One purpose for seeking common alleles that are associated with disease is to use them to improve models for projecting individualized disease risk. Two genome-wide association studies and a study of candidate genes recently identified seven common single-nucleotide polymorphisms (SNPs) that were associated with breast cancer risk in independent samples. These seven SNPs were located in FGFR2, TNRC9 (now known as TOX3), MAP3K1, LSP1, CASP8, chromosomal region 8q, and chromosomal region 2q35. I used estimates of relative risks and allele frequencies from these studies to estimate how much these SNPs could improve discriminatory accuracy measured as the area under the receiver operating characteristic curve (AUC). A model with these seven SNPs (AUC = 0.574) and a hypothetical model with 14 such SNPs (AUC = 0.604) have less discriminatory accuracy than a model, the National Cancer Institute's Breast Cancer Risk Assessment Tool (BCRAT), that is based on ages at menarche and at first live birth, family history of breast cancer, and history of breast biopsy examinations (AUC = 0.607). Adding the seven SNPs to BCRAT improved discriminatory accuracy to an AUC of 0.632, which was, however, less than the improvement from adding mammographic density. Thus, these seven common alleles provide less discriminatory accuracy than BCRAT but have the potential to improve the discriminatory accuracy of BCRAT modestly. Experience to date and quantitative arguments indicate that a huge increase in the numbers of case patients with breast cancer and control subjects would be required in genome-wide association studies to find enough SNPs to achieve high discriminatory accuracy.

We report a genome-wide association study for melanoma that was conducted by the GenoMEL Consortium. Our discovery phase included 2,981 individuals with melanoma and 1,982 study-specific control individuals of European ancestry, as well as an additional 6,426 control subjects from French or British populations, all of whom were genotyped for 317,000 or 610,000 single-nucleotide polymorphisms (SNPs). Our analysis replicated previously known melanoma susceptibility loci. Seven new regions with at least one SNP with P < 10(-5) and further local imputed or genotyped support were selected for replication using two other genome-wide studies (from Australia and Texas, USA). Additional replication came from case-control series from the UK and The Netherlands. Variants at three of the seven loci replicated at P < 10(-3): an SNP in ATM (rs1801516, overall P = 3.4 × 10(-9)), an SNP in MX2 (rs45430, P = 2.9 × 10(-9)) and an SNP adjacent to CASP8 (rs13016963, P = 8.6 × 10(-10)). A fourth locus near CCND1 remains of potential interest, showing suggestive but inconclusive evidence of replication (rs1485993, overall P = 4.6 × 10(-7) under a fixed-effects model and P = 1.2 × 10(-3) under a random-effects model). These newly associated variants showed no association with nevus or pigmentation phenotypes in a large British case-control series.

Aberrant DNA methylation is an important epigenetic alteration in hepatocellular carcinoma (HCC). However, the molecular processes underlying the methylator phenotype and the contribution of hepatitis viruses are poorly understood. The current study is a comprehensive methylation analysis of human liver tissue specimens. A total of 176 liver tissues, including 77 pairs of HCCs and matching noncancerous liver and 22 normal livers, were analyzed for methylation. Methylation of 19 epigenetic markers was quantified, and the results were correlated with different disease states and the presence or absence of hepatitis B virus (HBV) and hepatitis C virus (HCV) infections. Based on methylation profiles, the 19 loci were categorized into 3 groups. Normal liver tissues showed methylation primarily in group 1 loci (HIC-1, CASP8, GSTP1, SOCS1, RASSF1A, p16, APC), which was significantly higher than group 2 (CDH1, RUNX3, RIZ1, SFRP2, MINT31) and group 3 markers (COX2, MINT1, CACNA1G, RASSF2, MINT2, Reprimo, DCC) (P < 0.0001). Noncancerous livers demonstrated increased methylation in both group 1 and group 2 loci. Methylation was significantly more abundant in HCV-positive livers compared with normal liver tissues. Conversely, HCC showed frequent methylation at each locus investigated in all 3 groups. However, the group 3 loci showed more dense and frequent methylation in HCV-positive cancers compared with both HBV-positive cancers and virus-negative cancers (P < 0.0001).

