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Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.
Fachal L, Aschard H, Beesley J, Barnes DR, Allen J, Kar S, Pooley KA, Dennis J, Michailidou K, Turman C, Soucy P, Lemaçon A, Lush M, Tyrer JP, Ghoussaini M, Moradi Marjaneh M, Jiang X, Agata S, Aittomäki K, Alonso MR, Andrulis IL, Anton-Culver H, Antonenkova NN, Arason A, Arndt V, Aronson KJ, Arun BK, Auber B, Auer PL, Azzollini J, Balmaña J, Barkardottir RB, Barrowdale D, Beeghly-Fadiel A, Benitez J, Bermisheva M, Białkowska K, Blanco AM, Blomqvist C, Blot W, Bogdanova NV, Bojesen SE, Bolla MK, Bonanni B, Borg A, Bosse K, Brauch H, Brenner H, Briceno I, Brock IW, Brooks-Wilson A, Brüning T, Burwinkel B, Buys SS, Cai Q, Caldés T, Caligo MA, Camp NJ, Campbell I, Canzian F, Carroll JS, Carter BD, Castelao JE, Chiquette J, Christiansen H, Chung WK, Claes KBM, Clarke CL, GEMO Study Collaborators, EMBRACE Collaborators, Collée JM, Cornelissen S, Couch FJ, Cox A, Cross SS, Cybulski C, Czene K, Daly MB, de la Hoya M, Devilee P, Diez O, Ding YC, Dite GS, Domchek SM, Dörk T, Dos-Santos-Silva I, Droit A, Dubois S, Dumont M, Duran M, Durcan L, Dwek M, Eccles DM, Engel C, Eriksson M, Evans DG, Fasching PA, Fletcher O, Floris G, Flyger H, Foretova L, Foulkes WD, Friedman E, Fritschi L, Frost D, Gabrielson M, Gago-Dominguez M, Gambino G, Ganz PA, Gapstur SM, Garber J, García-Sáenz JA, Gaudet MM, Georgoulias V, Giles GG, Glendon G, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Tibiletti MG, Greene MH, Grip M, Gronwald J, Grundy A, Guénel P, Hahnen E, Haiman CA, Håkansson N, Hall P, Hamann U, Harrington PA, Hartikainen JM, Hartman M, He W, Healey CS, Heemskerk-Gerritsen BAM, Heyworth J, Hillemanns P, Hogervorst FBL, Hollestelle A, Hooning MJ, Hopper JL, Howell A, Huang G, Hulick PJ, Imyanitov EN, KConFab Investigators, HEBON Investigators, ABCTB Investigators, Isaacs C, Iwasaki M, Jager A, Jakimovska M, Jakubowska A, James PA, Janavicius R, Jankowitz RC, John EM, Johnson N, Jones ME, Jukkola-Vuorinen A, Jung A, Kaaks R, Kang D, Kapoor PM, Karlan BY, Keeman R, Kerin MJ, Khusnutdinova E, Kiiski JI, Kirk J, Kitahara CM, Ko YD, Konstantopoulou I, Kosma VM, Koutros S, Kubelka-Sabit K, Kwong A, Kyriacou K, Laitman Y, Lambrechts D, Lee E, Leslie G, Lester J, Lesueur F, Lindblom A, Lo WY, Long J, Lophatananon A, Loud JT, Lubiński J, MacInnis RJ, Maishman T, Makalic E, Mannermaa A, Manoochehri M, Manoukian S, Margolin S, Martinez ME, Matsuo K, Maurer T, Mavroudis D, Mayes R, McGuffog L, McLean C, Mebirouk N, Meindl A, Miller A, Miller N, Montagna M, Moreno F, Muir K, Mulligan AM, Muñoz-Garzon VM, Muranen TA, Narod SA, Nassir R, Nathanson KL, Neuhausen SL, Nevanlinna H, Neven P, Nielsen FC, Nikitina-Zake L, Norman A, Offit K, Olah E, Olopade OI, Olsson H, Orr N, Osorio A, Pankratz VS, Papp J, Park SK, Park-Simon TW, Parsons MT, Paul J, Pedersen IS, Peissel B, Peshkin B, Peterlongo P, Peto J, Plaseska-Karanfilska D, Prajzendanc K, Prentice R, Presneau N, Prokofyeva D, Pujana MA, Pylkäs K, Radice P, Ramus SJ, Rantala J, Rau-Murthy R, Rennert G, Risch HA, Robson M, Romero A, Rossing M, Saloustros E, Sánchez-Herrero E, Sandler DP, Santamariña M, Saunders C, Sawyer EJ, Scheuner MT, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schöttker B, Schürmann P, Scott C, Scott RJ, Senter L, Seynaeve CM, Shah M, Sharma P, Shen CY, Shu XO, Singer CF, Slavin TP, Smichkoska S, Southey MC, Spinelli JJ, Spurdle AB, Stone J, Stoppa-Lyonnet D, Sutter C, Swerdlow AJ, Tamimi RM, Tan YY, Tapper WJ, Taylor JA, Teixeira