Noncoding SNP at rs1663689 represses ADGRG6 via interchromosomal interaction and reduces lung cancer progression.

A previous genome-wide association study (GWAS) revealed an association of the noncoding SNP rs1663689 with susceptibility to lung cancer in the Chinese population. However, the underlying mechanism is unknown. In this study, using allele-specific 4C-seq in heterozygous lung cancer cells combined with epigenetic information from CRISPR/Cas9-edited cell lines, we show that the rs1663689 C/C variant represses the expression of ADGRG6, a gene located on a separate chromosome, through an interchromosomal interaction of the rs1663689 bearing region with the ADGRG6 promoter. This reduces downstream cAMP-PKA signaling and subsequently tumor growth both in vitro and in xenograft models. Using patient-derived organoids, we show that rs1663689 T/T-but not C/C-bearing lung tumors are sensitive to the PKA inhibitor H89, potentially informing therapeutic strategies. Our study identifies a genetic variant-mediated interchromosomal interaction underlying ADGRG6 regulation and suggests that targeting the cAMP-PKA signaling pathway may be beneficial in lung cancer patients bearing the homozygous risk genotype at rs1663689.

Diagnosis, treatment and survival from bladder, upper urinary tract, and urethral cancers: real-world findings from NHS England between 2013 and 2019.

OBJECTIVE: We report NHS England data for patients with bladder cancer (BC), upper tract urothelial cancer (UTUC: renal pelvic and ureteric), and urethral cancers from 2013 to 2019. MATERIALS AND METHODS: Hospital episode statistics, waiting times, and cancer registrations were extracted from NHS Digital. RESULTS: Registrations included 128 823 individuals with BC, 16 018 with UTUC, and 2533 with urethral cancer. In 2019, 150 816 persons were living with a diagnosis of BC, of whom 113 067 (75.0%) were men, 85 117 (56.5%) were aged >75 years, and 95 553 (91.7%) were Caucasian. Incidence rates were stable (32.7-34.3 for BC, 3.9-4.2 for UTUC and 0.6-0.7 for urethral cancer per 100 000 population). Most patients 52 097 (mean [range] 41.3% [40.7-42.0%]) were referred outside the 2-week-wait pathway and 15 340 (mean [range] 12.2% [11.7-12.6%]) presented as emergencies. Surgery, radiotherapy, chemotherapy, or multimodal treatment use varied with disease stage, patient factors and Cancer Alliance. Between 27% and 29% (n = 6616) of muscle-invasive BCs did not receive radical treatment. Survival rates reflected stage, grade, location, and tumour histology. Overall survival rates did not improve over time (relative change: 0.97, 95% confidence interval 0.97-0.97) at 2 years in contrast to other cancers. CONCLUSION: The diagnostic pathway for BC needs improvement. Increases in survival might be delivered through greater use of radical treatment. NHS Digital data offers a population-wide picture of this disease but does not allow individual outcomes to be matched with disease or patient features and key parameters can be missing or incomplete.

Incidence and Outcomes of Early Cancers After Kidney Transplantation.

Outcomes of early cancers after kidney transplantation are not well-understood. We included recipients of first live and deceased donor kidney transplants who developed de novo cancers in Australia and New Zealand between 1980-2016. We compared the frequency and stage of specific cancer types that developed early (≤12-months) and late (>12-months) post-transplantation. Risk factors for death were evaluated using multivariable Cox regression analyses. Of 2,759 recipients who developed de novo cancer, followed-up for 40,035 person-years, 243 (8.8%) patients were diagnosed with early cancer. Post-transplant lymphoproliferative disease, urinary cancers and melanoma were the most common cancer types (26%, 18%, and 12%) and the majority were either in-situ or locally invasive lesions (55%, 84%, and 86%). Tumors arising early from the gastrointestinal and respiratory systems were uncommon but aggressive, with 40% presenting with metastatic disease at time of diagnosis. Overall, 32% of patients with early cancers died within a median of 4.7 months (IQR:0.6-16) post-diagnosis and 91% were cancer-related deaths. Older recipient and donor age were associated with an increased risk of all-cause death. Early cancers, though infrequent in kidney transplant recipients, are associated with poor outcomes, as nearly 1 in 3 died from cancer-related death; with majority of deaths occurring within 12-months of cancer diagnosis.

omicsGAT: Graph Attention Network for Cancer Subtype Analyses.