CONCLUSIONS

Methylation in HCC is frequent but occurs in a gene-specific and disease-specific manner. Methylation profiling allowed us to determine that aberrant methylation is commonly present in normal aging livers, and sequentially progresses with advancing stages of chronic viral infection. Finally, our data provide evidence that HCV infection may accelerate the methylation process and suggests a continuum of increasing methylation with persistent viral infection and carcinogenesis in the liver.

The pronecrotic kinase, receptor interacting protein (RIP1, also called RIPK1) mediates programmed necrosis and, together with its partner, RIP3 (RIPK3), drives midgestational death of caspase 8 (Casp8)-deficient embryos. RIP1 controls a second vital step in mammalian development immediately after birth, the mechanism of which remains unresolved. Rip1(-/-) mice display perinatal lethality, accompanied by gross immune system abnormalities. Here we show that RIP1 K45A (kinase dead) knockin mice develop normally into adulthood, indicating that development does not require RIP1 kinase activity. In the face of complete RIP1 deficiency, cells develop sensitivity to RIP3-mixed lineage kinase domain-like-mediated necroptosis as well as to Casp8-mediated apoptosis activated by diverse innate immune stimuli (e.g., TNF, IFN, double-stranded RNA). When either RIP3 or Casp8 is disrupted in combination with RIP1, the resulting double knockout mice exhibit slightly prolonged survival over RIP1-deficient animals. Surprisingly, triple knockout mice with combined RIP1, RIP3, and Casp8 deficiency develop into viable and fertile adults, with the capacity to produce normal levels of myeloid and lymphoid lineage cells. Despite the combined deficiency, these mice sustain a functional immune system that responds robustly to viral challenge. A single allele of Rip3 is tolerated in Rip1(-/-)Casp8(-/-)Rip3(+/-) mice, contrasting the need to eliminate both alleles of either Rip1 or Rip3 to rescue midgestational death of Casp8-deficient mice. These observations reveal a vital kinase-independent role for RIP1 in preventing pronecrotic as well as proapoptotic signaling events associated with life-threatening innate immune activation at the time of mammalian parturition.

Interleukin-1β (IL-1β) is a cytokine whose bioactivity is controlled by activation of the inflammasome. However, in response to lipopolysaccharide, human monocytes secrete IL-1β independently of classical inflammasome stimuli. Here, we report that this constituted a species-specific response that is not observed in the murine system. Indeed, in human monocytes, lipopolysaccharide triggered an "alternative inflammasome" that relied on NLRP3-ASC-caspase-1 signaling, yet was devoid of any classical inflammasome characteristics including pyroptosome formation, pyroptosis induction, and K(+) efflux dependency. Genetic dissection of the underlying signaling pathway in a monocyte transdifferentiation system revealed that alternative inflammasome activation was propagated by TLR4-TRIF-RIPK1-FADD-CASP8 signaling upstream of NLRP3. Importantly, involvement of this signaling cascade was limited to alternative inflammasome activation and did not extend to classical NLRP3 activation. Because alternative inflammasome activation embraces both sensitivity and promiscuity of TLR4, we propose a pivotal role for this signaling cascade in TLR4-driven, IL-1β-mediated immune responses and immunopathology in humans.

CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homology-modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close homology modeling. The new computational costly remote homology-modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is <20 min. The web server is available at http://www.cbs.dtu.dk/services/CPHmodels/.

