Development of a preoperative prediction nomogram for lymph node metastasis in colorectal cancer based on a novel serum miRNA signature and CT scans

DNA methylation biomarkers for predicting lymph node metastasis in colorectal cancer

Colorectal cancer is one of the most common cancers worldwide. Lymph node metastasis is an important marker of colorectal cancer progression and plays a key role in the evaluation of patient prognosis. Accurate preoperative assessment of lymph node metastasis is crucial for devising appropriate treatment plans. However, current clinical imaging methods have limitations in many aspects. Therefore, the discovery of a method for accurately predicting lymph node metastasis is crucial clinical decision-making. DNA methylation is a common epigenetic modification that can regulate gene expression, which also has an important impact on the development of colorectal cancer. It is considered to be a promising biomarker with good specificity and stability and has promising application in predicting lymph node metastasis in patients with colorectal cancer. This article reviews the characteristics and limitations of currently available methods for predicting lymph node metastasis in patients with colorectal cancer and discusses the role of DNA methylation as a biomarker.

Infiltrating characteristics and prognostic value of tertiary lymphoid structures in resected gastric neuroendocrine neoplasm patients

Objectives

Tertiary lymphoid structures (TLSs) are lymphocyte aggregates that play an anti-tumor role in most solid tumors. However, the functions of TLS in gastric neuroendocrine neoplasms (GNENs) remain unknown. This study aimed to determine the characteristics and prognostic values of TLS in resected GNEN patients.

Methods

Haematoxylin-eosin, immunohistochemistry (IHC) and multiple fluorescent IHC staining were used to assess TLS to investigate the correlation between TLSs and clinicopathological characteristics and its prognostic value.

Results

Tertiary lymphoid structures were identified in 84.3% of patients with GNEN. They were located in the stromal area or outside the tumor tissue and mainly composed of B and T cells. A high density of TLSs promoted an anti-tumor immune response in GNEN. CD15+ TANs and FOXP3+ Tregs in TLSs inhibited the formation of TLSs. High TLS density was significantly associated with prolonged recurrence-free survival (RFS) and overall survival (OS) of GNENs. Univariate and multivariate Cox regression analyses revealed that TLS density, tumor size, tumor-node-metastasis (TNM) stage and World Health Organisation (WHO) classification were independent prognostic factors for OS, whereas TLS density, tumor size and TNM stage were independent prognostic factors for RFS. Finally, OS and RFS nomograms were developed and validated, which were superior to the WHO classification and the TNM stage.

Conclusion

Tertiary lymphoid structures were mainly located in the stromal area or outside the tumor area, and high TLS density was significantly associated with the good prognosis of patients with GNEN. Incorporating TLS density into a nomogram may improve survival prediction in patients with resected GNEN.

Dissecting the heterogeneities of the tumor microenvironment between metastatic and nonmetastatic primary colorectal cancer patients by single-cell RNA sequencing

AIMS

One of the main factors hampering the long-term prognosis of colorectal cancer (CRC) patients is distant metastasis. However, the driving factors of CRC metastasis have not been clarified at the single-cell level, which limits the in-depth study of accurate prediction and prevention of CRC metastasis to improve the prognosis.

MATERIALS AND METHODS

Heterogeneities in the tumor microenvironment (TME) between metastatic and nonmetastatic CRC were investigated by single-cell RNA (scRNA) sequencing data. In detail, 50,462 single cells from 20 primary CRC samples, including 40,910 cells from nonmetastatic CRC (M0 group) and 9552 cells from metastatic CRC (M1 group), were systematically analyzed in this study.

KEY FINDINGS

Based on the single-cell atlas, we revealed that cancer cells and fibroblasts accounted for relatively high proportions in metastatic CRC compared with nonmetastatic CRC. Moreover, two specific cancer cell subtypes (FGGY⁺SLC6A6⁺ and IGFBP3⁺KLK7⁺ cancer cells) and three specific fibroblast subtypes (ADAMTS6⁺CAPG⁺, PIM1⁺SGK1⁺ and CA9⁺UPP1⁺ fibroblasts) in metastatic CRC were identified. The functional and differentiation characteristics of these specific cell subclusters were elucidated by enrichment and trajectory analyses.

SIGNIFICANCE

These results provide fundamental knowledge for future in-depth research to screen effective methods and drugs to predict and prevent CRC metastasis to improve prognosis.

Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancer

The current staging method is inadequate to identify high-risk recurrence patients with stage II colon cancer (CC). Using a systematic and comprehensive-biomarker discovery and validation method, we aimed to construct a lncRNA-based signature to improve the prognostic prediction of stage II CC. We identified 1,377 differently expressed lncRNAs by analyzing 16 paired stage II CC tumor tissue and adjacent normal mucosal tissue from the TCGA dataset. Subsequently, using a univariable and step multivariable Cox regression model, we trained an 11-lncRNA signature in the training cohort (n = 141), which could divide patients into high-risk and low-risk groups (AUC at 3 years = 0.801, 95% CI: 0.724-0.877; AUC at 5 years = 0.801, 95% CI: 0.718-0.885). Significantly, patients in the high-risk group had poorer recurrence-free survival (RFS) compared with the low-risk group (log-rank test, P < 0.001 in the training cohort). This lncRNA-based signature was further confirmed in the validation cohort (P < 0.001). Multivariate Cox regression and stratified survival analyses showed that the prognostic value of this signature was independent of other clinicopathological risk factors (CEA, T stage, and chemotherapy). Time-dependent receiver operating characteristic (ROC) analysis demonstrated that this signature had better prognostic ability than any other clinical risk factors or single lncRNAs (all P < 0.05). A nomogram was constructed for clinical use, which integrated both the lncRNA-based signature and clinical risk factors (CEA and T stage) and performed well in the calibration plots. Altogether, our lncRNA-based signature was an independent prognostic factor and possessed a stronger predictive power compared with the currently used clinicopathological risk factors when predicting the recurrence of patients with stage II CC. Collectively, this lncRNA-based signature might facilitate individualized treatment decisions and postoperative counseling, ultimately contributing to improved survival.

