SLAM: Structure-aware lysine β-hydroxybutyrylation prediction with protein language model.

Post-translational modifications (PTMs) diversify protein functions by adding/removing chemical groups to certain amino acid. As a newly-reported PTM, lysine β-hydroxybutyrylation (Kbhb) presents a new avenue to functional proteomics. Therefore, accurate and efficient prediction of Kbhb sites is imperative.

Exploring the molecular characteristics of the malignant potential of gastric adenocarcinoma with enteroblastic differentiation.

Aims: Gastric adenocarcinoma with enteroblastic differentiation (GAED) is a rare subset of alpha-fetoprotein (AFP)-producing carcinomas with poor prognosis. However, the molecular features associated with the malignant potential of GEAD remain partially elucidated.

Methods And Results: In this study, the relationship between clinicopathological parameters and aggressive biological behaviour was analysed in 37 patients with GAED.

Development of a nomogram based on serum cytokine-related riskscore in breast cancer.

Background: Cytokines are involved in many inflammatory diseases and thus play an important role in tumor immune regulation. In recent years, researchers have found that breast cancer is not only related to genetic and environmental factors, but also to the chronic inflammation and immunity. However, the correlation between serum cytokines and blood tests indicators remain unclear.

Optimal therapy for concomitant EGFR and TP53 mutated non-small cell lung cancer: a real-world study.

Background: Non-small cell cancer (NSCLC) patients with concomitant epidermal growth factor receptor (EGFR) and TP53 mutations have a poor prognosis with the treatment of tyrosine kinase inhibitors (TKIs), and may benefit from a combination regimen preferentially. The present study aims to compare the benefits of EGFR-TKIs and its combination with antiangiogenic drugs or chemotherapy in patients with NSCLC harboring EGFR and TP53 co-mutation in a real-life setting.

Methods: This retrospective analysis included 124 patients with advanced NSCLC having concomitant EGFR and TP53 mutations, who underwent next-generation sequencing prior to treatment.

Water channel protein AQP1 in cytoplasm is a critical factor in breast cancer local invasion.

Background: Metastasis of breast cancer grows from the local invasion to the distant colonization. Blocking the local invasion step would be promising for breast cancer treatment. Our present study demonstrated AQP1 was a crucial target in breast cancer local invasion.

Screening for Lipid-Metabolism-Related Genes and Identifying the Diagnostic Potential of ANGPTL6 for HBV-Related Early-Stage Hepatocellular Carcinoma.

Lipid metabolic reprogramming is one of the hallmarks of hepatocarcinogenesis and development. Therefore, lipid-metabolism-related genes may be used as potential biomarkers for hepatocellular carcinoma (HCC). This study aimed to screen for genes with dysregulated expression related to lipid metabolism in HCC and explored the clinical value of these genes.

Pretreatment Thoracic CT Radiomic Features to Predict Brain Metastases in Patients With -Rearranged Non-Small Cell Lung Cancer.

To identify CT imaging biomarkers based on radiomic features for predicting brain metastases (BM) in patients with -rearranged non-small cell lung cancer (NSCLC). NSCLC patients with pathologically confirmed rearrangement from January 2014 to December 2020 in our hospital were enrolled retrospectively in this study. Finally, 77 patients were included according to the inclusion and exclusion criteria.

Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer.

Objectives: To develop a nomogram based on pretreatment dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in patients with triple-negative breast cancer (TNBC).

Methods: A total of 108 female patients with TNBC treated with neoadjuvant chemotherapy followed by surgery between January 2017 and October 2020 were enrolled. The patients were randomly divided into the primary cohort (n = 87) and validation cohort (n = 21) at a ratio of 4:1.

Endocytic protein intersectin1-S shuttles into nucleus to suppress the DNA replication in breast cancer.

Breast cancer is the most common type of cancer worldwide. However, the well-known molecular biomarkers are not enough to meet the needs of precision medicine. In search for novel targets in this regard, we reported ITSN1 (intersectin1) as one of the candidates through mRNA microarray analysis.

Identification of hub genes and their novel diagnostic and prognostic significance in pancreatic adenocarcinoma.

Objective: The main reasons for the poor prognoses of pancreatic adenocarcinoma (PA) patients are rapid early-stage progression, advanced stage metastasis, and chemotherapy resistance. Identification of novel diagnostic and prognostic biomarkers of PA is therefore urgently needed.

Methods: Three mRNA microarray datasets were obtained from the Gene Expression Omnibus database to select differentially expressed genes (DEGs).

nhKcr: a new bioinformatics tool for predicting crotonylation sites on human nonhistone proteins based on deep learning.

Lysine crotonylation (Kcr) is a newly discovered type of protein post-translational modification and has been reported to be involved in various pathophysiological processes. High-resolution mass spectrometry is the primary approach for identification of Kcr sites. However, experimental approaches for identifying Kcr sites are often time-consuming and expensive when compared with computational approaches.

iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization.