Receptor interacting protein kinase 1 (RIPK1) has an essential role in the signalling triggered by death receptors and pattern recognition receptors. RIPK1 is believed to function as a node driving NF-κB-mediated cell survival and inflammation as well as caspase-8 (CASP8)-dependent apoptotic or RIPK3/MLKL-dependent necroptotic cell death. The physiological relevance of this dual function has remained elusive because of the perinatal death of RIPK1 full knockout mice. To circumvent this problem, we generated RIPK1 conditional knockout mice, and show that mice lacking RIPK1 in intestinal epithelial cells (IECs) spontaneously develop severe intestinal inflammation associated with IEC apoptosis leading to early death. This early lethality was rescued by antibiotic treatment, MYD88 deficiency or tumour-necrosis factor (TNF) receptor 1 deficiency, demonstrating the importance of commensal bacteria and TNF in the IEC Ripk1 knockout phenotype. CASP8 deficiency, but not RIPK3 deficiency, rescued the inflammatory phenotype completely, indicating the indispensable role of RIPK1 in suppressing CASP8-dependent apoptosis but not RIPK3-dependent necroptosis in the intestine. RIPK1 kinase-dead knock-in mice did not exhibit any sign of inflammation, suggesting that RIPK1-mediated protection resides in its kinase-independent platform function. Depletion of RIPK1 in intestinal organoid cultures sensitized them to TNF-induced apoptosis, confirming the in vivo observations. Unexpectedly, TNF-mediated NF-κB activation remained intact in these organoids. Our results demonstrate that RIPK1 is essential for survival of IECs, ensuring epithelial homeostasis by protecting the epithelium from CASP8-mediated IEC apoptosis independently of its kinase activity and NF-κB activation.

Breast cancers demonstrate substantial biological, clinical and etiological heterogeneity. We investigated breast cancer risk associations of eight susceptibility loci identified in GWAS and two putative susceptibility loci in candidate genes in relation to specific breast tumor subtypes. Subtypes were defined by five markers (ER, PR, HER2, CK5/6, EGFR) and other pathological and clinical features. Analyses included up to 30 040 invasive breast cancer cases and 53 692 controls from 31 studies within the Breast Cancer Association Consortium. We confirmed previous reports of stronger associations with ER+ than ER- tumors for six of the eight loci identified in GWAS: rs2981582 (10q26) (P-heterogeneity = 6.1 × 10(-18)), rs3803662 (16q12) (P = 3.7 × 10(-5)), rs13281615 (8q24) (P = 0.002), rs13387042 (2q35) (P = 0.006), rs4973768 (3p24) (P = 0.003) and rs6504950 (17q23) (P = 0.002). The two candidate loci, CASP8 (rs1045485, rs17468277) and TGFB1 (rs1982073), were most strongly related with the risk of PR negative tumors (P = 5.1 × 10(-6) and P = 4.1 × 10(-4), respectively), as previously suggested. Four of the eight loci identified in GWAS were associated with triple negative tumors (P ≤ 0.016): rs3803662 (16q12), rs889312 (5q11), rs3817198 (11p15) and rs13387042 (2q35); however, only two of them (16q12 and 2q35) were associated with tumors with the core basal phenotype (P ≤ 0.002). These analyses are consistent with different biological origins of breast cancers, and indicate that tumor stratification might help in the identification and characterization of novel risk factors for breast cancer subtypes. This may eventually result in further improvements in prevention, early detection and treatment.

BACKGROUND

The Breast Cancer Association Consortium (BCAC) is an international collaboration that was established to provide large sample sizes for examining genetic associations. We conducted combined analyses on all single-nucleotide polymorphisms (SNPs) whose associations with breast cancer have been investigated by at least three participating groups.

METHODS

Data from up to 12 studies were pooled for each SNP (ADH1C I350V, AURKA F31I, BRCA2 N372H, CASP8 D302H, ERCC2 D312N, IGFBP3 -202 c>a, LIG4 D501D, PGR V660L, SOD2 V16A, TGFB1 L10P, TP53 R72P, XRCC1 R399Q, XRCC2 R188H, XRCC3 T241M, XRCC3 5' UTR, and XRCC3 IVS7-14). Genotype frequencies in case and control subjects were compared, and genotype-specific odds ratios for the risk of breast cancer in heterozygotes and homozygotes for the rare allele compared with homozygotes for the common allele were estimated with logistic regression. Statistical tests were two-sided.

RESULTS

The total number of subjects for analysis of each SNP ranged from 12,013 to 31,595. For five SNPs--CASP8 D302H, IGFBP3 -202 c>a, PGR V660L, SOD2 V16A, and TGFB1 L10P--the associations with breast cancer were of borderline statistical significance (P = .016, .060, .047, .056, and .0088 respectively). The remaining 11 SNPs were not associated with breast cancer risk; genotype-specific odds ratios were close to unity. There was some evidence for between-study heterogeneity (P<.05) for four of the 11 SNPs (ADH1C I350V, ERCC2 D312N, XRCC1 R399Q, and XRCC3 IVS5-14).