A novel DNA methylation marker to identify lymph node metastasis of colorectal cancer

Lymph node metastasis (LNM) of colorectal cancer (CRC) is an important factor for both prognosis and treatment. Given the deficiencies of conventional tests, we aim to discover novel DNA methylation markers to efficiently identify LNM status of CRC. In this study, genome-wide methylation sequencing was performed in a cohort (n=30) using fresh CRC tissue to discover differentially methylated markers. These markers were subsequently validated with fluorescence quantitative PCR in a cohort (n=221), and the optimal marker was compared to conventional diagnostic methods. Meanwhile, immunohistochemistry was used to verify the effectiveness of the antibody corresponding to this marker in a cohort (n=56). LBX2 achieved an AUC of 0.87, specificity of 87.3%, sensitivity of 75.7%, and accuracy of 81.9%, which outperformed conventional methods including imaging (CT, PET-CT) with an AUC of 0.52, CA199 with an AUC of 0.58, CEA with an AUC of 0.56. LBX2 was also superior to clinicopathological indicators including the depth of tumor invasion and lymphatic invasion with an AUC of 0.61and 0.63 respectively. Moreover, the AUC of LBX2 antibody was 0.84, which was also better than these conventional methods. In conclusion, A novel methylation marker LBX2 could be used as a simple, cost-effective, and reliable diagnostic method for LNM of CRC.

Highly Sensitive Exosome Detection for Early Diagnosis of Pancreatic Cancer Using Immunoassay Based on Hierarchical Surface-Enhanced Raman Scattering Substrate

Exosomes have emerged as potential biomarkers for pancreatic cancer (PaC). However, it is still challenging to get quantitative detection of exosomes with the specific surface receptors. In this study, a highly sensitive detection system is first constructed for the direct quantitation of specific exosomes in real samples using hierarchical surface-enhanced Raman scattering substrate (H-SERS substrate) and rapid enrichment strategy magnetic beads @ exosomes @ SERS detection probes (MEDP). It is found that the detection system (MEDP @ H-SERS substrate) could provide a 3.5 times higher SERS intensity compared with MEDP sandwich immunocomplex only. Moreover, LRG1-positive exosomes (LRG1-Exos) and GPC1-positive exosomes (GPC1-Exos) are chosen to distinguish PaC through exosome proteomics and database screening. The lower limit of detection (LOD) is 15 particles µL-1 using the MEDP @ H-SERS substrate. Significantly, the detection in clinical samples shows that the innovative combination of LRG1-Exos and GPC1-Exos could improve the diagnostic efficiency of PaC, with an area under the operating characteristic curve (AUC) of 0.95. Even for the early-stage PaC, the diagnostic accuracy is still high (AUC = 0.95). Collectively, the findings indicate that the MEDP @ H-SERS substrate has great potential for the early diagnosis of PaC.

A model of multiple tumor marker for lymph node metastasis assessment in colorectal cancer: a retrospective study

Background

Assessment of colorectal cancer (CRC) lymph node metastasis (LNM) is critical to the decision of surgery, prognosis, and therapy strategy. In this study, we aimed to develop and validate a multiple tumor marker nomogram for predicting LNM in CRC patients.

Methods

A total of 674 patients who met the inclusion criteria were collected and randomly divided into primary cohort and internal test cohort at a ratio of 7:3. An external test cohort enrolled 178 CRC patients from the West China Hospital. Clinicopathologic variables were obtained from electronic medical records. The least absolute shrinkage and selection operator (LASSO) and interquartile range analysis were carried out for variable dimensionality reduction and feature selection. Multivariate logistic regression analysis was conducted to develop predictive models of LNM. The performance of the established models was evaluated by the receiver operating characteristic (ROC) curve, calibration belt, and clinical usefulness.

Results

Based on minimum criteria, 18 potential features were reduced to six predictors by LASSO and interquartile range in the primary cohort. The model demonstrated good discrimination and ROC curve (AUC = 0.721 in the internal test cohort, AUC = 0.758 in the external test cohort) in LNM assessment. Good calibration was shown for the probability of CRC LNM in the internal and external test cohorts. Decision curve analysis illustrated that multi-tumor markers nomogram was clinically useful.

Conclusions

The study proposed a reliable nomogram that could be efficiently and conveniently utilized to facilitate the assessment of individually-tailored LNM in patients with CRC, complementing imaging and biopsy tests.

A Six-microRNA Signature Nomogram for Preoperative Prediction of Tumor Deposits in Colorectal Cancer

Purpose

Tumor deposits (TDs) are acknowledged negative prognostic factors in colorectal cancer (CRC), and their pathogenesis remains a puzzle. This study aimed to construct and validate a nomogram available for preoperative TDs prediction in CRC patients.

Patients and Methods

Patients from the Surveillance, Epidemiology, and End Results (SEER) and the cancer genome atlas (TCGA) databases were randomly divided into training and validation sets according to the sample size ratio of 7:3. Univariate logistic regression was performed for identifying differentially expressed microRNAs between TDs and non-TDs. Nomograms for TDs prediction were developed from the multivariate logistic regression model with least absolute shrinkage and selection operator and were validated internally in terms of accuracy, calibration, and clinical utility. Based on the target genes, pathways tightly associated with TDs were selected using enrichment analysis.

Results

Six clinicopathologic factors and expressions of six microRNAs (miR-614, miR-1197, miR-4770, miR-3136, miR-3173, and miR-4636) differed significantly between TDs and non-TDs CRC patients from the SEER and TCGA training sets. We compared potential prediction discrimination between two nomograms: a clinicopathologic nomogram and a six-microRNA signature nomogram. The six-microRNA signature nomogram revealed better accuracy than the clinicopathologic one for TDs prediction (AUC values of 0.96 and 0.93 in the validation cohort). The calibration plots and decision curve analysis demonstrated that the six-microRNA signature nomogram had better validity and a greater prognostic benefit versus the clinicopathologic one for TDs prediction. Calcium signaling pathways were closely associated with roles of the six microRNAs in TDs of CRC patients.

