Widespread and Functional RNA Circularization in Localized Prostate Cancer.

The cancer transcriptome is remarkably complex, including low-abundance transcripts, many not polyadenylated. To fully characterize the transcriptome of localized prostate cancer, we performed ultra-deep total RNA-seq on 144 tumors with rich clinical annotation. This revealed a linear transcriptomic subtype associated with the aggressive intraductal carcinoma sub-histology and a fusion profile that differentiates localized from metastatic disease. Analysis of back-splicing events showed widespread RNA circularization, with the average tumor expressing 7,232 circular RNAs (circRNAs). The degree of circRNA production was correlated to disease progression in multiple patient cohorts. Loss-of-function screening identified 11.3% of highly abundant circRNAs as essential for cell proliferation; for ∼90% of these, their parental linear transcripts were not essential. Individual circRNAs can have distinct functions, with circCSNK1G3 promoting cell growth by interacting with miR-181. These data advocate for adoption of ultra-deep RNA-seq without poly-A selection to interrogate both linear and circular transcriptomes.

CIBRA identifies genomic alterations with a system-wide impact on tumor biology.

MOTIVATION: Genomic instability is a hallmark of cancer, leading to many somatic alterations. Identifying which alterations have a system-wide impact is a challenging task. Nevertheless, this is an essential first step for prioritizing potential biomarkers. We developed CIBRA (Computational Identification of Biologically Relevant Alterations), a method that determines the system-wide impact of genomic alterations on tumor biology by integrating two distinct omics data types: one indicating genomic alterations (e.g. genomics), and another defining a system-wide expression response (e.g. transcriptomics). CIBRA was evaluated with genome-wide screens in 33 cancer types using primary and metastatic cancer data from the Cancer Genome Atlas and Hartwig Medical Foundation. RESULTS: We demonstrate the capability of CIBRA by successfully confirming the impact of point mutations in experimentally validated oncogenes and tumor suppressor genes (0.79 AUC). Surprisingly, many genes affected by structural variants were identified to have a strong system-wide impact (30.3%), suggesting that their role in cancer development has thus far been largely under-reported. Additionally, CIBRA can identify impact with only 10 cases and controls, providing a novel way to prioritize genomic alterations with a prominent role in cancer biology. Our findings demonstrate that CIBRA can identify cancer drivers by combining genomics and transcriptomics data. Moreover, our work shows an unexpected substantial system-wide impact of structural variants in cancer. Hence, CIBRA has the potential to preselect and refine current definitions of genomic alterations to derive more nuanced biomarkers for diagnostics, disease progression, and treatment response. AVAILABILITY AND IMPLEMENTATION: The R package CIBRA is available at https://github.com/AIT4LIFE-UU/CIBRA.

Genome-wide cell-free DNA fragmentation in patients with cancer.

Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.

Predicting early extrahepatic recurrence after local treatment of colorectal liver metastases.

BACKGROUND: Patients who develop early extrahepatic recurrence (EHR) may not benefit from local treatment of colorectal liver metastases (CRLMs). This study aimed to develop a prediction model for early EHR after local treatment of CRLMs using a national data set. METHODS: A Cox regression prediction model for EHR was developed and validated internally using data on patients who had local treatment for CRLMs with curative intent. Performance assessment included calibration, discrimination, net benefit, and generalizability by internal-external cross-validation. The prognostic relevance of early EHR (within 6 months) was evaluated by landmark analysis. RESULTS: During a median follow-up of 35 months, 557 of the 1077 patients had EHR and 249 died. Median overall survival was 19.5 (95 per cent c.i. 15.6 to 23.0) months in patients with early EHR after CRLM treatment, compared with not reached (45.3 months to not reached) in patients without an early EHR. The EHR prediction model included side and stage of the primary tumour, RAS/BRAFV600E mutational status, and number and size of CRLMs. The range of 6-month EHR predictions was 5.9-56.0 (i.q.r. 12.9-22.0) per cent. The model demonstrated good calibration and discrimination. The C-index through 6 and 12 months was 0.663 (95 per cent c.i. 0.624 to 0.702) and 0.661 (0.632 to 0.689) respectively. The observed 6-month EHR risk was 6.5 per cent for patients in the lowest quartile of predicted risk compared with 32.0 per cent in the highest quartile. CONCLUSION: Early EHR after local treatment of CRLMs can be predicted.