MR, Tengström M, Teo SH, Terry MB, Teulé A, Thomassen M, Thull DL, Tischkowitz M, Toland AE, Tollenaar RAEM, Tomlinson I, Torres D, Torres-Mejía G, Troester MA, Truong T, Tung N, Tzardi M, Ulmer HU, Vachon CM, van Asperen CJ, van der Kolk LE, van Rensburg EJ, Vega A, Viel A, Vijai J, Vogel MJ, Wang Q, Wappenschmidt B, Weinberg CR, Weitzel JN, Wendt C, Wildiers H, Winqvist R, Wolk A, Wu AH, Yannoukakos D, Zhang Y, Zheng W, Hunter D, Pharoah PDP, Chang-Claude J, García-Closas M, Schmidt MK, Milne RL, Kristensen VN, French JD, Edwards SL, Antoniou AC, Chenevix-Trench G, Simard J, Easton DF, Kraft P, Dunning AM
(2020) Nat Genet 52: 56-73
MeSH Terms: Bayes Theorem, Biomarkers, Tumor, Breast Neoplasms, Chromosome Mapping, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Regulatory Sequences, Nucleic Acid, Risk Factors
Show Abstract · Added March 3, 2020
Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
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Upregulated claudin-1 expression promotes colitis-associated cancer by promoting β-catenin phosphorylation and activation in Notch/p-AKT-dependent manner.
Gowrikumar S, Ahmad R, Uppada SB, Washington MK, Shi C, Singh AB, Dhawan P
(2019) Oncogene 38: 5321-5337
MeSH Terms: Animals, Biomarkers, Tumor, Cells, Cultured, Claudin-1, Colitis, Colonic Neoplasms, Gene Expression Regulation, Neoplastic, HT29 Cells, Humans, Inflammatory Bowel Diseases, Intestinal Mucosa, Mice, Mice, Inbred C57BL, Mice, Transgenic, Phosphorylation, Prognosis, Protein Processing, Post-Translational, Proto-Oncogene Proteins c-akt, Receptors, Notch, Signal Transduction, Up-Regulation, beta Catenin
Show Abstract · Added April 24, 2019
In IBD patients, integration between a hyper-activated immune system and epithelial cell plasticity underlies colon cancer development. However, molecular regulation of such a circuity remains undefined. Claudin-1 (Cld-1), a tight-junction integral protein deregulation alters colonic epithelial cell (CEC) differentiation, and promotes colitis severity while impairing colitis-associated injury/repair. Tumorigenesis is a product of an unregulated wound-healing process and therefore we postulated that upregulated Cld-1 levels render IBD patients susceptible to the colitis-associated cancer (CAC). Villin Cld-1 mice are used to carryout overexpressed studies in mice. The role of deregulated Cld-1 expression in CAC and the underlying mechanism was determined using a well-constructed study scheme and mouse models of DSS colitis/recovery and CAC. Using an inclusive investigative scheme, we here report that upregulated Cld-1 expression promotes susceptibility to the CAC and its malignancy. Increased mucosal inflammation and defective epithelial homeostasis accompanied the increased CAC in Villin-Cld-1-Tg mice. We further found significantly increased levels of protumorigenic M2 macrophages and β-cateninSer552 (β-CatSer552) expression in the CAC in Cld-1Tg vs. WT mice. Mechanistic studies identified the role of PI3K/Akt signaling in Cld-1-dependent activation of the β-CatSer552, which, in turn, was dependent on proinflammatory signals. Our studies identify a critical role of Cld-1 in promoting susceptibility to CAC. Importantly, these effects of deregulated Cld-1 were not associated with altered tight junction integrity, but on its noncanonical role in regulating Notch/PI3K/Wnt/ β-CatSer552 signaling. Overall, outcome from our current studies identifies Cld-1 as potential prognostic biomarker for IBD severity and CAC, and a novel therapeutic target.