CONCLUSIONS

Pooling data within a large consortium has helped to clarify associations of SNPs with breast cancer. In the future, consortia such as the BCAC will be important in the analysis of rare polymorphisms and gene x gene or gene x environment interactions, for which individual studies have low power to identify associations, and in the validation of associations identified from genome-wide association studies.

BACKGROUND

More than 1000 reports have been published in the past two decades on associations between variants in candidate genes and risk of breast cancer. Results have been generally inconsistent. We did a literature search and meta-analyses to provide a synopsis of the current understanding of the genetic architecture of breast-cancer risk.

METHODS

A systematic literature search for candidate-gene association studies of breast-cancer risk was done in two stages, using PubMed on or before Feb 28, 2010. A total of 24,500 publications were identified, of which 1059 were deemed eligible for inclusion. Meta-analyses were done for 279 genetic variants in 128 candidate genes or chromosomal loci that had at least three data sources. Variants with significant associations by meta-analysis were assessed using the Venice criteria and scored as having strong, moderate, or weak cumulative evidence for an association with breast-cancer risk.

RESULTS

51 variants in 40 genes showed significant associations with breast-cancer risk. Cumulative epidemiological evidence of an association was graded as strong for ten variants in six genes (ATM, CASP8, CHEK2, CTLA4, NBN, and TP53), moderate for four variants in four genes (ATM, CYP19A1, TERT, and XRCC3), and weak for 37 variants. Additionally, in meta-analyses that included a minimum of 10,000 cases and 10,000 controls, convincing evidence of no association with breast-cancer risk was identified for 45 variants in 37 genes.

CONCLUSIONS

Whereas most genetic variants assessed in previous candidate-gene studies showed no association with breast-cancer risk in meta-analyses, 14 variants in nine genes had moderate to strong evidence for an association. Further evaluation of these variants is warranted.

BACKGROUND

US National Cancer Institute.

Gingivo-buccal oral squamous cell carcinoma (OSCC-GB), an anatomical and clinical subtype of head and neck squamous cell carcinoma (HNSCC), is prevalent in regions where tobacco-chewing is common. Exome sequencing (n=50) and recurrence testing (n=60) reveals that some significantly and frequently altered genes are specific to OSCC-GB (USP9X, MLL4, ARID2, UNC13C and TRPM3), while some others are shared with HNSCC (for example, TP53, FAT1, CASP8, HRAS and NOTCH1). We also find new genes with recurrent amplifications (for example, DROSHA, YAP1) or homozygous deletions (for example, DDX3X) in OSCC-GB. We find a high proportion of C>G transversions among tobacco users with high numbers of mutations. Many pathways that are enriched for genomic alterations are specific to OSCC-GB. Our work reveals molecular subtypes with distinctive mutational profiles such as patients predominantly harbouring mutations in CASP8 with or without mutations in FAT1. Mean duration of disease-free survival is significantly elevated in some molecular subgroups. These findings open new avenues for biological characterization and exploration of therapies.

OBJECTIVE

Aggressive cutaneous squamous cell carcinoma (cSCC) is often a disfiguring and lethal disease. Very little is currently known about the mutations that drive aggressive cSCC.

METHODS

Whole-exome sequencing was performed on 39 cases of aggressive cSCC to identify driver genes and novel therapeutic targets. Significantly, mutated genes were identified with MutSig or complementary methods developed to specifically identify candidate tumor suppressors based upon their inactivating mutation bias.

RESULTS

Despite the very high-mutational background caused by UV exposure, 23 candidate drivers were identified, including the well-known cancer-associated genes TP53, CDKN2A, NOTCH1, AJUBA, HRAS, CASP8, FAT1, and KMT2C (MLL3). Three novel candidate tumor suppressors with putative links to cancer or differentiation, NOTCH2, PARD3, and RASA1, were also identified as possible drivers in cSCC. KMT2C mutations were associated with poor outcome and increased bone invasion.