Conclusion

The six-microRNA signature nomogram can be used as an efficient tool for preoperative TDs prediction in CRC patients.

Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer

Background

We aimed to develop a radiomic model based on pre-treatment computed tomography (CT) to predict the pathological complete response (pCR) in patients with rectal cancer after neoadjuvant treatment and tried to integrate our model with magnetic resonance imaging (MRI)-based radiomic signature.

Methods

This was a secondary analysis of the FOWARC randomized controlled trial. Radiomic features were extracted from pre-treatment portal venous-phase contrast-enhanced CT images of 177 patients with rectal cancer. Patients were randomly allocated to the primary and validation cohort. The least absolute shrinkage and selection operator regression was applied to select predictive features to build a radiomic signature for pCR prediction (rad-score). This CT-based rad-score was integrated with clinicopathological variables using gradient boosting machine (GBM) or MRI-based rad-score to construct comprehensive models for pCR prediction. The performance of CT-based model was evaluated and compared by receiver operator characteristic (ROC) curve analysis. The LR (likelihood ratio) test and AIC (Akaike information criterion) were applied to compare CT-based rad-score, MRI-based rad-score and the combined rad-score.

Results

We developed a CT-based rad-score for pCR prediction and a gradient boosting machine (GBM) model was built after clinicopathological variables were incorporated, with improved AUCs of 0.997 [95% CI 0.990–1.000] and 0.822 [95% CI 0.649–0.995] in the primary and validation cohort, respectively. Moreover, we constructed a combined model of CT- and MRI-based radiomic signatures that achieve better AIC (75.49 vs. 81.34 vs.82.39) than CT-based rad-score (P = 0.005) and MRI-based rad-score (P = 0.003) alone did.

Conclusions

The CT-based radiomic models we constructed may provide a useful and reliable tool to predict pCR after neoadjuvant treatment, identify patients that are appropriate for a 'watch and wait' approach, and thus avoid overtreatment. Moreover, the CT-based radiomic signature may add predictive value to the MRI-based models for clinical decision making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02919-x.

NAT1 is a critical prognostic biomarker and inhibits proliferation of colorectal cancer through modulation of PI3K/Akt/mTOR

The aim of this study was to analyze the correlations between NAT1 and clinicopathological features of and prognosis in colorectal cancer (CRC). RNA sequencing data and clinical information were retrieved from The Cancer Genome Atlas database. Wilcoxon test, logistic regression and Kaplan-Meier method were used to estimate the association between NAT1 and prognosis in CRC. In vitro experiments were conducted to confirm the role of NAT1. NAT1 is significantly less expressed in CRC and independently associated with poor prognosis in CRC patients. The authors further confirmed that expression of NAT1 was significantly lower in SW116 colon cancer cells than in NCM460 cells. Overexpressed NAT1 obviously inhibited the growth of CRC cells by downregulating phosphorylation of the PI3K/Akt/mTOR signaling pathway. NAT1 may be a potential therapeutic target for CRC.

Development and validation of a collagen signature-based nomogram for preoperatively predicting lymph node metastasis and prognosis in colorectal cancer

Background

Current preoperative evaluation approaches cannot provide adequate information for the prediction of lymph node (LN) metastasis in colorectal cancer (CRC). Collagen alterations in the tumor microenvironment affect the progression of tumor cells. To more accurately assess the LN status of CRC preoperatively, we developed and validated a collagen signature-based nomogram for predicting LN metastasis in CRC.

Methods

In total, 342 consecutive CRC patients were assigned to the training and validation cohorts. A total of 148 fully quantitative collagen features were extracted based on preoperative biopsies using multiphoton imaging, and the least absolute shrinkage and selection operator method was utilized to construct the collagen signature. A collagen signature-based nomogram was developed by multivariable logistic regression in the training cohort. Nomogram performance was evaluated for its discrimination, calibration, and clinical usefulness and then validated in the validation cohort. The prognostic values of the nomogram were also evaluated.

Results

A seven-feature-based collagen signature was built. We found that the collagen signature showed a significant association with LN metastasis in CRC. Additionally, a nomogram incorporating preoperative tumor differentiation, computed tomography-reported T stage and LN status, carcinoembryonic antigen level, carbohydrate antigen 19-9 level and collagen signature was developed. This nomogram had good discrimination and calibration, with AUROCs of 0.826 and 0.846 in the training and validation cohorts, respectively, and had a sensitivity of 86.5%, a specificity of 68.2%, an accuracy of 76.9%, a negative predictive value of 84.9%, and a positive predictive value of 71.2% for all patients. Compared to the clinicopathological model, which consisted of the clinicopathological risk factors for LN metastasis, the collagen signature-based nomogram demonstrated a significantly improved ability to discriminate LN status. Moreover, a nomogram-predicted high-risk subgroup had remarkably reduced survival compared with that of the low-risk subgroup.

Conclusions

The collagen signature in the tumor microenvironment of preoperative biopsies is an independent predictor for LN metastasis in CRC, and the collagen signature-based nomogram is helpful for tailored treatment and prognostic predictions in CRC preoperatively.

Exosome-transmitted miRNA-335-5p promotes colorectal cancer invasion and metastasis by facilitating EMT via targeting RASA1

Exosomal microRNA (miRNA) secretion has been characterized as a vital factor in intercellular communication among cancer cells. However, little is known about cancer-secreted miRNAs specifically involved in metastasis of colorectal cancer (CRC). Here, we found that exosomes derived from metastatic CRC cell line SW620 promoted migration, invasion, and epithelial-mesenchymal transition (EMT) of CRC cells. The profiling of exosome miRNAs revealed that microRNA (miR)-335-5p was highly expressed in exosomes from metastatic SW620 cells compared to those derived from primary SW480 cells. miR-335-5p was transmitted from metastatic SW620 cells to CRC cells via exosomes and promoted migration, invasion, and EMT of CRC cells. Moreover, exosome-transmitted miRNA-335-5p promotes CRC cell invasion and metastasis by facilitating EMT via targeting RAS p21 protein activator 1 (RASA1). Overexpression of RASA1 abolished the promotive effects of exosomal miR-335-5p on CRC cell migration, invasion, and EMT. Collectively, our data revealed that exosomal miR-335-5p derived from metastatic CRC cells promotes CRC cell invasion and metastasis by facilitating EMT via targeting RASA1, which may serve as a potential therapeutic target for CRC metastasis.

