Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Step-by-step Elimination Algorithm Based on Modified Radial Data Visualization to Predict the Response to FOLFOX Treatment of CRC Patients

View through CrossRef
Abstract Background: The application of the FOLFOX chemotherapy scheme to colorectal cancer (CRC) patients often results in the development of resistance to its components, leading to therapeutic failure. This study aimed to develop a functional and easy-to-use algorithm to predict patients’ response to FOLFOX treatment. The transcriptomic data of samples from CRC patients treated with FOLFOX were downloaded from the Gene Expression Omnibus (GEO) database (GSE83129, GSE28702, GSE69657, GSE19860 and GSE41568). By comparing the expression of the top up- and downregulated genes in the FOLFOX responder and nonresponder patient groups, we selected 30 potential markers that were used to create a step-by-step elimination procedure based on modified radial data visualization, which depicts the interplay between the expression levels of chosen attributes (genes) to locate data points in low-dimensional space. Results: Our analysis revealed that FOLFOX-resistant CRC samples are predominantly characterized by upregulated expression of TMEM182and MCM9 and downregulated expression of LRRFIP1. Additionally, we developed a procedure based on the expression levels of TMEM182, MCM9, LRRFIP1, LAMP1, FAM161A, KLHL36, ETV5, RNF168, SRSF11, NCKAP5, CRTAP, VAMP2, ZBTB49 and RIMBP2 that could predict the response to FOLFOX therapy. Conclusion: Our approach can provide unique insight into clinical decision-making regarding therapy scheme administration, potentially increasing patient survival and, as a consequence, medical futility due to incorrect therapy.
Title: Step-by-step Elimination Algorithm Based on Modified Radial Data Visualization to Predict the Response to FOLFOX Treatment of CRC Patients
Description:
Abstract Background: The application of the FOLFOX chemotherapy scheme to colorectal cancer (CRC) patients often results in the development of resistance to its components, leading to therapeutic failure.
This study aimed to develop a functional and easy-to-use algorithm to predict patients’ response to FOLFOX treatment.
The transcriptomic data of samples from CRC patients treated with FOLFOX were downloaded from the Gene Expression Omnibus (GEO) database (GSE83129, GSE28702, GSE69657, GSE19860 and GSE41568).
By comparing the expression of the top up- and downregulated genes in the FOLFOX responder and nonresponder patient groups, we selected 30 potential markers that were used to create a step-by-step elimination procedure based on modified radial data visualization, which depicts the interplay between the expression levels of chosen attributes (genes) to locate data points in low-dimensional space.
Results: Our analysis revealed that FOLFOX-resistant CRC samples are predominantly characterized by upregulated expression of TMEM182and MCM9 and downregulated expression of LRRFIP1.
Additionally, we developed a procedure based on the expression levels of TMEM182, MCM9, LRRFIP1, LAMP1, FAM161A, KLHL36, ETV5, RNF168, SRSF11, NCKAP5, CRTAP, VAMP2, ZBTB49 and RIMBP2 that could predict the response to FOLFOX therapy.
Conclusion: Our approach can provide unique insight into clinical decision-making regarding therapy scheme administration, potentially increasing patient survival and, as a consequence, medical futility due to incorrect therapy.

Related Results

Radial Data Visualization-Based Step-by-Step Eliminative Algorithm to Predict Colorectal Cancer Patients’ Response to FOLFOX Therapy
Radial Data Visualization-Based Step-by-Step Eliminative Algorithm to Predict Colorectal Cancer Patients’ Response to FOLFOX Therapy
Application of the FOLFOX scheme to colorectal cancer (CRC) patients often results in the development of chemo-resistance, leading to therapy failure. This study aimed to develop a...
Small Cell Lung Cancer and Tarlatamab: A Meta-Analysis of Clinical Trials
Small Cell Lung Cancer and Tarlatamab: A Meta-Analysis of Clinical Trials
Abstract Introduction Tarlatamab is a Delta-like ligand 3 (DLL3) -directed bispecific T-cell engager recently approved for use in patients with advanced small cell lung cancer (SCL...
Synchronous/Metachronous Endometrial and Colorectal Malignancies in Taiwanese Women: A Population-Based Nationwide Study
Synchronous/Metachronous Endometrial and Colorectal Malignancies in Taiwanese Women: A Population-Based Nationwide Study
Abstract Introduction Endometrial cancer (EC) and colorectal cancer (CRC) may share a common genetic background. In a subset of patients, the two malignancies can coexist ...
FOLFOX vs. FOLFIRI in Colorectal Adenocarcinoma: A Retrospective Study of Treatment Patterns, Side Effects, and Treatment Response
FOLFOX vs. FOLFIRI in Colorectal Adenocarcinoma: A Retrospective Study of Treatment Patterns, Side Effects, and Treatment Response
Background: Colorectal adenocarcinoma (CRC) is a prevalent malignancy with a high recurrence rate, necessitating multimodal treatment strategies. Chemotherapy regimens like FOLFOX ...
Treatment outcomes of advanced hepatocellular carcinoma in real‐life practice: Chemotherapy versus multikinase inhibitors
Treatment outcomes of advanced hepatocellular carcinoma in real‐life practice: Chemotherapy versus multikinase inhibitors
AbstractBackgroundMultikinase inhibitors (MKIs) represent the main treatment options for advanced hepatocellular carcinoma (aHCC). However, accessibility in developing countries is...
Abstract LB121: Endothelial cells mediated paracrine signaling alters immune cell modulators on colorectal cancer cells
Abstract LB121: Endothelial cells mediated paracrine signaling alters immune cell modulators on colorectal cancer cells
Abstract Background: Metastatic colorectal cancer (mCRC) is the second leading cause of cancer related deaths in the US. Various factors in the tumor microenvironmen...

Back to Top