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22 MeSH Terms
Papillary thyroid carcinoma behavior: clues in the tumor microenvironment.
Bergdorf K, Ferguson DC, Mehrad M, Ely K, Stricker T, Weiss VL
(2019) Endocr Relat Cancer 26: 601-614
MeSH Terms: Adolescent, Adult, Aged, Aged, 80 and over, Biomarkers, Tumor, Female, Follow-Up Studies, Humans, Lymphocytes, Tumor-Infiltrating, Male, Middle Aged, Mutation, Prognosis, Thyroid Cancer, Papillary, Thyroid Neoplasms, Tumor Microenvironment, Young Adult
Show Abstract · Added April 15, 2019
The prevalence of thyroid carcinoma is increasing and represents the most common endocrine malignancy, with papillary thyroid carcinoma (PTC) being the most frequent subtype. The genetic alterations identified in PTCs fail to distinguish tumors with different clinical behaviors, such as extra-thyroidal extension and lymph node metastasis. We hypothesize that the immune microenvironment may play a critical role in tumor invasion and metastasis. Computational immunogenomic analysis was performed on 568 PTC samples in The Cancer Genome Atlas using CIBERSORT, TIMER and TIDE deconvolution analytic tools for characterizing immune cell composition. Immune cell infiltrates were correlated with histologic type, mutational type, tumor pathologic T stage and lymph node N stage. Dendritic cells (DCs) are highly associated with more locally advanced tumor T stage (T3/T4, odds ratio (OR) = 2.6, CI = 1.4-4.5, P = 5.4 × 10-4). Increased dendritic cells (OR = 3.4, CI = 1.9-6.3, P = 5.5 × 10-5) and neutrophils (OR = 10.5, CI = 2.7-44, P = 8.7 × 10-4) significantly correlate with lymph node metastasis. In addition, dendritic cells positively correlate with tall cell morphology (OR = 4.5, CI = 1.6-13, P = 4.9 × 10-3) and neutrophils negatively correlate with follicular morphology (OR = 1.3 × 10-3, CI = 5.3 × 10-5-0.031, P = 4.1 × 10-5). TIDE analysis indicates an immune-exclusive phenotype that may be mediated by increased galectin-3 found in PTCs. Thus, characterization of the PTC immune microenvironment using three computational platforms shows that specific immune cells correlate with mutational type, histologic type, local tumor extent and lymph node metastasis. Immunologic evaluation of PTCs may provide a better indication of biologic behavior, resulting in the improved diagnosis and treatment of thyroid cancer.
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Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk.
Yang Y, Wu L, Shu X, Lu Y, Shu XO, Cai Q, Beeghly-Fadiel A, Li B, Ye F, Berchuck A, Anton-Culver H, Banerjee S, Benitez J, Bjørge L, Brenton JD, Butzow R, Campbell IG, Chang-Claude J, Chen K, Cook LS, Cramer DW, deFazio A, Dennis J, Doherty JA, Dörk T, Eccles DM, Edwards DV, Fasching PA, Fortner RT, Gayther SA, Giles GG, Glasspool RM, Goode EL, Goodman MT, Gronwald J, Harris HR, Heitz F, Hildebrandt MA, Høgdall E, Høgdall CK, Huntsman DG, Kar SP, Karlan BY, Kelemen LE, Kiemeney LA, Kjaer SK, Koushik A, Lambrechts D, Le ND, Levine DA, Massuger LF, Matsuo K, May T, McNeish IA, Menon U, Modugno F, Monteiro AN, Moorman PG, Moysich KB, Ness RB, Nevanlinna H, Olsson H, Onland-Moret NC, Park SK, Paul J, Pearce CL, Pejovic T, Phelan CM, Pike MC, Ramus SJ, Riboli E, Rodriguez-Antona C, Romieu I, Sandler DP, Schildkraut JM, Setiawan VW, Shan K, Siddiqui N, Sieh W, Stampfer MJ, Sutphen R, Swerdlow AJ, Szafron LM, Teo SH, Tworoger SS, Tyrer JP, Webb PM, Wentzensen N, White E, Willett WC, Wolk A, Woo YL, Wu AH, Yan L, Yannoukakos D, Chenevix-Trench G, Sellers TA, Pharoah PDP, Zheng W, Long J
(2019) Cancer Res 79: 505-517
MeSH Terms: Biomarkers, Tumor, Carcinoma, Ovarian Epithelial, Cohort Studies, DNA Methylation, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Humans, Models, Genetic, Ovarian Neoplasms, Predictive Value of Tests, Risk, Women's Health
Show Abstract · Added March 26, 2019
DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study ( = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of < 7.94 × 10. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely , and . We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. SIGNIFICANCE: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
©2018 American Association for Cancer Research.
