Baseline Mutations and ctDNA Dynamics as Prognostic and Predictive Factors in ER-Positive/HER2-Negative Metastatic Breast Cancer Patients.

PURPOSE: Prognostic and predictive biomarkers to cyclin-dependent kinases 4 and 6 inhibitors are lacking. Circulating tumor DNA (ctDNA) can be used to profile these patients and dynamic changes in ctDNA could be an early predictor of treatment efficacy. Here, we conducted plasma ctDNA profiling in patients from the PEARL trial comparing palbociclib+fulvestrant versus capecitabine to investigate associations between baseline genomic landscape and on-treatment ctDNA dynamics with treatment efficacy. EXPERIMENTAL DESIGN: Correlative blood samples were collected at baseline [cycle 1-day 1 (C1D1)] and prior to treatment [cycle 1-day 15 (C1D15)]. Plasma ctDNA was sequenced with a custom error-corrected capture panel, with both univariate and multivariate Cox models used for treatment efficacy associations. A prespecified methodology measuring ctDNA changes in clonal mutations between C1D1 and C1D15 was used for the on-treatment ctDNA dynamic model. RESULTS: 201 patients were profiled at baseline, with ctDNA detection associated with worse progression-free survival (PFS)/overall survival (OS). Detectable TP53 mutation showed worse PFS and OS in both treatment arms, even after restricting population to baseline ctDNA detection. ESR1 mutations were associated with worse OS overall, which was lost when restricting population to baseline ctDNA detection. PIK3CA mutations confer worse OS only to patients on the palbociclib+fulvestrant treatment arm. ctDNA dynamics analysis (n = 120) showed higher ctDNA suppression in the capecitabine arm. Patients without ctDNA suppression showed worse PFS in both treatment arms. CONCLUSIONS: We show impaired survival irrespective of endocrine or chemotherapy-based treatments for patients with hormone receptor-positive/HER2-negative metastatic breast cancer harboring plasma TP53 mutations. Early ctDNA suppression may provide treatment efficacy predictions. Further validation to fully demonstrate clinical utility of ctDNA dynamics is warranted.

CCNE1 and PLK1 Mediate Resistance to Palbociclib in HR+/HER2- Metastatic Breast Cancer.

PURPOSE: In hormone receptor-positive (HR+)/HER2- metastatic breast cancer (MBC), it is imperative to identify patients who respond poorly to cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) and to discover therapeutic targets to reverse this resistance. Non-luminal breast cancer subtype and high levels of CCNE1 are candidate biomarkers in this setting, but further validation is needed. EXPERIMENTAL DESIGN: We performed mRNA gene expression profiling and correlation with progression-free survival (PFS) on 455 tumor samples included in the phase III PEARL study, which assigned patients with HR+/HER2- MBC to receive palbociclib+endocrine therapy (ET) versus capecitabine. Estrogen receptor-positive (ER+)/HER2- breast cancer cell lines were used to generate and characterize resistance to palbociclib+ET. RESULTS: Non-luminal subtype was more prevalent in metastatic (14%) than in primary tumor samples (4%). Patients with non-luminal tumors had median PFS of 2.4 months with palbociclib+ET and 9.3 months with capecitabine; HR 4.16, adjusted P value < 0.0001. Tumors with high CCNE1 expression (above median) also had worse median PFS with palbociclib+ET (6.2 months) than with capecitabine (9.3 months); HR 1.55, adjusted P value = 0.0036. In patients refractory to palbociclib+ET (PFS in the lower quartile), we found higher levels of Polo-like kinase 1 (PLK1). In an independent data set (PALOMA3), tumors with high PLK1 show worse median PFS than those with low PLK1 expression under palbociclib+ET treatment. In ER+/HER2- cell line models, we show that PLK1 inhibition reverses resistance to palbociclib+ET. CONCLUSIONS: We confirm the association of non-luminal subtype and CCNE1 with resistance to CDK4/6i+ET in HR+ MBC. High levels of PLK1 mRNA identify patients with poor response to palbociclib, suggesting PLK1 could also play a role in the setting of resistance to CDK4/6i.

