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  • 1
    In: Clinical & Experimental Metastasis, Springer Science and Business Media LLC, Vol. 33, No. 8 ( 2016-12), p. 765-773
    Type of Medium: Online Resource
    ISSN: 0262-0898 , 1573-7276
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2016
    detail.hit.zdb_id: 1496876-9
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  • 2
    Online Resource
    Online Resource
    American Society of Clinical Oncology (ASCO) ; 2023
    In:  Journal of Clinical Oncology Vol. 41, No. 16_suppl ( 2023-06-01), p. e18855-e18855
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 41, No. 16_suppl ( 2023-06-01), p. e18855-e18855
    Abstract: e18855 Background: Approximately 40-45,000, women die from breast cancer each year, most of which are due to metastatic recurrence of stage I-III cancers. Stage I and II cancers are considered highly curable, but they also include most patients. The goal of this analysis is to examine the contribution of stage I, II, III, and IV disease to annual breast cancer-specific death and assess time trends. Methods: Data from patients diagnosed with stage I-IV breast cancer between 1975-2018 (N = 1,545,502) were obtained from The Surveillance, Epidemiology, and End Results (SEER) Program. After filtering for the female sex, one primary site only, surgery performed, known AJCC stage 〉 0, and survival data available we included N = 1,018,331 patients. We estimated the year of breast cancer-specific death (BCSD) by adding time to BCSD to a year of diagnosis for each patient. We summarized the proportion of BCSD by stage at diagnosis in each year between 2000 and 2017. All temporal trends were assessed by fitting the linear model with interactions between stage and year, then running the ANOVA to test model coefficient significance. For each year of diagnosis, Kaplan-Meier curves were fitted to patient data grouped by stage, and 5-year survival was estimated. Results: The study population included 24% ER-, 73% ER+ (the rest unknown) cancers; 35% HER2-, 6% HER2+ (the rest unknown); 24% were 〈 50 and 76% 〉 50 years of age; 60% received adjuvant chemotherapy. Over time, the frequency of stage I cancers increased from 49% in 2000 to 54% by 2017 (slope = 0.37 [95% CI: 0.32; 0.42]), and stage II and III decreased from 35.2% to 34.9% (slope = - 0.09 [-0.15; -0.04] ) and from 14% to 10% (slope = -0.23 [-0.29; -0.18]), respectively. Five-year breast cancer-specific survivals remained stable for stage I cancers and increased significantly for stage II (slope = 0.002 [0.001;0.003] ), stage III (slope = 0.006 [0.005;0.007]) and IV cancers (slope = 0.011 [0.010; 0.012] ). The contribution of stage I cancers to annual breast cancer death increased and reached 23% in 2017, while death from stage III disease decreased to 30%. Since 2003, 〉 50% of breast cancer deaths are from stage I-II cancers. Conclusions: The prevalence of stage I breast cancers increased in the past 20 years, and despite excellent overall prognosis, stage I-II cancers account for over 60% of all BCSD. To substantially reduce breast cancer death, we need to better identify the minority of Stage I-II patients who remain at risk for recurrence and death. [Table: see text]
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2023
    detail.hit.zdb_id: 2005181-5
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  • 3
    Online Resource
    Online Resource
    Public Library of Science (PLoS) ; 2015
    In:  PLOS ONE Vol. 10, No. 7 ( 2015-7-31), p. e0134256-
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  • 4
    Online Resource
    Online Resource
    Frontiers Media SA ; 2021
    In:  Frontiers in Genetics Vol. 12 ( 2021-12-9)
    In: Frontiers in Genetics, Frontiers Media SA, Vol. 12 ( 2021-12-9)
    Abstract: A typical genome-wide association study (GWAS) analyzes millions of single-nucleotide polymorphisms (SNPs), several of which are in a region of the same gene. To conduct gene set analysis (GSA), information from SNPs needs to be unified at the gene level. A widely used practice is to use only the most relevant SNP per gene; however, there are other methods of integration that could be applied here. Also, the problem of nonrandom association of alleles at two or more loci is often neglected. Here, we tested the impact of incorporation of different integrations and linkage disequilibrium (LD) correction on the performance of several GSA methods. Matched normal and breast cancer samples from The Cancer Genome Atlas database were used to evaluate the performance of six GSA algorithms: Coincident Extreme Ranks in Numerical Observations (CERNO), Gene Set Enrichment