Loss of enteric neuronal Ndrg4 promotes colorectal cancer via increased release of Nid1 and Fbln2.

The N-Myc Downstream-Regulated Gene 4 (NDRG4), a prominent biomarker for colorectal cancer (CRC), is specifically expressed by enteric neurons. Considering that nerves are important members of the tumor microenvironment, we here establish different Ndrg4 knockout (Ndrg4-/- ) CRC models and an indirect co-culture of primary enteric nervous system (ENS) cells and intestinal organoids to identify whether the ENS, via NDRG4, affects intestinal tumorigenesis. Linking immunostainings and gastrointestinal motility (GI) assays, we show that the absence of Ndrg4 does not trigger any functional or morphological GI abnormalities. However, combining in vivo, in vitro, and quantitative proteomics data, we uncover that Ndrg4 knockdown is associated with enlarged intestinal adenoma development and that organoid growth is boosted by the Ndrg4-/- ENS cell secretome, which is enriched for Nidogen-1 (Nid1) and Fibulin-2 (Fbln2). Moreover, NID1 and FBLN2 are expressed in enteric neurons, enhance migration capacities of CRC cells, and are enriched in human CRC secretomes. Hence, we provide evidence that the ENS, via loss of Ndrg4, is involved in colorectal pathogenesis and that ENS-derived Nidogen-1 and Fibulin-2 enhance colorectal carcinogenesis.

Data-Independent Acquisition Mass Spectrometry Analysis of FFPE Rectal Cancer Samples Offers In-Depth Proteomics Characterization of the Response to Neoadjuvant Chemoradiotherapy.

Locally advanced rectal cancer (LARC) presents a challenge in identifying molecular markers linked to the response to neoadjuvant chemoradiotherapy (nCRT). This study aimed to utilize a sensitive proteomic method, data-independent mass spectrometry (DIA-MS), to extensively analyze the LARC proteome, seeking individuals with favorable initial responses suitable for a watch-and-wait approach. This research addresses the unmet need to understand the response to treatment, potentially guiding personalized strategies for LARC patients. Post-treatment assessment included MRI scans and proctoscopy. This research involved 97 LARC patients treated with intense chemoradiotherapy, comprising radiation and chemotherapy. Out of 97 LARC included in this study, we selected 20 samples with the most different responses to nCRT for proteome profiling (responders vs. non-responders). This proteomic approach shows extensive proteome coverage in LARC samples. The analysis identified a significant number of proteins compared to a prior study. A total of 915 proteins exhibited differential expression between the two groups, with certain signaling pathways associated with response mechanisms, while top candidates had good predictive potential. Proteins encoded by genes SMPDL3A, PCTP, LGMN, SYNJ2, NHLRC3, GLB1, and RAB43 showed high predictive potential of unfavorable treatment outcome, while RPA2, SARNP, PCBP2, SF3B2, HNRNPF, RBBP4, MAGOHB, DUT, ERG28, and BUB3 were good predictive biomarkers of favorable treatment outcome. The identified proteins and related biological processes provide promising insights that could enhance the management and care of LARC patients.

KCNQ1 and lymphovascular invasion are key features in a prognostic classifier for stage II and III colon cancer.

BACKGROUND: The risk of recurrence after resection of a stage II or III colon cancer, and therefore qualification for adjuvant chemotherapy (ACT), is traditionally based on clinicopathological parameters. However, the parameters used in clinical practice are not able to accurately identify all patients with or without minimal residual disease. Some patients considered 'low-risk' do develop recurrence (undertreatment), whilst other patients receiving ACT might not have developed recurrence at all (overtreatment). We previously analysed tumour tissue expression of 28 protein biomarkers that might improve identification of patients at risk of recurrence. In the present study we aimed to build a prognostic classifier based on these 28 biomarkers and clinicopathological parameters. METHODS: Classification and regression tree (CART) analysis was used to build a prognostic classifier based on a well described cohort of 386 patients with stage II and III colon cancer. Separate classifiers were built for patients who were or were not treated with ACT. Routine clinicopathological parameters and tumour tissue immunohistochemistry data were included, available for 28 proteins previously published. Classification trees were pruned until lowest misclassification error was obtained. Survival of the identified subgroups was analysed, and robustness of the selected CART variables was assessed by random forest analysis (1000 trees). RESULTS: In patients not treated with ACT, prognosis was estimated best based on expression of KCNQ1. Poor disease-free survival (DFS) was observed in those with loss of expression of KCNQ1 (HR = 3.38 (95% CI 2.12 - 5.40); p < 0.001). In patients treated with ACT, key prognostic factors were lymphovascular invasion (LVI) and expression of KCNQ1. Patients with LVI showed poorest DFS, whilst patients without LVI and high expression of KCNQ1 showed most favourable survival (HR = 7.50 (95% CI 3.57-15.74); p < 0.001). Patients without LVI and loss of expression of KCNQ1 had intermediate survival (HR = 3.91 (95% CI 1.76 - 8.72); p = 0.001). CONCLUSION: KCNQ1 and LVI were identified as key features in prognostic classifiers for disease-free survival in stage II and III colon cancer patients.

