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  • 1
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    Abstract 1993: A comprehensive benchmarking of paired whole exome and transcriptome biomarker analysis of response to cancer immunotherapy
    American Association for Cancer Research (AACR) ; 2020
    In:  Cancer Research Vol. 80, No. 16_Supplement ( 2020-08-15), p. 1993-1993
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 1993-1993
    Abstract: Recent advances in cancer immunotherapy have revolutionized cancer treatment. Notably, pembrolizumab - an anti-PD1 checkpoint inhibitor - has been approved as first-line treatment for metastatic non-small cell lung cancer. Clinical response to checkpoint inhibitors has been demonstrated in other cancer types; however, durable response is not observed in all patients. As a result, development of new biomarkers for response to checkpoint inhibitors has become an active area of research. Due to the complexity of the anti-tumor immune response, a single biomarker may not accurately predict patient response to immunotherapy. In parallel, dramatic decreases in the costs of next generation sequencing (NGS) have enabled broad whole exome sequencing (WES) and whole transcriptome sequencing (WTS)-based studies, enabling a new phase in both academic and clinical cancer research. Despite the proven utility of NGS-based biomarker analysis, the accuracy of combined WES/WTS results compared to other assays, specifically in clinical tumor tissues, has not been demonstrated. In this study, we perform comprehensive benchmarking of several immuno-oncology (IO) biomarkers on cell lines, fresh frozen tumor tissues, and formalin-fixed paraffin-embedded (FFPE) tumor tissues. WES and WTS libraries were generated using Illumina Nextera Flex for Enrichment, TruSight Oncology, and TruSeq Stranded Total RNA library prep methods, and sequenced on a NovaSeq 6000. Using an internally developed bioinformatics pipeline, the accuracy of several IO biomarker measurements was evaluated. Specifically, we investigated the performance of tumor-only (T) and/or paired tumor-normal (TN) WES/WTS in assessing tumor mutational burden (TMB), microsatellite instability (MSI), tumor purity, copy number variants (CNV), human leukocyte antigen (HLA) type, fusions, and tumor infiltrating lymphocytes (TILs) levels, among other features. Our benchmarking results demonstrated correlations of 0.99 and 0.98 for TMB as measured by TN and T, respectively (truth: FOCR reported TMB); 100.0% PPV and NPV for MSI status as measured by both TN and T (truth: MSI-PCR); 0.86 correlation for tumor purity estimates based on TN (0.64 based on T; truth: cell-line titration levels); 100% PPV for both TN and T CNV calling (truth: ddPCR); 92% accuracy for both TN and T HLA typing (truth: IHW HLA types); 92.9% sensitivity for fusion calling (truth: ddPCR); and R2 values of 0.87, 0.70, and 0.48 for CD19+, CD4+, and CD8+ TIL levels, respectively (truth: FACS). Taken together, this study demonstrates WES/WTS can not only be utilized for broad exome- and transcriptome-wide biomarker discovery, but can also be an accurate, comprehensive alternative to iteratively testing IO biomarkers. Future studies should further standardize assay and analysis approaches for NGS-based biomarker measurements to ensure consistent and accurate reporting. Citation Format: Mahdi Golkaram, Michael Salmans, Raakhee Vijayaraghavan, Shannon Kaplan, Robert Haigis, Joyee Yao, Kristina Kruglyak, Li Liu, Traci Pawlowski, Sven Bilke, Shile Zhang. A comprehensive benchmarking of paired whole exome and transcriptome biomarker analysis of response to cancer immunotherapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1993.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2020-1993
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 2
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    Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain
    American Association for the Advancement of Science (AAAS) ; 2016
    In:  Science Vol. 352, No. 6293 ( 2016-06-24), p. 1586-1590
    Details
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 352, No. 6293 ( 2016-06-24), p. 1586-1590
    Abstract: The human brain has enormously complex cellular diversity and connectivities fundamental to our neural functions, yet difficulties in interrogating individual neurons has impeded understanding of the underlying transcriptional landscape. We developed a scalable approach to sequence and quantify RNA molecules in isolated neuronal nuclei from a postmortem brain, generating 3227 sets of single-neuron data from six distinct regions of the cerebral cortex. Using an iterative clustering and classification approach, we identified 16 neuronal subtypes that were further annotated on the basis of known markers and cortical cytoarchitecture. These data demonstrate a robust and scalable method for identifying and categorizing single nuclear transcriptomes, revealing shared genes sufficient to distinguish previously unknown and orthologous neuronal subtypes as well as regional identity and transcriptomic heterogeneity within the human brain.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    URL: Article