Triple-Negative PAM50 Non-Basal Breast Cancer Subtype Predicts Benefit from Extended Adjuvant Capecitabine.

PURPOSE: Predictive biomarkers for capecitabine benefit in triple-negative breast cancer (TNBC) have been recently proposed using samples from phase III clinical trials, including non-basal phenotype and biomarkers related to angiogenesis, stroma, and capecitabine activation genes. We aimed to validate these findings on the larger phase III GEICAM/CIBOMA clinical trial. EXPERIMENTAL DESIGN: Tumor tissues from patients with TNBC randomized to standard (neo)adjuvant chemotherapy followed by capecitabine versus observation were analyzed using a 164-gene NanoString custom nCounter codeset measuring mRNA expression. A prespecified statistical plan sought to verify the predictive capacity of PAM50 non-basal molecular subtype and tested the hypotheses that breast tumors with increased expression of (meta)genes for cytotoxic cells, mast cells, endothelial cells, PDL2, and 38 individual genes benefit from adjuvant capecitabine for distant recurrence-free survival (DRFS; primary endpoint) and overall survival. RESULTS: Of the 876 women enrolled in the GEICAM/CIBOMA trial, 658 (75%) were evaluable for analysis (337 with capecitabine and 321 without). Of these cases, 553 (84%) were profiled as PAM50 basal-like whereas 105 (16%) were PAM50 non-basal. Non-basal subtype was the most significant predictor for capecitabine benefit [HRcapecitabine, 0.19; 95% confidence interval (CI), 0.07-0.54; P < 0.001] when compared with PAM50 basal-like (HRcapecitabine, 0.9; 95% CI, 0.63-1.28; P = 0.55; Pinteraction<0.001, adjusted P value = 0.01). Analysis of biological processes related to PAM50 non-basal subtype revealed its enrichment for mast cells, extracellular matrix, angiogenesis, and features of mesenchymal stem-like TNBC subtype. CONCLUSIONS: In this prespecified correlative analysis of the GEICAM/CIBOMA trial, PAM50 non-basal status identified patients with early-stage TNBC most likely to benefit from capecitabine.

Derived Neutrophil-to-Lymphocyte Ratio Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

BACKGROUND: Derived neutrophil-to-lymphocyte ratio (dNLR) is a biomarker associated with clinical outcome in breast cancer (BC). We analyzed the association of dNLR with pathological complete response (pCR) in triple-negative BC (TNBC) patients receiving neoadjuvant chemotherapy (CT). METHODS: This is a retrospective analysis of two randomized studies involving early stage/locally advanced TNBC patients receiving anthracycline/taxane-based CT+/-carboplatin (GEICAM/2006-03) or nab-paclitaxel/paclitaxel followed by anthracycline regimen (ETNA). dNLR was calculated as the ratio of neutrophils to the difference between total leukocytes and neutrophils in peripheral blood before CT (baseline) and at the end of treatment (EOT). Logistic regression analyses were used to explore dNLR association with pCR. RESULTS: In total, 308 TNBC patients were analyzed, 216 from ETNA and 92 from GEICAM/2006-03. Baseline median dNLR was 1.61 (interquartile range (IQR): 1.25-2.04) and at EOT 1.53 (IQR: 0.96-2.22). Baseline dNLR showed positive correlation with increased tumor size (p-value = 1e-04). High baseline dNLR, as continuous variable or using median cutoff, was associated with lower likelihood of pCR in univariate analysis. High EOT dNLR as continuous variable or using quartiles was also associated with lower pCR rate in uni- and multivariate analyses. CONCLUSIONS: High baseline and EOT dNLR correlates with lower benefit from neoadjuvant CT in TNBC.

Re-interpretation of PAM50 gene expression as quantitative tumor dimensions shows utility for clinical trials: application to prognosis and response to paclitaxel in breast cancer.

