Studies on the Dual Activity of EGFR and HER-2 Inhibitors Using Structure-Based Drug Design Techniques

Angelo, Rafaela Molina de; Almeida, Michell O.; Paula, Heberth de; Honório, Káthia Maria

doi:10.3390/ijms19123728

Cited by 9 publications

(3 citation statements)

References 33 publications

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“…Patients with HER2-amplified mCRC that harbor RAS, BRAF, or PIK3CA mutations show limited response to HER2 inhibitors[ 211 ], and therefore require a novel therapeutic strategy that would concomitantly block feedback loops involving EGFR , BRAF , and KRAS in mutated mCRC. In terms of the first strategy, several compounds are currently under clinical investigation and new drugs are being proposed as candidates to inhibit both molecules and improve efficacy of CRC targeted therapy, particularly in HER2-positive mCRC[ 212 , 213 ] (Table 1 ). In fact, HER2 amplification has been linked with resistance to EGFR inhibition[ 214 ] and thus, may serve as a biomarker for these treatment regimens.…”

Section: Beating Resistance To Targeted Therapymentioning

confidence: 99%

Molecular mechanisms targeting drug-resistance and metastasis in colorectal cancer: Updates and beyond

Bitar¹,

El-Sabban²,

Doughan³

et al. 2023

World J Gastroenterol

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Colorectal cancer (CRC) is the third most diagnosed malignancy and a major leading cause of cancer-related deaths worldwide. Despite advances in therapeutic regimens, the number of patients presenting with metastatic CRC (mCRC) is increasing due to resistance to therapy, conferred by a small population of cancer cells, known as cancer stem cells. Targeted therapies have been highly successful in prolonging the overall survival of patients with mCRC. Agents are being developed to target key molecules involved in drug-resistance and metastasis of CRC, and these include vascular endothelial growth factor, epidermal growth factor receptor, human epidermal growth factor receptor-2, mitogen-activated extracellular signal-regulated kinase, in addition to immune checkpoints. Currently, there are several ongoing clinical trials of newly developed targeted agents, which have shown considerable clinical efficacy and have improved the prognosis of patients who do not benefit from conventional chemotherapy. In this review, we highlight recent developments in the use of existing and novel targeted agents against drug-resistant CRC and mCRC. Furthermore, we discuss limitations and challenges associated with targeted therapy and strategies to combat intrinsic and acquired resistance to these therapies, in addition to the importance of implementing better preclinical models and the application of personalized therapy based on predictive biomarkers for treatment selection.

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Section: Beating Resistance To Targeted Therapymentioning

confidence: 99%

Molecular mechanisms targeting drug-resistance and metastasis in colorectal cancer: Updates and beyond

Bitar¹,

El-Sabban²,

Doughan³

et al. 2023

World J Gastroenterol

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“…Quantitative structure-activity relationship (QSAR) is a method largely used for predicting the activity of a substance against a biological target through the relationships between biological data and molecular descriptors that are dependent on the molecular structure [ 15 ]. To model these relationships, different ML techniques can be employed, such as Random Forests (RF) and SVM [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Deep Learning models for predicting ALK-5 inhibition

et al. 2021

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Computational methods have been widely used in drug design. The recent developments in machine learning techniques and the ever-growing chemical and biological databases are fertile ground for discoveries in this area. In this study, we evaluated the performance of Deep Learning models in comparison to Random Forest, and Support Vector Regression for predicting the biological activity (pIC50) of ALK-5 inhibitors as candidates to treat cancer. The generalization power of the models was assessed by internal and external validation procedures. A deep neural network model obtained the best performance in this comparative study, achieving a coefficient of determination of 0.658 on the external validation set with mean square error and mean absolute error of 0.373 and 0.450, respectively. Additionally, the relevance of the chemical descriptors for the prediction of biological activity was estimated using Permutation Importance. We can conclude that the forecast model obtained by the deep neural network is suitable for the problem and can be employed to predict the biological activity of new ALK-5 inhibitors.

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“…HER2-positive tumors display an overexpression or amplification of the HER2 oncogene and can be clinically treated with the anti-HER2 monoclonal antibody trastuzumab, in combination with conventional chemotherapy, improving the survival rate by 30% [9,10,11,12].…”

Section: Introductionmentioning

confidence: 99%

p63 at the Crossroads between Stemness and Metastasis in Breast Cancer

Gatti

Bongiorno-Borbone

Fernanda

et al. 2019

IJMS

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After lung cancer, breast cancer (BC) is the most frequent cause of cancer death among women, worldwide. Although advances in screening approaches and targeted therapeutic agents have decreased BC incidence and mortality, over the past five years, triple-negative breast cancer (TNBC) remains the breast cancer subtype that displays the worst prognosis, mainly due to the lack of clinically actionable targets. Genetic and molecular profiling has unveiled the high intrinsic heterogeneity of TNBC, with the basal-like molecular subtypes representing the most diffuse TNBC subtypes, characterized by the expression of basal epithelial markers, such as the transcription factor p63. In this review, we will provide a broad picture on the physiological role of p63, in maintaining the basal epithelial identity, as well as its involvement in breast cancer progression, emphasizing its relevance in tumor cell invasion and stemness.

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Studies on the Dual Activity of EGFR and HER-2 Inhibitors Using Structure-Based Drug Design Techniques

Cited by 9 publications

References 33 publications

Molecular mechanisms targeting drug-resistance and metastasis in colorectal cancer: Updates and beyond

Molecular mechanisms targeting drug-resistance and metastasis in colorectal cancer: Updates and beyond

Evaluating Deep Learning models for predicting ALK-5 inhibition

p63 at the Crossroads between Stemness and Metastasis in Breast Cancer

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