LAT1 and ASCT2 Related microRNAs as Potential New Therapeutic Agents against Colorectal Cancer Progression

The development and progression of colorectal cancer (CRC) have been associated with genetic and epigenetic alterations and more recently with changes in cell metabolism. Amino acid transporters are key players in tumor development, and it is described that tumor cells upregulate some AA transporters in order to support the increased amino acid (AA) intake to sustain the tumor additional needs for tumor growth and proliferation through the activation of several signaling pathways. LAT1 and ASCT2 are two AA transporters involved in the regulation of the mTOR pathway that has been reported as upregulated in CRC. Some attempts have been made in order to develop therapeutic approaches to target these AA transporters, however none have reached the clinical setting so far. MiRNA-based therapies have been gaining increasing attention from pharmaceutical companies and now several miRNA-based drugs are currently in clinical trials with promising results. In this review we combine a bioinformatic approach with a literature review in order to identify a miRNA profile with the potential to target both LAT1 and ASCT2 with potential to be used as a therapeutic approach against CRC.

Prediction of Lymph-Node Metastasis in Cancers Using Differentially Expressed mRNA and Non-coding RNA Signatures

Accurate prediction of lymph-node metastasis in cancers is pivotal for the next targeted clinical interventions that allow favorable prognosis for patients. Different molecular profiles (mRNA and non-coding RNAs) have been widely used to establish classifiers for cancer prediction (e.g., tumor origin, cancerous or non-cancerous state, cancer subtype). However, few studies focus on lymphatic metastasis evaluation using these profiles, and the performance of classifiers based on different profiles has also not been compared. Here, differentially expressed mRNAs, miRNAs, and lncRNAs between lymph-node metastatic and non-metastatic groups were identified as molecular signatures to construct classifiers for lymphatic metastasis prediction in different cancers. With this similar feature selection strategy, support vector machine (SVM) classifiers based on different profiles were systematically compared in their prediction performance. For representative cancers (a total of nine types), these classifiers achieved comparative overall accuracies of 81.00% (67.96-92.19%), 81.97% (70.83-95.24%), and 80.78% (69.61-90.00%) on independent mRNA, miRNA, and lncRNA datasets, with a small set of biomarkers (6, 12, and 4 on average). Therefore, our proposed feature selection strategies are economical and efficient to identify biomarkers that aid in developing competitive classifiers for predicting lymph-node metastasis in cancers. A user-friendly webserver was also deployed to help researchers in metastasis risk determination by submitting their expression profiles of different origins.

Regulators at Every Step-How microRNAs Drive Tumor Cell Invasiveness and Metastasis

Tumor cell invasiveness and metastasis are the main causes of mortality in cancer. Tumor progression is composed of many steps, including primary tumor growth, local invasion, intravasation, survival in the circulation, pre-metastatic niche formation, and metastasis. All these steps are strictly controlled by microRNAs (miRNAs), small non-coding RNA that regulate gene expression at the post-transcriptional level. miRNAs can act as oncomiRs that promote tumor cell invasion and metastasis or as tumor suppressor miRNAs that inhibit tumor progression. These miRNAs regulate the actin cytoskeleton, the expression of extracellular matrix (ECM) receptors including integrins and ECM-remodeling enzymes comprising matrix metalloproteinases (MMPs), and regulate epithelial-mesenchymal transition (EMT), hence modulating cell migration and invasiveness. Moreover, miRNAs regulate angiogenesis, the formation of a pre-metastatic niche, and metastasis. Thus, miRNAs are biomarkers of metastases as well as promising targets of therapy. In this review, we comprehensively describe the role of various miRNAs in tumor cell migration, invasion, and metastasis.

Regulators at Every Step—How microRNAs Drive Tumor Cell Invasiveness and Metastasis

Tumor cell invasiveness and metastasis are the main causes of mortality in cancer. Tumor progression is composed of many steps, including primary tumor growth, local invasion, intravasation, survival in the circulation, pre-metastatic niche formation, and metastasis. All these steps are strictly controlled by microRNAs (miRNAs), small non-coding RNA that regulate gene expression at the post-transcriptional level. miRNAs can act as oncomiRs that promote tumor cell invasion and metastasis or as tumor suppressor miRNAs that inhibit tumor progression. These miRNAs regulate the actin cytoskeleton, the expression of extracellular matrix (ECM) receptors including integrins and ECM-remodeling enzymes comprising matrix metalloproteinases (MMPs), and regulate epithelial–mesenchymal transition (EMT), hence modulating cell migration and invasiveness. Moreover, miRNAs regulate angiogenesis, the formation of a pre-metastatic niche, and metastasis. Thus, miRNAs are biomarkers of metastases as well as promising targets of therapy. In this review, we comprehensively describe the role of various miRNAs in tumor cell migration, invasion, and metastasis.

Two machine learning methods identify a metastasis-related prognostic model that predicts overall survival in medulloblastoma patients

Approximately 30% of medulloblastoma (MB) patients exhibit metastasis at initial diagnosis, which often leads to a poor prognosis. Here, by using univariate Cox regression analysis, two machine learning methods (Lasso-penalized Cox regression and random survival forest-variable hunting (RSF-VH)), and multivariate Cox regression analysis, we established two metastasis-related prognostic models, including the 47-mRNA-based model based on the Lasso method and the 21-mRNA-based model based on the RSF-VH method. In terms of the results of the receiver operating characteristic (ROC) curve analyses, we selected the 47-mRNA metastasis-associated model with the higher area under the curve (AUC). The 47-mRNA-based prognostic model could classify MB patients into two subgroups with different prognoses. The ROC analyses also suggested that the 47-mRNA metastasis-associated model may have a better predictive ability than MB subgroup. Multivariable Cox regression analysis demonstrated that the 47-mRNA-based model was independent of other clinical characteristics. In addition, a nomogram comprising the 47-mRNA-based model was built. The results of ROC analyses suggested that the nomogram had good discrimination ability. Our 47-mRNA metastasis-related prognostic model and nomogram might be an efficient and valuable tool for overall survival (OS) prediction and provide information for individualized treatment decisions in patients with MB.

