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Results 1 through 20 out of 2038

in category cancer biology

 

1: Report of Partial findings from the National Toxicology Program Carcinogenesis Studies of Cell Phone Radiofrequency Radiation in Hsd: Sprague Dawley® SD rats (Whole Body Exposure)

Michael Wyde, Mark Cesta et al.

237,282 downloads (posted 26 May 2016)

The U.S. National Toxicology Program (NTP) has carried out extensive rodent toxicology and carcinogenesis studies of radiofrequency radiation (RFR) at frequencies and modulations used in the U.S. telecommunications industry. This report presents partial findings from these studies. The occurrences of two tumor types in male Harlan Sprague Dawley rats exposed to RFR, malignant gliomas in the brain and schwannomas of the heart, were considered of particular interest and are the subject of this report. The findings in this report were reviewed by expert peer reviewers selected by the NTP and National Institutes of Health (NIH). These reviews and responses to comments are included as appendices to this report, and revisions to the current document have incorporated and addressed these comments. When the studies are completed, they will undergo additional peer review before publication in full as part of the NTP's Toxicology and Carcinogenesis Technical Reports Series. No portion of this work has been submitted for publication in a scientific journal. Supplemental information in the form of four additional manuscripts has or will soon be submitted for publication. These manuscripts describe in detail the designs and performance of the RFR exposure system, the dosimetry of RFR exposures in rats and mice, the results to a series of pilot studies establishing the ability of the animals to thermoregulate during RFR exposures, and studies of DNA damage. (1) Capstick M, Kuster N, Kuhn S, Berdinas-Torres V, Wilson P, Ladbury J, Koepke G, McCormick D, Gauger J, and Melnick R. A radio frequency radiation reverberation chamber exposure system for rodents; (2) Yijian G, Capstick M, McCormick D, Gauger J, Horn T, Wilson P, Melnick RL, and Kuster N. Life time dosimetric assessment for mice and rats exposed to cell phone radiation; (3) Wyde ME, Horn TL, Capstick M, Ladbury J, Koepke G, Wilson P, Stout MD, Kuster N, Melnick R, Bucher JR, and McCormick D. Pilot studies of the National Toxicology Program's cell phone radiofrequency radiation reverberation chamber exposure system; (4) Smith-Roe SL, Wyde ME, Stout MD, Winters J, Hobbs CA, Shepard KG, Green A, Kissling GE, Tice RR, Bucher JR, and Witt KL. Evaluation of the genotoxicity of cell phone radiofrequency radiation in male and female rats and mice following subchronic exposure.

https://rxivist.org/papers/21370
https://doi.org/10.1101/055699

2: The Repertoire of Mutational Signatures in Human Cancer

Ludmil Alexandrov, Jaegil Kim et al.

12,282 downloads (posted 15 May 2018)

Somatic mutations in cancer genomes are caused by multiple mutational processes each of which generates a characteristic mutational signature. Using 84,729,690 somatic mutations from 4,645 whole cancer genome and 19,184 exome sequences encompassing most cancer types we characterised 49 single base substitution, 11 doublet base substitution, four clustered base substitution, and 17 small insertion and deletion mutational signatures. The substantial dataset size compared to previous analyses enabled discovery of new signa...

https://rxivist.org/papers/21200
https://doi.org/10.1101/322859

3: Integrating single-cell RNA-Seq with spatial transcriptomics in pancreatic ductal adenocarcinoma using multimodal intersection analysis

Reuben Moncada, Florian Wagner et al.

10,057 downloads (posted 26 Jan 2018)

To understand the architecture of a tissue it is necessary to know both the cell populations and their physical relationships to one another. Single-cell RNA-Seq (scRNA-Seq) has made significant progress towards the unbiased and systematic characterization of the cell populations within a tissue, as well as their cellular states, by studying hundreds and thousands of cells in a single experiment. However, the characterization of the spatial organization of individual cells within a tissue has been more elusive. The rece...

https://rxivist.org/papers/21328
https://doi.org/10.1101/254375

4: Why cancer cells have a more hyperpolarised mitochondrial membrane potential and emergent prospects for therapy

Michael D Forrest

8,522 downloads (posted 21 Aug 2015)

Cancer cells have a more hyperpolarised mitochondrial membrane potential (Ψ) than normal cells. Ψ = ~-220 mV in cancer cells as compared to ~-140 mV in normal cells. Until now it has not been known why. This paper explains this disparity, in a mathematical framework, and identifies molecular targets and operations unique to cancer cells. These are thence prospective cancer drug targets. BMS-199264 is proposed as an anti-cancer drug. It inhibits the reverse, proton-pumping mode of ATP synthase, which this paper identifie...

https://rxivist.org/papers/21855
https://doi.org/10.1101/025197

5: The evolutionary history of 2,658 cancers

Moritz Gerstung, Clemency Jolly et al.