The use of high-throughput omics technologies is becoming increasingly popular in all facets of biomedical science. The mRNA sequencing (RNA-seq) method reports quantitative measures of more than tens of thousands of biological features. It provides a more comprehensive molecular perspective of studied cancer mechanisms compared to traditional approaches. Graph-based learning models have been proposed to learn important hidden representations from gene expression data and network structure to improve cancer outcome prediction, patient stratification, and cell clustering. However, these graph-based methods cannot rank the importance of the different neighbors for a particular sample in the downstream cancer subtype analyses. In this study, we introduce omicsGAT, a graph attention network (GAT) model to integrate graph-based learning with an attention mechanism for RNA-seq data analysis. The multi-head attention mechanism in omicsGAT can more effectively secure information of a particular sample by assigning different attention coefficients to its neighbors. Comprehensive experiments on The Cancer Genome Atlas (TCGA) breast cancer and bladder cancer bulk RNA-seq data and two single-cell RNA-seq datasets validate that (1) the proposed model can effectively integrate neighborhood information of a sample and learn an embedding vector to improve disease phenotype prediction, cancer patient stratification, and cell clustering of the sample and (2) the attention matrix generated from the multi-head attention coefficients provides more useful information compared to the sample correlation-based adjacency matrix. From the results, we can conclude that some neighbors play a more important role than others in cancer subtype analyses of a particular sample based on the attention coefficient.

Genomic and epigenetic aberrations of chromosome 1p36.13 have prognostic implications in malignancies.

Deletions of chromosome 1p36 are common in malignancies; however, there is limited information regarding the biological and prognostic implications of 1p36 in cancer. Steroid Receptor-Associated and Regulated Protein (SRARP) is a tumor suppressor on chromosome 1p36.13 that its inactivation predicts poor cancer outcome, indicating that the 1p36.13 segment requires further studies. Therefore, a comprehensive multi-omics analysis of The Cancer Genome Atlas (TCGA), the Pan-Cancer Analysis of Whole Genomes (PCAWD), the International Cancer Genome Consortium (ICGC), and the Genomic Data Commons (GDC) Pan-Cancer datasets was conducted to investigate the prognostic implications of 1p36.13 in malignancies. This study revealed that expression and DNA methylation of multiple genes on 1p36.13 are significantly associated with survival in primary tumors and normal adjacent tissues. In addition, copy-number loss in every gene on 1p36.13 predicts poor cancer outcome. Importantly, copy-number loss and somatic mutations of chromosome 1p36.13 segment are associated with worse survival in primary tumors, and DNA hypermethylation of 1p36.13 predicts poor outcome in normal adjacent tissues. Therefore, genomic and epigenetic aberrations of chromosome 1p36.13 have promising prognostic implications in cancer.

Mask-Guided Convolutional Neural Network for Breast Tumor Prognostic Outcome Prediction on 3D DCE-MR Images.

In this proof-of-concept work, we have developed a 3D-CNN architecture that is guided by the tumor mask for classifying several patient-outcomes in breast cancer from the respective 3D dynamic contrast-enhanced MRI (DCE-MRI) images. The tumor masks on DCE-MRI images were generated using pre- and post-contrast images and validated by experienced radiologists. We show that our proposed mask-guided classification has a higher accuracy than that from either the full image without tumor masks (including background) or the masked voxels only. We have used two patient outcomes for this study: (1) recurrence of cancer after 5 years of imaging and (2) HER2 status, for comparing accuracies of different models. By looking at the activation maps, we conclude that an image-based prediction model using 3D-CNN could be improved by even a conservatively generated mask, rather than overly trusting an unguided, blind 3D-CNN. A blind CNN may classify accurately enough, while its attention may really be focused on a remote region within 3D images. On the other hand, only using a conservatively segmented region may not be as good for classification as using full images but forcing the model's attention toward the known regions of interest.

Detection of crown-like structures in breast adipose tissue and clinical outcomes among African-American and White women with breast cancer.

