Top 8 Biorxiv Papers Today in Cancer Biology


2.02 Mikeys
#1. Targeting Cellular DNA Damage Responses: Predicting in vivo treatment responses using an in vitro-calibrated agent-based mathematical model.
Sara Jasmin Hamis, James Yates, Mark AJ Chaplain, Gibin G Powathil
The ATR (ataxia telangiectasia mutated and rad3-related kinase) inhibitor AZD6738 is an anti-cancer drug that potentially hinders tumour proliferation by targeting cellular DNA damage responses. In this study, we combine a systems pharmacology approach with an agent-based modelling approach to simulate AZD6738 treatment responses in silico. The mathematical model is governed by a set of empirically observable rules. By adjusting only the rules, whilst keeping the fundamental mathematical framework and model parameters intact, the mathematical model can first be calibrated by in vitro data and thereafter be used to successfully predict treatment responses in human tumour xenografts in vivo qualitatively, and quantitatively up to approximately 10 days post tumour injection.
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biorxivpreprint: Targeting Cellular DNA Damage Responses: Predicting in vivo treatment responses using an in vitro-calibrated agent-based mathematical model. https://t.co/itlQBrlu85 #bioRxiv
biorxiv_cancer: Targeting Cellular DNA Damage Responses: Predicting in vivo treatment responses using an in vitro-calibrated agent-based mathematical ... https://t.co/y5DcS9XD8B #biorxiv_cancer
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Authors: 4
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2.004 Mikeys
#2. Loss of macpΨ ribosomal RNA modification is a major feature of cancer
Artem Babaian, Katharina Rothe, Dylan Girodat, Igor Minia, Sara Djondovic, Miha Milek, Hans-Joachim Wieden, Markus Landthaler, Gregg B. Morin, Dixie L. Mager
The ribosome is an RNA-protein complex essential for translation in all domains of life. The structural and catalytic core of the ribosome is its ribosomal RNA (rRNA). While mutations in ribosomal protein (RP) gene are known drivers of oncogenesis, oncogenic rRNA variants have remained elusive. We discovered a cancer-specific single nucleotide variation at 18S.1248U in the 18S rRNA of up to 45.9% colorectal carcinoma (CRC) patients and across >22 cancer types. This is the site of a unique hyper-modified base, 1-methyl-3-α-amino-α-carboxyl-propyl pseudouridine (macpΨ), a modification that is >1 billion years conserved at the ribosome's peptidyl decoding-site. A sub-set of CRC tumors we term 'hypo-macpΨ', show sub-stoichiometric macpΨ-modification unlike normal control tissues. Our macpΨ knockout model and hypo-macpΨ patient tumors share a translational signature, characterized by highly abundant ribosomal proteins. Thus, macpΨ-deficient rRNA forms an uncharacterized class of 'onco-ribosome' which may serve as an innovative...
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An open science investigation of human ribosomal DNA variation

Repository: Crown
User: ababaian
Language: Jupyter Notebook
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Authors: 10
Total Words: 9637
Unqiue Words: 3277