Development of a Novel Serum Exosomal MicroRNA Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Esophageal Squamous Cell Carcinoma

Preoperative prediction of lymph node (LN) metastasis is accepted as a crucial independent risk factor for treatment decision-making for esophageal squamous cell carcinoma (ESCC) patients. Our study aimed to establish a non-invasive nomogram to identify LN metastasis preoperatively in ESCC patients. Construction of the nomogram involved three sequential phases with independent patient cohorts. In the discovery phase (N = 20), LN metastasis-associated microRNAs (miRNAs) were selected from next-generation sequencing (NGS) assay of human ESCC serum exosome samples. In the training phase (N = 178), a nomogram that incorporated exosomal miRNA model and clinicopathologic was developed by multivariate logistic regression analysis to preoperatively predict LN status. In the validation phase (n = 188), we validated the predicted nomogram's calibration, discrimination, and clinical usefulness. Four differently expressed miRNAs (chr 8-23234-3p, chr 1-17695-5p, chr 8-2743-5p, and miR-432-5p) were tested and selected in the serum exosome samples from ESCC patients who have or do not have LN metastasis. Subsequently, an optimized four-exosomal miRNA model was constructed and validated in the clinical samples, which could effectively identify ESCC patients with LN metastasis, and was significantly superior to preoperative computed tomography (CT) report. In addition, a clinical nomogram consisting of the four-exosomal miRNA model and CT report was established in training cohort, which showed high predictive value in both training and validation cohorts [area under the receiver operating characteristic curve (AUC): 0.880 and 0.869, respectively]. The Hosmer–Lemeshow test and decision curve analysis implied the nomogram's clinical applicability. Our novel non-invasive nomogram is a robust prediction tool with promising clinical potential for preoperative LN metastasis prediction of ESCC patients, especially in T1 stage.

A deep learning nomogram kit for predicting metastatic lymph nodes in rectal cancer

Background

Preoperative diagnoses of metastatic lymph nodes (LNs) by the most advanced deep learning technology of Faster Region‐based Convolutional Neural Network (Faster R‐CNN) have not yet been reported.

Materials and Methods

In total, 545 patients with pathologically confirmed rectal cancer between January 2016 and March 2019 were included and were randomly allocated with a split ratio of 2:1 to the training and validation sets, respectively. The MRI images for metastatic LNs were evaluated by Faster R‐CNN. Multivariate regression analyses were used to develop the predictive models. Faster R‐CNN nomograms were constructed based on the multivariate analyses in the training sets and were validated in the validation sets.

Results

The Faster R‐CNN nomogram for predicting metastatic LN status contained predictors of age, metastatic LNs by Faster R‐CNN and differentiation degrees of tumors, with areas under the curves (AUCs) of 0.862 (95% CI: 0.816‐0.909) and 0.920 (95% CI: 0.876‐0.964) in the training and validation sets, respectively. The Faster R‐CNN nomogram for predicting LN metastasis degree contained predictors of metastatic LNs by Faster R‐CNN and differentiation degrees of tumors, with AUCs of 0.859 (95% CI: 0.804‐0.913) and 0.886 (95% CI: 0.822‐0.950) in the training and validation sets, respectively. Calibration plots and decision curve analyses demonstrated good calibrations and clinical utilities. The two nomograms were used jointly as a kit for predicting metastatic LNs.

Conclusion

The Faster R‐CNN nomogram kit exhibits excellent performance in discrimination, calibration, and clinical utility and is convenient and reliable for predicting metastatic LNs preoperatively.

Clinical trial registration: ChiCTR‐DDD‐17013842.

Construction of an immune-related genes nomogram for the preoperative prediction of axillary lymph node metastasis in triple-negative breast cancer

Immune system disorder is associated with metastasis of triple-negative breast cancers (TNBCs). A robust, individualized immune-related genes (IRGs)-based classifier was aimed to develop and validate in our study to precisely estimate the axillary lymph node (ALN) status preoperatively in patients with early-stage TNBC. We first analyzed RNA sequencing profiles in TNBC patients from The Cancer Genome Atlas database by using bioinformatics approaches, and screened 23 differentially expressed IRGs. A 9-gene panel was generated with an area under the curve (AUC) of 0.77 [95% confidence interval (95% CI), 0.68-0.87]. We detected the 9 ALN-status-related IRGs in the training set (n = 133) and developed a reduced and optimized five-IRGs signature, which effectively distinguished TNBC patients with ALN metastasis (AUC, 0.80; 95% CI, 0.65-0.86), and was superior to preoperative ultrasound-based ALN status (AUC, 0.73; 95% CI, 0.53-0.93). Predictive efficiency (AUC, 0.77; 95% CI 0.61-0.93) of this five-IRGs signature was validated in the validation set (n = 81). Furthermore, IRGs nomogram incorporated IRGs signature with US-based ALN status showed higher ALN status prediction efficacy than US-based ALN status and five-IRGs signature alone in both training and validation sets. IRGs nomogram may aid in identifying patients who can be exempted from axillary surgery.Novelty and impact: An immune-related genes (IRGs) nomogram was first developed and externally validated in our study, which incorporated the IRGs signature with ultrasound (US)-based axillary lymph nodes (ALN) status. IRGs nomogram is superior to IRGs signature alone for preoperative estimation of ALN metastasis in patients with triple-negative breast cancer (TNBC). It is a favourable biomarker for preoperatively predicting ALN metastasis risk and may aid in clinical decision-making in early-stage TNBCs.