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Should Ki67 immunohistochemistry be performed on all lesions in multifocal small intestinal neuroendocrine tumours?
Numbere N, Huber AR, Shi C, Cates JMM, Gonzalez RS
(2019) Histopathology 74: 424-429
MeSH Terms: Adult, Aged, Aged, 80 and over, Biomarkers, Tumor, Disease-Free Survival, Female, Humans, Immunohistochemistry, Intestinal Neoplasms, Intestine, Small, Ki-67 Antigen, Male, Middle Aged, Neoplasm Grading, Neuroendocrine Tumors, Proportional Hazards Models
Show Abstract · Added November 1, 2018
AIMS - Well-differentiated small intestinal neuroendocrine tumours (SI-NETs) are often multifocal, and this has been suggested to impart worse disease-free survival. Practice guidelines have not been established for World Health Organisation (WHO) grading of multiple primary lesions.
METHODS AND RESULTS - We identified 68 patients with ileal/jejunal SI-NET for a combined total of 207 primary lesions. Each case was evaluated for patient age and sex; size of all tumours; presence of lymph node metastases, mesenteric tumour deposits or distant metastases; and disease-specific outcome. Ki67 staining was performed on all 207 primary lesions. The relationship between multifocality and clinicopathological factors was compared using Fisher's exact test. Outcome was tested using Cox proportional hazard regression. Forty-two patients had unifocal disease, and 26 had multifocal disease (median five lesions, range = 2-32). Most tumours were WHO grade 1 (201 of 207, 97%). Of the five patients with grades 2/3 tumours, three patients had unifocal disease, one patient had two subcentimetre grade 2 lesions (including the largest) and eight subcentimetre grade 1 lesions, and one patient had one 1.6-cm grade 3 lesion and one subcentimetre grade 1 lesion. There was a positive correlation between tumour size and Ki67 index (coefficient 0.28; 95% confidence interval 0.05-0.52, P = 0.017). There was no significant association between multifocality and nodal metastases, mesenteric tumour deposits, distant metastases or disease-specific survival.
CONCLUSIONS - In patients with multifocal SI-NET, unless a particular lesion has a high mitotic rate, only staining the largest lesion for Ki67 should serve to grade almost all cases accurately. Multifocality does not appear to significantly impact patient survival.
© 2018 John Wiley & Sons Ltd.
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16 MeSH Terms
Emerin Deregulation Links Nuclear Shape Instability to Metastatic Potential.
Reis-Sobreiro M, Chen JF, Novitskaya T, You S, Morley S, Steadman K, Gill NK, Eskaros A, Rotinen M, Chu CY, Chung LWK, Tanaka H, Yang W, Knudsen BS, Tseng HR, Rowat AC, Posadas EM, Zijlstra A, Di Vizio D, Freeman MR
(2018) Cancer Res 78: 6086-6097
MeSH Terms: Animals, Apoptosis, Biomarkers, Tumor, Cell Line, Tumor, Cell Movement, Cell Nucleus, Disease Progression, Gene Expression Regulation, Neoplastic, Humans, Male, Membrane Proteins, Mice, Mice, SCID, Neoplasm Invasiveness, Neoplasm Metastasis, Neoplastic Cells, Circulating, Nuclear Envelope, Nuclear Proteins, Prostatic Neoplasms
Show Abstract · Added April 10, 2019
Abnormalities in nuclear shape are a well-known feature of cancer, but their contribution to malignant progression remains poorly understood. Here, we show that depletion of the cytoskeletal regulator, Diaphanous-related formin 3 (DIAPH3), or the nuclear membrane-associated proteins, lamin A/C, in prostate and breast cancer cells, induces nuclear shape instability, with a corresponding gain in malignant properties, including secretion of extracellular vesicles that contain genomic material. This transformation is characterized by a reduction and/or mislocalization of the inner nuclear membrane protein, emerin. Consistent with this, depletion of emerin evokes nuclear shape instability and promotes metastasis. By visualizing emerin localization, evidence for nuclear shape instability was observed in cultured tumor cells, in experimental models of prostate cancer, in human prostate cancer tissues, and in circulating tumor cells from patients with metastatic disease. Quantitation of emerin mislocalization discriminated cancer from benign tissue and correlated with disease progression in a prostate cancer cohort. Taken together, these results identify emerin as a mediator of nuclear shape stability in cancer and show that destabilization of emerin can promote metastasis. This study identifies a novel mechanism integrating the control of nuclear structure with the metastatic phenotype, and our inclusion of two types of human specimens (cancer tissues and circulating tumor cells) demonstrates direct relevance to human cancer. http://cancerres.aacrjournals.org/content/canres/78/21/6086/F1.large.jpg .
