AIMC Topic: Gene Expression Regulation, Neoplastic

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Global DNA methylation signatures associated with chemoresistance and poor prognosis of high grade serous ovarian cancer.

Scientific reports
Ovarian cancer (OVCA) is third most lethal gynecologic cancers and acquired chemoresistance is the key link in the high mortality rate of OVCA patients. Currently, there are no reliable methods to predict chemoresistance in OVCA. In our study, we ide...

CRLS1 influences liver metastasis in colon cancer by regulating lipid metabolism pathways.

Functional & integrative genomics
Colon cancer is one of the leading causes of cancer-related mortality, with liver metastasis commonly complicating its progression and significantly worsening patient prognosis. This study aims to explore the relationship between liver metastasis in ...

Single-cell multi-omics uncovers CPS1 as a breast cancer immune evasion therapeutic target.

Scientific reports
Despite significant advances in early detection and therapeutic interventions, breast cancer persists as the most frequently diagnosed malignancy and the leading cause of cancer-related deaths among women globally. Although multiple prognostic signat...

SLC25A39 regulates Hedgehog signaling to promote tumor progression and sorafenib resistance in hepatocellular carcinoma.

Scientific reports
Sorafenib is the standard treatment for advanced hepatocellular carcinoma (HCC), yet resistance limits its efficacy. The Hedgehog (HH) signaling pathway contributes to drug resistance by maintaining HCC stem cell characteristics, but its role at the ...

A prognostic model for gastric cancer constructed by multiple machine learning algorithms.

Journal of molecular histology
Gastric cancer (GC) is a highly heterogeneous disease that requires highly accurate prognostic models. Machine learning is a powerful tool for identifying predictive biomarkers and developing prognostic models. Here, we aim to integrate bioinformatic...

Identification and tissue-level validation of ferroptosis-related genes in small intestinal neuroendocrine neoplasms based on machine learning.

BMC gastroenterology
BACKGROUND: Small intestinal neuroendocrine neoplasms (SI-NENs), a subgroup of neuroendocrine tumors originating from neuroendocrine cells in the small intestine, present significant therapeutic challenges, and their relationship with ferroptosis-a r...

Machine learning analysis of coagulation-related genes for breast cancer diagnosis and prognosis prediction.

Scientific reports
The purpose of this study was to investigate the relationship between coagulation related genes (CRGs) and breast cancer (BC). First, we found that most CRGs are abnormally expressed in BC patients and correlated with their prognosis. Therefore, we e...

Single-cell and spatial transcriptomics reveal post-translational modifications in osteosarcoma progression and tumor microenvironment.

PloS one
Emerging evidence suggests that post-translational modifications (PTMs) contribute to osteosarcoma pathogenesis, yet their exact molecular roles require further elucidation. Using the AddModuleScore method, we classified tumor cells on the basis of P...

Multi-omics identification of RNASE6 as an immune regulatory RNA-binding protein associated with melanoma metastasis.

Autoimmunity
BACKGROUND: Cutaneous melanoma is a highly invasive tumor. It enhances metastasis and resistance to immunotherapy immunosuppressive mechanisms. Understanding RNA-binding proteins (RBPs) in melanoma's immune alterations is limited. This study explore...

Decision tree-based machine learning methods for identifying colorectal cancer-associated microRNA signatures and their regulatory networks.

Scientific reports
This study aimed to identify candidate diagnostic miRNAs from the serum of colorectal cancer (CRC) patients using Boruta, a wrapper-based feature selection technique, in combination with decision tree-based machine learning methods. We analyzed three...