Clinical Validation of a Multitarget Fecal Immunochemical Test for Colorectal Cancer Screening : A Diagnostic Test Accuracy Study.

BACKGROUND: The fecal immunochemical test (FIT) is used in colorectal cancer (CRC) screening, yet it leaves room for improvement. OBJECTIVE: To develop a multitarget FIT (mtFIT) with better diagnostic performance than FIT. DESIGN: Diagnostic test accuracy study. SETTING: Colonoscopy-controlled series. PARTICIPANTS: Persons (n = 1284) from a screening (n = 1038) and referral (n = 246) population were classified by their most advanced lesion (CRC [n = 47], advanced adenoma [n = 135], advanced serrated polyp [n = 30], nonadvanced adenoma [n = 250], and nonadvanced serrated polyp [n = 53]), along with control participants (n = 769). MEASUREMENTS: Antibody-based assays were developed and applied to leftover FIT material. Classification and regression tree (CART) analysis was applied to biomarker concentrations to identify the optimal combination for detecting advanced neoplasia. Performance of this combination, the mtFIT, was cross-validated using a leave-one-out approach and compared with FIT at equal specificity. RESULTS: The CART analysis showed a combination of hemoglobin, calprotectin, and serpin family F member 2-the mtFIT-to have a cross-validated sensitivity for advanced neoplasia of 42.9% (95% CI, 36.2% to 49.9%) versus 37.3% (CI, 30.7% to 44.2%) for FIT (P = 0.025), with equal specificity of 96.6%. In particular, cross-validated sensitivity for advanced adenomas increased from 28.1% (CI, 20.8% to 36.5%) to 37.8% (CI, 29.6% to 46.5%) (P = 0.006). On the basis of these results, early health technology assessment indicated that mtFIT-based screening could be cost-effective compared with FIT. LIMITATION: Study population is enriched with persons from a referral population. CONCLUSION: Compared with FIT, the mtFIT showed better diagnostic accuracy in detecting advanced neoplasia because of an increased detection of advanced adenomas. Moreover, early health technology assessment indicated that these results provide a sound basis to pursue further development of mtFIT as a future test for population-based CRC screening. A prospective screening trial is in preparation. PRIMARY FUNDING SOURCE: Stand Up to Cancer/Dutch Cancer Society, Dutch Digestive Foundation, and HealthHolland.

Molecular characterization of colorectal adenomas reveals POFUT1 as a candidate driver of tumor progression.

Removal of colorectal adenomas is an effective strategy to reduce colorectal cancer (CRC) mortality rates. However, as only a minority of adenomas progress to cancer, such strategies may lead to overtreatment. The present study aimed to characterize adenomas by in-depth molecular profiling, to obtain insights into altered biology associated with the colorectal adenoma-to-carcinoma progression. We obtained low-coverage whole genome sequencing, RNA sequencing and tandem mass spectrometry data for 30 CRCs, 30 adenomas and 18 normal adjacent colon samples. These data were used for DNA copy number aberrations profiling, differential expression, gene set enrichment and gene-dosage effect analysis. Protein expression was independently validated by immunohistochemistry on tissue microarrays and in patient-derived colorectal adenoma organoids. Stroma percentage was determined by digital image analysis of tissue sections. Twenty-four out of 30 adenomas could be unambiguously classified as high risk (n = 9) or low risk (n = 15) of progressing to cancer, based on DNA copy number profiles. Biological processes more prevalent in high-risk than low-risk adenomas were related to proliferation, tumor microenvironment and Notch, Wnt, PI3K/AKT/mTOR and Hedgehog signaling, while metabolic processes and protein secretion were enriched in low-risk adenomas. DNA copy number driven gene-dosage effect in high-risk adenomas and cancers was observed for POFUT1, RPRD1B and EIF6. Increased POFUT1 expression in high-risk adenomas was validated in tissue samples and organoids. High POFUT1 expression was also associated with Notch signaling enrichment and with decreased goblet cells differentiation. In-depth molecular characterization of colorectal adenomas revealed POFUT1 and Notch signaling as potential drivers of tumor progression.

