed that chromosome destabilizations occur early in tumour progression. This review summarizes the most common genetic alterations leading to instability in sporadic gastric cancers and its consequences.

Aberrant methylation patterns in cancer: a clinical view

Epigenetic mechanisms, such as DNA methylation, DNA hydroxymethylation, post-translational modifications (PTMs) of histone proteins affecting nucleosome remodelling, and regulation by small and large non-coding RNAs (ncRNAs) work in concert with cis and trans acting elements to drive appropriate gene expression. Advances in detection methods and development of dedicated platforms and methylation arrays resulted in an explosion of information on aberrantly methylated sequences linking deviations in epigenetic landscape with the initiation and progression of complex diseases. Here, we consider how DNA methylation changes in malignancies, such as breast, pancreatic, colorectal, and gastric cancer could be exploited for the purpose of developing specific diagnostic tools. DNA methylation changes can be applicable as biomarkers for detection of malignant disease in easily accessible tissues. Methylation signatures are already proving to be an important marker for determination of drug sensitivity. Even more, promoter methylation patterns of some genes, such as MGMT, SHOX2, and SEPT9, have already been translated into commercial clinical assays aiding in patient assessment as adjunct diagnostic tools. In conclusion, the changes in DNA methylation patterns in tumour cells are slowly gaining entrance into routine diagnostic tests as promising biomarkers and as potential therapeutic targets.

Proteomic approaches in biomarker discovery: new perspectives in cancer diagnostics.

Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies.

Proteomic strategies and challenges in tumor metastasis research

The rapidly evolving field of proteomics offers new approaches to understanding the pathogenesis of cancer and metastatic disease. Although numerous tumor markers have been identified with different genomic methods in the past, most are either not specific or sensitive enough to be used in routine clinical setting. The rationale for proteomic profiling is based on the fact that proteins represent the dynamic state of the cells, reflecting pathophysiological changes in the disease more accurately than genomic and epigenetic alterations. Emerging proteomic techniques allow simultaneous assessment of a large number of proteins at one time. The study of protein profiles in complex systems, such as plasma, serum or tissues of cancer patients is likely to become valuable for monitoring the response of patients during treatment or for detecting recurrence of the disease.

Mutations in the hMLH1 gene in Slovenian patients with gastric carcinoma

Alterations of multiple oncogenes and tumor suppressor genes, together with genetic instability, are responsible for carcinogenesis in gastric cancer. The microsatellite mutator phenotype is the cause of many somatic frameshift and point mutations in non‐coding repetitive sequences and in coding regions associated with cell proliferation and apoptosis. Genetic mutations in hMLH1 and transcriptional silencing of its promoter by hypermethylation lead to the inactivation of the mismatch repair system. In our study, we screened for mutations the hMLH1 gene in patients expressing the microsatellite instability genotype by using single‐strand conformational polymorphism analysis and direct sequencing. Seven changes were identified; of these, three (A92P, E433Q, and K618A) were germline mutations and the other four (IVS5 453u2003+u200379 Au2003>u2003G, I219V, 1039u2003−u20037 del (T)n, and IVS15 1668u2003−u200319 Au2003>u2003G) germline polymorphisms. A92P and E433Q are novel, previously unidentified mutations. In addition, we found a rather complex distribution of mutations and polymorphisms in individual patients and in two cases also a methylated hMLH1 promoter.

The progress of proteomic approaches in searching for cancer biomarkers

Biomarkers are indicators of a specific biological state. Their detection in pathological conditions, such as cancer, is important for clinical disease management. One of their greatest values could be in early diagnosis and detection of neoplasms when the cancer is more manageable. Protein biomarkers are expected to be reliable predictors of pathological conditions, as they represent the endpoint of biological processes. The proteomic methodology has rapidly evolved in the past ten years, thus enabling discovery of a vast amount of potential biomarker candidates. However, the majority of novel candidates have not yet reached the integration into clinical environment. To do that, well-constructed large population validation studies are necessary as well as development of new algorithms for deciphering complex biological interactions and their involvement in pathological processes. This review focuses on advances in classical proteomic approaches and emerging high-throughput proteomic technologies for identifying cancer biomarkers.