CONCLUSIONS

The mutational spectrum of cSCC is similar to that of head and neck squamous cell carcinoma and dominated by tumor-suppressor genes. These results improve the foundation for understanding this disease and should aid in identifying and treating aggressive cSCC.

BACKGROUND

Recently, several genome-wide association studies have identified various genetic susceptibility loci for breast cancer. Relatively little is known about the possible interactions between these loci and the established risk factors for breast cancer.

METHODS

To assess interactions between single-nucleotide polymorphisms (SNPs) and established risk factors, we prospectively collected DNA samples and questionnaire data from 8576 breast cancer case subjects and 11 892 control subjects nested within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). We genotyped 17 germline SNPs (FGFR2-rs2981582, FGFR2-rs3750817, TNRC9-rs3803662, 2q35-rs13387042, MAP3K1-rs889312, 8q24-rs13281615, CASP8-rs1045485, LSP1-rs3817198, COL1A1-rs2075555, COX11-rs6504950, RNF146-rs2180341, 6q25-rs2046210, SLC4A7-rs4973768, NOTCH2-rs11249433, 5p12-rs4415084, 5p12-rs10941679, RAD51L1-rs999737), and odds ratios were estimated by logistic regression to confirm previously reported associations with breast cancer risk. We performed likelihood ratio test to assess interactions between 17 SNPs and nine established risk factors (age at menarche, parity, age at menopause, use of hormone replacement therapy, family history, height, body mass index, smoking status, and alcohol consumption), and a correction for multiple testing of 153 tests (adjusted P value threshold = .05/153 = 3 × 10(-4)) was done. Case-case comparisons were performed for possible differential associations of polymorphisms by subgroups of tumor stage, estrogen and progesterone receptor status, and age at diagnosis. All statistical tests were two-sided.

RESULTS

We confirmed the association of 14 SNPs with breast cancer risk (P(trend) = 2.57 × 10(-3) -3.96 × 10(-19)). Three SNPs (LSP1-rs3817198, COL1A1-rs2075555, and RNF146-rs2180341) did not show association with breast cancer risk. After accounting for multiple testing, no statistically significant interactions were detected between the 17 SNPs and the nine risk factors. We also confirmed that SNPs in FGFR2 and TNRC9 were associated with greater risk of estrogen receptor-positive than estrogen receptor-negative breast cancer (P(heterogeneity) = .0016 for FGFR2-rs2981582 and P(heterogeneity) = .0053 for TNRC9-rs3803662). SNP 5p12-rs10941679 was statistically significantly associated with greater risk of progesterone receptor-positive than progesterone receptor-negative breast cancer (P(heterogeneity) = .0028).

CONCLUSIONS

This study does not support the hypothesis that known common breast cancer susceptibility loci strongly modify the associations between established risk factors and breast cancer.

Caspases are important in the life and death of immune cells and therefore influence immune surveillance of malignancies. We tested whether genetic variants in CASP8, CASP10 and CFLAR, three genes important for death receptor-induced cell killing residing in tandem order on chromosome 2q33, are associated with cancer susceptibility. Using a haplotype-tagging SNP approach, we identified a six-nucleotide deletion (-652 6N del) variant in the CASP8 promoter associated with decreased risk of lung cancer. The deletion destroys a stimulatory protein 1 binding site and decreases CASP8 transcription. Biochemical analyses showed that T lymphocytes with the deletion variant had lower caspase-8 activity and activation-induced cell death upon stimulation with cancer cell antigens. Case-control analyses of 4,995 individuals with cancer and 4,972 controls in a Chinese population showed that this genetic variant is associated with reduced susceptibility to multiple cancers, including lung, esophageal, gastric, colorectal, cervical and breast cancers, acting in an allele dose-dependent manner. These results support the hypothesis that genetic variants influencing immune status modify cancer susceptibility.

