ITCC-P4: Molecular characterization and multi-omics analysis of pediatric patient tumor and Patient-Derived Xenograft (PDX) models for preclinical model selection

Cancer persists as one of the prevailing causes of death in children and adolescents aged 0 to 19 years. There remains to be an unmet need for identification of therapeutic biomarkers and better treatment interventions for these patients. Advancements in state-of-the-art molecular profiling techniques have resulted in better understanding of pediatric cancers and their driver events. It has become apparent that pediatric malignancies are significantly more heterogeneous than previously thought as evidenced by the number of novel entities and subtypes that have been identified with distinct molecular and clinical characteristics. For most of these newly recognized entities there are currently extremely limited treatment options available. Unfortunately, there is also a lack of compiled and consistently analysed molecular data available, along with limited data of characterization and documentation of patient-derived models and/or genetic mouse models from high-risk pediatric tumors. Both my studies fall under the “Innovative Therapies for Children with Cancer Pediatric Preclinical Proof-of-concept Platform” (ITCC-P4) consortium which is an international collaboration between different European academic institutes, several partnering pharmaceutical companies and three contract research organizations. The two studies aim to shed light on identification of potential promising treatment options that specifically match the patient’s specific molecular tumour characteristics and the patient’s genetic data. Genetic information at the molecular level from pediatric tumors in relapsed patients has contributed to advancing our understanding of disease progression and treatment resistance. The first study overall aims to establish a sustainable platform of >400 molecularly well- characterized PDX models of high-risk pediatric cancers, including the analysis of their original tumors and matching controls. This will enable the selection of PDX models for in vivo testing of novel mechanism-of-action based treatments. Hence, facilitating the prioritization of pediatric drug development and clinical stratification of patients across entities. In a first batch, 251 models were fully characterized, including 180 brain and 71 non- brain PDX models, representing 112 primary models, 93 relapse, 42 metastasis and 4 progressions under treatment models. Using low-coverage whole-genome and deep whole exome sequencing, complemented with total RNA sequencing and methylation analysis, the aim was to define genetic features in the ITCC-P4 PDX cohort and assess the molecular fidelity of PDX models compared to the original tumor. Based on DNA methylation profiling 43 different tumor subgroups within 18 cancer entities were included. Mutational landscape analysis identified key somatic and germline oncogenic drivers where Ependymoma PDX models displayed the C11orf95-RELA fusion event, YAP1, C11orf95 and RELA structural variants. Medulloblastoma models were driven by MYCN, TP53, GLI2, SUFU and PTEN. High-grade glioma samples showed TP53, ATRX, MYCN and PIK3CA somatic SNVs, along with focal deletions in CDKN2A in chromosome 9. Neuroblastoma models were enriched for ALK SNVs and/or MYCN focal amplification, ATRX SNVs and CDKN2A/B deletions. Sarcoma models displayed characteristic alterations with PAX3-FOXO1 fusions detected in embryonal rhabdomyosarcoma, along with TP53, CDKN2A, NRAS SNVs, NCOA1 gains, NF1 and CDK4 SVs. Ewing sarcoma PDX models displayed the defining EWSR1-FLI1 gene fusion in most cases, along with two rarer cases of EWSR1-ERG and EWSR1-FEV observed in the cohort. Osteosarcomas were defined by highly unstable genomes with large chromosomal alterations, TP53 and RB1 tumor suppressor genes were frequently altered and ATRX loss and MYC gains were observed. Additional sarcomas such as clear cell sarcoma of the kidney showed CDKN2A loss, MYC gain, NF1 loss, TP53 mutations, while Synovial sarcoma models were driven by SSX gene fusions and alterations. Large chromosomal aberrations (deletions, duplications) detected in the PDX models were concurrent with molecular alterations frequently observed in each tumor type –isochromosome 17 was detected in five medulloblastoma models, while deletion of chromosome arm 1p or gain of parts of 17q in neuroblastomas which correlate with tumor progression. Tumor mutational burden across entities and copy number analysis was performed to identify allele-specific copy number events in tumor-normal pairs. Clonal evolution of somatic variants was not only found in certain PDX-tumor pairs but also between disease states. Across the 16 serial model cases, discordance in targetable SNV, SV and CNV, alterations were observed in later disease progressed states compared to the primary models. The multi-omics approach in this study provides insight into the mutational landscape and patterns of the PDX models thus providing an overview of molecular mechanisms facilitating the identification and prioritization of oncogenic drivers and potential biomarkers for optimal treatment. The second study was a Target Actionability Review on replication stress. Detrimental long-term side effects due to chemotherapy drastically affect the lives of patients under treatment, hence there is an urgent need to identify novel target driven therapies. Decades of published data provide evidence for targeting replication stress therapeutically. Hence, in this study, we evaluated specific targets within the replication stress response (RSR) pathway. A comprehensive, well-structured, and critically evaluated overview of literature related to replication stress across 16 pediatric solid malignancies was generated. The methodology focuses on the systemic extraction and structured evaluation of replication stress as a target. This aims to align targeted anti- cancer therapeutic interventions with specific cancer subtypes based on clinical studies. ATR, ATM, PARP, WEEI were observed to represent the most promising targets either using single agents or in combination with chemotherapy or radiotherapy. Evidence on CHK1 and DNA-PK although limited, showed potential to further investigate these promising targets over broader tumor types. The collective data and results from both studies, the “ITCC-P4: Molecular characterization and multi-omics analysis of Patient-Derived Xenograft (PDX) models from high-risk pediatric cancer” and the “Target actionability review on replication stress”, can be explored further on the interactively designed R2 platform, once users create an account to gain access to the cohort data. (https://r2-itcc-p4.amc.nl/)