Assessing pathogenicity of MLH1 variants by co-expression of human MLH1 and PMS2 genes in yeast

BackgroundLoss of DNA mismatch repair (MMR) in humans, mainly due to mutations in the hMLH1 gene, is linked to hereditary nonpolyposis colorectal cancer (HNPCC). Because not all MLH1 alterations result in loss of MMR function, accurate characterization of variants and their classification in terms of their effect on MMR function is essential for reliable genetic testing and effective treatment. To date, in vivo assays for functional characterization of MLH1 mutations performed in various model systems have used episomal expression of the modified MMR genes. We describe here a novel approach to determine accurately the functional significance of hMLH1 mutations in vivo, based on co-expression of human MLH1 and PMS2 in yeast cells.MethodsYeast MLH1 and PMS1 genes, whose protein products form the MutLα complex, were replaced by human orthologs directly on yeast chromosomes by homologous recombination, and the resulting MMR activity was tested.ResultsThe yeast strain co-expressing hMLH1 and hPMS2 exhibited the same mutation rate as the wild-type. Eight cancer-related MLH1 variants were introduced, using the same approach, into the prepared yeast model, and their effect on MMR function was determined. Five variants (A92P, S93G, I219V, K618R and K618T) were classified as non-pathogenic, whereas variants T117M, Y646C and R659Q were characterized as pathogenic.ConclusionResults of our in vivo yeast-based approach correlate well with clinical data in five out of seven hMLH1 variants and the described model was thus shown to be useful for functional characterization of MLH1 variants in cancer patients found throughout the entire coding region of the gene.

Gene Expression Profiling of Rat Fetuses Exposed to 2-Dimensional Ultrasound

This study evaluated the possible effects of ultrasound (US) on gene expression in brain tissue of rat embryos.

PKD1 and PKD2 mutations in Slovenian families with autosomal dominant polycystic kidney disease

BackgroundAutosomal dominant polycystic kidney disease (ADPKD) is a genetically heterogeneous disorder caused by mutations in at least two different loci. Prior to performing mutation screening, if DNA samples of sufficient number of family members are available, it is worthwhile to assign the gene involved in disease progression by the genetic linkage analysis.MethodsWe collected samples from 36 Slovene ADPKD families and performed linkage analysis in 16 of them. Linkage was assessed by the use of microsatellite polymorphic markers, four in the case of PKD1 (KG8, AC2.5, CW3 and CW2) and five for PKD2 (D4S1534, D4S2929, D4S1542, D4S1563 and D4S423). Partial PKD1 mutation screening was undertaken by analysing exons 23 and 31–46 and PKD2 .ResultsLod scores indicated linkage to PKD1 in six families and to PKD2 in two families. One family was linked to none and in seven families linkage to both genes was possible. Partial PKD1 mutation screening was performed in 33 patients (including 20 patients from the families where linkage analysis could not be performed). We analysed PKD2 in 2 patients where lod scores indicated linkage to PKD2 and in 7 families where linkage to both genes was possible. We detected six mutations and eight polymorphisms in PKD1 and one mutation and three polymorphisms in PKD2.ConclusionIn our study group of ADPKD patients we detected seven mutations: three frameshift, one missense, two nonsense and one putative splicing mutation. Three have been described previously and 4 are novel. Three newly described framesfift mutations in PKD1 seem to be associated with more severe clinical course of ADPKD. Previously described nonsense mutation in PKD2 seems to be associated with cysts in liver and milder clinical course.

Association between polymorphisms in segregation genes BUB1B and TTK and gastric cancer risk

Abstract Background Malignant transformation of normal gastric cells is a complex and multistep process, resulting in development of heterogeneous tumours. Susceptible genetic background, accumulation of genetic changes, and environmental factors play an important role in gastric carcinogenesis. Single nucleotide polymorphisms (SNPs) in mitotic segregation genes could be responsible for inducing the slow process of accumulation of genetic changes, leading to genome instability. Patients and methods We performed a case-control study of polymorphisms in mitotic kinases TTK rs151658 and BUB1B rs1031963 and rs1801376 to assess their effects on gastric cancer risk. We examined the TTK abundance in gastric cancer tissues using immunoblot analysis. Results C/G genotype of rs151658 was more frequent in patients with diffuse type of gastric cancer and G/G genotype was more common in intestinal types of gastric cancers (p = 0.049). Polymorphic genotype A/A of rs1801376 was associated with higher risk for developing diffuse type of gastric cancer in female population (p = 0.007), whereas A/A frequencies were increased in male patients with subserosa tumour cell infiltration (p = 0.009). T/T genotype of rs1031963 was associated with well differentiated tumours (p = 0.035). TT+CT genotypes of rs1031963 and GG+AG genotypes of rs1801376 were significantly associated with gastric cancer risk (dominant model; OR = 2,929, 95% CI: 1.281-6.700; p = 0.017 and dominant model; OR = 0,364, 95% CI: 0.192-0.691; p = 0.003 respectively). Conclusions Our results suggest that polymorphisms in mitotic kinases TTK and BUB1B may contribute to gastric tumorigenesis and risk of tumour development. Further investigations on large populations and populations of different ethnicity are needed to determine their clinical utility.