AIMC Topic: Biomarkers, Tumor

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An immunohistochemistry-based classification of colorectal cancer resembling the consensus molecular subtypes using convolutional neural networks.

Scientific reports
Colorectal cancer (CRC) represents a major global disease burden with nearly 1 million cancer-related deaths annually. TNM staging has served as the foundation for predicting patient prognosis, despite variation across staging groups. The consensus m...

Integrated machine learning survival framework develops a prognostic model based on macrophage-related genes and programmed cell death signatures in a multi-sample Kidney renal clear cell carcinoma.

Cell biology and toxicology
BACKGROUND: Macrophages are closely associated with the progression of Kidney renal clear cell carcinoma (KIRC) and can influence programmed cell death (PCD) of tumour cells. To identify prognostic biomarkers for KIRC, it is essential to investigate ...

Identification of key genes regulating colorectal cancer stem cell characteristics by bioinformatics analysis.

Medicine
Cancer stem cells (CSCs), distinguished by their abilities to differentiate and self-renew, play a pivotal role in the progression of colorectal cancer (CRC). However, the mechanisms that sustain CSCs in CRC remain unclear. This study aimed to identi...

Machine learning identifies SRD5A3 as a propionate-related prognostic biomarker in triple-negative breast cancer.

Scientific reports
The increased risk of recurrence and metastasis are obstacles to treating TNBC. Propionate-related genes play an important role in tumor development and immune cell infiltration. The study was to identify the association between propionate-related ge...

Saliva-derived transcriptomic signature for gastric cancer detection using machine learning and leveraging publicly available datasets.

Scientific reports
Saliva, a non-invasive, self-collected liquid biopsy, holds promise for early gastric cancer (GC) screening. This study aims to assess the potential of saliva as a proxy for malignant gastric transformation and its diagnostic value through transcript...

Chaperonin containing TCP1 subunit 5 as a novel pan-cancer prognostic biomarker for tumor stemness and immunotherapy response: insights from multi-omics data, integrated machine learning, and experimental validation.

Cancer immunology, immunotherapy : CII
BACKGROUND: Chaperonin containing TCP1 subunit 5 (CCT5), a vital component of the molecular chaperonin complex, has been implicated in tumorigenesis, cancer stemness maintenance, and therapeutic resistance. Nevertheless, its comprehensive roles in pa...

Predicting high confidence ctDNA somatic variants with ensemble machine learning models.

Scientific reports
Circulating tumour DNA (ctDNA) is a minimally invasive cancer biomarker that can be used to inform treatment of cancer patients. The utility of ctDNA as a cancer biomarker depends on the ability to accurately detect somatic variants associated with c...

Identification of molecular subtypes and a prognostic signature based on machine learning and purine metabolism-related genes in breast cancer.

Medicine
Breast cancer (BC), one of the most prevalent malignant tumors worldwide, lacks efficacious diagnostic biomarkers and therapeutic targets. This study harnesses multi-omics data to identify novel purine metabolism-related genes (PMRG) as potential bio...

Predictive value of machine learning for PD-L1 expression in NSCLC: a systematic review and meta-analysis.

World journal of surgical oncology
BACKGROUND: As machine learning (ML) continuously develops in cancer diagnosis and treatment, some researchers have attempted to predict the expression of programmed death ligand-1 (PD-L1) in non-small cell lung cancer (NSCLC) by ML. However, there i...

Accurate Cancer Diagnosis and Treatment Monitoring through Multiplexed Profiling of Protein Markers on Small Extracellular Vesicles.

ACS nano
The detection of small extracellular vesicles (sEVs) is currently a pivotal liquid biopsy approach for noninvasive cancer diagnosis. However, the lack of adequate specificity and sensitivity, as well as labor-intensive purification and analysis proce...