Risk Factors Predicting Colorectal Cancer Recurrence Following Initial Treatment: A 5-year Cohort Study

Prognostic models for colorectal cancer recurrence using carcinoembryonic antigen measurements

Objective

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. A considerable percentage of patients who undergo surgery with curative intent will experience cancer recurrence. Early identification of individuals with a higher risk of recurrence is crucial for healthcare professionals to intervene promptly and devise appropriate treatment strategies. In this study, we developed prognostic models for CRC recurrence using machine learning models on a limited number of CEA measurements.

Method

A dataset of 1927 patients diagnosed with Stage I-III CRC and referred to Zuyderland Hospital for surgery between 2008 and 2016 was utilized. Machine learning models were trained using this comprehensive dataset, which included demographic details, clinicopathological factors, and serial measurements of Carcinoembryonic Antigen (CEA). In this study, the predictive performance of these models was assessed, and the key prognostic factors influencing colorectal cancer (CRC) recurrence were pinpointed.

Result

Among the evaluated models, the gradient boosting classifier demonstrated superior performance, achieving an Area Under the Curve (AUC) score of 0.81 and a balanced accuracy rate of 0.73. Recurrence prediction was shown to be feasible with an AUC of 0.71 when using only five post-operative CEA measurements. Furthermore, key factors influencing recurrence were identified and elucidated.

Conclusion

This study shows the transformative role of machine learning in recurrence prediction for CRC, particularly by investigating the minimum number of CEA measurements required for effective recurrence prediction. This approach not only contributes to the optimization of clinical workflows but also facilitates the development of more effective, individualized treatment plans, thereby laying the groundwork for future advancements in this area. Future directions involve validating these models in larger and more diverse cohorts. Building on these efforts, our ultimate goal is to develop a risk-based follow-up strategy that can improve patient outcomes and enhance healthcare efficiency.

Machine learning based local recurrence prediction in colorectal cancer using polarized light imaging

Significance

Current treatment for stage III colorectal cancer (CRC) patients involves surgery that may not be sufficient in many cases, requiring additional adjuvant systemic therapy. Identification of this latter cohort that is likely to recur following surgery is key to better personalized therapy selection, but there is a lack of proper quantitative assessment tools for potential clinical adoption.

Aim

The purpose of this study is to employ Mueller matrix (MM) polarized light microscopy in combination with supervised machine learning (ML) to quantitatively analyze the prognostic value of peri-tumoral collagen in CRC in relation to 5-year local recurrence (LR).

Approach

A simple MM microscope setup was used to image surgical resection samples acquired from stage III CRC patients. Various potential biomarkers of LR were derived from MM elements via decomposition and transformation operations. These were used as features by different supervised ML models to distinguish samples from patients that locally recurred 5 years later from those that did not.

Results

Using the top five most prognostic polarimetric biomarkers ranked by their relevant feature importances, the best-performing XGBoost model achieved a patient-level accuracy of 86%. When the patient pool was further stratified, 96% accuracy was achieved within a tumor-stage-III sub-cohort.

Conclusions

ML-aided polarimetric analysis of collagenous stroma may provide prognostic value toward improving the clinical management of CRC patients.

Risk-factors for locally advanced rectal cancer relapse after neoadjuvant chemoradiotherapy: A single center experience

The overall prognosis of locally advanced rectal cancer (LARC) remains unsatisfactory due to a high incidence of disease relapse. The present understanding of the factors that determine the likelihood of recurrence is limited or ineffective. We aimed to identify the main risk factors influencing tumor relapse in LARC patients after neoadjuvant chemoradiotherapy (nCRT) and surgical treatment in a single center in Republika Srpska. Patients with stage II or stage III who received nCRT before surgery for primary rectal cancer at the Oncology Clinic, University Clinical Center of Republika Srpska from January 2017 and December 2022 were included in the study. We collected patient demographics, clinical stage and characteristics, neoadjuvant therapy, and surgical methods, along with the pathological response after treatment completion, and analyzed them to identify the risk factors for tumor relapse. Out of 109 patients diagnosed with LARC, 34 (31,2%) had tumor relapse. The median time to relapse was 54 months. Participants with clinical T4 stage had a significantly shorter relapse time compared to the patients with clinical T2/3 stage. Subjects with positive lymph nodes removed, perivascular and perineural invasion, intraoperative perforation and patients without ypN stage improvement had significantly shorter time to relapse. Subjects with T4 stage had more than 4 times higher risk of relapse than patients with clinical T2/3 stage. Higher clinical T stage was an essential risk factor for tumor relapse in LARC patients after nCRT and surgical treatment. Comprehensive understanding and identification of the risk factors for tumor relapse in LARC patients are crucial for improving their long-term outcomes.

Integrative analysis reveals a four-gene signature for predicting survival and immunotherapy response in colon cancer patients using bulk and single-cell RNA-seq data

Background

Colon cancer (CC) ranks as one of the leading causes of cancer-related mortality globally. Single-cell transcriptome sequencing (scRNA-seq) offers precise gene expression data for distinct cell types. This study aimed to utilize scRNA-seq and bulk transcriptome sequencing (bulk RNA-seq) data from CC samples to develop a novel prognostic model.

Methods

scRNA-seq data was downloaded from the GSE161277 database. R packages including "Seurat", "Harmony", and "singleR" were employed to categorize eight major cell types within normal and tumor tissues. By comparing tumor and normal samples, differentially expressed genes (DEGs) across these major cell types were identified. Gene Ontology (GO) enrichment analyses of DEGs for each cell type were conducted using "Metascape". DEGs-based signature construction involved Cox regression and least absolute shrinkage operator (LASSO) analyses, performed on The Cancer Genome Atlas (TCGA) training cohort. Validation occurred in the GSE39582 and GSE33382 datasets. The expression pattern of prognostic genes was verified using spatial transcriptome sequencing (ST-seq) data. Ultimately, an established prognostic nomogram based on the gene signature and age was established and calibrated. Sensitivity to chemotherapeutic drugs was predicted with the "oncoPredict" R package.

