Signatures of co-deregulated genes and their transcriptional regulators in colorectal cancer

Mastrogamvraki, Natalia; Zaravinos, Apostolos

doi:10.1038/s41540-020-00144-8

Cited by 25 publications

(15 citation statements)

References 139 publications

(166 reference statements)

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“…In this study, we provide the first evidence demonstrating that CTSE overexpression is significantly correlated with inferior clinical outcomes and acts as an unfavorable predictive biomarker for rectal cancer patients treated with preoperative CCRT. In addition, it has been reported that CTSE is upregulated in CRC tissue samples compared with normal controls [17], further supporting our findings.…”

Section: Discussionsupporting

confidence: 92%

CTSE Overexpression Is an Adverse Prognostic Factor for Survival among Rectal Cancer Patients Receiving CCRT

Chou

Chen

Tian

et al. 2021

Life

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The introduction of preoperative concurrent chemoradiotherapy (CCRT) increases the rate of anal preservation and allows tumor downstaging for clinical stage T3/T4 or node-positive rectal cancer patients. However, there is no precise predictive tool to verify the presence of residual tumor apart from surgical resection. The gastrointestinal (GI) tract not only digests nutrients but also coordinates immune responses. As the outermost layer of the GI tract, mucus plays a key role in mediating the interaction between the digestive and immune systems, and aberrant mucus mesh formation may cause chemoresistance by impeding drug delivery. However, the correlations among digestion-related genes, mucin synthesis, and chemoresistance remain poorly understood. In the present study, we evaluated genes related to digestion (GO: 0007586) and identified cathepsin E (CTSE), which is involved in immune regulation, as the most significantly upregulated gene associated with CCRT resistance in rectal cancer in a public transcriptome dataset (GSE35452). We recovered 172 records of rectal cancer patients receiving CCRT followed by surgical resection from our biobank and evaluated the expression level of CTSE using immunohistochemistry. The results revealed that tumors with CTSE overexpression were significantly correlated with pre-CCRT and post-CCRT positive nodal status (both p < 0.001), advanced pre-CCRT and post-CCRT tumor status (p < 0.001 and p = 0.002), perineural invasion (p = 0.023), vascular invasion (p < 0.001), and a lesser degree of tumor regression (p = 0.003). At the univariate level, CTSE overexpression was an adverse prognostic factor for all three endpoints: disease-specific survival (DSS), metastasis-free survival (MeFS) (both p < 0.0001), and local recurrence-free survival (LRFS) (p = 0.0001). At the multivariate level, CTSE overexpression remained an independent prognostic factor for poor DSS, MeFS (both p = 0.005), and LRFS (p = 0.019). Through bioinformatics analysis, we speculated that CTSE overexpression may confer CCRT resistance by forming a defensive mucous barrier. Taken together, these results suggest that CTSE overexpression is related to CCRT resistance and inferior survival in rectal cancer patients, highlighting the potential predictive and prognostic value of CTSE expression.

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Section: Discussionsupporting

confidence: 92%

CTSE Overexpression Is an Adverse Prognostic Factor for Survival among Rectal Cancer Patients Receiving CCRT

Chou

Chen

Tian

et al. 2021

Life

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“…LINCS datasets, along with others, have been used to identify repurposing candidates from drugs that can reverse the expression profiles of cancer-specific gene signatures (obtained by comparing expression of cancer cells with normal cells; refs. [83][84][85]. DNNs trained on drug-perturbed transcriptional profiles from LINCS have also been used to predict the therapeutic use category for drugs (e.g., vasodilator, antineoplastic) and to prioritize repurposing candidates by their chemical structural similarity with approved cancer drugs (86).…”