BACKGROUND: Crown-like structures in breast adipose tissue (CLS-B), composed of necrotic adipocytes encircled by macrophages, are associated with obesity and hypothesized to worsen breast cancer prognosis; however, data are sparse, particularly in multi-racial populations. METHODS: We assessed specimens for CLS-B from 174 African-American and 168 White women with stage I-III breast cancer treated by mastectomy. Benign breast tissue from an uninvolved quadrant was immunohistochemically stained for CD68 to determine CLS-B presence and density (per cm2 of adipose tissue). Demographic and lifestyle factors, collected via medical record review, were analyzed for associations with CLS-B using logistic regression. Multivariable Cox proportional hazards models were used to compute hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between CLS-B and overall (OS) or progression-free (PFS) survival. RESULTS: Detection of any CLS-B was similar between African-American (32%) and White (29%) patients with no evidence of an association between race and CLS-B in multivariable models (OR = 0.82, 95% CI = 0.49-1.36). Detection of CLS-B was associated with obesity (OR = 4.73, 95% CI = 2.48-9.01) and age ≥ 60 years at diagnosis (OR = 1.78, 95% CI = 0.99-3.21). There was some evidence of associations with parity and current smoking status. Detection of CLS-B was not associated with OS (HR = 1.02, 95% CI = 0.55-1.87) or PFS (HR = 0.99, 95% CI = 0.59-1.67). CONCLUSIONS: Our results show a strong, positive association between BMI and CLS-B in non-tumor tissue similar to previous findings. Detection of CLS-B did not vary by race and was not associated with worse OS or PFS.

Metabolic syndrome and early stage breast cancer outcome: results from a prospective observational study.

PURPOSE: Obesity and insulin resistance have been associated with poor prognosis in breast cancer (BC). The present prospective study aimed to investigate the impact of metabolic syndrome (MetS) and its components on early BC (eBC) patients' outcome. METHODS: MetS was defined by the presence of 3 to 5 of the following components: waist circumference > 88 cm, blood pressure ≥ 130/≥ 85 mmHg, serum levels of triglycerides ≥ 150 mg/dL, high density lipoprotein < 50 mg/dL and fasting glucose ≥ 110 mg/dL. Seven hundred and seventeen patients with data on ≥ 4 MetS components at BC diagnosis were enrolled. Study population was divided into two groups: patients with < 3 (non-MetS) vs. ≥ 3 components (MetS). Categorical variables were analyzed by Chi-square test and survival data by log-rank test and Cox proportional hazards regression model. RESULTS: Overall, 544 (75.9%) and 173 (24.1%) women were categorized as non-MetS and MetS, respectively. MetS patients were more likely to be older, postmenopausal, and insulin-resistant compared to non-MetS patients (p < 0.05). In multivariate analysis, MetS patients had a numerically higher risk of relapse [disease-free survival (DFS), hazard ratio (HR) 1.51, p = 0.07] and a significantly higher risk of death compared to non-MetS patients [overall survival (OS), HR 3.01, p < 0.0001; breast cancer-specific survival (BCSS), HR 3.16, p = 0.001]. Additionally, patients with 1 to 2 components of MetS had an increased risk of dying compared to patients with 0 components (OS, HR 4.90, p = 0.01; BCSS, HR 6.07, p = 0.02). CONCLUSIONS: MetS correlated with poor outcome in eBC patients. Among patients without full criteria for MetS diagnosis, the presence of 1 or 2 components of the syndrome may predict for worse survival.

Diagnostic, prognostic, and therapeutic potency of microRNA 21 in the pathogenesis of colon cancer, current status and prospective.

Aberrant microRNA (miR) expression is implicated in multiple human malignancies. miR-21, acting as a proto-oncogene, is involved in a variety of cellular processes and tumorigenesis and is frequently overexpressed in some cancer types. Several tumor suppressors, metastatic, and apoptotic genes have been identified as miR-21 targets, including Ras homolog gene family member B, PTEN, Sprouty2, programmed cell death 4, Integrin-ß4, and E-cadherin thereby regulating tumor growth, invasion, and metastasis. There is a growing evidence that miR-21 expression is associated with clinical outcomes in patients with colorectal cancer (CRC). In this review, we summarize the potential diagnostic, prognostic, and therapeutic values of miR-21 in CRC progression for a better understanding and hence a better management of this disease.

Cutaneous toxicity as a predictive biomarker for clinical outcome in patients receiving anticancer therapy.