Results

Using scRNA-Seq data, we examined 33,213 cells, categorizing them into eight cell types within normal and tumor samples. GO enrichment analysis revealed various cancer-related pathways across DEGs in these cell types. Among the 55 DEGs identified via univariate Cox regression, four independent prognostic genes emerged: PTPN6, CXCL13, SPINK4, and NPDC1. Expression validation through ST-seq confirmed PTPN6 and CXCL13 predominance in immune cells, while SPINK4 and NPDC1 were relatively epithelial cell-specific. Creating a four-gene prognostic signature, Kaplan-Meier survival analyses emphasized higher risk scores correlating with unfavorable prognoses, confirmed across training and validation cohorts. The risk score emerged as an independent prognostic factor, supported by a reliable nomogram. Intriguingly, drug sensitivity analysis unveiled contrasting anti-cancer drug responses in the two risk groups, suggesting significant clinical implications.

Conclusion

We developed a novel prognostic four-gene risk model, and these genes may act as potential therapeutic targets for CC.

Recurrence and Postoperative Death in Patients with Colorectal Cancer: A New Perspective via Semi-competing Risk Framework

BACKGROUND/AIMS

Cancer studies suffer from an overestimation of prediction of survival when both recurrence and death are of interest. This longitudinal study aimed to mitigate this problem utilizing a semi-competing risk approach evaluating the factors affecting recurrence and postoperative death in patients with colorectal cancer.

MATERIALS AND METHODS

This longitudinal prospective study was conducted in 284 patients with resected colorectal cancer who were referred to the Imam Khomeini Clinic in Hamadan, Iran, during 2001-2017. Primary outcomes were postoperative outcomes and patient survival, including time to recurrence (of colorectal cancer), time to death, and time to death after recurrence. All patients who were alive at the end of the study were censored for death and who did not experience recurrence of colorectal cancer were also censored for recurrent colorectal cancer. The relationship between underlying demographics and clinical factors and the outcomes was assessed using a semicompeting risk approach.

RESULTS

The results of the multivariable analysis showed that having metastasis to other sites (hazard ratio = 36.03; 95% CI = 19.48- 66.64) and higher pathological node (pN) stage (hazard ratio = 2.46; 95% CI = 1.32-4.56) were associated with a raised hazard of recurrence. The fewer chemotherapies (hazard ratio = 0.39; 95% CI = 0.17-0.88) and higher pN stages (hazard ratio = 4.32; 95% CI = 1.27-14.75) showed significantly higher hazards of death without recurrence. Having metastasis to other sites (hazard ratio = 2.67; 95% CI = 1.24-5.74) and higher pN stages (hazard ratio = 1.91; 95% CI = 1.02-3.61) were linked with the higher hazard of death after recurrence.

CONCLUSION

Considering findings on death /recu rrenc e-spe cific predictors obtained in this study to manage the outcomes in patients with colorectal cancer, tailored strategies for preventive and interventional plans should be deliberated.

Extracellular matrix-based gene signature for predicting prognosis in colon cancer and immune microenvironment

Background

The extracellular matrix (ECM) plays a vital role in progression, expansion, and prognosis of malignancies. In this study, we aimed to explore a novel ECM-based prognostic model for patients with colon cancer (CC).

Methods

ECM-related genes were obtained from Molecular Signatures database. Differential expression analysis was performed using the CC dataset from The Cancer Genome Atlas (TCGA) database. Four ECM-related genes related to overall survival were identified using the Cox regression and LASSO analysis. Then an ECM-related signature was developed and verified in three independent CC cohorts (GSE33882, GSE39582 and GSE29621) from the Gene Expression Omnibus (GEO). A prognostic nomogram was developed incorporating the ECM-related gene signature with clinical risk factors. CIBERSORT was used to explore the immune cell infiltration level. Human Protein Atlas (HPA) database was utilized to validate the expression levels of identified prognostic ECM genes.

Results

Four ECM-related genes (CXCL13, CXCL14, SFRP5 and THBS4) were identified to develop an ECM-based gene signature and demarcated CC patients into the high- and low-risk groups. In training and validation datasets, patients in the low-risk group had better overall survival outcomes than those in the high-risk group (log-rank P<0.001). In addition, ECM-related signature was significantly associated with consensus molecular subtype 4 (CMS4) as well as other known clinical risk factors such as a higher Tumor, Nodal Involvement, Metastasis (TNM) stage. Moreover, the risk score derived from the ECM-based gene signature could be utilized as an independent prognostic factor for CC patients. A nomogram including the ECM-related gene signature, age and stage was developed to serve clinical practice. CIBERSORT analysis showed immune cell infiltration was different between high- and low-risk groups. The immunohistochemical results derived from HPA indicated differential expression of prognosis-related ECM genes in CC and normal tissues.

Conclusions

In the present study, a novel risk model based on ECM-signature could effectively reflect individual risk classification and provide potential therapeutic targets for CC patients. Moreover, the prognostic nomogram may help predict individualized survival.

A bayesian approach to model the underlying predictors of early recurrence and postoperative death in patients with colorectal Cancer

Objective

This study aimed at utilizing a Bayesian approach semi-competing risks technique to model the underlying predictors of early recurrence and postoperative Death in patients with colorectal cancer (CRC).