BACKGROUND: We recently showed PAM50 gene expression data can be represented by five quantitative, orthogonal, multi-gene breast tumor traits. These novel tumor 'dimensions' were superior to categorical intrinsic subtypes for clustering in high-risk breast cancer pedigrees, indicating potential to represent underlying genetic susceptibilities and biological pathways. Here we explore the prognostic and predictive utility of these dimensions in a sub-study of GEICAM/9906, a Phase III randomized prospective clinical trial of paclitaxel in breast cancer. METHODS: Tumor dimensions, PC1-PC5, were calculated using pre-defined coefficients. Univariable and multivariable Cox proportional hazards (PH) models for disease-free survival (DFS) were used to identify associations between quantitative dimensions and prognosis or response to the addition of paclitaxel. Results were illustrated using Kaplan-Meier curves. RESULTS: Dimensions PC1 and PC5 were associated with DFS (Cox PH p = 6.7 [Formula: see text] 10-7 and p = 0.036), remaining significant after correction for standard clinical-pathological prognostic characteristics. Both dimensions were selected in the optimal multivariable model, together with nodal status and tumor size (Cox PH p = 1.4 [Formula: see text] 10-12). Interactions with treatment were identified for PC3 and PC4. Response to paclitaxel was restricted to tumors with low PC3 and PC4 (log-rank p = 0.0021). Women with tumors high for PC3 or PC4 showed no survival advantage. CONCLUSIONS: Our proof-of-concept application of quantitative dimensions illustrated novel findings and clinical utility beyond standard clinical-pathological characteristics and categorical intrinsic subtypes for prognosis and predicting chemotherapy response. Consideration of expression data as quantitative tumor dimensions offers new potential to identify clinically important patient subsets in clinical trials and advance precision medicine.

Predicting Response to Standard First-line Treatment in High-grade Serous Ovarian Carcinoma by Angiogenesis-related Genes.

BACKGROUND/AIM: Predicting response to treatment in high-grade serous ovarian carcinoma (HGSOC) still remains a clinical challenge. The standard-of-care for first-line chemotherapy, based on a combination of carboplatin and paclitaxel, achieves a high response rate. However, the development of drug resistance is one of the major limitations to efficacy. Therefore, identification of biomarkers able to predict response to chemotherapy in patients with HGSOC is a critical step for prognosis and treatment of the disease. Several studies suggest that angiogenesis is an important process in the development of ovarian carcinoma and chemoresistance. The aim of this study was to identify a profile of angiogenesis-related genes as a biomarker for response to first-line chemotherapy in HGSOC. MATERIALS AND METHODS: Formalin-fixed paraffin-embedded samples from 39 patients with HGSOC who underwent surgical cytoreduction and received a first-line chemotherapy with carboplatin and paclitaxel were included in this study. Expression levels of 82 angiogenesis-related genes were measured by quantitative real-time polymerase chain reaction using TaqMan low-density arrays. RESULTS: Univariate analysis identified five genes [angiopoietin 1 (ANGPT1), aryl hydrocarbon receptor nuclear translocator (ARNT), CD34, epidermal growth factor (EGF) and matrix metallopeptidase 3 (MMP3)] as being statistically associated with response to treatment. Multivariable analysis by Lasso-penalized Cox regression generated a model with the combined expression of seven genes [angiotensinogen (AGT), CD34, EGF, erythropoietin receptor (EPOR), interleukin 8 (IL8), MMP3 and MMP7)]. The area under the receiver operating characteristics curve (0.679) and cross-validated Kaplan-Meier survival curves were used to estimate the accuracy of these predictors. CONCLUSION: An angiogenesis-related gene expression profile useful for response prediction in HGSOC was identified, supporting the important role of angiogenesis in HGSOC.

The role of glycosyltransferase enzyme GCNT3 in colon and ovarian cancer prognosis and chemoresistance.