The relationship between treatment outcome and cutaneous toxicity induced by anticancer therapy has gained attention in the past decade. In this article, we have provided an overview of the 3 main classes of anticancer agents-specifically, molecularly targeted kinase inhibitors, immune checkpoint inhibitors, and cytotoxic chemotherapeutics-and described the data evaluating the association between cutaneous toxicity induced by these agents and survival benefit. Although preliminary studies are promising with regard to the potential role of cutaneous toxicities as a surrogate biomarker of efficacy of treatment, larger prospective studies are needed to confirm this relationship. Dermatologists have a unique opportunity to collaborate with oncologists in the multidisciplinary treatment paradigm by helping to identify and manage these dermatologic events in patients with cancer. A heightened awareness of these toxicities is critical, as it can potentially allow recognition of the efficacy of anticancer therapy and may influence treatment decisions and patient outcomes.

Lymph node location is a risk factor for papillary thyroid cancer-related death.

PURPOSE: Papillary thyroid cancer (PTC) has good prognosis with a very low chance of mortality. The prognostic role of metastatic lymph node location was judged controversial and more recently (TNM VIII ed.) was considered to have no impact on the prognosis of older patients. The aim of the study was to evaluate the role of metastasized node location on PTC-related mortality. METHODS: PTC-related mortality was analysed in a consecutive retrospective series of 1653 PTC patients followed at our Thyroid Clinic (mean follow-up 5.9 years). RESULTS: Sixteen out of 1653 patients (0.96%) died because of PTC. Average age was 68 years at presentation and 74.7 at death. F/M ratio was 1:1. The death rate increased in relation to the lymph node status: 0.2% in N0, 0.3% in N1a and 3.0% in N1b. CONCLUSIONS: The presence of lymph node metastases in the N1b compartment should be considered as a risk factor for distant metastatic spread and for cancer-related death and included in post-surgery evaluation.

Protocol of the PANCALYZE trial: a multicenter, prospective study investigating the tumor biomarkers CXCR4, SMAD4, SOX9 and IFIT3 in patients with resected pancreatic adenocarcinoma to predict the pattern of recurrence of the disease.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies today with an urgent need for novel therapeutic strategies. Biomarker analysis helps to better understand tumor biology and might emerge as a tool to develop personalized therapies. The aim of the study is to investigate four promising biomarkers to predict the clinical course and particularly the pattern of tumor recurrence after surgical resection. DESIGN: Patients undergoing surgery for PDAC can be enrolled into the PANCALYZE trial. Biomarker expression of CXCR4, SMAD4, SOX9 and IFIT3 will be prospectively assessed by immunohistochemistry and verified by rt.-PCR from tumor and adjacent healthy pancreatic tissue of surgical specimen. Immunohistochemistry expression pattern of all four biomarkers will be combined into a single score. Beginning with the hospital stay clinical data from enrolled patients will be collected and followed. Different adjuvant chemotherapy protocols will be used to create subgroups. The combined biomarker expression score will be correlated with the further clinical course of the patients to test the hypothesis if CXCR4 positive, SMAD4 negative, SOX9 positive, IFIT3 positive tumors will predominantly develop metastatic spread. DISCUSSION: Pancreatic cancer is associated with different patterns of progression requiring personalized therapeutic strategies. Biomarker expression analysis might be a tool to predict the pattern of tumor recurrence and discriminate patients that develop systemic metastatic disease from those with tumors that rather develop local recurrence over time. This data might lead to personalized adjuvant treatment decisions as patients with tumors that stay localized might benefit from adjuvant local therapies like radiochemotherapy as compared to those with systemic recurrence who would benefit exclusively from chemotherapy. Moreover, the pattern of propagation might be a predefined characteristic of pancreatic cancer determined by the genetic signature of the tumor. In the future, biomarker expression analysis could be performed on tumor biopsies to develop personalized therapeutic pathways right after diagnosis of cancer. TRIAL REGISTRATION: German Clinical Trials Register, DRKS00006179 .

Latero-cervical lymph node metastases (N1b) represent an additional risk factor for papillary thyroid cancer outcome.