Analysis (GSEA), GSEA-SNP, improved GSEA for GWAS (i-GSEA4GWAS), Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA), and Over-Representation Analysis (ORA). Association of SNPs to phenotype was calculated using modified McNemar’s test. Results for SNPs mapped to the same gene were integrated using Fisher and Stouffer methods and compared with the minimum p -value method. Four common measures were used to quantify the performance of all combinations of methods. Results of GSA analysis on GWAS were compared to the one performed on gene expression data. Comparing all evaluation metrics across different GSA algorithms, integrations, and LD correction, we highlighted CERNO, and MAGENTA with Stouffer as the most efficient. Applying LD correction increased prioritization and specificity of enrichment outcomes for all tested algorithms. When Fisher or Stouffer were used with LD, sensitivity and reproducibility were also better. Using any integration method was beneficial in comparison with a minimum p -value method in specific combinations. The correlation between GSA results from genomic and transcriptomic level was the highest when Stouffer integration was combined with LD correction. We thoroughly evaluated different approaches to GSA in GWAS in terms of performance to guide others to select the most effective combinations. We showed that LD correction and Stouffer integration could increase the performance of enrichment analysis and encourage the usage of these techniques.
    Type of Medium: Online Resource
    ISSN: 1664-8021
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2606823-0
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 5_Supplement ( 2023-03-01), p. PD9-09-PD9-09
    Abstract: Background: The RxPONDER and TAILORx trials demonstrated benefit from adjuvant chemotherapy in patients & lt; 50 years with node-positive breast cancer and Recurrence Score (RS) 0-25, and with node-negative disease and RS 16-25, respectively. Neither trial showed benefit in older women with RS & lt; 26. It is unclear what explains the interaction between age and adjuvant chemotherapy benefit. Methods: We analyzed transcriptomic and genomic data from n=4,507 ER+/HER2- breast cancers to compare differences in estrogen receptor (ER), proliferation, and immune-related gene expressions, and somatic mutation patterns and mutation burden between younger ( & lt; 50 years of age) and older ( & gt;55 years) patients. We restricted our analysis to patients in the lower 80% range of in silico RS distribution to mimic the RxPONDER and TAILORx populations. Results: Five data sets were analyzed independently to assess consistency of results (TCGA n=530; microarray cohort A n=865; Cohort B n=609, METABRIC n=867, SCAN-B n=1636). Older patients had significantly higher somatic mutation burden and more frequent copy number gain in ESR1, LATS1, ARID1B, SGK1, and MYB genes (odds ratio [OR] & gt; 8.5, FDR & lt; 0.05), but lower frequency of GATA3 mutations (12% versus 26%, P & lt; 0.0001). Younger patients had higher rate of ESR1 copy number loss (OR: 0.45, FDR: 0.03). There was no difference in proliferation-related gene expression. ESR1 mRNA expression was significantly lower in younger women in all cohorts (P & lt; 0.001). A regression model of ESR1 mRNA expression using age and ER IHC positivity indicated that lower ER expression in younger patients is primarily driven by lower ESR1 mRNA per cancer cell and not by fewer ER positive cells. We also assessed four gene signatures associated with endocrine therapy sensitivity including a 4-gene ERS, a 7-gene ERS-Lum, a 106-gene ERS-Pos signature, and a 59-gene ERS-Neg signature associated with endocrine resistance. In the TCGA and METABRIC cohorts, the ERS, ERS-Lum, and ERS-Pos signatures were all lower (FDR & lt; 0.03) while the ERS-Neg signature was higher (FDR & lt; 0.001) in younger patients. Similarly, in both microarray cohorts, and in the SCAN-B-cohort, the ERS-Pos signature was lower and the ERS-Neg signature was higher in younger patients (FDR & lt; 0.002). Next, we assessed 4 different immune cell signatures that have been associated with response to chemotherapy. In the TCGA, B-cell, T-cell, Mast-cell, and TIS signatures were significantly higher (FDR & lt;.05). In the microarray Cohort-A, B cells and mast cells were significantly higher, and the T cell and TIS signatures showed a trend for higher expression. In Cohort-B, T cells, B cells, TIS, and dendritic cells signatures were significantly higher in younger patients. Significantly higher expression of immune gene signatures in younger patients were also seen in the METABRIC and SCAN-B data sets. The ER-related and immune-related