Glycosyltransferase enzyme GCNT3, has been proposed as a biomarker for prognosis in colorectal cancer (CRC). Our study goes in depth into the molecular basis of GCNT3 role in tumorigenesis and drug resistance, and it explores its potential role as biomarker in epithelial ovarian cancer (EOC). High levels of GCNT3 are associated with increased sensibility to 5-fluoracil in metastatic cells. Accordingly, GCNT3 re-expression leads to the gain of anti-carcinogenic cellular properties by reducing cell growth, invasion and by changing metabolic capacities. Integrated transcriptomic and proteomic analyses reveal that GCNT3 is linked to cellular cycle, mitosis and proliferation, response to drugs and metabolism pathways. The vascular epithelial growth factor A (VEGFA) arises as an attractive partner of GCNT3 functions in cell invasion and resistance. Finally, GCNT3 expression was analyzed in a cohort of 56 EOC patients followed by a meta-analysis of more than one thousand patients. This study reveals that GCNT3 might constitute a prognostic factor also in EOC, since its overexpression is associated with better clinical outcome and response to initial therapy. GCNT3 emerges as an essential glycosylation-related molecule in CRC and EOC progression, with potential interest as a predictive biomarker of response to chemotherapy.

The transcriptional and mutational landscapes of lipid metabolism-related genes in colon cancer.

Metabolic alterations encountered in tumors are well recognized and considered as a hallmark of cancer. In addition to Warburg Effect, epidemiological and experimental studies support the crucial role of lipid metabolism in colorectal cancer (CRC). The overexpression of four lipid metabolism-related genes (ABCA1, ACSL1, AGPAT1 and SCD genes) has been proposed as prognostic marker of stage II CRC (ColoLipidGene signature). In order to explore in depth the transcriptomic and genomic scenarios of ABCA1, ACSL1, AGPAT1 and SCD genes, we performed a transcriptomic meta-analysis in more than one thousand CRC individuals. Additionally we analyzed their genomic coding sequence in 95 patients, to find variants that could orchestrate CRC prognosis. We found that genetic variant rs3071, located on SCD gene, defines a 9.77% of stage II CRC patients with high risk of death. Moreover, individuals with upregulation of ABCA1 and AGPAT1 expression have an increased risk of CRC recurrence, independently of tumor stage. ABCA1 emerges as one of the main contributors to signature's prognostic effect. Indeed, both high ABCA1 expression and presence of tumoral genetic variants located in ABCA1 coding region, seem to be associated with CRC risk of death. In addition the non-synonymous polymorphism rs2230808, located on ABCA1, is associated with gene expression. Patients carrying at least one copy of minor allele showed higher levels of ABCA1 expression than patients carrying homozygous major allele. This study broaden the prognostic value of ABCA1, ACSL1, AGPAT1 and SCD genes, independently of CRC tumor stage, leading to future precision medicine approaches and "omics"-guided therapies.

Targeting the lipid metabolic axis ACSL/SCD in colorectal cancer progression by therapeutic miRNAs: miR-19b-1 role.

An abnormal acyl-CoA synthetase/stearoyl-CoA desaturase (ACSL/SCD) lipid network fuels colon cancer progression, endowing cells with invasive and migratory properties. Therapies against this metabolic network may be useful to improve clinical outcomes. Because micro-RNAs (miRNAs/miRs) are important epigenetic regulators, we investigated novel miRNAs targeting this pro-tumorigenic axis; hence to be used as therapeutic or prognostic miRNAs. Thirty-one putative common miRNAs were predicted to simultaneously target the three enzymes comprising the ACSL/SCD network. Target validation by quantitative RT-PCR, Western blotting, and luciferase assays showed miR-544a, miR-142, and miR-19b-1 as major regulators of the metabolic axis, ACSL/SCD Importantly, lower miR-19b-1 expression was associated with a decreased survival rate in colorectal cancer (CRC) patients, accordingly with ACSL/SCD involvement in patient relapse. Finally, miR-19b-1 regulated the pro-tumorigenic axis, ACSL/SCD, being able to inhibit invasion in colon cancer cells. Because its expression correlated with an increased survival rate in CRC patients, we propose miR-19b-1 as a potential noninvasive biomarker of disease-free survival and a promising therapeutic miRNA in CRC.

MicroRNA-661 modulates redox and metabolic homeostasis in colon cancer.