PURPOSE: Papillary thyroid carcinoma (PTC), the most common thyroid cancer histotype, has a good prognosis even when spread to the neck lymph node (LN). The prognostic role of LN metastases' location is still controversial. The aim of the present study was to evaluate the clinical relevance of the number and location of LN metastases at presentation in PTCs. METHODS: This retrospective study included a consecutive series of 1653 PTC patients followed for a mean period of 5.9 years in a referral thyroid cancer clinic. All patients have undergone thyroidectomy with the dissection of at least six LNs. According to the LN status, patients were subdivided into 569 N0 (34.4%), 644 N1a (39.0%, central compartment) and 440 N1b (26.6%, latero-cervical compartment). RESULTS: Age at diagnosis was significantly lower in N1b (39.8, IQR 30.7-51.6) and N1a (40.1, IQR 31.3-50.1) than in N0 (44.7, IQR 36.6-55.0 yrs). The male gender was more prevalent in N1b than in N1a and N0 (F/M = 1.9/1, 4.0/1 and 5.5/1, respectively). Persistent/recurrent disease at last control was significantly more frequent in N1b (29.8%) than in N1a (14.3%), and in N1a than in N0 (4.2%) (p < 0.01 for all). Also, distant metastases were significantly (p < 0.001) more frequent in N1b (14.1%) than in N1a (4.3%) and N0 (1.6%). LN metastases' number (>5) was a significant risk factor for persistent/recurrent disease only for N1a patients. CONCLUSIONS: These data indicate that persistent/recurrent disease and distant metastases are significantly more frequent in patients with latero-cervical LN (N1b) metastases and that the LN location should be used for a better postsurgical risk stratification.

The OncoSim model: development and use for better decision-making in Canadian cancer control.

The Canadian Partnership Against Cancer was created in 2007 by the federal government to accelerate cancer control across Canada. Its OncoSim microsimulation model platform, which consists of a suite of specific cancer models, was conceived as a tool to augment conventional resources for population-level policy- and decision-making. The Canadian Partnership Against Cancer manages the OncoSim program, with funding from Health Canada and model development by Statistics Canada. Microsimulation modelling allows for the detailed capture of population heterogeneity and health and demographic history over time. Extensive data from multiple Canadian sources were used as inputs or to validate the model. OncoSim has been validated through expert consultation; assessments of face validity, internal validity, and external validity; and model fit against observed data. The platform comprises three in-depth cancer models (lung, colorectal, cervical), with another in-depth model (breast) and a generalized model (25 cancers) being in development. Unique among models of its class, OncoSim is available online for public sector use free of charge. Users can customize input values and output display, and extensive user support is provided. OncoSim has been used to support decision-making at the national and jurisdictional levels. Although simulation studies are generally not included in hierarchies of evidence, they are integral to informing cancer control policy when clinical studies are not feasible. OncoSim can evaluate complex intervention scenarios for multiple cancers. Canadian decision-makers thus have a powerful tool to assess the costs, benefits, cost-effectiveness, and budgetary effects of cancer control interventions when faced with difficult choices for improvements in population health and resource allocation.

Association of very low prostate-specific antigen levels with increased cancer-specific death in men with high-grade prostate cancer.

BACKGROUND: The objective of this study was to determine whether a very low presenting prostate-specific antigen (PSA) level was associated with greater prostate cancer-specific mortality (PCSM) among men with a Gleason score (GS) of 8 to 10. METHODS: The Surveillance, Epidemiology, and End Results program was used to identify 328,904 men diagnosed with clinicalT1 (cT1)-4N0M0 prostate cancer between 2004 and 2010. A multivariate Fine-Gray competing risks regression analysis was used to determine PCSM as a function of the PSA level (≤ 2.5, 2.6-4, 4.1-10, 10.1-20, 20.1-40, or > 40 ng/mL) and GS (8-10 vs ≤ 7). RESULTS: The median follow-up was 38 months. Among men with GS 8-10 disease, with a PSA level of 4.1 to 10 ng/mL as the referent, the adjusted hazard ratio for PCSM for men was 2.15 with a PSA level ≤ 2.5 ng/mL (95% confidence interval [CI], 1.65-2.79; P < .001), 1.60 with a PSA level of 2.6 to 4 ng/mL (95% CI, 1.22-2.10; P = .001), 1.60 with a PSA level of 10.1 to 20 ng/mL (95% CI, 1.41-1.82; P < .001), 2.08 with a PSA level of 20.1 to 40 ng/mL (95% CI, 1.81-2.38; P < .001), and 3.23 with a PSA level > 40 ng/mL (95% CI, 2.85-3.65; P < .001). This suggested a U-shaped distribution. There was a significant interaction between the PSA level and GS (P(interaction) < .001) such that only a PSA level ≤ 2.5 ng/mL significantly predicted poorer PCSM among patients with GS 8-10 disease. CONCLUSIONS: Among patients with high-grade disease, patients with PSA levels ≤ 2.5 ng/mL or PSA levels of 2.6 to 4 ng/mL appear to have a higher risk for cancer-specific death in comparison with patients with PSA levels of 10.1 to 20 ng/mL, and this supports the notion that low PSA levels in GS 8-10 disease may be a sign of aggressive and very poorly differentiated or anaplastic low PSA-producing tumors. Patients with low-PSA, GS 8-10 disease should be considered for clinical trials studying the use of chemotherapy and other novel agents for very high-risk prostate cancers.

