Article
Cell Biology
Chunli Wei, Yun Liu, Xiaoyan Liu, Jingliang Cheng, Jiewen Fu, Xiuli Xiao, Robb E. Moses, Xiaotao Li, Junjiang Fu
Summary: This study reveals a new mechanism by which SPOP regulates TWIST1 degradation in breast cancer, suppressing cancer cell migration and invasion. The expression levels of SPOP and TWIST1 are closely associated with the prognosis of breast cancer patients, particularly those with metastatic triple-negative breast cancer.
CELL DEATH DISCOVERY
(2022)
Article
Oncology
Kejia Hu, Chengshi Wang, Chuanxu Luo, Hong Zheng, Huan Song, Jacob Bergstedt, Katja Fall, Ting Luo, Kamila Czene, Unnur A. Valdimarsdottir, Fang Fang, Donghao Lu
Summary: This study found that somatic mutations in genes of neuroendocrine pathways, particularly in the glucocorticoid pathway, may influence breast cancer prognosis through dysregulated gene expression in tumor tissue.
Article
Cell & Tissue Engineering
Mariela Cortes-Lopez, Paulina Chamely, Allegra G. Hawkins, Robert F. Stanley, Ariel D. Swett, Saravanan Ganesan, Tarek H. Mouhieddine, Xiaoguang Dai, Lloyd Kluegel, Celine Chen, Kiran Batta, Nili Furer, Rahul S. Vedula, John Beaulaurier, Alexander W. Drong, Scott Hickey, Neville Dusaj, Gavriel Mullokandov, Adam M. Stasiw, Jiayu Su, Ronan Chaligne, Sissel Juul, Eoghan Harrington, David A. Knowles, Catherine J. Potenski, Daniel H. Wiseman, Amos Tanay, Liran Shlush, Robert C. Lindsley, Irene M. Ghobrial, Justin Taylor, Omar Abdel-Wahab, Federico Gaiti, Dan A. Landau
Summary: In this study, the impact of mutated splicing factors on RNA splicing during hematopoiesis was investigated using a combination of genotyping of transcriptomes, long-read single-cell transcriptomics, and proteogenomics. The study found that mutations in the core splicing factor SF3B1 led to expansion of erythroid progenitor cells, as well as stage-specific aberrant splicing during erythroid differentiation. Additionally, the study revealed specific cryptic 30 splice site usage in SF3B1-mutated cells and an erythroid bias in clonal hematopoiesis samples before overt myelodysplastic syndrome.
Article
Oncology
Hang Yin, Tabitha A. Harrison, Sushma S. Thomas, Cassie L. Sather, Amanda L. Koehne, Rachel C. Malen, Adriana M. Reedy, Michelle A. Wurscher, Li Hsu, Amanda Phipps, Syed H. E. Zaidi, Polly A. Newcomb, Ulrike Peters, Jeroen R. Huyghe
Summary: The T cell-inflamed gene expression profile (GEP) is a prognostic biomarker in non-hypermutated microsatellite-stable colorectal cancer (CRC), and can guide patient stratification for immunotherapy. In addition, immune-inhibitory gene expression signals may provide potential targets for therapeutic combinations with immunotherapy.
Article
Biochemical Research Methods
Martin Pirkl, Niko Beerenwinkel
Summary: A novel mathematical method has been developed to analyze cancer driver genes and patient-specific perturbation profiles by combining genetic aberrations with gene expression data in a causal network derived across patients to infer unobserved perturbations. The method has been shown to predict perturbations in simulations, CRISPR perturbation screens, and breast cancer samples from The Cancer Genome Atlas.
Article
Oncology
R. Tyler McLaughlin, Maansi Asthana, Marc Di Meo, Michele Ceccarelli, Howard J. Jacob, David L. Masica
Summary: Accurately identifying somatic mutations is crucial for precision oncology and calculating tumor-mutational burden (TMB), which predicts response to immunotherapy. This study applies machine learning models to classify somatic vs germline mutations in tumor-only solid tumor samples, achieving state-of-the-art performance. The addition of a machine-learning classifier improves the concordance of TMB estimates and eliminates racial bias in tumor-only variant calling.
NPJ PRECISION ONCOLOGY
(2023)
Article
Oncology
Adam Nagy, Balazs Gyorffy
Summary: Large oncology repositories containing paired genomic and transcriptomic data were utilized to identify mutations altering gene expression and gene expression changes related to gene mutations. The study validated the pipeline and established a portal for rapid identification of novel mutational targets, demonstrating the potential for identifying biomarkers and therapeutic targets in solid tumors.