©2018 American Association for Cancer Research.
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19 MeSH Terms
Somatostatin receptor 2 signaling promotes growth and tumor survival in small-cell lung cancer.
Lehman JM, Hoeksema MD, Staub J, Qian J, Harris B, Callison JC, Miao J, Shi C, Eisenberg R, Chen H, Chen SC, Massion PP
(2019) Int J Cancer 144: 1104-1114
MeSH Terms: AMP-Activated Protein Kinases, Animals, Apoptosis, Basic Helix-Loop-Helix Transcription Factors, Biomarkers, Tumor, Cell Line, Tumor, Cell Proliferation, Disease Progression, Down-Regulation, Humans, Lung Neoplasms, Mice, Mice, Nude, Nerve Tissue Proteins, RNA, Messenger, Receptors, Somatostatin, Signal Transduction, Small Cell Lung Carcinoma
Show Abstract · Added March 31, 2020
Somatostatin receptor 2 (SSTR2) is overexpressed in a majority of neuroendocrine neoplasms, including small-cell lung carcinomas (SCLCs). SSTR2 was previously considered an inhibitory receptor on cell growth, but its agonists had poor clinical responses in multiple clinical trials. The role of this receptor as a potential therapeutic target in lung cancer merits further investigation. We evaluated the expression of SSTR2 in a cohort of 96 primary tumors from patients with SCLC and found 48% expressed SSTR2. Correlation analysis in both CCLE and an SCLC RNAseq cohort confirmed high-level expression and identified an association between NEUROD1 and SSTR2. There was a significant association with SSTR2 expression profile and poor clinical outcome. We tested whether SSTR2 expression might contribute to tumor progression through activation of downstream signaling pathways, using in vitro and in vivo systems and downregulated SSTR2 expression in lung cancer cells by shRNA. SSTR2 downregulation led to increased apoptosis and dramatically decreased tumor growth in vitro and in vivo in multiple cell lines with decreased AMPKα phosphorylation and increased oxidative metabolism. These results demonstrate a role for SSTR2 signaling in SCLC and suggest that SSTR2 is a poor prognostic biomarker in SCLC and potential future therapeutic signaling target.
© 2018 UICC.
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Biomarkers for early identification of recurrences in HPV-driven oropharyngeal cancer.
Mirghani H, Lang Kuhs KA, Waterboer T
(2018) Oral Oncol 82: 108-114
MeSH Terms: Alphapapillomavirus, Antibodies, Viral, Biomarkers, Tumor, DNA, Viral, Humans, Neoplasm Recurrence, Local, Oropharyngeal Neoplasms, Papillomavirus Infections, Saliva
Show Abstract · Added March 20, 2020
One of the major concerns in oncology lies in the ability to detect recurrences at their earliest stage to increase the likelihood of cure following second line, or salvage, therapy. Although human papillomavirus (HPV)-driven oropharyngeal cancers have a good prognosis, 20-25% of patients will recur within 5 years of treatment and a significant portion will die from their disease. In recent years, great effort has been put toward evaluating the potential clinical utility of HPV-related biomarkers for early diagnosis of recurrent disease. Indeed, following completion of treatment, detection of HPV-DNA in oral rinses or blood and serologic assays against HPV oncoproteins could be helpful to track residual disease or recurrence. Several recent studies have reported promising findings, thus potentially paving the way for the use of biomarkers in the management of HPV-OPC. In this review, we evaluate and discuss the current knowledge on this topic and provide some directions for future research.
Copyright © 2018 Elsevier Ltd. All rights reserved.
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Integrative radiomics expression predicts molecular subtypes of primary clear cell renal cell carcinoma.