Forecasting truck traffic growth at West Virginia non-interstate highways

Reliable estimates of truck volumes are important in transportation planning and design applications, such as pavement design and management. This study evaluates different statistical methods based on their accuracy and data requirements, to calculate the truck growth rates by developing statistical models. Nine years of data from 1995 to 2003 was used to develop these models for calculating the truck growth rates at non-interstate highways of West Virginia. The literature review and the current practices for the state DOT was conducted to better understand and select the different forecasting methods that could be applicable to the given data. As a result, the two techniques namely, the regression analysis and the growth factor method were used for the purpose. These techniques were applied to each site and for each truck classification. For a clear perspective of truck traffic patterns across the state, the sites were grouped based on the location of the counters, i.e., the rural and the urban, and trucks were grouped according to the number of axles. Precision test was then conducted to validate the models. All the results from the methods used for this study were compared and was concluded that the regression analysis is the best suited method for the given data, in West Virginia. The comprehensive approach to the evaluation can be used by the state DOT

DUCTAL CARCINOMA IN SITU AND INVASIVE BREAST CANCER-BASED DIFFERENTIAL GENE EXPRESSION STUDY FOR THERAPEUTIC DEVELOPMENT

ABSTRACTObjective: Breast cancer is the second most common cancer in women globally. Multiple inherited mutations in genes are predominantly associatedwith breast cancer. The gene expression profiling of breast tumors generated by DNA microarray analysis provides molecular phenotyping thatdetermines and characterizes the classifications of these tumors.Methods: In this work, we used gene expression profiling of breast cancer samples from Gene Expression Omnibus (GEO) database. The datasetGSE41194, retrieved from GEO, was used to investigate differential gene expression in ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC).The dataset contains 26 DCIS and 24 IBC samples. The data were analyzed in R and Bioconductor. To normalize the data Robust Multiarray Average(RMA) method was applied, limma software was used to identify the differentially expressed genes (DEGs) in DCIS and IBC; an adjusted p value ≤0.05was used to filter differentially expressed probe sets, and a fold change (FC) ≥ 2 to identify upregulated and ≤−2 for downregulated genes. The DEGsretrieved were clustered and annotated using Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resourceswith an EASE score ≤0.1 and count 2.Results: The analysis obtained 72 DEGs with a p≤0.05. The FC≥2 identified 38 upregulated probesets and FC≤−2 identified 34 downregulated probesets. The up and downregulated genes obtained in various comparisons were characterized based on gene ontology (GO) and pathway analyses inDAVID, which retrieved six genes that had principal pathways targeting breast cancer.Conclusion: Identification of these genes and pathways enhances the knowledge and progression of DCIS to IBC; paving a novel way for developingnew therapies for treating patients with breast cancer.Keywords: Molecular phenotyping, Gene Expression, Ductal carcinoma in situ, Invasive breast cancer