Silencing Core Spliceosome Sm Gene Expression Induces a Cytotoxic Splicing Switch in the Proteasome Subunit Beta 3 mRNA in Non-Small Cell Lung Cancer Cells.

The core spliceosomal Sm proteins were recently proposed as cancer-selective lethal targets in non-small cell lung cancer (NSCLC). In contrast, the loss of the commonly mutated cancer target SF3B1 appeared to be toxic to non-malignant cells as well. In the current study, the transcriptomes of A549 NSCLC cells, in which SF3B1 or SNRPD3 was silenced, were compared using RNA sequencing. The skipping of exon 4 of the proteasomal subunit beta type-3 (PSMB3) mRNA, resulting in a shorter PSMB3-S variant, occurred only after silencing SNRPD3. This observation was extended to the other six Sm genes. Remarkably, the alternative splicing of PSMB3 mRNA upon Sm gene silencing was not observed in non-malignant IMR-90 lung fibroblasts. Furthermore, PSMB3 was found to be overexpressed in NSCLC clinical samples and PSMB3 expression correlated with Sm gene expression. Moreover, a high PSMB3 expression corresponds to worse survival in patients with lung adenocarcinomas. Finally, silencing the canonical full-length PSMB3-L, but not the shorter PSMB3-S variant, was cytotoxic and was accompanied by a decrease in proteasomal activity. Together, silencing Sm genes, but not SF3B1, causes a cytotoxic alternative splicing switch in the PSMB3 mRNA in NSCLC cells only.

[Feasibility study of therapeutic exposure in virtual reality for pathological gamblers]. / Étude de faisabilité d'une exposition thérapeutique en réalité virtuelle pour joueurs pathologiques.

The experiment presented is the result of a partnership between the Paris-Nanterre University (CLIPSYD laboratory, EA 4430) and the CSAPA Imagine (Simone Veil Hospital, GH Eaubonne-Montmorency). Virtual reality immersion exposure for pathological gamblers is beneficial in the context of cognitive and behavioral interventions. It can be used to evoke the desire to play and to have access to automatic thoughts and mistaken beliefs of the players when they find themselves in a gambling context. Exposure is used until the urge to play diminishes and disappears which is the process of desensitization or extinction. OBJECTIVE: The objective of the study was to investigate the possibilities implemented by virtual reality in the case of an exhibition for pathological gamers to create a desire to play and work with the patient in an environment identical to the ecological one. Two hypotheses were proposed. On the one hand, the virtual reality exhibition will help to change the desire to play in relation to the game. On the other hand, virtual exhibition sessions associated with cognitive restructuring will have a greater impact on the perception of reality. METHOD: After a diagnosis was made, participation in the study was offered to patients (n=10) in routine care and able to participate (exclusion criteria). It consisted of four virtual reality exposure sessions integrated with traditional care. Exposure did not exceed 20minutes. To carry out this study we used the virtual reality headset "Oculus Rift CV1" and the headphones measuring EEG waves, "Emotiv Epoc". A battery of questionnaires were proposed to evaluate gambling-related behaviors (ICJP, GRCS, UPPS), to analyze the interest of the virtual reality exhibition (SIS, CGI, TEI, EVA), and to glimpse the immersion abilities (QEP and QPI). RESULTS: Ten participants aged 25 to 60 agreed to participate in the study. The results of this study demonstrated the viability of RV gamers' exposure as a tool that can help reduce pathological gambling symptoms and the severity perceived by therapists (CPI: t=1.6, P=0.001; CGI: t=4.87, P=0.001) between the beginning of the care and the end of the care and at D+1. We were also able to observe significant results (P<0.05) concerning a decrease in cognitive distortions (GRCS tot, Illusion of control, Power of prediction, Favorable interpretation). CONCLUSION: The feasibility study shows that the desire to play is very present during the virtual reality exhibition in accordance with literature studies. The results also demonstrate the utility of virtual reality to allow the patient to elaborate on the cognitive distortions associated with the practice of pathological gambling. From a therapeutic point of view, the results suggest that virtual reality can increase the effectiveness of cognitive restructuring and increase understanding of the urge to play related to stimuli in the environment of play.