Section: Drug Repurposingmentioning

confidence: 99%

Artificial Intelligence in Cancer Research and Precision Medicine

Bhinder

Gilvary²,

Madhukar³

et al. 2021

Cancer Discovery

364

153

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Convolutional neural networks (CNN) have been the most popular deep learning architectures used for image classification in cancer ( Fig. 1 ). CNNs apply a series of nonlinear transformations to structured data (such as raw pixels of an image) to learn relevant features automatically, unlike conventional machine learning models that frequently require manual feature curation. On the fl ip side, it is diffi cult to tell what features are learned by the CNNs, making them what many have referred to as a "black box." One consequence is that images used for CNNs should be carefully prepro cessed to reduce the risk that the model learns from image artifacts. There are two major approaches for CNN models; one is transfer learning that uses images from a large collection of natural objects (such as in ImageNet) to train the initial layers of a model (where the model learns to identify general features such as shapes and edges) and then uses the diseasespecifi c data to fi ne-tune the training parameters in the last layers. The second variation of CNN is based on an autoencoder where the model learns background features from a subset of representative images and encodes a compressed representation of the basic features later used to initialize the CNN. In the CAMELYON16 Challenge-a crowdsourced competition to identify and classify lymph node metastasis in patients with breast cancer from whole slide images (WSI) of hematoxylin and eosin (H&E)-stained tumors-25 of the 32 submitted algorithms were CNNs, and the top 5 classifi cation models were exclusively based on transfer learning, which were GoogLeNet, ResNet, VGG-16 ( 2 ). Khosravi and colleagues trained and tested several state-of-the-art deep learning models to classify WSI from H&E-stained tumor tissues of The Cancer Genome Atlas (TCGA) cohort and reported on the

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“…Furthermore, high CDK1 expression is predominant in patients with resistance to 5-fluorouracil (5-Fu), a common CRC treatment, and it seems to reduce the effect of chemotherapy (Zhu et al, 2020). An upregulation of CDK1 in CRC has been also observed in response to other drugs such as: betaxol, penbutolol and propofol amongst others (Mastrogamvraki and Zaravinos, 2020).…”

Section: Cyclin-dependent Kinase Expression In Human Colorectal Cancermentioning

confidence: 99%

“…CDK2, 4 and 6 levels in CRC are closely related to the Rb protein hyperphosphorylation, which seems to promote cancer progression. CDK4/6 is usually amplified in colon tumors compared to healthy epithelium ( Mastrogamvraki and Zaravinos, 2020 ; Jardim et al, 2021 ). Abundant levels of CDK4 are especially observed in CRC patients with enhanced dysplasia and are correlated to increased tumor cell proliferation ( Zhang et al, 1997 ; Bartkova et al, 2001 ).…”

Section: Cyclin-dependent Kinase Expression In Human Colorectal Cancermentioning

confidence: 99%

Cyclin-Dependent Kinase Inhibitors and Their Therapeutic Potential in Colorectal Cancer Treatment

Thoma

Waldner

2021

Front. Pharmacol.

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Cyclin-dependent kinases (CDKs) are key players in cell cycle regulation. So far, more than ten CDKs have been described. Their direct interaction with cyclins allow progression through G1 phase, transitions to S and G2 phase and finally through mitosis (M). While CDK activation is important in cell renewal, its aberrant expression can lead to the development of malignant tumor cells. Dysregulations in CDK pathways are often encountered in various types of cancer, including all gastrointestinal (GI) tract tumors. This prompted the development of CDK inhibitors as novel therapies for cancer. Currently, CDK inhibitors such as CDK4/6 inhibitors are used in pre-clinical studies for cancer treatment. In this review, we will focus on the therapeutic role of various CDK inhibitors in colorectal cancer, with a special focus on the CDK4/6 inhibitors.

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Signatures of co-deregulated genes and their transcriptional regulators in colorectal cancer

Cited by 25 publications

References 139 publications

CTSE Overexpression Is an Adverse Prognostic Factor for Survival among Rectal Cancer Patients Receiving CCRT

CTSE Overexpression Is an Adverse Prognostic Factor for Survival among Rectal Cancer Patients Receiving CCRT

Artificial Intelligence in Cancer Research and Precision Medicine

Cyclin-Dependent Kinase Inhibitors and Their Therapeutic Potential in Colorectal Cancer Treatment

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