INTERNATIONAL JOURNAL OF CANCER
(2021)
Article
Multidisciplinary Sciences
Kasumi Murai, Stefan Dentro, Swee Hoe Ong, Roshan Sood, David Fernandez-Antoran, Albert Herms, Vasiliki Kostiou, Irina Abnizova, Benjamin A. Hall, Moritz Gerstung, Philip H. Jones
Summary: Aging normal oesophagus accumulates p53 mutant clones which play a role in cancer development. Using transgenic mice, it is shown that these clones form and contribute to tumour growth.
NATURE COMMUNICATIONS
(2022)
Article
Oncology
Lingling Guo, Fuping Zhou, Huiying Liu, Xiaoxia Kou, Hongjuan Zhang, Xiaofeng Chen, Jinrong Qiu
Summary: This study investigates the mutation characteristics and prognostic mechanisms of biliary tract cancers in the Chinese population, identifying poor prognostic factors associated with KRAS mutations, VEGFA pathway mutations, and high tumor mutation burden (TMB).
AMERICAN JOURNAL OF TRANSLATIONAL RESEARCH
(2022)
Article
Multidisciplinary Sciences
Aseel Shomar, Omri Barak, Naama Brenner
Summary: This article proposes a framework of learning theory to explain the complexities of drug resistance and metastasis in cancer. The learning process at the single-cell level is driven by stress and involves trial-and-error exploration to diminish stress. At the population level, the tissue is viewed as a network of exploring agents that communicate with each other, maintaining health by restraining cancer formation.
Article
Oncology
Ilenia Migliaccio, Marta Paoli, Emanuela Risi, Chiara Biagioni, Laura Biganzoli, Matteo Benelli, Luca Malorni
Summary: This study aims to investigate the prognostic value of PIK3CA mutations and copy number gain in hormone receptor-positive and HER2-negative breast cancer. Analysis of samples from three datasets revealed that 8-10% of patients had PIK3CA mutations and gain, which were associated with worse outcome. The clinical benefit of targeted treatment was found to be similar among patients with different mutation types.
Article
Multidisciplinary Sciences
Xiaoyu Song, Jiayi Ji, Joseph H. Rothstein, Stacey E. Alexeeff, Lori C. Sakoda, Adriana Sistig, Ninah Achacoso, Eric Jorgenson, Alice S. Whittemore, Robert J. Klein, Laurel A. Habel, Pei Wang, Weiva Sieh
Summary: Researchers have developed a new cell-type-aware transcriptome-wide association study approach to predict cell-type level gene expression and identify disease-associated genes. This approach provides insights into the genetic and cellular etiology of diseases such as breast cancer.
NATURE COMMUNICATIONS
(2023)
Article
Biochemical Research Methods
Zexian Zeng, Chengsheng Mao, Andy Vo, Xiaoyu Li, Janna Ore Nugent, Seema A. Khan, Susan E. Clare, Yuan Luo
Summary: DeepCues is a deep learning model that utilizes convolutional neural networks to derive features unbiasedly from raw cancer DNA sequencing data for disease classification and relevant gene discovery. By amalgamating germline variants and somatic mutations, including insertions and deletions, DeepCues showed significant improvement in cancer type prediction and successfully identified new cancer relevant genes.
BMC BIOINFORMATICS
(2021)
Article
Oncology
Jonathan D. Young, Shuangxia Ren, Lujia Chen, Xinghua Lu
Summary: By designing an interpretable deep learning model, we were able to encode the impact of SGAs on cellular signaling systems and tumor gene expression, uncover drivers affecting common signaling pathways, and partially resolve the causal structure of signaling proteins. This early attempt to use a transparent deep learning model provides interpretable insights into cancer cell signaling systems, shedding light on disease mechanisms and guiding precision medicine.
Article
Oncology
Rong Bu, Abdul K. Siraj, Tariq Masoodi, Sandeep Kumar Parvathareddy, Kaleem Iqbal, Maha Al-Rasheed, Wael Haqawi, Mark Diaz, Ingrid G. Victoria, Saud M. Aldughaither, Saif S. Al-Sobhi, Fouad Al-Dayel, Khawla S. Al-Kuraya
Summary: This study evaluated the prevalence of MAP2K1 mutations in PTC and CRC in the Middle Eastern population, finding rates of 1.1% and 0.9%, respectively, in MAPK wildtype cases. The mutually exclusive nature of MAP2K1 and MAPK mutations suggests that they may function as initiating mutations in tumorigenesis.
FRONTIERS IN ONCOLOGY
(2021)