2.0 Mikeys
#3. Predicting master transcription factors from pan-cancer expression data
Jessica Reddy, Marcos A. S. Fonseca, Rosario I Corona, Robbin Nameki, Felipe Segato Dezem, Isaac A. Klein, Heidi Chang, Daniele Chaves-Moreira, Lena Afeyan, Tathiane M Malta, Xianzhi Lin, Forough Abbasi, Alba Font-Tello, Thais Sabedot, Paloma Cejas, Norma Rodríguez-Malavé, Ji-Heui Seo, De-Chen Lin, Ursula Matulonis, Beth Y Karlan, Simon A Gayther, Alexander Gusev, Houtan Noushmehr, Henry Long, Matthew L. Freedman, Ronny Drapkin, Brian J Abraham, Richard A. Young, Kate Lawrenson
The function of critical developmental regulators can be subverted by cancer cells to control expression of oncogenic transcriptional programs. These "master transcription factors" (MTFs) are often essential for cancer cell survival and represent vulnerabilities that can be exploited therapeutically. The current approaches to identify candidate MTFs examine super-enhancer associated transcription factor-encoding genes with high connectivity in network models. This relies on chromatin immunoprecipitation-sequencing (ChIP-seq) data, which is technically challenging to obtain from primary tumors, and is currently unavailable for many cancer types and clinically relevant subtypes. In contrast, gene expression data are more widely available, especially for rare tumors and subtypes where MTFs have yet to be discovered. We have developed a predictive algorithm called CaCTS (Cancer Core Transcription factor Specificity) to identify candidate MTFs using pan-cancer RNA-sequencing data from The Cancer Genome Atlas. The algorithm identified...
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PromPreprint: Predicting master transcription factors from pan-cancer expression data https://t.co/ZlhQRVZ4SH
jklee_lab: RT @biorxivpreprint: Predicting master transcription factors from pan-cancer expression data https://t.co/gKSSxHeXeU #bioRxiv
DelgiornoKathy: RT @biorxivpreprint: Predicting master transcription factors from pan-cancer expression data https://t.co/gKSSxHeXeU #bioRxiv
Karl_SmithByrne: RT @biorxivpreprint: Predicting master transcription factors from pan-cancer expression data https://t.co/gKSSxHeXeU #bioRxiv
TimSomerville8: RT @biorxiv_cancer: Predicting master transcription factors from pan-cancer expression data https://t.co/1lv2gDXn1O #biorxiv_cancer
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1.997 Mikeys
#4. HIP IMO Report: Analyzing Phenotypic Properties of Bladder Cancer Using Ordinary Differential Equation (ODE) Models
Benjamin C Sherwin
Bladder cancer is composed of proliferative and immunogenic phenotypes, which ultimately play a significant role in the growth of the tumor. By using ordinary differential equation models, this paper models the impact of high and low immunogenic cell populations on non-muscle invasive bladder cancer when treated with and without the Bacillus Calmette-Guerin vaccine. Furthermore, this paper models the impact that the Bacillus Calmette-Guerin vaccine has on inflammatory cytokines, which inhibit the growth of tumors by stimulating an immune response. We focus primarily on how the immunogenicity phenotype impacts population dynamics in non-muscle invasive bladder cancer.
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biorxivpreprint: HIP IMO Report: Analyzing Phenotypic Properties of Bladder Cancer Using Ordinary Differential Equation (ODE) Models https://t.co/RzTFeTmPrB #bioRxiv
biorxiv_cancer: HIP IMO Report: Analyzing Phenotypic Properties of Bladder Cancer Using Ordinary Differential Equation (ODE) Models https://t.co/dO5jrtt9MC #biorxiv_cancer
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Authors: 1
Total Words: 3301
Unqiue Words: 1065

1.997 Mikeys
#5. Characterization of GRK5 as a novel regulator of rhabdomyosarcoma tumor cell growth and self-renewal
Thao Pham, Kristin Robinson, Terra Vleeshouwer-Neumann, James Annis, Eleanor Chen
Rhabdomyosarcoma (RMS) is the most common soft-tissue pediatric sarcoma. Treatment options remain limited, presenting an urgent need for novel therapeutic targets. Using a high-throughput siRNA screen against the human kinome, we identified GRK5, a G-protein receptor kinase, as a novel regulator of RMS tumor cell growth and self-renewal. Through functional assays in vitro and in vivo, we show that GRK5 regulates cell cycling in a kinase-independent manner to promote RMS tumor cell growth. GRK5 interacts with NFAT to facilitate autoregulation of NFAT1 expression in a kinase independent manner, and loss of NFAT1 phenocopies GRK5 loss-of-function effects on cell cycle arrest. Self-renewal of RMS, required for recapitulation of tumor heterogeneity, is significantly reduced with loss of GRK5 due to increased cell death. Treatment of human RMS xenografts in mice with CCG-215022, a GRK5-selective inhibitor, reduces tumor growth of RMS. GRK5 represents a novel therapeutic target for the treatment of RMS.
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biorxivpreprint: Characterization of GRK5 as a novel regulator of rhabdomyosarcoma tumor cell growth and self-renewal https://t.co/YhpbC7U6XB #bioRxiv
biorxiv_cancer: Characterization of GRK5 as a novel regulator of rhabdomyosarcoma tumor cell growth and self-renewal https://t.co/T1dbmG3Te1 #biorxiv_cancer
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Authors: 5
Total Words: 7573
Unqiue Words: 2102