Cancer cell survival and metastasis are dependent on metabolic reprogramming that is capable of increasing resistance to oxidative and energetic stress. Targeting these two processes can be crucial for cancer progression. Herein, we describe the role of microRNA-661 (miR661) as epigenetic regulator of colon cancer (CC) cell metabolism. MicroR661 induces a global increase in reactive oxygen species, specifically in mitochondrial superoxide anions, which appears to be mediated by decreased carbohydrate metabolism and pentose phosphate pathway, and by a higher dependency on mitochondrial respiration. MicroR661 overexpression in non-metastatic human CC cells induces an epithelial-to-mesenchymal transition phenotype, and a reduced tolerance to metabolic stress. This seems to be a general effect of miR661 in CC, since metastatic CC cell metabolism is also compromised upon miR661 overexpression. We propose hexose-6-phosphate dehydrogenase and pyruvate kinase M2 as two key players related to the observed metabolic reprogramming. Finally, the clinical relevance of miR661 expression levels in stage-II and III CC patients is discussed. In conclusion, we propose miR661 as a potential modulator of redox and metabolic homeostasis in CC.

3'UTR Polymorphism in ACSL1 Gene Correlates with Expression Levels and Poor Clinical Outcome in Colon Cancer Patients.

Strong evidence suggests that lipid metabolism (LM) has an essential role in tumor growth to support special energetic and structural requirements of tumor cells. Recently, overexpression of LM-related genes, apolipoproteins related to metabolic syndrome, and ACSL/SCD network involved in fatty acid activation have been proposed as prognostic markers of colon cancer (CC). Furthermore, activation of this latter lipid network has been recently demonstrated to confer invasive and stem cell properties to tumor cells promoting tumor aggressiveness and patient relapse. With the aim of elucidating whether any genetic variation within these genes could influence basal expression levels and consequent susceptibility to relapse, we genotype, in 284 CC patients, 57 polymorphisms located in the 7 genes of these lipid networks previously associated with worse clinical outcome of CC patients (ABCA1, ACSL1, AGPAT1, APOA2, APOC1, APOC2 and SCD), some of them related to CC aggressiveness. After adjusting with clinical confounding factors and multiple comparisons, an association between genotype and disease-free survival (DFS) was shown for rs8086 in 3'-UTR of ACSL1 gene (HR 3.08; 95% CI 1.69-5.63; adjusted p = 0.046). Furthermore, the risk T/T genotype had significantly higher ACSL1 gene expression levels than patients carrying C/T or C/C genotype (means = 5.34; 3.73; 2.37 respectively; p-value (ANOVA) = 0.019), suggesting a functional role of this variant. Thus, we have identified a "risk genotype" of ACSL1 gene that confers constitutive high levels of the enzyme, which is involved in the activation of fatty acids through conversion to acyl-CoA and has been recently related to increased invasiveness of tumor cells. These results suggest that rs8086 of ACSL1 could be a promising prognostic marker in CC patients, reinforcing the relevance of LM in the progression of CC.

Predictive value of angiogenesis-related gene profiling in patients with HER2-negative metastatic breast cancer treated with bevacizumab and weekly paclitaxel.

Bevacizumab plus weekly paclitaxel improves progression-free survival (PFS) in HER2-negative metastatic breast cancer (mBC), but its use has been questioned due to the absence of a predictive biomarker, lack of benefit in overall survival (OS) and increased toxicity. We examined the baseline tumor angiogenic-related gene expression of 60 patients with mBC with the aim of finding a signature that predicts benefit from this drug.Multivariate analysis by Lasso-penalized Cox regression generated two predictive models: one, named G-model, including 11 genes, and the other one, named GC-model, including 13 genes plus 5 clinical covariates. Both models identified patients with improved PFS (HR (Hazard Ratio) 2.57 and 4.04, respectively) and OS (HR 3.29 and 3.43, respectively). The G-model distinguished low and high risk patients in the first 6 months, whereas the GC-model maintained significance over time.

A link between lipid metabolism and epithelial-mesenchymal transition provides a target for colon cancer therapy.