Methods

In this prospective cohort study, 284 patients with colorectal cancer, who underwent surgery, referred to Imam Khomeini clinic in Hamadan from 2001 to 2017. The primary outcomes were the probability of recurrence, the probability of Mortality without recurrence, and the probability of Mortality after recurrence. The patients ‘recurrence status was determined from patients’ records. The Bayesian survival modeling was carried out by semi-competing risks illness-death models, with accelerated failure time (AFT) approach, in R 4.1 software. The best model was chosen according to the lowest deviance information criterion (DIC) and highest logarithm of the pseudo marginal likelihood (LPML).

Results

The log-normal model (DIC = 1633, LPML = -811), was the optimal model. The results showed that gender(Time Ratio = 0.764: 95% Confidence Interval = 0.456–0.855), age at diagnosis (0.764: 0.538–0.935 ), T₃ stage (0601: 0.530–0.713), N₂ stage (0.714: 0.577–0.935 ), tumor size (0.709: 0.610–0.929), grade of differentiation at poor (0.856: 0.733–0.988), and moderate (0.648: 0.503–0.955) levels, and the number of chemotherapies (1.583: 1.367–1.863) were significantly related to recurrence. Also, age at diagnosis (0.396: 0.313–0.532), metastasis to other sites (0.566: 0.490–0.835), T₃ stage (0.363: 0.592 − 0.301), T₄ stage (0.434: 0.347–0.545), grade of differentiation at moderate level (0.527: 0.387–0.674), tumor size (0.595: 0.500–0.679), and the number of chemotherapies (1.541: 1.332–2.243) were the significantly predicted the death. Also, age at diagnosis (0.659: 0.559–0.803), and the number of chemotherapies (2.029: 1.792–2.191) were significantly related to mortality after recurrence.

Conclusion

According to specific results obtained from the optimal Bayesian log-normal model for terminal and non-terminal events, appropriate screening strategies and the earlier detection of CRC leads to substantial improvements in the survival of patients.

Advanced stage presentation and its determinant factors among colorectal cancer patients in Amhara regional state Referral Hospitals, Northwest Ethiopia

INTRODUCTION

Nowadays, the burden of colorectal cancer (CRC) has been increasing in the world, particularly in developing nations. This could be related to the poor prognosis of the disease due to late presentation at diagnosis and poor treatment outcomes. In Ethiopia, studies related to the stage of colorectal cancer at diagnosis and its determinants are limited. Therefore, the study was intended to assess advanced stage presentation and its associated factors among colorectal cancer patients in northwest Ethiopia.

METHODS

An institution-based retrospective study was conducted among 367 CRC patients at two oncologic centers (the University of Gondar and Felege Hiwot comprehensive specialized hospitals) from January 1, 2017, to December 31, 2020. Data were entered into EPi-data 4.2.0.0 and transferred to STATA version 14 statistical software for analysis. Binary logistic regression was used to identify factors associated with the outcome variable. All variables with P-value < 0.2 during bi-variable analysis were considered for multivariable logistic regression. The level of statistical significance was declared at P-value <0.05.

RESULTS

The magnitude of advanced stage presentation of colorectal cancer was 83.1%. Being rural dwellers (Adjusted odds ratio (AOR) = 3.6; 95% CI: 1.8,7.2), not medically insured (AOR = 3.9; 95% CI: 1.9,7.8), patients delay (AOR = 6.5; 95% CI:3.2, 13.3), recurrence of the disease (AOR = 2.3; 95% CI: 1.1,4.7), and no comorbidity illness (AOR = 4.4; 95% CI: 2.1, 9.1) were predictors of advanced stage presentation of CRC.

CONCLUSION

The current study revealed that the advanced-stage presentation of colorectal cancer patients was high. It is recommended that the community shall be aware of the signs and symptoms of the disease using different media, giving more emphasis to the rural community, expanding health insurance, and educating patients about the recurrence chance of the disease. Moreover, expansion of colorectal treatment centers and screening of colorectal cancer should be given emphasis.

The Role of Liquid Biopsy Analytes in Diagnosis, Treatment and Prognosis of Colorectal Cancer

Colorectal cancer (CRC) is one of the most common malignant tumors of the digestive tract worldwide and is a serious threat to human life and health. CRC occurs and develops in a multi-step, multi-stage, and multi-gene process, in which abnormal gene expression plays an important role. CRC is currently diagnosed via endoscopy combined with tissue biopsy. Compared with tissue biopsy, liquid biopsy technology has received increasingly more attention and applications in the field of molecular detection due to its non-invasive, safe, comprehensive, and real-time dynamic nature. This review article discusses the application and limitations of current liquid biopsy analytes in the diagnosis, treatment, and prognosis of CRC, as well as directions for their future development.

Targeting tumor innervation: premises, promises, and challenges

A high intratumoral nerve density is correlated with poor survival, high metastasis, and high recurrence across multiple solid tumor types. Recent research has revealed that cancer cells release diverse neurotrophic factors and exosomes to promote tumor innervation, in addition, infiltrating nerves can also mediate multiple tumor biological processes via exosomes and neurotransmitters. In this review, through seminal studies establishing tumor innervation, we discuss the communication between peripheral nerves and tumor cells in the tumor microenvironment (TME), and revealed the nerve-tumor regulation mechanisms on oncogenic process, angiogenesis, lymphangiogenesis, and immunity. Finally, we discussed the promising directions of ‘old drugs newly used’ to target TME communication and clarified a new line to prevent tumor malignant capacity.