    DOI: 10.1126/science.aaf1204
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2016
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  • 3
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    Meta-analysis of new genome-wide association studies of colorectal cancer risk
    Springer Science and Business Media LLC ; 2012
    In:  Human Genetics Vol. 131, No. 2 ( 2012-2), p. 217-234
    Details
    In: Human Genetics, Springer Science and Business Media LLC, Vol. 131, No. 2 ( 2012-2), p. 217-234
    Type of Medium: Online Resource
    ISSN: 0340-6717 , 1432-1203
    URL: Article
    DOI: 10.1007/s00439-011-1055-0
    RVK:
    WA 15000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2012
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  • 4
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    Abstract 435: Accurate measurement of tumor mutation burden through tumor-only sequencing using a 500-gene panel
    American Association for Cancer Research (AACR) ; 2018
    In:  Cancer Research Vol. 78, No. 13_Supplement ( 2018-07-01), p. 435-435
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 435-435
    Abstract: Introduction: Recently, it has been shown by various studies that tumor mutation burden (TMB) can correlate with a cancer patient's responsiveness to checkpoint inhibitor immunotherapy. These findings have stimulated a widespread interest in the development of cost-effective assays that accurately measure TMB. Here we assess whether TMB measured through next-generation sequencing (NGS) of a 2-megabase 500-gene panel correlates with that determined through whole exome sequencing (WES). We further investigate whether sequencing tumor samples alone combined with a germline filtering and background noise removal algorithm can measure TMB accurately compared with sequencing of tumor-normal pairs. Experimental Method: WES data of tumor and subject-matched normal DNA were either downloaded from The Cancer Genome Atlas (TCGA) or generated in-house. A 500-gene targeted DNA sequencing panel, which includes various cancer-relevant genes and covers two megabases, was also developed in-house. TMB was calculated as mutations (single nucleotide variants, insertions, and deletions) per megabase. Data Summary: Using downloaded TCGA data from 2,385 subjects across colon, lung and melanoma cancer types, TMB was measured using tumor-normal WES or the in-silico-filtered tumor-only 500-gene panel and the two approaches correlated linearly (R2 = 0.96). Furthermore, we demonstrated that the targeted panel achieved & gt;90% sensitivity and & gt;85% specificity when classifying TMB-high and low tumor samples at the cutoff of 15 compared to the same TCGA data. TMB as determined from tumor-only WES was also analyzed using computational germline-filtering and background noise-removal to demonstrate excellent concordance with WES of tumor-normal pairs. To further validate these findings, by analyzing WES data and 500-gene panel targeted NGS data of & gt;45 subjects generated in house. Through interrogating the 500-gene NGS data, we found that TMB determined using tumor-only sequencing was also similar from that ascertained through tumor-normal pairs. Of interest, further analysis showed that TMB determined from the 500-gene panel data using tumor-only sequencing along with germline filtering and background noise removing was comparable to that calculated from WES of tumor-normal pairs. Conclusion: Collectively, our data demonstrates that TMB determined from NGS of a two megabase DNA region utilizing a 500 gene panel correlates strongly with TMB measured through WES, with a sensitivity of & gt;90% and a specificity of & gt;85%. In addition, sequencing tumor samples alone combined with bioinformatic germline-filtering and background noise-removal was similar to sequencing subject-matched normal DNA. These findings support the use of a 500 gene panel for accurate measurement of TMB while the addition of bioinformatics enables tumor-only sequencing. Citation Format: Alex Steven So, Shannon Kaplan, Chen Zhao, Shile Zhang, Li Liu, Phillip Le, Raakhee Vijayaraghavan, Tingting Jiang, Sven Bilke, Traci Pawlowski, Karen Gutekunst. Accurate measurement of tumor mutation burden through tumor-only sequencing using a 500-gene panel [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 435.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2018-435
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 5
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    Single-cell sequencing links multiregional immune landscapes and tissue-resident T cells in ccRCC to tumor topology and therapy efficacy
    Elsevier BV ; 2021
    In:  Cancer Cell Vol. 39, No. 5 ( 2021-05), p. 662-677.e6
    Details
    In: Cancer Cell, Elsevier BV, Vol. 39, No. 5 ( 2021-05), p. 662-677.e6