Selection of microRNAs in extracellular vesicles for diagnosis of malignant pleural mesothelioma by in vitro analysis

Malignant pleural mesothelioma (MPM) is a malignant tumor which is a challenge for diagnosis and is associated with a poor patient prognosis. Thus, early diagnostic interventions will improve the quality of life and life expectancy of these patients. Recently, cellular microRNAs (miRNAs) have been found to be involved in maintaining homeostasis, and abnormal miRNA expression has often been observed in various diseases including cancer. Extracellular vesicles (EVs) released by many cells contain proteins and nucleic acids. miRNAs are secreted from all cells via EVs and circulate throughout the body. In this study, culture media were passed sequentially through membrane filters 220–50 nm in size, and EVs with diameters of 50 to 220 nm (EVcap50/220) were collected. miRNAs (EV50-miRNAs) in EVcap50/220 were purified, and microarray analysis was performed. EV50-miRNA expression profiles were compared between MPM cells and a normal pleural mesothelial cell line, and six EV50-miRNAs were selected for further investigation. Of these, hsa-miR-193a-5p and hsa-miR-551b-5p demonstrated higher expression in MPM-derived EVcap50/220. These miRNAs reduced the expression of several genes involved in cell-cell interactions and cell-matrix interactions in normal pleural mesothelial cells. Our data suggest that hsa-miR-193a-5p and hsa-miR-551b-5p in EVcap50/220 could be diagnostic markers for MPM.

MicroRNAs for Diagnosis and Treatment of Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer worldwide, with high morbidity and mortality rates. The diagnosis and treatment of CRC have the most significant value for disease- free survival. Early diagnosis and early surgical resection are generally considered to be the most effective ways to reduce CRC mortality. In the past few years, many researchers have focused on the role of microRNAs in different tumors, making the functions of microRNAs gradually clear. The present study reviews the role of microRNAs in the diagnosis and treatment of colorectal cancer. Compared with the usual diagnosis methods and biomarker, circulating microRNAs can be promising new effective biomarkers for CRC diagnosis and treatment.

Liquid Biopsy of Extracellular Vesicle-Derived miR-193a-5p in Colorectal Cancer and Discovery of Its Tumor-Suppressor Functions

Previously, abnormal extracellular vesicle (EV) sorting of miR-193a was identified in colorectal cancer (CRC) progression. Although a reduced level of miR-193a-5p in plasma/serum has been reported in many different types of cancer, the EV-derived miR-193a-5p level in CRC and its potential application as a minimally invasive biomarker are still unknown. Here, we evaluated the circulating EV-derived miR-193a-5p expression levels in a cohort of 101 participants by real-time quantitative polymerase chain reaction (RT-qPCR). We found that plasma EV-miR-193a-5p decreased significantly in CRC patients as compared with precancerous colorectal adenoma (CA) and non-cancerous control (NC) individuals. The circulating EV-miR-193a-5p showed an area under the receiver operating characteristic curve (AUC) of 0.740 in distinguishing CRC from CA and an AUC of 0.759 in distinguishing CRC from NC. Furthermore, the suppression on CRC cells of miR-193a-5p was verified by transwell, MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium), EdU, RT-qPCR, and western blotting. Bioinformatic analysis predicted 32 genes, which were the most likely miR-193a-5p targeted and mainly focused on tumor progression. Among them, we revealed that miR-193a-5p could inhibit CRC migration and invasion via targeting tumor-associated genes like CUT-like homeobox 1 (CUX1) and intersectin 1 (ITSN1). In conclusion, miR-193a-5p could suppress CRC development, and decreased plasma EV-miR-193a-5p could be a promising biomarker for human CRC detection.

MicroRNAs in Colon and Rectal Cancer - Novel Biomarkers from Diagnosis to Therapy

Colorectal cancer (CRC) is one of the most common cancers and a significant cause of tumor- related deaths worldwide. Traditional biomarkers, such as CEA and CA199, are not sensitive enough to provide useful information for early diagnosis and treatment and are rather used to track the clinical progression of the disease. There is growing evidence that microRNAs (miRNA) are potentially superior to traditional biomarkers as promising non-invasive biomarkers for the timely diagnosis and prediction of prognosis or treatment response in the management of CRC. In this review, the latest studies on the dysregulation of miRNAs expression in CRC and the potential for miRNAs to serve as biomarkers were collected. Given the limitations of miRNA, as discussed in this paper, its clinical applications as a diagnostic biomarker should be limited to use in combination with other biomarkers. Further research is necessary to elucidate the clinical applications of miRNA in therapy for CRC.

Unique metastasis-associated lncRNA signature optimizes prediction of tumor relapse in lung adenocarcinoma

Background

Local relapses and metastases are primary causes of death in lung cancer patients. In the present study, we aimed to develop a prognostic signature based on metastasis‐associated lncRNAs in patients with lung adenocarcinoma (LUAD).

Methods

Firstly, the potential metastasis‐associated lncRNAs were identified by analyzing high‐throughput data from The Cancer Genome Atlas (TCGA), and based on which, an lncRNA signature was constructed for prediction of relapse in LUAD patients using Cox proportional hazards regression analysis. Moreover, the prognostic performance of the lncRNA signature was evaluated using Kaplan‐Meier survival analysis, time‐dependent receiver operating characteristic (ROC) curve and Cox analysis, respectively. In addition, the potential metastasis‐associated function of these six lncRNAs was confirmed by lncRNA over‐expression or depletion and in vitro transwell assays in LUAD cells.

Results

An lncRNA signature consisting of six most important prognostic factors (LINC01819, ZNF649‐AS1, HNF4A‐AS1, FAM222A‐AS1, LINC02323 and LINC00672) was developed. The signature was an independent predictor for patients' relapse‐free survival (RFS), which could provide higher tumor relapse prediction capability compared with the TNM staging system at three years and five years, respectively (P = 0.0209 and P = 0.0468). Furthermore, the combination of this lncRNA signature and TNM stage had better prognostic value than TNM stage alone at three and five years, respectively (P = 0.0006 and P = 0.0096). Additionally, all the lncRNAs of the signature had a regulatory role in the LUAD cell mobility.

