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New treatment alternatives for primary and metastatic colorectal cancer by an integrated transcriptome and network analyses
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A chromosome-scale fishing cat reference genome for the evaluation of potential germline risk variants
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The impact of telomere length on prostate cancer aggressiveness, genomic instability and health disparities
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Identification of molecular subtypes and a prognostic signature based on m6A/m5C/m1A-related genes in lung adenocarcinoma
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Investigating diagnostic potential of long non-coding RNAs in head and neck squamous cell carcinoma using TCGA database and clinical specimens
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CRISPR/Cas9 targeting of passenger single nucleotide variants in haploinsufficient or essential genes expands cancer therapy prospects
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Extend the benchmarking indel set by manual review using the individual cell line sequencing data from the Sequencing Quality Control 2 (SEQC2) project
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Clinically-observed FOXA1 mutations upregulate SEMA3C through transcriptional derepression in prostate cancer
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Single-cell RNA sequencing unveils tumor heterogeneity and immune microenvironment between subungual and plantar melanoma
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Prediction uncertainty estimates elucidate the limitation of current NSCLC subtype classification in representing mutational heterogeneity
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Identification of expression profiles and prognostic value of RFCs in colorectal cancer
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Challenges in the discovery of tumor-specific alternative splicing-derived cell-surface antigens in glioma
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Polygenic risk score-based prediction of breast cancer risk in Taiwanese women with dense breast using a retrospective cohort study
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Identifying microRNAs associated with tumor immunotherapy response using an interpretable machine learning model
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Prognostic mutation signature would serve as a potential prognostic predictor in patients with diffuse large B-cell lymphoma
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A comprehensive analysis and experimental validation of TK1 in uterine corpus endometrial carcinoma
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Tumor location matters, next generation sequencing mutation profiling of left-sided, rectal, and right-sided colorectal tumors in 552 patients
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Comprehensive analyses of solute carrier family members identify SLC12A2 as a novel therapy target for colorectal cancer
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Integrating artificial intelligence in osteosarcoma prognosis: the prognostic significance of SERPINE2 and CPT1B biomarkers
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TRIP6 a potential diagnostic marker for colorectal cancer with glycolysis and immune infiltration association
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Genetic variants associated with osteosarcoma risk: a systematic review and meta-analysis
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Pan-caner analysis identifies PSMA7 as a targets for amplification at 20q13.33 in tumorigenesis
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DEEPOMICS FFPE, a deep neural network model, identifies DNA sequencing artifacts from formalin fixed paraffin embedded tissue with high accuracy
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Establish a novel tumor budding-related signature to predict prognosis and guide clinical therapy in colorectal cancer
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Empirical Bayes single nucleotide variant-calling for next-generation sequencing data
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Developing a prognosis and chemotherapy evaluating model for colon adenocarcinoma based on mitotic catastrophe-related genes
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Anoikis related genes may be novel markers associated with prognosis for ovarian cancer
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LncRNA SOX9-AS1 triggers a transcriptional program involved in lipid metabolic reprogramming, cell migration and invasion in triple-negative breast cancer
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PIEZO2 expression is an independent biomarker prognostic for gastric cancer and represents a potential therapeutic target
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Identification of an inflammation-related risk signature for prognosis and immunotherapeutic response prediction in bladder cancer
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SLMO2 is a potential prognostic and immunological biomarker in human pan-cancer
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Uncovering hidden cancer self-dependencies through analysis of shRNA-level dependency scores
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Development and validation of a novel lysosome-related LncRNA signature for predicting prognosis and the immune landscape features in colon cancer
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Whole‑exome sequencing reveals Lewis lung carcinoma is a hypermutated Kras/Nras–mutant cancer with extensive regional mutation clusters in its genome
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MAD2L2, a key regulator in ovarian cancer and promoting tumor progression
- Kejun Xu
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Characterization of Wnt signaling pathway under treatment of Lactobacillus acidophilus postbiotic in colorectal cancer using an integrated in silico and in vitro analysis
- Nafiseh Erfanian
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Association between copy number alterations estimated using low-pass whole genome sequencing of formalin-fixed paraffin-embedded prostate tumor tissue and cancer-specific clinical parameters
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Debiased inference for heterogeneous subpopulations in a high-dimensional logistic regression model
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Small-scale mutations are infrequent as mechanisms of resistance in post-PARP inhibitor tumour samples in high grade serous ovarian cancer
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Low incidence of microsatellite instability in gastric cancers and its association with the clinicopathological characteristics: a comparative study
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Deep learning-enabled breast cancer endocrine response determination from H&E staining based on ESR1 signaling activity
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Nucleotide excision repair deficiency is a targetable therapeutic vulnerability in clear cell renal cell carcinoma
- Aurel Prosz
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Revealing the potential of necroptosis-related genes in prognosis, immune characteristics, and treatment strategies for head and neck squamous cell carcinoma
- Junhua Cao
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Efficacy of futibatinib, an irreversible fibroblast growth factor receptor inhibitor, in FGFR-altered breast cancer
- Turcin Saridogan
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Modeling phenotypic heterogeneity towards evolutionarily inspired osteosarcoma therapy
- Darcy L. Welch
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Optimizing the risk stratification of astrocytic tumors by applying the cIMPACT-NOW Update 3 signature: real-word single center experience
- Carmen Molica
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The network structure of hematopoietic cancers
- Arturo Kenzuke Nakamura-García
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Biological and genetic characterization of a newly established human external auditory canal carcinoma cell line, SCEACono2
- Noritaka Komune
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Delta radiomics analysis for prediction of intermediary- and high-risk factors for patients with locally advanced cervical cancer receiving neoadjuvant therapy
- Rong-Rong Wu
- , Yi-Min Zhou
- & Wen-Juan Chen
Essentiality, protein–protein interactions and evolutionary properties are key predictors for identifying cancer-associated genes using machine learning