Prognostic value of microvessel density in stage II and III colon cancer patients: a retrospective cohort study.

BACKGROUND: Microvessel density (MVD), as a derived marker for angiogenesis, has been associated with poor outcome in several types of cancer. This study aimed to evaluate the prognostic value of MVD in stage II and III colon cancer and its relation to tumour-stroma-percentage (TSP) and expression of HIF1A and VEGFA. METHODS: Formalin-fixed paraffin-embedded (FFPE) colon cancer tissues were collected from 53 stage II and 54 (5-fluorouracil-treated) stage III patients. MVD was scored by digital morphometric analysis of CD31-stained whole tumour sections. TSP was scored using haematoxylin-eosin stained slides. Protein expression of HIF1A and VEGFA was determined by immunohistochemical evaluation of tissue microarrays. RESULTS: Median MVD was higher in stage III compared to stage II colon cancers (11.1% versus 5.6% CD31-positive tissue area, p < 0.001). High MVD in stage II patients tended to be associated with poor disease free survival (DFS) in univariate analysis (p = 0.056). In contrast, high MVD in 5FU-treated stage III patients was associated with better DFS (p = 0.006). Prognostic value for MVD was observed in multivariate analyses for both cancer stages. CONCLUSIONS: MVD is an independent prognostic factor associated with poor DFS in stage II colon cancer patients, and with better DFS in stage III colon cancer patients treated with adjuvant chemotherapy.

Identification of Differentially Expressed Splice Variants by the Proteogenomic Pipeline Splicify.

Proteogenomics, i.e. comprehensive integration of genomics and proteomics data, is a powerful approach identifying novel protein biomarkers. This is especially the case for proteins that differ structurally between disease and control conditions. As tumor development is associated with aberrant splicing, we focus on this rich source of cancer specific biomarkers. To this end, we developed a proteogenomic pipeline, Splicify, which can detect differentially expressed protein isoforms. Splicify is based on integrating RNA massive parallel sequencing data and tandem mass spectrometry proteomics data to identify protein isoforms resulting from differential splicing between two conditions. Proof of concept was obtained by applying Splicify to RNA sequencing and mass spectrometry data obtained from colorectal cancer cell line SW480, before and after siRNA-mediated downmodulation of the splicing factors SF3B1 and SRSF1. These analyses revealed 2172 and 149 differentially expressed isoforms, respectively, with peptide confirmation upon knock-down of SF3B1 and SRSF1 compared with their controls. Splice variants identified included RAC1, OSBPL3, MKI67, and SYK. One additional sample was analyzed by PacBio Iso-Seq full-length transcript sequencing after SF3B1 downmodulation. This analysis verified the alternative splicing identified by Splicify and in addition identified novel splicing events that were not represented in the human reference genome annotation. Therefore, Splicify offers a validated proteogenomic data analysis pipeline for identification of disease specific protein biomarkers resulting from mRNA alternative splicing. Splicify is publicly available on GitHub (https://github.com/NKI-TGO/SPLICIFY) and suitable to address basic research questions using pre-clinical model systems as well as translational research questions using patient-derived samples, e.g. allowing to identify clinically relevant biomarkers.

Novel Stool-Based Protein Biomarkers for Improved Colorectal Cancer Screening: A Case-Control Study.