A Prediction Model for Tumor Recurrence in Stage II–III Colorectal Cancer Patients: From a Machine Learning Model to Genomic Profiling

Background: Colorectal cancer (CRC) is one of the most prevalent malignant diseases worldwide. Risk prediction for tumor recurrence is important for making effective treatment decisions and for the survival outcomes of patients with CRC after surgery. Herein, we aimed to explore a prediction algorithm and the risk factors for postoperative tumor recurrence using a machine learning (ML) approach with standardized pathology reports for patients with stage II and III CRC. Methods: Pertinent clinicopathological features were compiled from medical records and standardized pathology reports of patients with stage II and III CRC. Four ML models based on logistic regression (LR), random forest (RF), classification and regression decision trees (CARTs), and support vector machine (SVM) were applied for the development of the prediction algorithm. The area under the curve (AUC) of the ML models was determined in order to compare the prediction accuracy. Genomic studies were performed using a panel-targeted next-generation sequencing approach. Results: A total of 1073 patients who received curative intent surgery at the National Cheng Kung University Hospital between January 2004 and January 2019 were included. Based on conventional statistical methods, chemotherapy (p = 0.003), endophytic tumor configuration (p = 0.008), TNM stage III disease (p < 0.001), pT4 (p < 0.001), pN2 (p < 0.001), increased numbers of lymph node metastases (p < 0.001), higher lymph node ratios (LNR) (p < 0.001), lymphovascular invasion (p < 0.001), perineural invasion (p < 0.001), tumor budding (p = 0.004), and neoadjuvant chemoradiotherapy (p = 0.025) were found to be correlated with the tumor recurrence of patients with stage II–III CRC. While comparing the performance of different ML models for predicting cancer recurrence, the AUCs for LR, RF, CART, and SVM were found to be 0.678, 0.639, 0.593, and 0.581, respectively. The LR model had a better accuracy value of 0.87 and a specificity value of 1 in the testing set. Two prognostic factors, age and LNR, were selected by multivariable analysis and the four ML models. In terms of age, older patients received fewer cycles of chemotherapy and radiotherapy (p < 0.001). Right-sided colon tumors (p = 0.002), larger tumor sizes (p = 0.008) and tumor volumes (p = 0.049), TNM stage II disease (p < 0.001), and advanced pT3–4 stage diseases (p = 0.04) were found to be correlated with the older age of patients. However, pN2 diseases (p = 0.005), lymph node metastasis number (p = 0.001), LNR (p = 0.004), perineural invasion (p = 0.018), and overall survival rate (p < 0.001) were found to be decreased in older patients. Furthermore, PIK3CA and DNMT3A mutations (p = 0.032 and 0.039, respectively) were more frequently found in older patients with stage II–III CRC compared to their younger counterparts. Conclusions: This study demonstrated that ML models have a comparable predictive power for determining cancer recurrence in patients with stage II–III CRC after surgery. Advanced age and high LNR were significant risk factors for cancer recurrence, as determined by ML algorithms and multivariable analyses. Distinctive genomic profiles may contribute to discrete clinical behaviors and survival outcomes between patients of different age groups. Studies incorporating complete molecular and genomic profiles in cancer prediction models are beneficial for patients with stage II–III CRC.

Evaluation of CD10 expression as a diagnostic marker for colorectal cancer

Aim

We aimed to determine the potential of CD10 as a marker for the early diagnosis of adenocarcinoma of the colon.

Background

Adenocarcinoma is diagnosed in one out of 20 individuals in the USA and western European countries. Its prognosis and treatment depend largely on the severity of the disease at the time of diagnosis. Additional new biological markers are being sought that can help diagnose colon cancer at an early stage. One such marker present in both serum and tumor tissue is CD10.

Methods

CD10 concentrations were tested by ELISA and immunohistochemistry in serum and tissue samples, respectively, from 113 patients diagnosed histopathologically and treated for adenocarcinoma of the colon. Additionally, the ROC curve with optimal cut-off point based on Youden's criterion was calculated for CD10.

Results

Serum concentrations of CD10 and its tissue expression in patients diagnosed with adenocarcinoma of the colon correlate with cancer staging based on the Astler-Coller-Dukes classification. To ascertain the optimal cut-off point for CD10 as a predictor of belonging to the study group, ROC curve was prepared for CD10. Optimal cut-off point for CD10 was 0.57, with prediction of belonging to the study group for CD10 ≥ 0.57.

Conclusion

CD10 can be a useful marker in the early diagnosis of adenocarcinoma of the colon.

Predicting Colorectal Cancer Recurrence and Patient Survival Using Supervised Machine Learning Approach: A South African Population-Based Study

Background: South Africa (SA) has the highest incidence of colorectal cancer (CRC) in Sub-Saharan Africa (SSA). However, there is limited research on CRC recurrence and survival in SA. CRC recurrence and overall survival are highly variable across studies. Accurate prediction of patients at risk can enhance clinical expectations and decisions within the South African CRC patients population. We explored the feasibility of integrating statistical and machine learning (ML) algorithms to achieve higher predictive performance and interpretability in findings.

Methods: We selected and compared six algorithms:- logistic regression (LR), naïve Bayes (NB), C5.0, random forest (RF), support vector machine (SVM) and artificial neural network (ANN). Commonly selected features based on OneR and information gain, within 10-fold cross-validation, were used for model development. The validity and stability of the predictive models were further assessed using simulated datasets.

Results: The six algorithms achieved high discriminative accuracies (AUC-ROC). ANN achieved the highest AUC-ROC for recurrence (87.0%) and survival (82.0%), and other models showed comparable performance with ANN. We observed no statistical difference in the performance of the models. Features including radiological stage and patient's age, histology, and race are risk factors of CRC recurrence and patient survival, respectively.