Prediction of non-muscle invasive bladder cancer outcomes assessed by innovative multimarker prognostic models.

BACKGROUND: We adapted Bayesian statistical learning strategies to the prognosis field to investigate if genome-wide common SNP improve the prediction ability of clinico-pathological prognosticators and applied it to non-muscle invasive bladder cancer (NMIBC) patients. METHODS: Adapted Bayesian sequential threshold models in combination with LASSO were applied to consider the time-to-event and the censoring nature of data. We studied 822 NMIBC patients followed-up >10 years. The study outcomes were time-to-first-recurrence and time-to-progression. The predictive ability of the models including up to 171,304 SNP and/or 6 clinico-pathological prognosticators was evaluated using AUC-ROC and determination coefficient. RESULTS: Clinico-pathological prognosticators explained a larger proportion of the time-to-first-recurrence (3.1 %) and time-to-progression (5.4 %) phenotypic variances than SNPs (1 and 0.01 %, respectively). Adding SNPs to the clinico-pathological-parameters model slightly improved the prediction of time-to-first-recurrence (up to 4 %). The prediction of time-to-progression using both clinico-pathological prognosticators and SNP did not improve. Heritability (h (2)) of both outcomes was <1 % in NMIBC. CONCLUSIONS: We adapted a Bayesian statistical learning method to deal with a large number of parameters in prognostic studies. Common SNPs showed a limited role in predicting NMIBC outcomes yielding a very low heritability for both outcomes. We report for the first time a heritability estimate for a disease outcome. Our method can be extended to other disease models.

Orbital Apex Metastases From Primary Colorectal Adenocarcinoma: A Rare Cause for Unilateral Vision Loss.

Colorectal cancer is one of the most common causes of cancer-related death in the United States. Although it frequently metastasizes to adjacent structures such as the liver, orbital metastases are exceedingly uncommon. Additionally, the morbidity and mortality associated with colorectal cancer appear to be shifting to a younger population, a phenomenon that is exacerbated in minority populations. We present a case of orbital metastasis from colorectal carcinoma in a young Hispanic male. This uncommon presentation of disease emphasizes the link between healthcare disparity and differential outcomes of colorectal cancer.

Integrative analysis of prostate cancer aggressiveness.

BACKGROUND: Clinical management of prostate cancer (PC) is still highly demanding on the identification of robust biomarkers which will allow a more precise prediction of disease progression. METHODS: We profiled both mRNA expression and DNA copy number alterations (CNAs) from laser capture microdissected cells from 31 PC patients and 17 patients with benign prostatic hyperplasia using Affymetrix GeneChip® technology. PC patients were subdivided into an aggressive (Gleason Score 8 or higher, and/or T3/T4 and/or N+/M+) and non-aggressive (all others) form of PC. Furthermore, we correlated the two datasets, as genes whose varied expression is due to a chromosomal alteration, may suggest a causal implication of these genes in the disease. All statistical analyses were performed in R version 2.15.0 and Bioconductor version 1.8.1., respectively. RESULTS: We confirmed several common altered chromosomal regions as well as recently discovered loci such as deletions on chromosomes 3p14.1-3p13 and 13q13.3-13q14.11 supporting a possible role for RYBP, RGC32, and ELF1 in tumor suppression. Integrative analysis of expression and CN data combined with data retrieved from online databases propose PTP4A3 and ELF1 as possible factors for tumor progression. CONCLUSIONS: Copy number data analysis revealed some significant differences between aggressive and non-aggressive tumors, while gene expression data alone could not define an aggressive group of patients. The assessment of CNA may have diagnostic and prognostic value in PC.