    Type of Medium: Online Resource
    ISSN: 1535-6108
    URL: Article
    DOI: 10.1016/j.ccell.2021.03.007
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
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    SSG: 12
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  • 6
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    Identification of biomarkers predictive of metastasis development in early-stage colorectal cancer using network-based regularization
    Springer Science and Business Media LLC ; 2023
    In:  BMC Bioinformatics Vol. 24, No. 1 ( 2023-01-16)
    Details
    In: BMC Bioinformatics, Springer Science and Business Media LLC, Vol. 24, No. 1 ( 2023-01-16)
    Abstract: Colorectal cancer (CRC) is the third most common cancer and the second most deathly worldwide. It is a very heterogeneous disease that can develop via distinct pathways where metastasis is the primary cause of death. Therefore, it is crucial to understand the molecular mechanisms underlying metastasis. RNA-sequencing is an essential tool used for studying the transcriptional landscape. However, the high-dimensionality of gene expression data makes selecting novel metastatic biomarkers problematic. To distinguish early-stage CRC patients at risk of developing metastasis from those that are not, three types of binary classification approaches were used: (1) classification methods (decision trees, linear and radial kernel support vector machines, logistic regression, and random forest) using differentially expressed genes (DEGs) as input features; (2) regularized logistic regression based on the Elastic Net penalty and the proposed iTwiner—a network-based regularizer accounting for gene correlation information; and (3) classification methods based on the genes pre-selected using regularized logistic regression. Classifiers using the DEGs as features showed similar results, with random forest showing the highest accuracy. Using regularized logistic regression on the full dataset yielded no improvement in the methods’ accuracy. Further classification using the pre-selected genes found by different penalty factors, instead of the DEGs, significantly improved the accuracy of the binary classifiers. Moreover, the use of network-based correlation information (iTwiner) for gene selection produced the best classification results and the identification of more stable and robust gene sets. Some are known to be tumor suppressor genes ( OPCML-IT2 ), to be related to resistance to cancer therapies ( RAC1P3 ), or to be involved in several cancer processes such as genome stability ( XRCC6P2 ), tumor growth and metastasis ( MIR602 ) and regulation of gene transcription ( NME2P2 ). We show that the classification of CRC patients based on pre-selected features by regularized logistic regression is a valuable alternative to using DEGs, significantly increasing the models’ predictive performance. Moreover, the use of correlation-based penalization for biomarker selection stands as a promising strategy for predicting patients’ groups based on RNA-seq data.
    Type of Medium: Online Resource
    ISSN: 1471-2105
    URL: Article
    DOI: 10.1186/s12859-022-05104-z
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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  • 7
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    Genetic and microenvironmental intra-tumor heterogeneity impacts colorectal cancer evolution and metastatic development
    Springer Science and Business Media LLC ; 2022
    In:  Communications Biology Vol. 5, No. 1 ( 2022-09-09)
    Details
    In: Communications Biology, Springer Science and Business Media LLC, Vol. 5, No. 1 ( 2022-09-09)
    Abstract: Colorectal cancer (CRC) is a highly diverse disease, where different genomic instability pathways shape genetic clonal diversity and tumor microenvironment. Although intra-tumor heterogeneity has been characterized in primary tumors, its origin and consequences in CRC outcome is not fully understood. Therefore, we assessed intra- and inter-tumor heterogeneity of a prospective cohort of 136 CRC samples. We demonstrate that CRC diversity is forged by asynchronous forms of molecular alterations, where mutational and chromosomal instability collectively boost CRC genetic and microenvironment intra-tumor heterogeneity. We were able to depict predictor signatures of cancer-related genes that can foresee heterogeneity levels across the different tumor consensus molecular subtypes (CMS) and primary tumor location. Finally, we show that high genetic and microenvironment heterogeneity are associated with lower metastatic potential, whereas late-emerging copy number variations favor metastasis development and polyclonal seeding. This study provides an exhaustive portrait of the interplay between genetic and microenvironment intra-tumor heterogeneity across CMS subtypes, depicting molecular events with predictive value of CRC progression and metastasis development.