Conclusions: Based on other studies and what is known in the field, we have affirmed important predictive factors for recurrence and survival using rigorous procedures. Outcomes of this study can be generalised to CRC patient population elsewhere in SA and other SSA countries with similar patient profiles.

Clinicopathological factors associated with synchronous distant metastasis and prognosis of stage T1 colorectal cancer patients

It is rare and understudied for patients with stage T1 colorectal cancer to have synchronous distant metastasis. This study was to determine the clinicopathological factors associated with distant metastasis and prognosis. T1 colorectal cancer patients diagnosed between 2010 and 2015 were obtained from the SEER database. Logistic regression was applied to determine risk factors related to distant metastasis. Cox-proportional hazard models were used to identify the prognostic factors for patients with distant metastasis. Among 21,321 patients identified, 359 (1.8%) had synchronous distant metastasis and 1807 (8.5%) had lymph node metastasis. Multivariate analysis revealed that younger age, positive serum CEA, larger tumor size, positive tumor deposit, perineural invasion, lymph node metastasis, histology of non-adenocarcinoma and poorer differentiation were significantly associated with the increased risk of synchronous distant metastasis. Older age, female, Black, positive CEA, positive lymph node metastasis, positive tumor deposit, larger tumor size, no chemotherapy, inadequate lymph node harvesting and no metastasectomy were correlated with worse survival in these patients with synchronous distant metastasis. Patients with metastasis to the liver displayed the highest rate of positive CEA. We conclude that T1 colorectal cancer patients with multiple risk factors need thorough examinations to exclude synchronous distant metastasis. Chemotherapy, adequate lymph node cleaning and metastasectomy are associated with improved survival for those patients with distant metastases. Positive serum CEA may be useful in predicting distant metastases in patients at stage T1.

Identification of Hub Genes and Construction of a Transcriptional Regulatory Network Associated With Tumor Recurrence in Colorectal Cancer by Weighted Gene Co-expression Network Analysis

Tumor recurrence is one of the most important risk factors that can negatively affect the survival rate of colorectal cancer (CRC) patients. However, the key regulators dictating this process and their exact mechanisms are understudied. This study aimed to construct a gene co-expression network to predict the hub genes affecting CRC recurrence and to inspect the regulatory network of hub genes and transcription factors (TFs). A total of 177 cases from the GSE17536 dataset were analyzed via weighted gene co-expression network analysis to explore the modules related to CRC recurrence. Functional annotation of the key module genes was assessed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein and protein interaction network was then built to screen hub genes. Samples from the Cancer Genome Atlas (TCGA) were further used to validate the hub genes. Construction of a TFs-miRNAs–hub genes network was also conducted using StarBase and Cytoscape approaches. After identification and validation, a total of five genes (TIMP1, SPARCL1, MYL9, TPM2, and CNN1) were selected as hub genes. A regulatory network of TFs-miRNAs-targets with 29 TFs, 58 miRNAs, and five hub genes was instituted, including model GATA6-MIR106A-CNN1, SP4-MIR424-TPM2, SP4-MIR326-MYL9, ETS1-MIR22-TIMP1, and ETS1-MIR22-SPARCL1. In conclusion, the identification of these hub genes and the prediction of the Regulatory relationship of TFs-miRNAs-hub genes may provide a novel insight for understanding the underlying mechanism for CRC recurrence.

Radiological Surveillance Post-Curative Colorectal Cancer Resection: Is There a Need for a Targeted Protocol?

Background

The frequency of radiological surveillance after curative colorectal cancer resection has long been a controversial issue with the need to balance potential harm from ionizing radiation and the financial burden of intense surveillance against advantages of early detection of recurrent disease. NICE guidelines issued in 2018 suggested having two surveillance computed tomography (CT) scans within three years of surgery without specifying the timing or the interval.

Aim

To examine whether an evidence-based flexible approach based on individual patients’ risk factors can add value to surveillance protocols. Reaching a targeted protocol that can maximize early detection of metastasis without consumption of resources and most important without compromising patient safety.

Methodology

A retrospective study involving five years of data of patients who underwent curative colorectal cancer resections. Data extracted after patients completed their three-year surveillance CT scans, CT reports retrieved together with post-operative histology reports, and a detailed database was constructed.

Results

Of 179 patients included, 66 developed recurrence (7 local and 59 distant). Recurrence increased from 23.5% in T1 to 66% in T4 (P=0.0001). The median time to recurrence 23 months in T4 disease compared to 36, 42 and 43 months for stages T1, T2 and T3, respectively (P=0.0001). A similar incremental increase in recurrence noted from 22% in the N0 stage to 73.5% in the N2 stage (P=0.0001); the median time to recurrence of 14 months in N2 patients compared to 45 and 33 months for stages N0 and N1, respectively (P=0.0001). Recurrence correlated well with positive extramural vascular invasion (EMVI) status, (71.7% versus 19.3% P=0.0001) being detected significantly earlier in EMVI positive group at 17 versus 45 months (P=0.0001).

Conclusion

Flexible protocol for radiological surveillance after curative resection of colorectal cancer, based on known pathological prognostic factors, is likely to be more effective in maximizing resource utilization as well as improving patient outcomes.

Specific causes of recurrence after surgery and mortality in patients with colorectal cancer: A competing risks survival analysis

Background

In situation where there are more than one cause of occurring the outcome such as recurrence after surgery and death, the assumption of classical survival analyses are not satisfied. To cover this issue, this study aimed at utilizing competing risks survival analysis to assess the specific risk factors of local-distance recurrence and mortality in patients with colorectal cancer (CRC) undergoing surgery.