BACKGROUND: The fecal immunochemical test (FIT) for detecting hemoglobin is used widely for noninvasive colorectal cancer (CRC) screening, but its sensitivity leaves room for improvement. OBJECTIVE: To identify novel protein biomarkers in stool that outperform or complement hemoglobin in detecting CRC and advanced adenomas. DESIGN: Case-control study. SETTING: Colonoscopy-controlled referral population from several centers. PARTICIPANTS: 315 stool samples from one series of 12 patients with CRC and 10 persons without colorectal neoplasia (control samples) and a second series of 81 patients with CRC, 40 with advanced adenomas, and 43 with nonadvanced adenomas, as well as 129 persons without colorectal neoplasia (control samples); 72 FIT samples from a third independent series of 14 patients with CRC, 16 with advanced adenomas, and 18 with nonadvanced adenomas, as well as 24 persons without colorectal neoplasia (control samples). MEASUREMENTS: Stool samples were analyzed by mass spectrometry. Classification and regression tree (CART) analysis and logistic regression analyses were performed to identify protein combinations that differentiated CRC or advanced adenoma from control samples. Antibody-based assays for 4 selected proteins were done on FIT samples. RESULTS: In total, 834 human proteins were identified, 29 of which were statistically significantly enriched in CRC versus control stool samples in both series. Combinations of 4 proteins reached sensitivities of 80% and 45% for detecting CRC and advanced adenomas, respectively, at 95% specificity, which was higher than that of hemoglobin alone (P < 0.001 and P = 0.003, respectively). Selected proteins could be measured in small sample volumes used in FIT-based screening programs and discriminated between CRC and control samples (P < 0.001). LIMITATION: Lack of availability of antibodies prohibited validation of the top protein combinations in FIT samples. CONCLUSION: Mass spectrometry of stool samples identified novel candidate protein biomarkers for CRC screening. Several protein combinations outperformed hemoglobin in discriminating CRC or advanced adenoma from control samples. Proof of concept that such proteins can be detected with antibody-based assays in small sample volumes indicates the potential of these biomarkers to be applied in population screening. PRIMARY FUNDING SOURCE: Center for Translational Molecular Medicine, International Translational Cancer Research Dream Team, Stand Up to Cancer (American Association for Cancer Research and the Dutch Cancer Society), Dutch Digestive Foundation, and VU University Medical Center.

Loss of KCNQ1 expression in stage II and stage III colon cancer is a strong prognostic factor for disease recurrence.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide. Accurately identifying stage II CRC patients at risk for recurrence is an unmet clinical need. KCNQ1 was previously identified as a tumour suppressor gene and loss of expression was associated with poor survival in patients with CRC liver metastases. In this study the prognostic value of KCNQ1 in stage II and stage III colon cancer patients was examined. METHODS: KCNQ1 mRNA expression was assessed in 90 stage II colon cancer patients (AMC-AJCCII-90) using microarray gene expression data. Subsequently, KCNQ1 protein expression was evaluated in an independent cohort of 386 stage II and stage III colon cancer patients by immunohistochemistry of tissue microarrays. RESULTS: Low KCNQ1 mRNA expression in stage II microsatellite stable (MSS) colon cancers was associated with poor disease-free survival (DFS) (P=0.025). Loss of KCNQ1 protein expression from epithelial cells was strongly associated with poor DFS in stage II MSS (P<0.0001), stage III MSS (P=0.0001) and stage III microsatellite instable colon cancers (P=0.041). KCNQ1 seemed an independent prognostic value in addition to other high-risk parameters like angio-invasion, nodal stage and microsatellite instability-status. CONCLUSIONS: We conclude that KCNQ1 is a promising biomarker for prediction of disease recurrence and may aid stratification of patients with stage II MSS colon cancer for adjuvant chemotherapy.

Glucose Transporter 1 (SLC2A1) and Vascular Endothelial Growth Factor A (VEGFA) Predict Survival After Resection of Colorectal Cancer Liver Metastasis.