Conclusions

This novel six‐lncRNA signature had considerable prognostic value for prediction of relapse in LUAD patients.

Key points

Prognostic value of a hypoxia-related microRNA signature in patients with colorectal cancer

Hypoxia has been particularly associated with poor prognosis in cancer patients. Recent studies have suggested that hypoxia-related miRNAs play a critical role in various cancers, including colorectal cancer (CRC). In the present study, we found 52 differentially expressed miRNAs in HT-29 cells under hypoxic conditions versus normoxic conditions by analyzing the profiles of miRNAs. Using Cox model, we developed a hypoxia-related miRNA signature consisting of four miRNAs, which could successfully discriminate high-risk patients in the Cancer Genome Atlas (TCGA) training cohort (n=381). The prognostic value of this signature was further confirmed in the TCGA testing cohort (n=190) and an independent validation cohort composed of formalin-fixed paraffin-embedded clinical CRC samples (n=220), respectively. Multivariable Cox regression and stratified survival analysis revealed this signature was an independent prognostic factor for CRC patients. Time-dependent receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) of this signature was significantly larger than that of any other clinical risk factors or single miRNA alone. A nomogram was constructed for clinical use, which incorporated both the miRNA signature and clinical risk factors and performed well in the calibration plots. Collectively, this novel hypoxia-related miRNA signature was an independent prognostic factor, and it possessed a stronger predictive power in identifying high-risk CRC patients than currently used clinicopathological features.

Association of the tumour stroma percentage in the preoperative biopsies with lymph node metastasis in colorectal cancer

BACKGROUND

Preoperative prediction of lymph node (LN) status is integral to determining the most appropriate treatment strategy for colorectal cancer (CRC). This study aimed to develop and validate a nomogram to predict LN metastasis in CRC preoperatively.

METHODS

A total of 530 patients were enrolled and divided into training and validation cohorts. The tumour stroma percentage (TSP) of the preoperative biopsies was assessed. The risk factors for LN metastasis were selected, and a nomogram was constructed subsequently. The performance of the nomogram was assessed by using the AUROC and the calibration curve, and then validated in the validation cohort.

RESULTS

High TSP was significantly associated with LN metastasis in both the training and validation cohorts. Computed tomography (CT)-reported T stage, CT-reported LN status, preoperative tumour differentiation, carcinoembryonic antigen, carbohydrate antigen 19-9 and TSP were independent predictors of LN metastasis in CRC. A nomogram incorporating the six predictors was constructed. The nomogram yielded good discrimination and calibration, with an AUROC of 0.846 (95% CI: 0.807-0.886) and 0.809 (95% CI: 0.745-0.872) in the training and validation cohorts, respectively.

CONCLUSIONS

Assessment of TSP in the preoperative biopsies provided additional information about the LN status. The nomogram was useful for tailored therapy in CRC preoperatively.

A Novel Saliva-Based miRNA Signature for Colorectal Cancer Diagnosis

Salivary microRNAs (miRNAs) are of high interest as diagnostic biomarkers for non-oral cancer. However, little is known about their value for colorectal cancer (CRC) detection. Our study aims to characterize salivary miRNAs in order to identify non-invasive markers for CRC diagnosis. The screening of 754 miRNAs was performed in saliva samples from 14 CRC and 10 healthy controls. The differential expressed miRNAs were validated by RT-qPCR in 51 CRC, 19 adenomas and 37 healthy controls. Receiver operating characteristic (ROC) curves and logistic regression models were performed to analyze the clinical value of these miRNAs. Twenty-two salivary miRNAs were significantly deregulated in CRC patients vs. healthy individuals (p < 0.05) in the discovery phase. From those, five upregulated miRNAs (miR-186-5p, miR-29a-3p, miR-29c-3p, miR-766-3p, and miR-491-5p) were confirmed to be significantly higher in the CRC vs. healthy group (p < 0.05). This five-miRNA signature showed diagnostic value (72% sensitivity, 66.67% specificity, AUC = 0.754) to detect CRC, which was even higher in combination with carcinoembryonic antigen (CEA) levels. Overall, after the first global characterization of salivary miRNAs in CRC, a five-miRNA panel was identified as a promising tool to diagnose this malignancy, representing a novel approach to detect cancer-associated epigenetic alterations using a non-invasive strategy.

Functions and mechanisms of miR-186 in human cancer

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the post-transcriptional level. Mounting evidence suggests the involvement of miRNAs in carcinogenesis and the development of human cancer. Among the miRNAs, miR-186 has been extensively studied in various cancers. The expression of miR-186 in tissues varies depending on the type of cancer and miR-186 in tissues and body fluids may serve as a marker for the diagnosis and prognosis of cancers. Various biological processes in human cancer are affected by miR-186. Additionally, miR-186 itself is regulated by several factors. Thus, this evidence highlights the potential value of miR-186 in the diagnosis, prognosis and treatment of human cancer.

Calcium-Activated Chloride Channel A4 (CLCA4) Plays Inhibitory Roles in Invasion and Migration Through Suppressing Epithelial-Mesenchymal Transition via PI3K/AKT Signaling in Colorectal Cancer

Background

Calcium-activated chloride channel A4 (CLCA4) is known as a tumor suppressor which contributes to the progression of a number of types of malignant tumors. However, little is known about the functional roles of CLCA4 in colorectal cancer (CRC).

Material/Methods

In this study, the expression patterns and dysregulation of mRNAs in CRC tissues were profiled by analyzing GSE21510 datasets from Gene Expression Omnibus database which contains 104 primary hepatocellular carcinoma tissues and 24 normal liver tissues, and by performing Kaplan-Meier analysis of TCGA data. Additionally, immunohistochemistry and quantitative real-time polymerase chain reaction (qRT-PCR) were performed using clinical tissues collected at our institute. In order to explore the functional role of CLCA4, gain-of-function cell models were constructed in SW620 and LoVo cells. Wound healing assay and Transwell assay were carried out to access the cell migration and invasion ability.