ASK1 activates JNK and p38 mitogen-activated protein kinases and constitutes a pivotal signaling pathway in cytokine- and stress-induced apoptosis. However, little is known about the mechanism of how ASK1 executes apoptosis. Here we investigated the roles of caspases and mitochondria in ASK1-induced apoptosis. We found that benzyloxycarbonyl-Val-Ala-Asp-fluoromethyl ketone (zVAD-fmk), a broad-spectrum caspase inhibitor, mostly inhibited ASK1-induced cell death, suggesting that caspases are required for ASK1-induced apoptosis. Overexpression of ASK1DeltaN, a constitutively active mutant of ASK1, induced cytochrome c release from mitochondria and activation of caspase-9 and caspase-3 but not of caspase-8-like proteases. Consistently, caspase-8-deficient (Casp8 (-/-)) cells were sensitive to ASK1-induced caspase-3 activation and apoptosis, suggesting that caspase-8 is dispensable for ASK1-induced apoptosis, whereas ASK1 failed to activate caspase-3 in caspase-9-dificient (Casp9 (-/-)) cells. Moreover, mitochondrial cytochrome c release, which was not inhibited by zVAD-fmk, preceded the onset of caspase-3 activation and cell death induced by ASK1. ASK1 thus appears to execute apoptosis mainly by the mitochondria-dependent caspase activation.

Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P=1.22×10(-14)), 18q21.33 (BCL2, P=7.76×10(-11)), 11p15.5 (C11orf21, P=2.15×10(-10)), 4q25 (LEF1, P=4.24×10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P=2.50×10(-9)), 9p21.3 (CDKN2B-AS1, P=1.27×10(-8)), 18q21.32 (PMAIP1, P=2.51×10(-8)), 15q15.1 (BMF, P=2.71×10(-10)) and 2p22.2 (QPCT, P=1.68×10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P=2.08×10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P=5.40×10(-8)) and 5p15.33 (TERT, P=1.92×10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.

BACKGROUND

Intrinsically unstructured proteins (IUPs) lack a well-defined three-dimensional structure. Some of them may assume a locally stable structure under specific conditions, e.g. upon interaction with another molecule, while others function in a permanently unstructured state. The discovery of IUPs challenged the traditional protein structure paradigm, which stated that a specific well-defined structure defines the function of the protein. As of December 2011, approximately 60 methods for computational prediction of protein disorder from sequence have been made publicly available. They are based on different approaches, such as utilizing evolutionary information, energy functions, and various statistical and machine learning methods.

RESULTS

Given the diversity of existing intrinsic disorder prediction methods, we decided to test whether it is possible to combine them into a more accurate meta-prediction method. We developed a method based on arbitrarily chosen 13 disorder predictors, in which the final consensus was weighted by the accuracy of the methods. We have also developed a disorder predictor GSmetaDisorder3D that used no third-party disorder predictors, but alignments to known protein structures, reported by the protein fold-recognition methods, to infer the potentially structured and unstructured regions. Following the success of our disorder predictors in the CASP8 benchmark, we combined them into a meta-meta predictor called GSmetaDisorderMD, which was the top scoring method in the subsequent CASP9 benchmark.

CONCLUSIONS

A series of disorder predictors described in this article is available as a MetaDisorder web server at http://iimcb.genesilico.pl/metadisorder/. Results are presented both in an easily interpretable, interactive mode and in a simple text format suitable for machine processing.

The childhood eye cancer retinoblastoma is initiated by the loss of both alleles of the prototypic tumor suppressor gene, RB1. However, a large number of cytogenetic and comparative genomic hybridization (CGH) studies have shown that these M1 and M2 mutational events--although necessary for initiation--are not the only genomic changes in retinoblastoma. Some of these subsequent changes, which we have termed M3 to Mn, are likely crucial for tumor progression not only in retinoblastoma but also in other cancers. Moreover, genes showing genomic change in cancer are more stable markers and, therefore, possible therapeutic targets than genes simply differentially expressed. In this review, we provide the first comprehensive summary of the genomic evidence implicating gain of 1q, 2p, 6p, and 13q, and loss of 16q in retinoblastoma oncogenesis, including karyotype, CGH, and microarray CGH data. We discuss the search for candidate oncogenes and tumor suppressor genes within these regions, including the candidates (KIF14, MDM4, MYCN, E2F3, DEK, CDH11, and others), plus associations between genomic changes and clinical parameters. We also review studies of other regions of the retinoblastoma genome, the epigenetic changes of aberrant methylation of MGMT, RASSF1A, CASP8, and MLH1, and the roles microRNAs might play in this cancer. Although many candidate genes have yet to be functionally validated in retinoblastoma, work in this field lays out a molecular cytogenetic pathway of retinoblastoma development. Candidate cancer genes carry diagnostic, prognostic, and therapeutic implications beyond retinoblastoma.