1.993 Mikeys
#6. Deep Discriminative Fine-Tuning for Cancer Type Classification
Alena Harley
Determining the primary site of origin for metastatic tumors is one of the open problems in cancer care because the efficacy of treatment often depends on the cancer tissue of origin. Classification methods that can leverage tumor genomic data and predict the site of origin are therefore of great value. Because tumor DNA point mutation data is very sparse, only limited accuracy (64.5% for 12 tumor classes) was previously demonstrated by methods that rely on point mutations as features (1). Tumor classification accuracy can be greatly improved (to over 90% for 33 classes) by relying on gene expression data (2). However, this additional data is often not readily available in clinical setting, because point mutations are better profiled and targeted by clinical mutational profiling. Here we sought to develop an accurate deep transfer learning and fine-tuning method for tumor sub-type classification, where predicted class is indicative of the primary site of origin. Our method significantly outperforms the state-of-the-art for tumor...
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1.993 Mikeys
#7. Recurrent Neoantigens in Colorectal Cancer as Potential Immunotherapy Targets
Chao Chen, Songming Liu, Bo Li
This study was aimed to investigate the mutations in colorectal cancer (CRC) for recurrent neoantigen identification. A total of 1,779 samples with whole exome sequencing (WES) data were obtained from 7 published CRC cohorts. Common HLA genotypes were used to predict the probability of neoantigens at high frequency mutants in the dataset. Based on the WES data, we not only obtained the most comprehensive CRC mutation landscape so far, but also found 1550 mutation sites which could be identified in at least 5 or more patients, including KRAS G12D (8%), KRAS G12V (5.8%), PIK3CA E545K (3.5%), PIK3CA H1047R (2.5%) and BMPR2 N583Tfs*44 (2.8%). These mutations can also be recognized by multiple common HLA molecules as potential 'public' neoantigens. Many of these mutations also have high mutation rates in metastatic pan-cancers, suggesting their value as therapeutic targets in different cancer types. Overall, our analysis provides recurrent neoantigens as potential cancer immunotherapy targets.
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1.946 Mikeys
#8. Kinobead profiling reveals reprogramming of B-cell receptor signaling in response to therapy within primary CLL cells.
Adam J Linley, Rebecca Griffin, Silvia Cicconi, Annalisa D'Avola, David J MacEwan, Andrew R Pettitt, Nagesh Kalakonda, Graham Packham, Ian Prior, Joseph Slupsky
Induction of signaling via cell surface receptor activation is a critical driver of CLL pathobiology, especially via the B-cell receptor (BCR), which promotes tumor survival and progression. The vital nature of BCR signaling has been recognized through the development of kinase inhibitors (KI), most notably ibrutinib, that target key nodes within this pathway. Current efforts to monitor signaling investigate expression of a highly confined series of kinases and phosphoproteins. While generating key insights, full appreciation of their wider significance to malignant pathology and therapy response remains an unresolved issue. Here, we describe a kinobead-based protocol, used in conjunction with mass-spectrometry (MS) or immunoblotting, to study surface-IgM (sIgM) signaling within primary CLL cells. Employing this approach, we isolated a fingerprint of over 30 kinases which displayed unique, patient-specific response to sIgM stimulation, and which displayed greater activation change in CLL cells from patients who had undergone prior...
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