Results

It was found that CLCA4 was an independent predictor for overall survival and lymph node metastasis. Additionally, immunohistochemistry and qRT-PCR results of the clinical tissues collected as part of our study further confirmed this correlation. In vitro experiments demonstrated that over-expression of CLCA4 could inhibit cell migration and invasion by suppressing epithelial-mesenchymal transition (EMT) via PI3K/ATK signaling and change the expression patterns of EMT markers in CLCA4-gain-of-function cell models.

Conclusions

CLCA4 inhibits migration and invasion by suppressing EMT via PI3K/ATK signaling and predicts favorable prognosis of CRC which may help to distinguish potential risk of lymph node metastasis in CRC.

A serum piRNA signature as promising non-invasive diagnostic and prognostic biomarkers for colorectal cancer

Purpose: Piwi-interacting RNAs (piRNAs) are a novel class of small non-coding RNAs, which are not easily degraded but detectable in human body fluids. Recent studies have shown that aberrant piRNA expression is a signature feature across multiple tumor types. However, the expressions of piRNAs in serum of tumor patients and their potential clinical values remain largely unclear. Patients and methods: High-throughput sequencing was performed to investigate the serum piRNA profiles, followed by evaluations in serum samples of 220 colorectal cancer (CRC) patients and 220 healthy controls using reverse transcription quantitative real-time PCR (RT-qPCR). Biomarker panels including piRNA-based Panel I and carcinoembryonic antigen (CEA)-based Panel II, were developed by logistic regression model, and their diagnostic potentials were compared. Fagan's nomogram was plotted to promote clinical application. Results: We identified five differentially expressed serum piRNAs (piR-001311, piR-004153, piR-017723, piR-017724 and piR-020365), which, when combined in the piRNA-based Panel I, outperformed the CEA-based Panel II (P<0.001) and could detect CRC with an area under the receiver operating characteristic curve of 0.867. In addition, Kaplan-Meier analysis showed that patients with low serum piR-017724 level had worse overall survival (OS) and progression-free survival (PFS). In multivariate Cox regression analysis, serum piR-017724 was an independent prognostic factor for OS and PFS (P<0.05). Conclusion: Our findings suggest serum piRNA expression signatures have potential for use as biomarkers for CRC detection and to predict prognosis at the time of diagnosis.

Relationship between Fusobacterium nucleatum, inflammatory mediators and microRNAs in colorectal carcinogenesis

AIM

To examine the effect of Fusobacterium nucleatum (F. nucleatum) on the microenvironment of colonic neoplasms and the expression of inflammatory mediators and microRNAs (miRNAs).

METHODS

Levels of F. nucleatum DNA, cytokine gene mRNA (TLR2, TLR4, NFKB1, TNF, IL1B, IL6 and IL8), and potentially interacting miRNAs (miR-21-3p, miR-22-3p, miR-28-5p, miR-34a-5p, miR-135b-5p) were measured by quantitative polymerase chain reaction (qPCR) TaqMan^® assays in DNA and/or RNA extracted from the disease and adjacent normal fresh tissues of 27 colorectal adenoma (CRA) and 43 colorectal cancer (CRC) patients. KRAS mutations were detected by direct sequencing and microsatellite instability (MSI) status by multiplex PCR. Cytoscape v3.1.1 was used to construct the postulated miRNA:mRNA interaction network.

RESULTS

Overabundance of F. nucleatum in neoplastic tissue compared to matched normal tissue was detected in CRA (51.8%) and more markedly in CRC (72.1%). We observed significantly greater expression of TLR4, IL1B, IL8, and miR-135b in CRA lesions and TLR2, IL1B, IL6, IL8, miR-34a and miR-135b in CRC tumours compared to their respective normal tissues. Only two transcripts for miR-22 and miR-28 were exclusively downregulated in CRC tumour samples. The mRNA expression of IL1B, IL6, IL8 and miR-22 was positively correlated with F. nucleatum quantification in CRC tumours. The mRNA expression of miR-135b and TNF was inversely correlated. The miRNA:mRNA interaction network suggested that the upregulation of miR-34a in CRC proceeds via a TLR2/TLR4-dependent response to F. nucleatum. Finally, KRAS mutations were more frequently observed in CRC samples infected with F. nucleatum and were associated with greater expression of miR-21 in CRA, while IL8 was upregulated in MSI-high CRC.

CONCLUSION

Our findings indicate that F. nucleatum is a risk factor for CRC by increasing the expression of inflammatory mediators through a possible miRNA-mediated activation of TLR2/TLR4.

Reduced Plasma Levels of Very-Long-Chain Dicarboxylic Acid 28:4 in Italian and Brazilian Colorectal Cancer Patient Cohorts

BACKGROUND

There are currently no blood-based biomarkers for early diagnosis of colorectal cancer. Previous research has suggested that very-long-chain dicarboxylic acid (VLCDCA) 28:4 might be such a biomarker.

METHODS

Using high-resolution mass spectrometry, we analyzed VLCDCA 28:4 in the plasma of colorectal cancer patients in Italian [n = 62] and Brazilian [n = 52] cohorts. Additionally, we investigated individuals diagnosed with familial adenomatous polyposis (FAP; n = 27), one of the most important clinical forms of inherited susceptibility to colorectal cancer. Results: Decrements in plasma levels of VLCDCA 28:4 were monitored in colorectal cancer patients. These decreases were independent of the stage of tumor development and the individual's age. However, no decrements in VLCDCA 28:4 were monitored in FAP patients.

CONCLUSIONS

The plasma levels of VLCDCA 28:4 represent a potential biomarker of sporadic colorectal cancer. In addition, it is possible that resupply of this anti-inflammatory lipid may represent a new therapeutic strategy for CRC and inflammatory disorders.