gene signatures showed negative correlation and joint analysis defined three subpopulations in younger women: (i) immune-high/ER-low, (ii) immune-intermediate/ER-intermediate and (iii) immune-low/ER-intermediate, whereas in older women the dominant pattern was immune-low/ER-high. Conclusion: ESR1 mRNA and ER-associated gene expression is lower in ER positive cancers of younger compared to older patients, while immune infiltration is higher. The cytotoxic and endocrine effects of adjuvant chemotherapy could both contribute to the survival benefit seen in younger patients, but the relative contributions of these effects may vary by ER and immune phenotype. We hypothesize that in immune-high/ER-low cancers, the cytotoxic effect of chemotherapy may drive the benefit, whereas in immune-low/ER-intermediate cancers chemotherapy induced ovarian suppression may play a more important role. Citation Format: Tao Qing, Thomas Karn, Mariya Rozenblit, Julia Foldi, Michal Marczyk, Naing Lin Shan, Kim Blenman, uwe Holtrich, Kevin Kalinsky, Funda Meric-Bernstam, Lajos Pusztai. Molecular differences between younger versus older estrogen receptor positive/human epidermal growth factor receptor-2 negative breast cancers [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD9-09.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 6
    In: Journal of the American Society of Cytopathology, Elsevier BV, Vol. 12, No. 1 ( 2023-01), p. 10-19
    Type of Medium: Online Resource
    ISSN: 2213-2945
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 2696592-6
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  • 7
    Online Resource
    Online Resource
    Institute of Electrical and Electronics Engineers (IEEE) ; 2019
    In:  IEEE/ACM Transactions on Computational Biology and Bioinformatics
    In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Institute of Electrical and Electronics Engineers (IEEE)
    Type of Medium: Online Resource
    ISSN: 1545-5963 , 1557-9964 , 2374-0043
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2019
    detail.hit.zdb_id: 2158957-4
    SSG: 12
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  • 8
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2021
    In:  Cancer Research Vol. 81, No. 4_Supplement ( 2021-02-15), p. PS19-05-PS19-05
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 4_Supplement ( 2021-02-15), p. PS19-05-PS19-05
    Abstract: Background: Cancer driver genes are characterized by frequently recurrent mutations, substantial functional impact on in vitro and in vivo cancer growth, and several of the represent clinically important therapeutic targets. Whole exome and genome sequencing studies identified mutations in at least one cancer driver gene in about 70% breast cancers. These studies also revealed that each cancer also harbors hundreds to thousands of additional non-recurrent mutations which follow a long-tail distribution. Historically, these long tail “passenger” mutations are considered random due to genomic instability and not expected to contribute to the biology of the disease. We hypothesize that “long-tail” mutations could also have functional importance and contribute to the unique biology of a given cancer. The goal of the current analysis was to identify the long-tail mutations in breast cancer, and estimate their overall functional importance. Methods: We obtained somatic mutations from the breast cancer TCGA cohort (N=1076) and calculated the somatic mutation frequency for each gene. The dNdScv algorithm was used to estimate significantly mutated genes. A gene was considered to be in the long tail of mutations if its somatic mutation frequency was 1-3%, and the dNdScv p-value was & lt; 0.05. We performed pathway enrichment analysis with 21 cancer pathways assembled by NanoString Technologies (Seattle, WA) for the long-tail genes using Fisher’s exact test and obtained gene dependency scores (DS) from The Cancer Dependency Map (DepMap) project which performed genome-wide pooled loss of function screening for 17,634 human genes using and CRISPR-Cas9-mediated (CRISPR) gene editing to estimate tumor cell viability after gene silencing in 563 cell lines. The more negative (i.e. lower) the dependency score the more important the gene is to sustain cell viability. We compared the DS of the long tail genes with known cancer driver genes and other human genes excluding known breast cancer driver genes. We also compared the dependency score of genes with long-tail mutations between breast cancer and other cancer types using the Mann-Whitney U test. We estimated the trend of average dependency score across genesets using the Jonckheere Terpstra test and