7,378 downloads (posted 11 Jul 2017)

Cancer develops through a process of somatic evolution. Here, we reconstruct the evolutionary history of 2,778 tumour samples from 2,658 donors spanning 39 cancer types. Characteristic copy number gains, such as trisomy 7 in glioblastoma or isochromosome 17q in medulloblastoma, are found amongst the earliest events in tumour evolution. The early phases of oncogenesis are driven by point mutations in a restricted set of cancer genes, often including biallelic inactivation of tumour suppressors. By contrast, increased gen...

https://rxivist.org/papers/21581
https://doi.org/10.1101/161562

6: Classification and Mutation Prediction from Non-Small Cell Lung Cancer Histopathology Images using Deep Learning

Nicolas Coudray, Andre L Moreira et al.

6,841 downloads (posted 03 Oct 2017)

Visual analysis of histopathology slides of lung cell tissues is one of the main methods used by pathologists to assess the stage, types and sub-types of lung cancers. Adenocarcinoma and squamous cell carcinoma are two most prevalent sub-types of lung cancer, but their distinction can be challenging and time-consuming even for the expert eye. In this study, we trained a deep learning convolutional neural network (CNN) model (inception v3) on histopathology images obtained from The Cancer Genome Atlas (TCGA) to accuratel...

https://rxivist.org/papers/21531
https://doi.org/10.1101/197574

7: Pan-cancer analysis of whole genomes

Peter J. Campbell, Gaddy Getz et al.

5,956 downloads (posted 12 Jul 2017)

We report the integrative analysis of more than 2,600 whole cancer genomes and their matching normal tissues across 39 distinct tumour types. By studying whole genomes we have been able to catalogue non-coding cancer driver events, study patterns of structural variation, infer tumour evolution, probe the interactions among variants in the germline genome, the tumour genome and the transcriptome, and derive an understanding of how coding and non-coding variations together contribute to driving individual patient's tumour...

https://rxivist.org/papers/21626
https://doi.org/10.1101/162784

8: Endogenous insulin contributes to pancreatic cancer development

Anni MY Zhang, Jamie Magrill et al.

5,869 downloads (posted 24 Jan 2019)

Obesity and early-stage type 2 diabetes (T2D) increase the risk for many cancers, including pancreatic ductal adenocarcinoma (PDAC). The mechanisms linking obesity and T2D to cancer have not been established, preventing targeted interventions. Arguments have been made that hyperinsulinemia, hyperglycemia, or inflammation could drive cancer initiation and/or progression. Hyperinsulinemia is a cardinal feature of obesity and T2D, and is independently associated with PDAC incidence and mortality, even in non-obese people. ...

https://rxivist.org/papers/42378
https://doi.org/10.1101/530097

9: Gene expression profiling reveals U1 snRNA regulates cancer gene expression

Zhi Cheng, Yu Sun et al.

5,480 downloads (posted 12 Jan 2017)

U1 small nuclear RNA (U1 snRNA), as one of the most abundant noncoding RNA in eukaryotic cells plays an important role in splicing of pre-mRNAs. Compared to other studies which have focused on the primary function of U1 snRNA and the neurodegenerative diseases caused by the abnormalities of U1 snRNA, this study is to investigate how the U1 snRNA over-expression affects the expression of genes on a genome-wide scale. In this study, we built a model of U1 snRNA over-expression in a rat cell line. By comparing the gene exp...

https://rxivist.org/papers/21731
https://doi.org/10.1101/099929

10: Comparing cancer cell lines and tumor samples by genomic profiles

Rileen Sinha, Nikolaus Schultz et al.

5,436 downloads (posted 02 Oct 2015)

Cancer cell lines are often used in laboratory experiments as models of tumors, although they can have substantially different genetic and epigenetic profiles compared to tumors. We have developed a general computational method, TumorComparer, to systematically quantify similarities and differences between tumor material when detailed genetic and molecular profiles are available. The comparisons can be flexibly tailored to a particular biological question by placing a higher weight on functional alterations of interest ...

https://rxivist.org/papers/21848
https://doi.org/10.1101/028159

11: The whole-genome panorama of cancer drivers

Radhakrishnan Sabarinathan, Oriol Pich et al.

5,188 downloads (posted 20 Sep 2017)

The advance of personalized cancer medicine requires the accurate identification of the mutations driving each patient's tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patient's tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, ...

https://rxivist.org/papers/21423
https://doi.org/10.1101/190330

12: Challenges in Using ctDNA to Achieve Early Detection of Cancer

Imran S. Haque, Olivier Elemento

4,845 downloads (posted 21 Dec 2017)

Early detection of cancer is a significant unmet clinical need. Improved technical ability to detect circulating tumor-derived DNA (ctDNA) in the cell-free DNA (cfDNA) component of blood plasma via next-generation sequencing and established correlations between ctDNA load and tumor burden in cancer patients have spurred excitement about the possibilities of detecting cancer early by performing ctDNA mutation detection. We reanalyze published data on the expected ctDNA allele fraction in early-stage cancer and the popula...

https://rxivist.org/papers/21428
https://doi.org/10.1101/237578

13: NADH as a cancer medicine

Michael D Forrest

4,843 downloads (posted 13 May 2015)

We propose that NADH will exert a specific kill action against some cancers. NADH is a natural metabolite. We envisage a low side effect profile and that NADH therapy will, additionally, combat the wastage and weakness of cancer patients, which can be the cause of death in some cases. Significantly, NADH can be administered orally and has already cleared clinical trials, all be it for other pathologies.

https://rxivist.org/papers/21864
https://doi.org/10.1101/019307

14: A simple high-throughput approach identifies actionable drug responses in patient-derived tumor organoids

Nhan Phan, Jenny J Hong et al.