    Type of Medium: Online Resource
    ISSN: 2399-3642
    URL: Article
    DOI: 10.1038/s42003-022-03884-x
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 8
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    HERVs establish a distinct molecular subtype in stage II/III colorectal cancer with poor outcome
    Springer Science and Business Media LLC ; 2021
    In:  npj Genomic Medicine Vol. 6, No. 1 ( 2021-02-15)
    Details
    In: npj Genomic Medicine, Springer Science and Business Media LLC, Vol. 6, No. 1 ( 2021-02-15)
    Abstract: Colorectal cancer (CRC) is one of the most lethal malignancies. The extreme heterogeneity in survival rate is driving the need for new prognostic biomarkers. Human endogenous retroviruses (hERVs) have been suggested to influence tumor progression, oncogenesis and elicit an immune response. We examined multiple next-generation sequencing (NGS)-derived biomarkers in 114 CRC patients with paired whole-exome and whole-transcriptome sequencing (WES and WTS, respectively). First, we demonstrate that the median expression of hERVs can serve as a potential biomarker for prognosis, relapse, and resistance to chemotherapy in stage II and III CRC. We show that hERV expression and CD8+ tumor-infiltrating T-lymphocytes (TILs) synergistically stratify overall and relapse-free survival (OS and RFS): the median OS of the CD8-/hERV+ subgroup was 29.8 months compared with 37.5 months for other subgroups (HR = 4.4, log-rank P   〈  0.001). Combing NGS-based biomarkers (hERV/CD8 status) with clinicopathological factors provided a better prediction of patient survival compared to clinicopathological factors alone. Moreover, we explored the association between genomic and transcriptomic features of tumors with high hERV expression and establish this subtype as distinct from previously described consensus molecular subtypes of CRC. Overall, our results underscore a previously unknown role for hERVs in leading to a more aggressive subtype of CRC.
    Type of Medium: Online Resource
    ISSN: 2056-7944
    URL: Article
    DOI: 10.1038/s41525-021-00177-w
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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  • 9
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    Abstract 5381: A highly sensitive method for noninvasive cancer profiling through targeted methylation sequencing of circulating cell-free DNA
    American Association for Cancer Research (AACR) ; 2017
    In:  Cancer Research Vol. 77, No. 13_Supplement ( 2017-07-01), p. 5381-5381
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 5381-5381
    Abstract: Liquid biopsies, by analyzing circulating cell-free DNA (cfDNA), have emerged as a promising tool for noninvasive cancer diagnostics and monitoring. Compared to the limited number of scattered DNA mutations in cancer patients, the genome-wide distribution of numerous densely clustered DNA methylation alterations may enable more robust cancer signal detection and higher sensitivity in cancer diagnostics. Furthermore, the cancer type specific methylation signatures potentially can be used for the identification of cancer tissue origin. To enable multivariate analysis of genome-wide methylation markers, we have developed a targeted methylation sequencing assay that can measure the methylation status of thousands of affected CpG (5'-C-phosphate-G-3') sites simultaneously. This assay allows low cfDNA input as little as 3ng while retaining good efficiency. The targeted sites were particularly selected for hypermethylated markers in more than 20 major cancer types based on The Cancer Genome Atlas (TCGA) database. Following bisulfite sequencing of cfDNA, methylation signals from targeted CpG sites were aggregated into a single score that measures deviation of a sample’s methylation profile from a reference baseline. Cancer/normal classification was performed by comparing the methylation score of a test sample to a cutoff established by a group of plasma samples from healthy individuals. Subsequently, methylation signals from cancer type specific markers were used to perform cancer type classification. In a study to evaluate the potential clinical applications of this method, we processed 25 blood samples collected from healthy individuals and 70 blood samples collected from 63 advanced cancer patients. The assay demonstrated a specificity of 100% (n=25), and a sensitivity of 94.3% in colorectal cancer (n=36), 72.7% in breast cancer (n=11), and 52.6% in lung cancer (n=19) detection, respectively. We further performed cancer type classification on the samples that were correctly classified as true positives in the cancer/normal