Caspase-8 is an essential component of death receptor-mediated apoptosis. Along with Fas-associated death domain protein, it is also essential for T cell proliferation in response to antigenic or mitogenic stimuli. To determine whether caspase-8 is also required for B cell proliferation, we generated mice with a B cell-specific Casp8 deficiency. Unlike T cells, caspase-8 was not required for Ag receptor-driven proliferation or Ab formation. Rather, Casp8-deficient B cells failed to proliferate in response to dsRNA and LPS, ligands for TLR3 and TLR4, respectively, but responded normally to the TLR9 agonist CpG DNA. Similarly, Ab production to trinitrophenol-LPS was selectively reduced in B cell-specific Casp8-deficient mice. The activation of NF-kappaB or IFN regulatory factor 3 was found to be unaffected by the loss of caspase-8, implicating it in a novel pathway important for some forms of innate immunity mediated by B cells.

T cells enigmatically require caspase-8, an inducer of apoptosis, for antigen-driven expansion and effective antiviral responses, and yet the pathways responsible for this effect have been elusive. A defect in caspase-8 expression does not affect progression through the cell cycle but causes an abnormally high rate of cell death that is distinct from apoptosis and does not involve a loss of NFkappaB activation. Instead, antigen or mitogen activated Casp8-deficient T cells exhibit an alternative type of cell death similar to programmed necrosis that depends on receptor interacting protein (Ripk1). The selective genetic ablation of caspase-8, NFkappaB, and Ripk1, reveals two forms of cell death that can regulate virus-specific T cell expansion.

BACKGROUND

Information is scarce about the combined effects on breast cancer incidence of low-penetrance genetic susceptibility polymorphisms and environmental factors (reproductive, behavioural, and anthropometric risk factors for breast cancer). To test for evidence of gene-environment interactions, we compared genotypic relative risks for breast cancer across the other risk factors in a large UK prospective study.

METHODS

We tested gene-environment interactions in 7610 women who developed breast cancer and 10 196 controls without the disease, studying the effects of 12 polymorphisms (FGFR2-rs2981582, TNRC9-rs3803662, 2q35-rs13387042, MAP3K1-rs889312, 8q24-rs13281615, 2p-rs4666451, 5p12-rs981782, CASP8-rs1045485, LSP1-rs3817198, 5q-rs30099, TGFB1-rs1982073, and ATM-rs1800054) in relation to prospectively collected information about ten established environmental risk factors (age at menarche, parity, age at first birth, breastfeeding, menopausal status, age at menopause, use of hormone replacement therapy, body-mass index, height, and alcohol consumption).

RESULTS

After allowance for multiple testing none of the 120 comparisons yielded significant evidence of a gene-environment interaction. By contrast with previous suggestions, there was little evidence that the genotypic relative risks were affected by use of hormone replacement therapy, either overall or for oestrogen-receptor-positive disease. Only one of the 12 polymorphisms was correlated with any of the ten other risk factors: carriers of the high-risk C allele of MAP3K1-rs889312 were significantly shorter than non-carriers (mean height 162.4 cm [95% CI 162.1-162.7] vs 163.1 cm [162.9-163.2]; p=0.01 after allowance for multiple testing).

CONCLUSIONS

Risks of breast cancer associated with low-penetrance susceptibility polymorphisms do not vary significantly with these ten established environmental risk factors.

BACKGROUND

Cancer Research UK and the UK Medical Research Council.