Materials and Methods

In this retrospective cohort study, 254 patients with CRC undergoing resection surgery were studied. Data of the outcome from the available documents in the hospital were gathered. Furthermore, based on pathological report, the diagnosis of CRC was considered. We model the risk factors on the hazard of recurrence and death using competing risk survival in R3.6.1 software.

Results

A total of 114 patients had local or distant recurrence (21 local recurrences, 72 distant recurrences, and 21 local and distant recurrence). Pathological stage (adjusted hazard ratio [AHR] = 4.28 and 5.37 for stage 3 and 4, respectively), tumor site (AHR = 2.45), recurrence (AHR = 3.92) and age (AHR = 3.15 for age >70) was related to hazard of death. Also based on cause-specific hazard model, pathological stage (AHR = 7.62 for stage 4), age (AHR = 1.46 for age >70), T stage (AHR = 1.8 and 2.7 for T3 and T4, respectively), N stage (AHR = 2.59 for N2), and white blood cells (AHR = 1.95) increased the hazard of recurrence in patients with CRC.

Conclusion

This study showed that older age, higher pathological, rectum tumor site and presence of recurrence were independent risk factors for mortality among CRC patients. Also age, higher T/N stage, higher pathological stage and higher values of WBC were significantly related to higher hazard of local/distance recurrence of patients with CRC.

Investigation the Effect of Low, Medium and High Dose of X-Radiation on the Expression of E-cadherin in Colorectal Cancer Cell Line

Background:

Radiotherapy has become a part of therapeutic process of more than 50 percent of patients suffering from cancer. However, recent studies have shown that radiation therapy might affect the expression of adhesive molecule related genes such as E-cadherin and cause cancer cells to move and migrate. Besides, various studies have reported that the expression of E-cadherin changes differently after radiation treatment. There are several studies which showed the loss of E-cadherin function after radiation; however, this reduction has not been observed in others.

Objective:

This study aims to investigate the effect of different radiation doses of X-ray on changes that might occur in the expression of E-cadherin gene in colorectal cancer cell line HT-29.

Material and Methods:

In this experimental study, the cells cultured in flasks were irradiated with X- rays in different doses, including 0.1, 2.5, 5, and 10 Gy; then, the expression of E-cadherin gene was measured using real-time PCR.

Results:

The expression of E-cadherin did not change significantly in post-irradiated HT-29 cell line after different radiation doses of X-ray.

Conclusion:

The results showed that low, medium and high doses of X- radiation did not change the expression of E-cadherin gene in HT-29 cancer cells. However, it has been reported that radiation mostly downregulated the expression of E-cadherin and mediated metastasis formation and invasiveness in different cancer cell lines. Therefore, further studies need to be conducted to investigate the effects of radiation dose on the molecular pathways contributing to regulation of E-cadherin in HT-29 cell line.

The Protein Secretome Is Altered in Rectal Cancer Tissue Compared to Normal Rectal Tissue, and Alterations in the Secretome Induce Enhanced Innate Immune Responses

Simple Summary

Rectal cancer occurs in the lower part of the bowel, and approximately half of all rectal cancer patients receive chemoradiotherapy before surgery. In ~22% of cases the tumour is eradicated, but the reasons for different response rates between patients are largely unknown. Inflammation and the immune system are important players in the response to cancer treatment, but we do not fully understand the role they play in this clinical setting. We examined the levels of 54 inflammatory markers in normal (non-cancerous) rectal tissue and rectal cancer tissue, and we found that rectal cancer tissue was more inflammatory, and the levels of inflammatory markers correlated with obesity status. We found that irradiating rectal cancer tissue enhanced the ability of immune cells to induce an anti-tumour immune response.

Abstract

Locally advanced rectal cancer is treated with neoadjuvant-chemoradiotherapy; however, only ~22% of patients achieve a complete response, and resistance mechanisms are poorly understood. The role of inflammation and immune cell biology in this setting is under-investigated. In this study, we profiled the inflammatory protein secretome of normal (non-cancer) (n = 8) and malignant rectal tissue (n = 12) pre- and post-radiation in human ex vivo explant models and examined the influence of these untreated and treated secretomes on dendritic cell biology (n = 8 for cancer and normal). These resultant profiles were correlated with patient clinical characteristics. Nineteen factors were secreted at significantly higher levels from the rectal cancer secretome when compared to the normal rectal secretome; Flt-1, P1GF, IFN-γ, IL-6, IL-10, CCL20, CCL26, CCL22, CCL3, CCL4, CCL17, GM-CSF, IL-12/IL-23p40, IL-17A, IL-1α, IL-17A/F, IL-1RA, TSLP and CXCL10 (p < 0.05). Radiation was found to have differential effects on normal rectal tissue and rectal cancer tissue with increased IL-15 and CCL22 secretion following radiation from normal rectal tissue explants (p < 0.05), while no significant alterations were observed in the irradiated rectal cancer tissue. Interestingly, however, the irradiated rectal cancer secretome induced the most potent effect on dendritic cell maturation via upregulation of CD80 and PD-L1. Patient’s visceral fat area correlated with secreted factors including CCL20, suggesting that obesity status may alter the tumour microenvironment (TME). These results suggest that radiation does not have a negative effect on the ability of the rectal cancer TME to induce an immune response. Understanding these responses may unveil potential therapeutic targets to enhance radiation response and mitigate normal tissue injury. Tumour irradiation in this cohort enhances innate immune responses, which may be harnessed to improve patient treatment outcome.