IoT based Driver Drowsiness and Pothole Detection Alert System

One of the common in progressing countries is the maintenance of roads. Well maintained roads contribute a major portion to the country’s economy. Identification of pavement distress such as potholes and humps not only help drivers to avoid accidents or vehicle damages, but also helps authorities to maintain roads. This paper discusses various pothole detection methods that have been developed and proposes a simple and cost-effective solution to identify the potholes and humps on roads and provide timely alerts to drivers to avoid accidents or vehicle damages. Not only Potholes and humps are the main cause of accidents other than over speeding and drowsiness of driver includes the issue of accidents. Drowsy state may be caused by lack of sleep, medication, tiredness, drugs or driving continuously for long period of time. So, here is the solution for detecting the potholes and humps and to alert the driver from drowsiness while driving. In this paper, the system is structured to detect potholes and to alert the drowsy driver by using the ultrasonic sensor, eyeblink sensor and IR sensor and microcontroller. Ultrasonic sensor senses the humps, IR sensor senses the potholes and eye blink sensor the blinking of eye and this sensing signals fed into the Arduino to alert the driver by buzzer sound

Body Awareness: Construct and Self-Report Measures

OBJECTIVES:Heightened body awareness can be adaptive and maladaptive. Improving body awareness has been suggested as an approach for treating patients with conditions such as chronic pain, obesity and post-traumatic stress disorder. We assessed the psychometric quality of selected self-report measures and examined their items for underlying definitions of the construct. DATA SOURCES:PubMed, PsychINFO, HaPI, Embase, Digital Dissertations Database. REVIEW METHODS:Abstracts were screened; potentially relevant instruments were obtained and systematically reviewed. Instruments were excluded if they exclusively measured anxiety, covered emotions without related physical sensations, used observer ratings only, or were unobtainable. We restricted our study to the proprioceptive and interoceptive channels of body awareness. The psychometric properties of each scale were rated using a structured evaluation according to the method of McDowell. Following a working definition of the multi-dimensional construct, an inter-disciplinary team systematically examined the items of existing body awareness instruments, identified the dimensions queried and used an iterative qualitative process to refine the dimensions of the construct. RESULTS:From 1,825 abstracts, 39 instruments were screened. 12 were included for psychometric evaluation. Only two were rated as high standard for reliability, four for validity. Four domains of body awareness with 11 sub-domains emerged. Neither a single nor a compilation of several instruments covered all dimensions. Key domains that might potentially differentiate adaptive and maladaptive aspects of body awareness were missing in the reviewed instruments. CONCLUSION:Existing self-report instruments do not address important domains of the construct of body awareness, are unable to discern between adaptive and maladaptive aspects of body awareness, or exhibit other psychometric limitations. Restricting the construct to its proprio- and interoceptive channels, we explore the current understanding of the multi-dimensional construct and suggest next steps for further research

P05.61. The multidimensional assessment of interoceptive awareness (MAIA)

This paper describes the development of a multidimensional self-report measure of interoceptive body awareness. The systematic mixed-methods process involved reviewing the current literature, specifying a multidimensional conceptual framework, evaluating prior instruments, developing items, and analyzing focus group responses to scale items by instructors and patients of body awareness-enhancing therapies. Following refinement by cognitive testing, items were field-tested in students and instructors of mind-body approaches. Final item selection was achieved by submitting the field test data to an iterative process using multiple validation methods, including exploratory cluster and confirmatory factor analyses, comparison between known groups, and correlations with established measures of related constructs. The resulting 32-item multidimensional instrument assesses eight concepts. The psychometric properties of these final scales suggest that the Multidimensional Assessment of Interoceptive Awareness (MAIA) may serve as a starting point for research and further collaborative refinement