The SAM-T08 web server is a protein structure prediction server that provides several useful intermediate results in addition to the final predicted 3D structure: three multiple sequence alignments of putative homologs using different iterated search procedures, prediction of local structure features including various backbone and burial properties, calibrated E-values for the significance of template searches of PDB and residue-residue contact predictions. The server has been validated as part of the CASP8 assessment of structure prediction as having good performance across all classes of predictions. The SAM-T08 server is available at http://compbio.soe.ucsc.edu/SAM_T08/T08-query.html.

BACKGROUND

Hepatocellular carcinoma (HCC) presents one of the major health threats in China today. A better understanding of the molecular genetics underlying malignant transformation of hepatocytes is critical to success in the battle against this disease. The methylation state of C5 of the cytosine in the CpG di-nucleotide that is enriched within or near the promoter region of over 50 % of the polymerase II genes has a drastic effect on transcription of these genes. Changes in the methylation profile of the promoters represent an alternative to genetic lesions as causative factors for the tumor-specific aberrant expression of the genes.

METHODS

We have used the methylation specific PCR method in conjunction with DNA sequencing to assess the methylation state of the promoter CpG islands of twenty genes. Aberrant expression of these genes have been attributed to the abnormal methylation profile of the corresponding promoter CpG islands in human tumors.

RESULTS

While the following sixteen genes remained the unmethylated in all tumor and normal tissues: CDH1, APAF1, hMLH1, BRCA1, hTERC, VHL, RARbeta, TIMP3, DAPK1, SURVIVIN, p14ARF, RB1, p15INK4b, APC, RASSF1c and PTEN, varying degrees of tumor specific hypermethylation were associated with the p16INK4a, RASSF1a, CASP8 and CDH13 genes. For instance, the p16INK4a was highly methylated in HCC (17/29, 58.6%) and less significantly methylated in non-cancerous tissue (4/29. 13.79%). The RASSF1a was fully methylated in all tumor tissues (29/29, 100%), and less frequently methylated in corresponding non-cancerous tissue (24/29, 82.75%).

CONCLUSIONS

Furthermore, co-existence of methylated with unmethylated DNA in some cases suggested that both genetic and epigenetic (CpG methylation) mechanisms may act in concert to inactivate the p16INK4a and RASSF1a in HCC. Finally, we found a significant association of cirrhosis with hypermethylation of the p16INK4a and hypomethylation of the CDH13 genes. For the first time, the survey was carried out on such an extent that it would not only provide new insights into the molecular mechanisms underscoring the aberrant expression of the genes in this study in HCC, but also offer essential information required for a good methylation-based diagnosis of HCC.

BACKGROUND

Employing methods to assess the quality of modeled protein structures is now standard practice in bioinformatics. In a broad sense, the techniques can be divided into methods relying on consensus prediction on the one hand, and single-model methods on the other. Consensus methods frequently perform very well when there is a clear consensus, but this is not always the case. In particular, they frequently fail in selecting the best possible model in the hard cases (lacking consensus) or in the easy cases where models are very similar. In contrast, single-model methods do not suffer from these drawbacks and could potentially be applied on any protein of interest to assess quality or as a scoring function for sampling-based refinement.

RESULTS

Here, we present a new single-model method, ProQ2, based on ideas from its predecessor, ProQ. ProQ2 is a model quality assessment algorithm that uses support vector machines to predict local as well as global quality of protein models. Improved performance is obtained by combining previously used features with updated structural and predicted features. The most important contribution can be attributed to the use of profile weighting of the residue specific features and the use features averaged over the whole model even though the prediction is still local.

CONCLUSIONS

ProQ2 is significantly better than its predecessors at detecting high quality models, improving the sum of Z-scores for the selected first-ranked models by 20% and 32% compared to the second-best single-model method in CASP8 and CASP9, respectively. The absolute quality assessment of the models at both local and global level is also improved. The Pearson's correlation between the correct and local predicted score is improved from 0.59 to 0.70 on CASP8 and from 0.62 to 0.68 on CASP9; for global score to the correct GDT_TS from 0.75 to 0.80 and from 0.77 to 0.80 again compared to the second-best single methods in CASP8 and CASP9, respectively. ProQ2 is available at http://proq2.wallnerlab.org.