OBJECTIVE: To investigate the individual and combined prognostic value of HIF1α, SLC2A1, and vascular endothelial growth factor A (VEGFA) in a multi-institutional cohort of patients with resected colorectal cancer liver metastasis (CRCLM). BACKGROUND: In the majority of patients with CRCLM, resection seems not to be curative, despite its curative intent. Overexpression of hypoxia-inducible factor 1α (HIF1α), glucose transporter 1 (SLC2A1; also known as GLUT1), and VEGFA has been associated with tumor progression and poor prognosis of patients with colorectal cancer (CRC). METHODS: Tissue microarrays were generated using CRCLM and patient-matched primary CRC from patients who underwent CRCLM resection between 1990 and 2010. Prognostic value of HIF1α, SLC2A1, and VEGFA was determined by immunohistochemistry. A 500-fold cross-validated hazard rate ratio (HRRav) for overall survival was calculated. RESULTS: HIF1α, SLC2A1, and VEGFA expression could be evaluated in 328, 350, and 335 patients, respectively. High SLC2A1 expression was associated with good prognosis (HRRav, 0.67; P (HRR >1)  < 0.01) and high VEGFA expression to poor prognosis (HRRav, 1.84; P (HRR < 1)  = 0.02), also after multivariate analysis including established clinicopathological prognostic variables (HRRav, 0.67; P (HRR > 1)  < 0.01 and HRRav, 1.50; P (HRR < 1)  = 0.02, respectively). SLC2A1 showed prognostic value particularly in patients treated with systemic therapy (P < 0.01), whereas the prognostic value of VEGFA expression was mainly observed in patients not treated with systemic therapy (P < 0.01). Prognosis was especially poor in patients with both low SLC2A1 and high VEGFA expression (P < 0.01). HIF1α expression was not associated with survival. CONCLUSIONS: SLC2A1 and VEGFA expression are prognostic molecular biomarkers for patients with CRCLM with added value to established clinicopathological variables.

Proteomics of differential extraction fractions enriched for chromatin-binding proteins from colon adenoma and carcinoma tissues.

BACKGROUND: Altered nuclear and genomic structure and function are hallmarks of cancer cells. Research into nuclear proteins in human tissues could uncover novel molecular processes in cancer. Here, we examine biochemical tissue fractions containing chromatin-binding (CB) proteins in the context of colorectal cancer (CRC) progression. METHODS: CB protein-containing fractions were biochemically extracted from human colorectal tissues, including carcinomas with chromosomal instability (CIN), carcinomas with microsatellite instability (MIN), and adenomas. The CB proteins were subjected to label-free LC-MS/MS and the data were analyzed by bioinformatics. RESULTS: Over 1700 proteins were identified in the CB fraction from colonic tissues, including 938 proteins associated with nuclear annotation. Of the latter, 169 proteins were differential between adenomas and carcinomas. In this adenoma-versus-carcinoma comparison, apart from specific changes in components of the splicing and protein translational machineries, we also identified significant changes in several proteins associated with chromatin-directed functions. Furthermore, several key cell cycle proteins as well as those involved in cellular stress were increased, whereas specific components of chromosome segregation and DNA recombination/repair systems were decreased. CONCLUSIONS: Our study identifies proteomic changes at the subnuclear level that are associated with CRC and may be further investigated. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Gambling and Attention Deficit Hyperactivity Disorders (ADHD) in a Population of French Students.

Attention deficit disorder with or without hyperactivity (ADD/ADHD) is a neurodevelopmental disorder that can be exacerbated by psychosocial factors. Various studies confirm that the severity of a psychiatric disorder, particularly when it comes to ADHD, is strongly correlated with the amount of use. This study (1) evaluated the association between ADHD and gambling among young students; (2) determined which symptom among ADHD's three symptoms (attention deficit, hyperactivity, or impulsivity) had the strongest association with video game addiction and gambling; and (3) determined the impact of the association between ADHD and video game addiction and gambling on self-esteem and academic performance of students. A total of 720 students (445 males and 274 females) were recruited from eight higher educational institutions of Ile de France. They all completed a battery of questionnaire consisting of Canadian Problem Gambling Index, UPPS Impulsive Behavior Scale, Wender Utah Rating Scale (WURS), Adult ADHD Self-Report Scale (ASRS) and Rosenberg scales, and socio-demographic data. 13.33% of the participants had symptoms of ADHD during childhood (WURS scale score) and 40.41% of them have symptoms of ADHD in adulthood (ASRS score). Finally, among the participants, 37.5% had excessive gambling addiction, have positive results on WURS and ASRS scales, thus having a probable ADHD, whereas 14.55% had no gambling addiction. The results demonstrated that adult ADHD was associated with gambling addiction. Significant associations were observed between ADHD and impulsivity, academic difficulties and gambling addiction. The association between ADHD and gambling seems to be common among vulnerable populations such as adolescents and could be related to variables such as self-esteem, which appears to potentially worsen the prognosis. Further research on this relationship is needed to optimize prevention strategies and effective treatment.

[A cyberbullying study: Analysis of cyberbullying, comorbidities and coping mechanisms]. / Étude sur la « cyber-intimidation ¼ : cyberbullying, comorbidités et mécanismes d'adaptations.