Yin Q, Hung SC, Rathmell WK, Shen L, Wang L, Lin W, Fielding JR, Khandani AH, Woods ME, Milowsky MI, Brooks SA, Wallen EM, Shen D
(2018) Clin Radiol 73: 782-791
MeSH Terms: Biomarkers, Tumor, Carcinoma, Renal Cell, Contrast Media, Humans, Imaging, Three-Dimensional, Kidney Neoplasms, Magnetic Resonance Imaging, Multimodal Imaging, Neoplasm Grading, Neoplasm Staging, Positron-Emission Tomography, Retrospective Studies
Show Abstract · Added October 30, 2019
AIM - To identify combined positron-emission tomography (PET)/magnetic resonance imaging (MRI)-based radiomics as a surrogate biomarker of intratumour disease risk for molecular subtype ccA and ccB in patients with primary clear cell renal cell carcinoma (ccRCC).
MATERIALS AND METHODS - PET/MRI data were analysed retrospectively from eight patients. One hundred and sixty-eight radiomics features for each tumour sampling based on the regionally sampled tumours with 23 specimens were extracted. Sparse partial least squares discriminant analysis (SPLS-DA) was applied to feature screening on high-throughput radiomics features and project the selected features to low-dimensional intrinsic latent components as radiomics signatures. In addition, multilevel omics datasets were leveraged to explore the complementing information and elevate the discriminative ability.
RESULTS - The correct classification rate (CCR) for molecular subtype classification by SPLS-DA using only radiomics features was 86.96% with permutation test p=7×10. When multi-omics datasets including mRNA, microvascular density, and clinical parameters from each specimen were combined with radiomics features to refine the model of SPLS-DA, the best CCR was 95.65% with permutation test, p<10; however, even in the case of generating the classification based on transcription features, which is the reference standard, there is roughly 10% classification ambiguity. Thus, this classification level (86.96-95.65%) of the proposed method represents the discriminating level that is consistent with reality.
CONCLUSION - Featured with high accuracy, an integrated multi-omics model of PET/MRI-based radiomics could be the first non-invasive investigation for disease risk stratification and guidance of treatment in patients with primary ccRCC.
Published by Elsevier Ltd.
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Gene expression in triple-negative breast cancer in relation to survival.
Wang S, Beeghly-Fadiel A, Cai Q, Cai H, Guo X, Shi L, Wu J, Ye F, Qiu Q, Zheng Y, Zheng W, Bao PP, Shu XO
(2018) Breast Cancer Res Treat 171: 199-207
MeSH Terms: Adult, Aged, Biomarkers, Tumor, Female, Gene Expression, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Humans, Middle Aged, Neoplasm Grading, Neoplasm Staging, Population Surveillance, Prognosis, Registries, Survival Analysis, Triple Negative Breast Neoplasms
Show Abstract · Added December 6, 2018
PURPOSE - The identification of biomarkers related to the prognosis of triple-negative breast cancer (TNBC) is critically important for improved understanding of the biology that drives TNBC progression.
METHODS - We evaluated gene expression in total RNA isolated from formalin-fixed paraffin-embedded tumor samples using the NanoString nCounter assay for 469 TNBC cases from the Shanghai Breast Cancer Survival Study. We used Cox regression to quantify Hazard Ratios (HR) and corresponding confidence intervals (CI) for overall survival (OS) and disease-free survival (DFS) in models that included adjustment for breast cancer intrinsic subtype. Of 302 genes in our discovery analysis, 22 were further evaluated in relation to OS among 134 TNBC cases from the Nashville Breast Health Study and the Southern Community Cohort Study; 16 genes were further evaluated in relation to DFS in 335 TNBC cases from four gene expression omnibus datasets. Fixed-effect meta-analysis was used to combine results across data sources.
RESULTS - Twofold higher expression of EOMES (HR 0.90, 95% CI 0.83-0.97), RASGRP1 (HR 0.89, 95% CI 0.82-0.97), and SOD2 (HR 0.80, 95% CI 0.66-0.96) was associated with better OS. Twofold higher expression of EOMES (HR 0.89, 95% CI 0.81-0.97) and RASGRP1 (HR 0.87, 95% CI 0.81-0.95) was also associated with better DFS. On the contrary, a doubling of FA2H (HR 1.14, 95% CI 1.06-1.22) and GSPT1 (HR 1.33, 95% CI 1.14-1.55) expression was associated with shorter DFS.
CONCLUSIONS - We identified five genes (EOMES, FA2H, GSPT1, RASGRP1, and SOD2) that may serve as potential prognostic biomarkers and/or therapeutic targets for TNBC.
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16 MeSH Terms