Sequence-based analysis and prediction are fundamental bioinformatic tasks that facilitate understanding of the sequence(-structure)-function paradigm for DNAs, RNAs and proteins. Rapid accumulation of sequences requires equally pervasive development of new predictive models, which depends on the availability of effective tools that support these efforts. We introduce iLearnPlus, the first machine-learning platform with graphical- and web-based interfaces for the construction of machine-learning pipelines for analysis and predictions using nucleic acid and protein sequences.

Computational identification of ubiquitination sites in Arabidopsis thaliana using convolutional neural networks.

We developed two CNNs for predicting ubiquitination sites in Arabidopsis thaliana, demonstrated their competitive performance, analyzed amino acid physicochemical properties and the CNN structures, and predicted ubiquitination sites in Arabidopsis. As an important posttranslational protein modification, ubiquitination plays critical roles in plant physiology, including plant growth and development, biotic and abiotic stress, metabolism, and so on. A lot of ubiquitination site prediction models have been developed for human, mouse and yeast.

Angiotensin-converting enzyme inhibitors have adverse effects in anti-angiogenesis therapy for hepatocellular carcinoma.

At present, anti-angiogenic drugs (AADs) are widely used in the systemic treatment of hepatocellular carcinoma (HCC) or other types of cancer, and have achieved good anti-cancer effect, whereas treatment-related proteinuria can affect the routine use of AADs, which in turn abates the overall efficacy. Currently, most clinicians prescribe angiotensin-converting enzyme inhibitors (ACEIs) to alleviate proteinuria according to diabetic nephropathy guidelines or expert recommendations. However, the efficacy of ACEIs in reducing AAD-related proteinuria and its effect on the anticancer effect of AADs is unknown.

Bioinformatics Analysis of Expression and Alterations of BARD1 in Breast Cancer.

Background: Breast cancer is one of the most common malignant tumor type in women worldwide. BARD1 could impact function of BRCA1 as its interaction partner. In the current study, we aimed to investigate the prognostic role of BARD1 expression as well as its alterations in breast cancer using different online tools.

Multiple MicroRNAs synergistically promote tolerance to epidermal growth factor receptor-targeted drugs in smoked lung cancer therapies.

Aims: Lung cancer is one of the leading causes of cancer-related mortality. Tobacco usage is considered as associated with the carcinogenesis, progression, and prognosis of lung cancer. Previous studies have demonstrated that the smoking inhibited medical therapy results from K-Ras gene mutation through suppressing the epidermal growth factor receptor (EGFR) pathway.

Single drug biomarker prediction for ER- breast cancer outcome from chemotherapy.

ER-negative breast cancer includes most aggressive subtypes of breast cancer such as triple negative (TN) breast cancer. Excluded from hormonal and targeted therapies effectively used for other subtypes of breast cancer, standard chemotherapy is one of the primary treatment options for these patients. However, as ER- patients have shown highly heterogeneous responses to different chemotherapies, it has been difficult to select most beneficial chemotherapy treatments for them.

FGF1 and IGF1-conditioned 3D culture system promoted the amplification and cancer stemness of lung cancer cells.

Lung cancer stem cells (LCSCs) are considered as the cellular origins of metastasis and relapse of lung cancer. However, routine two-dimensional culture system (2D-culture) hardly mimics the growth and functions of LCSCs in vivo and therefore significantly decreases the stemness activity of LCSCs. In this study, we constructed a special BME-based three-dimensional culture system (3D-culture) to amplify LCSCs in human lung adenocarcinoma cell line A549 cells and found 3D-culture promoted the enrichment and amplification of LCSCs in A549 cells displaying higher proliferation potential and invasion activity, but lower apoptosis.

Dysfunctional activation of neurotensin/IL-8 pathway in hepatocellular carcinoma is associated with increased inflammatory response in microenvironment, more epithelial mesenchymal transition in cancer and worse prognosis in patients.

Aim: To investigate the role of neurotensin (NTS) in hepatocellular carcinoma (HCC) sub- grouping and the clinical and pathological significance of activation of NTS/IL-8 pathway in HCC.

Methods: The genome-wide gene expression profiling were conducted in 10 pairs of cancer tissues and corresponding normal adjacent tissues samples using Affymetrix GeneChip® Human Genome U133 Plus 2.0 microarray to screen differentially expressing genes and enrich dysfunctional activated pathways among different HCC subgroups.

SUMOhydro: a novel method for the prediction of sumoylation sites based on hydrophobic properties.

Sumoylation is one of the most essential mechanisms of reversible protein post-translational modifications and is a crucial biochemical process in the regulation of a variety of important biological functions. Sumoylation is also closely involved in various human diseases. The accurate computational identification of sumoylation sites in protein sequences aids in experimental design and mechanistic research in cellular biology.

Prediction of ubiquitination sites by using the composition of k-spaced amino acid pairs.

As one of the most important reversible protein post-translation modifications, ubiquitination has been reported to be involved in lots of biological processes and closely implicated with various diseases. To fully decipher the molecular mechanisms of ubiquitination-related biological processes, an initial but crucial step is the recognition of ubiquitylated substrates and the corresponding ubiquitination sites. Here, a new bioinformatics tool named CKSAAP_UbSite was developed to predict ubiquitination sites from protein sequences.