Near-infrared photoimmunotherapy is effective treatment for colorectal cancer in orthotopic nude-mouse models

BACKGROUND

Photoimmunotherapy (PIT) employs the use of a near-infrared (NIR) laser to activate an antibody conjugated to a NIR-activatable dye to induce cancer cell death. PIT has shown to be effective in a number of studies, however, there are no data on its use in colorectal cancer in an orthotopic model.

METHODS

Humanized anti-CEA antibody (M5A) was conjugated to NIR-activatable IRDye700DX (M5A-700). PIT was validated in vitro with a colon cancer cell-line, using a laser intensity of either 4 J/cm2, 8 J/cm2, or 16 J/cm2. Orthotopic colon cancer mouse models were established by surgical implantation of LS174T tumor fragments onto the cecum. M5A-700 was administered and PIT was performed 24 hours later using a 690 nm laser. Repeat PIT was performed after 7 days in one group. Control mice received laser treatment only.

RESULTS

In vitro PIT demonstrated tumor cell death in a laser intensity dose-dependent fashion. In orthotopic models, control mice demonstrated persistent tumor growth. Mice that underwent PIT one time had tumor growth arrested for one week, after which re-growth occurred. The group that received repeated PIT exposure had persistent inhibition of tumor growth.

CONCLUSION

PIT arrests tumor growth in colon cancer orthotopic nude-mouse models. Repeated PIT arrests colon cancer growth for a longer period of time. PIT may be a useful therapy in the future as an adjunct to surgical resection or as primary therapy to suppress tumor progression.

Transcriptomic Analyses Revealed Systemic Alterations in Gene Expression in Circulation and Tumor Microenvironment of Colorectal Cancer Patients

Colorectal cancer (CRC) is among the leading causes of cancer-related deaths worldwide, underscoring a need for better understanding of the disease and development of novel diagnostic biomarkers and therapeutic interventions. Herein, we performed transcriptome analyses on peripheral blood mononuclear cells (PBMCs), CRC tumor tissue and adjacent normal tissue from 10 CRC patients and PBMCs from 15 healthy controls. Up regulated transcripts from CRC PBMCs were associated with functions related to immune cell trafficking and cellular movement, while downregulated transcripts were enriched in cellular processes related to cell death. Most affected signaling networks were those involved in tumor necrosis factor (TNF) and interleukin signaling. The expression of selected immune-related genes from the RNA-Seq data were further validated using qRT-PCR. Transcriptome analysis of CRC tumors and ingenuity pathway analysis revealed enrichment in several functional categories related to cellular movement, cell growth and proliferation, DNA replication, recombination and repair, while functional categories related to cell death were suppressed. Upstream regulator analysis revealed activation of ERBB2 and FOXM1 networks. Interestingly, there were 18 common upregulated and 36 common downregulated genes when comparing PBMCs and tumor tissue, suggesting transcriptomic changes in the tumor microenvironment could be reflected, in part, in the periphery with potential utilization as disease biomarkers.

The Use of Circulating Tumor DNA to Monitor and Predict Response to Treatment in Colorectal Cancer

Background: Colorectal cancer is one of the most common cancers worldwide and has a high mortality rate following disease recurrence. Treatment efficacy is maximized by providing tailored cancer treatment, ideally involving surgical resection and personalized neoadjuvant and adjuvant therapies, including chemotherapy, radiotherapy and increasingly, targeted therapy. Early detection of recurrence or disease progression results in more treatable disease and is essential to improving survival outcomes. Recent advances in the understanding of tumor genetics have resulted in the discovery of circulating tumor DNA (ctDNA). A growing body of evidence supports the use of these sensitive biomarkers in detecting residual disease and diagnosing recurrence as well as enabling targeted and tumor-specific adjuvant therapies. Methods: A literature search in Pubmed was performed to identify all original articles preceding April 2019 that utilize ctDNA for the purpose of monitoring response to colorectal cancer treatment. Results: Ninety-two clinical studies were included. These studies demonstrate that ctDNA is a reliable measure of tumor burden. Studies show the utility of ctDNA in assessing the adequacy of surgical tumor clearance and changes in ctDNA levels reflect response to systemic treatments. ctDNA can be used in the selection of targeted treatments. The reappearance or increase in ctDNA, as well as the emergence of new mutations, correlates with disease recurrence, progression, and resistance to therapy, with ctDNA measurement allowing more sensitive monitoring than currently used clinical tools. Conclusions: ctDNA shows enormous promise as a sensitive biomarker for monitoring response to many treatment modalities and for targeting therapy. Thus, it is emerging as a new way for guiding treatment decisions-initiating, altering, and ceasing treatments, or prompting investigation into the potential for residual disease. However, many potentially useful ctDNA markers are available and more work is needed to determine which are best suited for specific purposes and for improving specific outcomes.

Augmented CD133 expression in distal margin correlates with poor prognosis in colorectal cancer

Pathological assessment of excised tumour and surgical margins in colorectal cancer (CRC) play crucial role in prognosis after surgery. Molecular assessment of margins could be more sensitive and informative than conventional histopathological analysis. Considering this view, we evaluated the distal surgical margins for expression of cancer stem cell (CSC) markers. Cellular and molecular assessment of normal, tumour and distal margin tissues were performed by flow cytometry, real-time q-PCR and immuno-histochemical analysis for CRC patients after tumour excision. CRC patients were evaluated for expression of CSC markers in their normal, tumour and distal tissues. Flow cytometry assay revealed CD133 and CD44 enriched cells in distal margin and tumour compared to normal colorectal tissues, which was further confirmed by immunohistochemistry. Most importantly, immunohistochemistry also revealed the enrichment of CSC markers expression in pathologically negative distal margins. Patients with distal margin enriched for CD133 expression showed an increased recurrence rate and decreased disease-free survival. This study proposes that although distal margin seems to be tumour free in conventional histopathological analysis, it could harbour cells enriched for CSC markers. Further CD133 could be a promising molecule to be used in molecular pathology for disease prognosis after surgery in CRC patients.