The alterations in carbohydrate metabolism that fuel tumor growth have been extensively studied. However, other metabolic pathways involved in malignant progression, demand further understanding. Here we describe a metabolic acyl-CoA synthetase/stearoyl-CoA desaturase ACSL/SCD network causing an epithelial-mesenchymal transition (EMT) program that promotes migration and invasion of colon cancer cells. The mesenchymal phenotype produced upon overexpression of these enzymes is reverted through reactivation of AMPK signaling. Furthermore, this network expression correlates with poorer clinical outcome of stage-II colon cancer patients. Finally, combined treatment with chemical inhibitors of ACSL/SCD selectively decreases cancer cell viability without reducing normal cells viability. Thus, ACSL/SCD network stimulates colon cancer progression through conferring increased energetic capacity and invasive and migratory properties to cancer cells, and might represent a new therapeutic opportunity for colon cancer treatment.

ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients.

Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group.

Clinical relevance of the differential expression of the glycosyltransferase gene GCNT3 in colon cancer.

Altered glycosylation is considered a universal cancer hallmark. Mucin-type core 2 1,6-N-acetylglucosaminyltransferase enzyme (C2GnT-M), encoded by the GCNT3 gene, has been reported to be altered in tumours and to possess tumour suppressor properties. In this work, we aimed to determine the possible role of GCNT3 gene expression as prognostic marker in colon cancer. We investigated the differential expression of GCNT3 gene among tumour samples from stage II colon cancer patients by quantitative reverse-transcription polymerase chain reaction (qRT-PCR). Univariate and Multivariate Cox regression analyses were used to determine the correlation between GCNT3 expression and disease-free survival. The risk of relapse in GCNT3 low-expressing cancer patients was significantly higher than that in GCNT3 high-expressing patients in both training (Hazard Ratio (HR) 4.26, p=0.002) and validation (HR 3.06, p=0.024) series of patients, and this association was independent of clinical factors. Additionally, qRT-PCR was used to explore the modulation of GCNT3 expression by different antitumour drugs. Three chemotherapeutic agents with different mechanism of action (5-fluorouracil, bortezomib and paclitaxel) significantly induced GCNT3 expression in several cancer cells, being observed the correlation between antitumour action and GCNT3 modulation, whereas this gene was not modulated in cells that do not respond to treatment. Overall, these results indicate that low GCNT3 expression is a promising prognostic biomarker for colon cancer that could be used to identify early-stage colon cancer patients at high risk of relapse. Additionally, our results suggest that this enzyme might also constitute a biomarker to monitor tumour response to chemotherapy in cancer patients.

Genes associated with metabolic syndrome predict disease-free survival in stage II colorectal cancer patients. A novel link between metabolic dysregulation and colorectal cancer.

Studies have recently suggested that metabolic syndrome and its components increase the risk of colorectal cancer. Both diseases are increasing in most countries, and the genetic association between them has not been fully elucidated. The objective of this study was to assess the association between genetic risk factors of metabolic syndrome or related conditions (obesity, hyperlipidaemia, diabetes mellitus type 2) and clinical outcome in stage II colorectal cancer patients. Expression levels of several genes related to metabolic syndrome and associated alterations were analysed by real-time qPCR in two equivalent but independent sets of stage II colorectal cancer patients. Using logistic regression models and cross-validation analysis with all tumour samples, we developed a metabolic syndrome-related gene expression profile to predict clinical outcome in stage II colorectal cancer patients. The results showed that a gene expression profile constituted by genes previously related to metabolic syndrome was significantly associated with clinical outcome of stage II colorectal cancer patients. This metabolic profile was able to identify patients with a low risk and high risk of relapse. Its predictive value was validated using an independent set of stage II colorectal cancer patients. The identification of a set of genes related to metabolic syndrome that predict survival in intermediate-stage colorectal cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy and avoid the toxic and unnecessary chemotherapy in patients classified as low risk. Our results also confirm the linkage between metabolic disorder and colorectal cancer and suggest the potential for cancer prevention and/or treatment by targeting these genes.

Genetic variation in the TP53 pathway and bladder cancer risk. a comprehensive analysis.