using Kendall's tau (τ) coefficient to show the increasing (positive value) or decreasing (negative value) trend. Results: Seventy percent of breast cancers (n=763) carried long-tail mutations in 115 different genes. The average number of long tail mutations was N=3 (range from 1 to 118). Genes with long-tail mutations were enriched in epithelial-mesenchymal transition, extracellular matrix, angiogenesis, adaptive immunity, MAPK, innate immunity, inflammation, and RAS pathways (FDR & lt;0.035). Genes with long-tail mutations showed the lowest average dependency score in breast cancer cell lines (n=28) with median DS= -0.080, the range of median DS was -0.079 to -0.056 in other cancer cell lines (P=0.70). In the breast cancer cell lines, known breast cancer driver genes (N=11) had the lowest DS (median=-0.352), followed by the long-tail genes (median=-0.0801), followed by all other human genes (median DS=-0.0528). An increasing trend (τ=1.78, P=0.024) of dependency score was observed across known cancer driver genes, long-tail genes, and other human genes which indicate that long-tail genes are important in cancer cell viability. Conclusions: Long-tail mutations are seen in most breast cancers in unique combinations. They primarily affect genes involved in key cancer pathways. Long tail genes have negative dependency scores across 563 cancer cell lines indicating functional importance in sustaining cancer viability. These results suggest that long-tail genes with mutations could contribute to the biology of breast cancers and might explain the broad range of differences in clinical behavior or morphologically similar cancers. Citation Format: Tao Qing, Hussein Mohsen, Mariya Rozenblit, Michal Marczyk, Julia Foldi, Kim Blenman, Vignesh Gunasekharan, Lajos Pusztai. Functional importance of long-tail mutations in breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS19-05.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 9
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 9 ( 2022-05-03), p. 1698-1711
    Abstract: Metabolic reprogramming is a hallmark of malignant transformation, and loss of isozyme diversity (LID) contributes to this process. Isozymes are distinct proteins that catalyze the same enzymatic reaction but can have different kinetic characteristics, subcellular localization, and tissue specificity. Cancer-dominant isozymes that catalyze rate-limiting reactions in critical metabolic processes represent potential therapeutic targets. Here, we examined the isozyme expression patterns of 1,319 enzymatic reactions in 14 cancer types and their matching normal tissues using The Cancer Genome Atlas mRNA expression data to identify isozymes that become cancer-dominant. Of the reactions analyzed, 357 demonstrated LID in at least one cancer type. Assessment of the expression patterns in over 600 cell lines in the Cancer Cell Line Encyclopedia showed that these reactions reflect cellular changes instead of differences in tissue composition; 50% of the LID-affected isozymes showed cancer-dominant expression in the corresponding cell lines. The functional importance of the cancer-dominant isozymes was assessed in genome-wide CRISPR and RNAi loss-of-function screens: 17% were critical for cell proliferation, indicating their potential as therapeutic targets. Lists of prioritized novel metabolic targets were developed for 14 cancer types; the most broadly shared and functionally validated target was acetyl-CoA carboxylase 1 (ACC1). Small molecule inhibition of ACC reduced breast cancer viability in vitro and suppressed tumor growth in cell line– and patient-derived xenografts in vivo. Evaluation of the effects of drug treatment revealed significant metabolic and transcriptional perturbations. Overall, this systematic analysis of isozyme expression patterns elucidates an important aspect of cancer metabolic plasticity and reveals putative metabolic vulnerabilities. Significance: This study exploits the loss of metabolic isozyme diversity common in cancer and reveals a rich pool of potential therapeutic targets that will allow the repurposing of existing inhibitors for anticancer therapy. See related commentary by Kehinde and Parker, p. 1695
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 10
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2013
    In:  BMC Bioinformatics Vol. 14, No. 1 ( 2013-12)
    In: BMC Bioinformatics, Springer Science and Business Media LLC, Vol. 14, No. 1 ( 2013-12)
    Type of Medium: Online Resource
    ISSN: 1471-2105
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2013
    detail.hit.zdb_id: 2041484-5
    SSG: 12
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