Methylation mediated silencing of TMS1/ASC gene in prostate cancer

BACKGROUND: Transcriptional silencing associated with aberrant promoter methylation has been established as an alternate pathway for the development of cancer by inactivating tumor suppressor genes. TMS1 (Target of Methylation induced Silencing), also known as ASC (Apoptosis Speck like protein containing a CARD) is a tumor suppressor gene which encodes for a CARD (caspase recruitment domain) containing regulatory protein and has been shown to promote apoptosis directly and by activation of downstream caspases. This study describes the methylation induced silencing of TMS1/ASC gene in prostate cancer cell lines. We also examined the prevalence of TMS1/ASC gene methylation in prostate cancer tissue samples in an effort to correlate race and clinico-pathological features with TMS1/ASC gene methylation. RESULTS: Loss of TMS1/ASC gene expression associated with complete methylation of the promoter region was observed in LNCaP cells. Gene expression was restored by a demethylating agent, 5-aza-2'deoxycytidine, but not by a histone deacetylase inhibitor, Trichostatin A. Chromatin Immunoprecipitation (ChIP) assay showed enrichment of MBD3 (methyl binding domain protein 3) to a higher degree than commonly associated MBDs and MeCP2. We evaluated the methylation pattern in 66 prostate cancer and 34 benign prostatic hyperplasia tissue samples. TMS1/ASC gene methylation was more prevalent in prostate cancer cases than controls in White patients (OR 7.6, p 0.002) while no difference between the cases and controls was seen in Black patients (OR 1.1, p 0.91). CONCLUSION: Our study demonstrates that methylation-mediated silencing of TMS1/ASC is a frequent event in prostate cancer, thus identifying a new potential diagnostic and prognostic marker for the treatment of the disease. Racial differences in TMS1/ASC methylation patterns implicate the probable role of molecular markers in determining in susceptibility to prostate cancer in different ethnic groups

Identification and validation of genes involved in gastric tumorigenesis

<p>Abstract</p> <p>Background</p> <p>Gastric cancer is one of the common cancers seen in south India. Unfortunately more than 90% are advanced by the time they report to a tertiary centre in the country. There is an urgent need to characterize these cancers and try to identify potential biomarkers and novel therapeutic targets.</p> <p>Materials and methods</p> <p>We used 24 gastric cancers, 20 Paired normal (PN) and 5 apparently normal gastric tissues obtained from patients with non-gastric cancers (Apparently normal - AN) for the microarray study followed by validation of the significant genes (n = 63) by relative quantitation using Taqman Low Density Array Real Time PCR. We then used a custom made Quantibody protein array to validate the expression of 15 proteins in gastric tissues (4 AN, 9 PN and 9 gastric cancers). The same array format was used to study the plasma levels of these proteins in 58 patients with gastric cancers and 18 from patients with normal/non-malignant gastric conditions.</p> <p>Results</p> <p>Seventeen genes (ASPN, CCL15/MIP-1δ, MMP3, SPON2, PRSS2, CCL3, TMEPAI/PMEPAI, SIX3, MFNG, SOSTDC1, SGNE1, SST, IGHA1, AKR1B10, FCGBP, ATP4B, NCAPH2) were shown to be differentially expressed between the tumours and the paired normal, for the first time. EpCAM (p = 0.0001), IL8 (p = 0.0003), CCL4/MIP-1β (p = 0.0026), CCL20/MIP-3α (p = 0.039) and TIMP1 (p = 0.0017) tissue protein levels were significantly different (Mann Whitney U test) between tumours versus AN & PN. In addition, median plasma levels of IL8, CXCL9/MIG, CCL3/MIP-1α, CCL20/MIP-3α, PDGFR-B and TIMP1 proteins were significantly different between the non-malignant group and the gastric cancer group. The post-surgical levels of EpCAM, IGFBP3, IL8, CXCL10/IP10, CXCL9/MIG, CCL3/MIP-1α, CCL20/MIP-3α, SPP1/OPN and PDGFR-B showed a uniform drop in all the samples studied.</p> <p>Conclusions</p> <p>Our study has identified several genes differentially expressed in gastric cancers, some for the first time. Some of these have been confirmed at the protein level, as well. Some of these proteins will need to be evaluated further for their potential as diagnostic biomarkers in gastric cancers and some could be useful as follow-up markers in gastric cancer.</p