Cargando…

Gene-Mutation-Based Algorithm for Prediction of Treatment Response in Colorectal Cancer Patients

SIMPLE SUMMARY: Despite the high incidence and mortality of metastatic colorectal cancer (mCRC), there are no new biomarker tools available for predicting treatment response at diagnosis. We used machine learning using gene mutations from primary tumors of patients and developed a new biomarker mode...

Descripción completa

Detalles Bibliográficos
Autores principales:	Johnson, Heather, El-Schich, Zahra, Ali, Amjad, Zhang, Xuhui, Simoulis, Athanasios, Wingren, Anette Gjörloff, Persson, Jenny L.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9030299/ https://www.ncbi.nlm.nih.gov/pubmed/35454952 http://dx.doi.org/10.3390/cancers14082045

Ejemplares similares

K-RAS Associated Gene-Mutation-Based Algorithm for Prediction of Treatment Response of Patients with Subtypes of Breast Cancer and Especially Triple-Negative Cancer
por: Johnson, Heather, et al.
Publicado: (2022)

Interfacing antibody-based microarrays and digital holography enables label-free detection for loss of cell volume
por: El-Schich, Zahra, et al.
Publicado: (2015)

Different expression levels of glycans on leukemic cells—a novel screening method with molecularly imprinted polymers (MIP) targeting sialic acid
por: El-Schich, Zahra, et al.
Publicado: (2016)

Targeted suppression of AR-V7 using PIP5K1α inhibitor overcomes enzalutamide resistance in prostate cancer cells
por: Sarwar, Martuza, et al.
Publicado: (2016)

Fluorescent Molecularly Imprinted Polymer Layers against Sialic Acid on Silica-Coated Polystyrene Cores—Assessment of the Binding Behavior to Cancer Cells
por: Beyer, Sarah, et al.
Publicado: (2022)

Digital Holographic Microscopy for Non-Invasive Monitoring of Cell Cycle Arrest in L929 Cells
por: Falck Miniotis, Maria, et al.
Publicado: (2014)

Recent Advances in Molecularly Imprinted Polymers and Their Disease-Related Applications
por: Cabaleiro-Lago, Celia, et al.
Publicado: (2023)

Reversible Self-Assembled Monolayers with Tunable Surface Dynamics for Controlling Cell Adhesion Behavior
por: Yeung, Sing Yee, et al.
Publicado: (2022)

FcγRIIIa receptor interacts with androgen receptor and PIP5K1α to promote growth and metastasis of prostate cancer
por: Larsson, Per Flodbring, et al.
Publicado: (2022)

In vitro effects of undifferentiated callus extracts from Plantago major L, Rhodiola rosea L and Silybum marianum L in normal and malignant human skin cells
por: Gjörloff Wingren, Anette, et al.
Publicado: (2023)

An Epitope‐Imprinted Biointerface with Dynamic Bioactivity for Modulating Cell–Biomaterial Interactions
por: Pan, Guoqing, et al.
Publicado: (2017)

PIP5K1α is Required for Promoting Tumor Progression in Castration-Resistant Prostate Cancer
por: Wang, Tianyan, et al.
Publicado: (2022)

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up
por: Johnson, Heather, et al.
Publicado: (2020)

A 23‐Gene Classifier urine test for prostate cancer prognosis
por: Guo, Jinan, et al.
Publicado: (2021)

Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients
por: Guo, Jinan, et al.
Publicado: (2021)

Targeted inhibition of ERα signaling and PIP5K1α/Akt pathways in castration‐resistant prostate cancer
por: Semenas, Julius, et al.
Publicado: (2020)

CYP2D6 variants and the prediction of tamoxifen response in randomized patients: author response
por: Wegman, Pia P, et al.
Publicado: (2005)

The functional interlink between AR and MMP9/VEGF signaling axis is mediated through PIP5K1α/pAKT in prostate cancer
por: Larsson, Per, et al.
Publicado: (2019)

Assessing the accuracy of [(18)F]PSMA-1007 PET/CT for primary staging of lymph node metastases in intermediate- and high-risk prostate cancer patients
por: Ingvar, Jacob, et al.
Publicado: (2022)

Establishment of Prostate Tumor Growth and Metastasis Is Supported by Bone Marrow Cells and Is Mediated by PIP5K1α Lipid Kinase
por: Karlsson, Richard, et al.
Publicado: (2020)

FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithms
por: Lu, Wei, et al.
Publicado: (2020)

FDG-PET/CT for lymph node staging prior to radical cystectomy
por: Pihl, Vilhelm, et al.
Publicado: (2023)

The sustainability and the survivability of Kyoto’s traditional craft industry revealed from supplier-customer network
por: Sato, Daisuke, et al.
Publicado: (2020)

An algorithm to predict advanced proximal colorectal neoplasia in Chinese asymptomatic population
por: Liwen Huang, Jason, et al.
Publicado: (2017)

Comprehensive assessment of computational algorithms in predicting cancer driver mutations
por: Chen, Hu, et al.
Publicado: (2020)

Digital Image Art Style Transfer Algorithm Based on CycleGAN
por: Fu, Xuhui
Publicado: (2022)

Prognostic and predictive value of common mutations for treatment response and survival in patients with metastatic colorectal cancer
por: Souglakos, J, et al.
Publicado: (2009)

KDR Mutation as a Novel Predictive Biomarker of Exceptional Response to Regorafenib in Metastatic Colorectal Cancer
por: Loaiza-Bonilla, Arturo, et al.
Publicado: (2016)

Prognostic and Predictive Roles of KRAS Mutation in Colorectal Cancer
por: Arrington, Amanda K., et al.
Publicado: (2012)

Benchmarking mutation effect prediction algorithms using functionally validated cancer-related missense mutations
por: Martelotto, Luciano G, et al.
Publicado: (2014)

Predicting diagnosis of Parkinson's disease: A risk algorithm based on primary care presentations
por: Schrag, Anette, et al.
Publicado: (2019)

Notch signaling mutations increase intra-tumor chemokine expression and predict response to immunotherapy in colorectal cancer
por: Wang, Fei, et al.
Publicado: (2022)

Response prediction by mutation- or methylation-specific detection of ctDNA dynamics in pretreated metastatic colorectal cancer
por: Doleschal, Bernhard, et al.
Publicado: (2023)

A Catalogue of Machine Learning Algorithms for Healthcare Risk Predictions †
por: Mavrogiorgou, Argyro, et al.
Publicado: (2022)

The predictive value of KRAS and NRAS mutations in metastatic colorectal cancer
por: Eshraghi, Abbas, et al.
Publicado: (2020)

Use of Machine Learning Algorithms for Prediction of Fetal Risk using Cardiotocographic Data
por: Hoodbhoy, Zahra, et al.
Publicado: (2019)

Chromosomal Instability, Aneuploidy, and Gene Mutations in Human Sporadic Colorectal Adenomas
por: Giaretti, Walter, et al.
Publicado: (2004)

Sequence and expression analysis of gaps in human chromosome 20
por: Minocherhomji, Sheroy, et al.
Publicado: (2012)

Mutational Slime Mould Algorithm for Gene Selection
por: Qiu, Feng, et al.
Publicado: (2022)

Dietary Fat Intake and KRAS Mutations in Colorectal Cancer in a Moroccan Population
por: El Asri, Achraf, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_59oic2mca3pk2bgtjccq4q2bsu