INTRODUCTION: Germline variants in TP63 have been consistently associated with several tumors, including bladder cancer, indicating the importance of TP53 pathway in cancer genetic susceptibility. However, variants in other related genes, including TP53 rs1042522 (Arg72Pro), still present controversial results. We carried out an in depth assessment of associations between common germline variants in the TP53 pathway and bladder cancer risk. MATERIAL AND METHODS: We investigated 184 tagSNPs from 18 genes in 1,058 cases and 1,138 controls from the Spanish Bladder Cancer/EPICURO Study. Cases were newly-diagnosed bladder cancer patients during 1998-2001. Hospital controls were age-gender, and area matched to cases. SNPs were genotyped in blood DNA using Illumina Golden Gate and TaqMan assays. Cases were subphenotyped according to stage/grade and tumor p53 expression. We applied classical tests to assess individual SNP associations and the Least Absolute Shrinkage and Selection Operator (LASSO)-penalized logistic regression analysis to assess multiple SNPs simultaneously. RESULTS: Based on classical analyses, SNPs in BAK1 (1), IGF1R (5), P53AIP1 (1), PMAIP1 (2), SERINPB5 (3), TP63 (3), and TP73 (1) showed significant associations at p-value≤0.05. However, no evidence of association, either with overall risk or with specific disease subtypes, was observed after correction for multiple testing (p-value≥0.8). LASSO selected the SNP rs6567355 in SERPINB5 with 83% of reproducibility. This SNP provided an OR = 1.21, 95%CI 1.05-1.38, p-value = 0.006, and a corrected p-value = 0.5 when controlling for over-estimation. DISCUSSION: We found no strong evidence that common variants in the TP53 pathway are associated with bladder cancer susceptibility. Our study suggests that it is unlikely that TP53 Arg72Pro is implicated in the UCB in white Europeans. SERPINB5 and TP63 variation deserve further exploration in extended studies.

Whole genome prediction of bladder cancer risk with the Bayesian LASSO.

To build a predictive model for urothelial carcinoma of the bladder (UCB) risk combining both genomic and nongenomic data, 1,127 cases and 1,090 controls from the Spanish Bladder Cancer/EPICURO study were genotyped using the HumanHap 1M SNP array. After quality control filters, genotypes from 475,290 variants were available. Nongenomic information comprised age, gender, region, and smoking status. Three Bayesian threshold models were implemented including: (1) only genomic information, (2) only nongenomic data, and (3) both sources of information. The three models were applied to the whole population, to only nonsmokers, to male smokers, and to extreme phenotypes to potentiate the UCB genetic component. The area under the ROC curve allowed evaluating the predictive ability of each model in a 10-fold cross-validation scenario. Smoking status showed the highest predictive ability of UCB risk (AUCtest = 0.62). On the other hand, the AUC of all genetic variants was poorer (0.53). When the extreme phenotype approach was applied, the predictive ability of the genomic model improved 15%. This study represents a first attempt to build a predictive model for UCB risk combining both genomic and nongenomic data and applying state-of-the-art statistical approaches. However, the lack of genetic relatedness among individuals, the complexity of UCB etiology, as well as a relatively small statistical power, may explain the low predictive ability for UCB risk. The study confirms the difficulty of predicting complex diseases using genetic data, and suggests the limited translational potential of findings from this type of data into public health interventions.

A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the breast cancer association consortium.

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

Recurrent inactivation of STAG2 in bladder cancer is not associated with aneuploidy.

Urothelial bladder cancer (UBC) is heterogeneous at the clinical, pathological and genetic levels. Tumor invasiveness (T) and grade (G) are the main factors associated with outcome and determine patient management. A discovery exome sequencing screen (n = 17), followed by a prevalence screen (n = 60), identified new genes mutated in this tumor coding for proteins involved in chromatin modification (MLL2, ASXL2 and BPTF), cell division (STAG2, SMC1A and SMC1B) and DNA repair (ATM, ERCC2 and FANCA). STAG2, a subunit of cohesin, was significantly and commonly mutated or lost in UBC, mainly in tumors of low stage or grade, and its loss was associated with improved outcome. Loss of expression was often observed in chromosomally stable tumors, and STAG2 knockdown in bladder cancer cells did not increase aneuploidy. STAG2 reintroduction in non-expressing cells led to reduced colony formation. Our findings indicate that STAG2 is a new UBC tumor suppressor acting through mechanisms that are different from its role in preventing aneuploidy.