INTRODUCTION: Cyberbullying is a relatively new form of bullying. This bullying is committed by means of an electronic act, the transmission of a communication by message, text, sound, or image by means of an electronic device, including but limited to, a computer phone, wireless telephone, or other wireless communication device, computer, games console or pager. Cyberbullying is characterized by deliberately threatening, harassing, intimidating, or ridiculing an individual or group of individuals; placing an individual in reasonable fear of harm; posting sensitive, private information about another person without his/her permission; breaking into another person's account and/or assuming another individual's identity in order to damage that person's reputation or friendships. LITERATURE FINDING: A review of the literature shows that between 6 and 40% of all youths have experienced cyberbullying at least once in their lives. Several cyberbullying definitions have been offered in the literature, many of which are derived from definitions of traditional bullying. In our study we asked clear definition of cyberbullying. Few studies explicate the psychosocial determinants of cyberbullying, and coping mechanisms. The authors of the literature recommend developing resiliency, but without analyzing the resilience factor. OBJECTIVES: The first aim of this study was to determine the prevalence of adolescents and adults engaged in cyberbullying. The second aim was to examine the coping mechanisms and comorbidity factors associated with the cyberbullied people. METHODOLOGY: The sample was composed of 272 adolescents (from a high school) and adults (mean age=16.44 ± 1). The Olweus Bully/Victim Questionnaire was used to identify profiles of cyberbullying. Coping mechanisms were investigated using the Hurt Disposition Scale (HDS) and the Brief Resilience Scale (BRS). Comorbidities were assessed using the Hospital Anxiety and Depression Scale (HAD), Liebowitz's Social Anxiety Scale (LSAS), and the Bermond-Vorst Alexithymia Questionnaire (BVAQ). RESULTS: Almost one student in three was involved in cyberbullying (34.9% as cyber-victim, 16.9 as cyberbully); 4.8% of our sample was concerned by bullying as a victim. The victims of bullying were also victims of cyberbullying. The mean age of victims of cyberbullying was 17.84 ± 5.9 years, and the mean age of victims of bullying was 16.3 ± 4.5 years. Correlation coefficient was significant for HAD, LSAS, BVAQ scales with CQ. The retaliatory variable of HDS scale was not significant. Finally, the coping strategies of students who reported victimization were explored. These strategies include coping, telling someone, figuring out the situation, and avoidant coping. The results showed for the victims of cyberbullying, that they take longer to recover from a stressful event, compared to victims of bullying. CONCLUSION: Results have indicated the importance of further study of cyberbullying because its association with comorbidities was distinct from traditional forms of bullying. The biggest risk factor for the adolescents is the severity of the consequences. These are: the adoption of the avoidance coping strategy, the occurrence of offline bullying during the situation, the adoption of the self-control coping strategy, the variety of cyberbullying acts, the victim's level of self-blame, the victim's perception of the duration of the situation, and the frequency of cyberbullying victimization.

Performance and Dimensionality of Pretreatment MRI Radiomics in Rectal Carcinoma Chemoradiotherapy Prediction.

(1) Background: This study aimed to develop a machine learning model based on radiomics of pretreatment magnetic resonance imaging (MRI) 3D T2W contrast sequence scans combined with clinical parameters (CP) to predict neoadjuvant chemoradiotherapy (nCRT) response in patients with locally advanced rectal carcinoma (LARC). The study also assessed the impact of radiomics dimensionality on predictive performance. (2) Methods: Seventy-five patients were prospectively enrolled with clinicopathologically confirmed LARC and nCRT before surgery. Tumor properties were assessed by calculating 2141 radiomics features. Least absolute shrinkage selection operator (LASSO) and multivariate regression were used for feature selection. (3) Results: Two predictive models were constructed, one starting from 72 CP and 107 radiomics features, and the other from 72 CP and 1862 radiomics features. The models revealed moderately advantageous impact of increased dimensionality, with their predictive respective AUCs of 0.86 and 0.90 in the entire cohort and 0.84 within validation folds. Both models outperformed the CP-only model (AUC = 0.80) which served as the benchmark for predictive performance without radiomics. (4) Conclusions: Predictive models developed in this study combining pretreatment MRI radiomics and clinicopathological features may potentially provide a routine clinical predictor of chemoradiotherapy responders, enabling clinicians to personalize treatment strategies for rectal carcinoma.