The aim of the study is to analyse gene typing with the use of the microarray technique (HG-U133A, Affymetrix), differentiating colorectal cancer tissues from tissues assessed histopathologically as healthy ones among a panel of 93 mRNA of gene encoding proteins involved in the activation of cellular signal transduction pathways by insulin-like growth factors. The study was conducted on a group of 8 colorectal cancer patients. Frozen tumor and healthy specimens from the patients were used in molecular tests. Transcript IGF2 differentiated cancer from healthy tissue. Among the genes participating in the cascade of signal transfer in cells activated by IGF, GRB10, PIK3R3, PIK3R1, and IRS1 were qualified as differentiating transcripts. IRS1 indicated over-expression in tumour. Transcript SMAD2 showed a significant changed in tumour samples (increased expression).

Download full-text PDF

Source
http://dx.doi.org/10.1177/039463201102400324DOI Listing

Publication Analysis

Top Keywords

colorectal cancer
12
gene encoding
8
encoding proteins
8
insulin-like growth
8
growth factors
8
analysis expression
4
expression profile
4
profile gene
4
proteins signal
4
signal cascades
4

Similar Publications

Epidemiology and anatomic distribution of colorectal cancer in South Africa.

S Afr J Surg

December 2024

Centre for Global Surgery, Department of Global Health, Stellenbosch University, South Africa.

Background: Colorectal cancer (CRC) is the fifth most common cancer in sub-Saharan Africa (SSA) and the third most common in South Africa (SA). CRC characteristics in SSA are not well described. The aim is to describe patient characteristics and anatomic location of colorectal adenocarcinoma (CRC-AC) in SA.

View Article and Find Full Text PDF

Early-onset colorectal cancer (CRC) has been on the rise since the start of the twenty-first century. While the etiology behind this increase remains unclear, the United States Preventive Services Task Force (USPSTF) has decreased the recommended age to begin screening for CRC to 45 years. This case report reviews the literature on CRC in the young population while presenting a case of a 21-year-old male with early-onset metastatic colorectal cancer without a hereditary etiology.

View Article and Find Full Text PDF

Background: Trifluridine/tipiracil (FTD/TPI) is approved as monotherapy and in combination with bevacizumab for the treatment of patients with refractory metastatic colorectal cancer (mCRC). FTD/TPI plus bevacizumab showed good tolerability in the phase 3 SOLSTICE (first-line) and SUNLIGHT (later-line) trials. This pooled analysis was performed to further characterize the safety of FTD/TPI plus bevacizumab and to compare safety in untreated and previously treated patients with mCRC.

View Article and Find Full Text PDF

Background: Colorectal cancer (CRC) is a common malignancy with notable recent shifts in its burden distribution. Current data on CRC burden can guide screening, early detection, and treatment strategies for efficient resource allocation.

Methods: This study utilized data from the latest Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study.

View Article and Find Full Text PDF

Decoding the Molecular Basis of the Specificity of an Anti-sTn Antibody.

JACS Au

January 2025

UCIBIO-Applied Molecular Biosciences Unit, Department of Chemistry, NOVA School of Science and Technology, NOVA University Lisbon, 2829-516 Caparica, Portugal.

The mucin -glycan sialyl Tn antigen (sTn, Neu5Acα2-6GalNAcα1--Ser/Thr) is an antigen associated with different types of cancers, often linked with a higher risk of metastasis and poor prognosis. Despite efforts to develop anti-sTn antibodies with high specificity for diagnostics and immunotherapy, challenges in eliciting high-affinity antibodies for glycan structures have limited their effectiveness, leading to low titers and short protection durations. Experimental structural insights into anti-sTn antibody specificity are lacking, hindering their optimization for cancer cell recognition.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!