4,594 downloads (posted 28 Jun 2017)

There is increasing interest in developing 3D tumor organoid models for drug development and personalized medicine applications. While tumor organoids are in principle amenable to high-throughput drug screenings, progress has been hampered by technical constraints and extensive manipulations required by current methodologies. Here, we introduce a miniaturized, fully automatable, flexible high-throughput method using a simplified geometry to rapidly establish 3D organoids from cell lines and primary tissue and robustly a...

https://rxivist.org/papers/20979
https://doi.org/10.1101/138412

15: Patterns of structural variation in human cancer

Yilong Li, Nicola D. Roberts et al.

4,417 downloads (posted 27 Aug 2017)

A key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments ranging in size from kilobases to whole chromosomes. We developed methods to group, classify and describe structural variants, applied to >2,500 cancer genomes. Nine signatures of structural variation emerged. Deletions have trimodal size distribution; assort unevenly across tumour types and patients; enrich in late-replicating regions; and correlate with inversions. Tandem duplications also ha...

https://rxivist.org/papers/21583
https://doi.org/10.1101/181339

16: The landscape of T cell infiltration in human cancer and its association with antigen presenting gene expression

Yasin Şenbabaoğlu

4,273 downloads (posted 01 Sep 2015)

Infiltrating T cells in the tumor microenvironment have crucial roles in the competing processes of pro-tumor and anti-tumor immune response. However, the infiltration level of distinct T cell subsets and the signals that draw them into a tumor, such as the expression of antigen presenting machinery (APM) genes, remain poorly characterized across human cancers. Here, we define a novel mRNA-based T cell infiltration score (TIS) and profile infiltration levels in 19 tumor types. We find that clear cell renal cell carcinom...

https://rxivist.org/papers/21852
https://doi.org/10.1101/025908

17: Pan-cancer whole genome analyses of metastatic solid tumors

Peter Priestley, Jonathan Baber et al.

4,257 downloads (posted 20 Sep 2018)

Metastatic cancer is one of the major causes of death and is associated with poor treatment efficiency. A better understanding of the characteristics of late stage cancer is required to help tailor personalised treatment, reduce overtreatment and improve outcomes. Here we describe the largest pan-cancer study of metastatic solid tumor genomes, including 2,520 whole genome-sequenced tumor-normal pairs, analyzed at a median depth of 106x and 38x respectively, and surveying over 70 million somatic variants. Metastatic lesi...

https://rxivist.org/papers/33015
https://doi.org/10.1101/415133

18: Deep learning reveals cancer metastasis and therapeutic antibody targeting in whole body

Chenchen Pan, Oliver Schoppe et al.

4,233 downloads (posted 05 Feb 2019)

Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long been needed to better understand and treat cancer metastasis. Here, we developed an integrated pipeline for automated quantification of cancer metastases and therapeutic antibody targeting, named DeepMACT. First, we enhanced the fluorescent signal of tumor cells more than 100-fold by applying the vDISCO method to image single cancer cells in intact transparent mice. Second, ...

https://rxivist.org/papers/43260
https://doi.org/10.1101/541862

19: Using Ordinary Differential Equations to Explore Cancer-Immune Dynamics and Tumor Dormancy

Kathleen P. Wilkie, Philip Hahnfeldt et al.

3,961 downloads (posted 22 Apr 2016)

Cancer is not solely a disease of the genome, but is a systemic disease that affects the host on many functional levels, including, and perhaps most notably, the function of the immune response, resulting in both tumor-promoting inflammation and tumor-inhibiting cytotoxic action. The dichotomous actions of the immune response induce significant variations in tumor growth dynamics that mathematical modeling can help to understand. Here we present a general method using ordinary differential equations (ODEs) to model and ...

https://rxivist.org/papers/21807
https://doi.org/10.1101/049874

20: Tumor evolution of glioma intrinsic gene expression subtype associates with immunological changes in the microenvironment

Qianghu Wang, Xin Hu et al.

3,923 downloads (posted 08 May 2016)

We leveraged IDH wild type glioblastomas and derivative neurospheres to define tumor-intrinsic transcription phenotypes. Transcriptomic multiplicity correlated with increased intratumoral heterogeneity and tumor microenvironment presence. In silico cell sorting demonstrated that M2 macrophages/microglia are the most frequent type of immune cells in the glioma microenvironment, followed by CD4 T lymphocytes and neutrophils. Hypermutation associated with CD8+ T cell enrichment. Longitudinal transcriptome analysis of 124 p...

https://rxivist.org/papers/21777
https://doi.org/10.1101/052076