Survival Rate of Colorectal Cancer in Iran: A Systematic Review and Meta-Analysis

Background: Different studies have been conducted to estimate the survival rate of colorectal cancer in Iran but there is no overall estimate of the survival rate. The aim of this study was to calculate the pooled 1, 3, and 5-year survival rate of the patients with colorectal cancer in Iran. Methods: To retrieve relevant studies, we conducted a systematic search in Iranian databases, including Iran Medex, Magiran, SID, and international databases such as Medlin/PubMed, Scopus, and Google scholar using “Colorectal Neoplasms” and “Survival Rate” as keywords up to December 1st, 2017. We used random effect model to estimate pooled 1, 3, and 5-year survival rates of the patients with colorectal cancer in Iran. To assess the heterogeneity, we used Chi-squared test at the 5 % significance level (p <0.05) and I2 Index. We used meta-regression and subgroup analysis to find a potential source of heterogeneity. Results: After a systematic search, 196 articles were found, of the 38 studies met the eligibility criteria and are included in our meta-analysis. The pooled 1, 3, and 5-year survival rates in patient with colorectal cancer were 0.84 (95% CI: 0.81-0.87), 0.64 (95%CI: 0.59-0.70), and 0.54 (95%CI: 0.49-0.58) respectively. The 5-year survival rate in the subgroup of women was 0.5 (0.44-0.56) and in male subgroup was 0.44 (0.40-0.48). In a subgroup of the tumor site, the 5-year survival rate in colon cancer was 0.6 (0.49-0.75) and rectum cancer was 0.54 (0.36-0.69). In multivariable models, there was a significant association between years of study and 5-year survival rate as a source of heterogeneity (β = 18.9, P=0.01). Conclusion: According to the results of this study, women had a better survival rate than men, and according to the tumor site, the 5-year survival rate in colon cancer was better than the rectum cancer.

Perineural invasion of cancer: a complex crosstalk between cells and molecules in the perineural niche

Perineural invasion (PNI) can be found in a variety of malignant tumors. It is a sign of tumor metastasis and invasion and portends the poor prognosis of patients. The pathological description and clinical significance of PNI are clearly understood, but exploration of the underlying molecular mechanism is ongoing. It was previously thought that the low-resistance channel in the anatomic region led to the occurrence of PNI. However, with rapid development of precision medicine and molecular biology, we have gradually realized that the occurrence of PNI is not the result of a single factor. The latest study suggests that PNI of cancer is a continuous and multistep process. A specific peripheral microenvironment, also called the perineural niche, is formed by neural cells, supporting cells, recruited inflammatory cells, altered extracellular matrix, blood vessels, and immune components in the background of carcinoma. Various soluble signaling molecules and their receptors comprise a complex signal network, which achieves the interaction between nerve and tumor. Nerve cells and tumor cells can interact directly or through the opening and closing of the signal transduction pathways and/or the recognition and response of the ligands and receptors. The information is transferred to the targets accurately and effectively, leading to the specific interactions between the nerve cells and the malignant tumor cells. PNI occurs through changes in nerve cells and supporting cells in the background of cancer; change and migration of the perineural matrix; enhancement of the viability, mobility, and invasiveness of the tumor cells; injury and regeneration of nerve cells; interaction, chemotactic movement, contact, and adherence of the nerve cells and the tumor cells; escape from autophagy, apoptosis, and immunological surveillance of tumor cells; and so on. Certainly, exploring the mechanism of PNI clearly has great significance for blocking tumor progression and improving patient survival. The current review aims to elucidate the cellular and molecular mechanisms of PNI, which may help us find a strategy for improving the prognosis of malignant tumors.

Interaction between Tumor-Associated Dendritic Cells and Colon Cancer Cells Contributes to Tumor Progression via CXCL1

Crosstalk of a tumor with its microenvironment is a critical factor contributing to cancer development. This study investigates the soluble factors released by tumor-associated dendritic cells (TADCs) responsible for increasing cancer stem cell (CSC) properties, cell mobility, and epithelial-to-mesenchymal transition (EMT). Dendritic cells (DCs) of colon cancer patients were collected for phenotype and CXCL1 expression by flow cytometry and Luminex assays. The transcriptome of CXCL1-treated cancer cells was established by next generation sequencing. Inflammatory chemokine CXCL1, present in large amounts in DCs isolated from colon cancer patients, and SW620-conditioned TADCs, enhance CSC characteristics in cancer, supported by enhanced anchorage-independent growth, CD133 expression and aldehyde dehydrogenase activity. Additionally, CXCL1 increases the metastatic ability of a cancer by enhancing cell migration, matrix metalloproteinase-7 expression and EMT. The enhanced CXCL1 expression in DCs is also noted in mice transplanted with colon cancer cells. Transcriptome analysis of CXCL1-treated SW620 cells indicates that CXCL1 increases potential oncogene expression in colon cancer, including PTHLH, TYRP1, FOXO1, TCF4 and ZNF880. Concurrently, CXCL1 displays a specific microRNA (miR) upregulated by the prototypical colon cancer onco-miR miR-105. Analysis of publicly available data reveals CXCL1-driven oncogenes and miR-105 have a negative prognostic impact on the outcome of colon cancer. This study indicates a new mechanism by which the colon cancer milieu exploits DC plasticity to support cancer progression.