classification. Our results showed a classification accuracy of 82.4% for colorectal cancer (n=34), 87.5% for breast cancer (n=8), and 70% for lung cancer (n=10). In summary, we have developed a comprehensive method that allows us to perform noninvasive cancer profiling through targeted methylation sequencing assay and novel analysis algorithms. This method can potentially be used in multiple validated clinical applications, such as early cancer detection, cancer diagnostics, and monitoring of minimal residual disease. Citation Format: Li Liu, Jonathan M. Toung, Raakhee Vijayaraghavan, Ruoyu Zhang, Helen J. Huang, Toshinori Hinoue, Hui Shen, Neeraj Salathia, Marina Bibikova, Richard Shen, Karen Gutekunst, Peter W. Laird, Filip Janku, Jian-Bing Fan. A highly sensitive method for noninvasive cancer profiling through targeted methylation sequencing of circulating cell-free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5381. doi:10.1158/1538-7445.AM2017-5381
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2017-5381
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 10
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    Abstract 4733: Gene-set analysis of colon cancer genome-wide association data: Identification of the TGF-beta pathway
    American Association for Cancer Research (AACR) ; 2010
    In:  Cancer Research Vol. 70, No. 8_Supplement ( 2010-04-15), p. 4733-4733
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 70, No. 8_Supplement ( 2010-04-15), p. 4733-4733
    Abstract: First results from genome-wide association studies (GWAS) have demonstrated considerable success in identifying genetic variants associated with colorectal cancer (CRC). To date, 10 CRC susceptibility loci have been identified. However, these marginal single nucleotide polymorphism (SNP) associations explain only ∼6% of the heritable variation underlying CRC risk. We employed a pathway-based approach using our recently developed Gene-set Ridge Regression in Association Studies (GRASS) method to assess whether sets of functionally related genes are enriched for SNPs associated with colon cancer risk. We used GWAS data from three studies: The Women's Health Initiative (WHI; 483 cases and 530 controls); the Prostate, Lung, Colon and Ovarian Cancer Screening Trial (PLCO; 546 cases and 1177 controls); and the Diet, Activity and Lifestyle population-based case-control study (DALS; 698 cases and 719 controls). Samples were genotyped on Illumina HumanHap 300K + 240K, 550K or 610K platforms. After applying stringent quality control criteria, our final analysis included 392,361 SNPs. We used genomic partition to assign SNPs to nearby genes and defined pathways using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We restricted our analysis to 170 pathways with 10 or more genes (range 10-253 genes). Our GRASS method uses eigenSNPs derived from principal components analysis within each gene. Regularized regression is performed for each pathway, using a novel group ridge penalty function. The penalty function results in selection of the most representative eigenSNPs within genes while assessing the association of all the genes, within a pathway, with disease risk. Permutations are used to standardize the test statistics and obtain p-values. The false discovery rate (FDR) was calculated using the Benjamini-Hochberg method. We analyzed WHI, PLCO and DALS separately, adjusting for age, sex, and genetic ancestry derived from principal components analysis, and performed a meta-analysis to combine the results. Five pathways were significant at a p-value cutoff of 0.05. The top pathway, the transforming growth factor beta (TGF-beta) signaling pathway (p-value=0.009), also met a FDR cutoff of 20%. This pathway remained significant (p=0.014) after excluding the known CRC susceptibility loci and all SNPs with linkage disequilibrium r2 & gt;0.2 with those 10 loci. The top genes in the pathway were TFGB1, SMAD4, FST, TFGB2, INHBA, PITX2, BMPR2 and PP2R2B (all p & lt;0.05). Our results provide statistical evidence that germline genetic variation in the TGF-beta signaling pathway, which has long been implicated in colon carcinogenesis due to its effects on cell growth and apoptosis, influences colon cancer susceptibility. This information can help prioritize SNPs for replication studies and supports further work to elucidate the role of variation underlying this pathway in relation to colon cancer etiology. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4733.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM10-4733
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2010
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