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Colorectal cancer is one of the most diagnosed types of cancer in developed countries. Current diagnostic methods are partly dependent on pathologist experience and laboratories instrumentation. In this study, we used Fourier Transform Infrared (FTIR) spectroscopy in transflection mode, combined with Principal Components Analysis followed by Linear Discriminant Analysis (PCA-LDA) and Partial Least Squares - Discriminant Analysis (PLS-DA), to build a classification algorithm to diagnose colon cancer in cell samples, based on absorption spectra measured in two spectral ranges of the mid-infrared spectrum. In particular, PCA technique highlights small biochemical differences between healthy and cancerous cells: these are related to the larger lipid content in the former compared with the latter and to the larger relative amount of protein and nucleic acid components in the cancerous cells compared with the healthy ones. Comparison of the classification accuracy of PCA-LDA and PLS-DA methods applied to FTIR spectra measured in the 1000-1800 cm -1 (low wavenumber range, LWR) and 2700-3700 cm -1 (high wavenumber range, HWR) remarks that both algorithms are able to classify hidden class FTIR spectra with excellent accuracy (100 %) in both spectral regions. This is a hopeful result for clinical translation of infrared spectroscopy: in fact, it makes reliable the predictions obtained using FTIR measurements carried out only in the HWR, in which the glass slides used in clinical laboratories are transparent to IR radiation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: The global healthcare system faces challenges in diagnosing and managing lung and colon cancers, which are significant health burdens. Traditional diagnostic methods are inefficient and prone to errors, while data privacy and security concerns persist., Objective: This study aims to develop a secure and transparent framework for remote consultation and classification of lung and colon cancer, leveraging blockchain technology and Microsoft Azure cloud services. Dataset and Features: The framework utilizes the LC25000 dataset, containing 25,000 histopathological images, for training and evaluating advanced machine learning models. Key features include secure data upload, anonymization, encryption, and controlled access via blockchain and Azure services., Methods: The proposed framework integrates Microsoft Azure's cloud services with a permissioned blockchain network. Patients upload CT scans through a mobile app, which are then preprocessed, anonymized, and stored securely in Azure Blob Storage. Blockchain smart contracts manage data access, ensuring only authorized specialists can retrieve and analyze the scans. Azure Machine Learning is used to train and deploy state-of-the-art machine learning models for cancer classification. Evaluation Metrics: The framework's performance is evaluated using metrics such as accuracy, precision, recall, and F 1- score , demonstrating the effectiveness of the integrated approach in enhancing diagnostic accuracy and data security., Results: The proposed framework achieves an impressive accuracy of 100% for lung and colon cancer classification using DenseNet, ResNet50, and MobileNet models with different split ratios (70-30, 80-20, 90-10). The F 1- score and k-fold cross-validation accuracy (5-fold and 10-fold) also demonstrate exceptional performance, with values exceeding 99.9%. Real-time notifications and secure remote consultations enhance the efficiency and transparency of the diagnostic process, contributing to better patient outcomes and streamlined cancer care management.

The consensus molecular subtype (CMS) classification divides colon tumors into four subtypes holding promise as a predictive biomarker. However, the effect of adjuvant chemotherapy on recurrence free survival (RFS) per CMS in stage III patients remains inadequately explored. With this intention, we selected stage III colon cancer (CC) patients from the MATCH cohort (n = 575) and RadboudUMC (n = 276) diagnosed between 2005 and 2018. Patients treated with and without adjuvant chemotherapy were matched based on tumor location, T- and N-stage (n = 522). Tumor material was available for 464 patients, with successful RNA extraction and CMS subtyping achieved in 390 patients (surgery alone group: 192, adjuvant chemotherapy group: 198). In the overall cohort, CMS4 was associated with poorest prognosis (HR 1.55; p = .03). Multivariate analysis revealed favorable RFS for the adjuvant chemotherapy group in CMS1, CMS2, and CMS4 tumors (HR 0.19; p = .01, HR 0.27; p < .01, HR 0.19; p < .01, respectively), while no significant difference between treatment groups was observed within CMS3 (HR 0.68; p = .51). CMS subtyping in this non-randomized cohort identified patients with poor prognosis and patients who may not benefit significantly from adjuvant chemotherapy., (© 2024 The Author(s). International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Lung and colon cancers are leading contributors to cancer-related fatalities globally, distinguished by unique histopathological traits discernible through medical imaging. Effective classification of these cancers is critical for accurate diagnosis and treatment. This study addresses critical challenges in the diagnostic imaging of lung and colon cancers, which are among the leading causes of cancer-related deaths worldwide. Recognizing the limitations of existing diagnostic methods, which often suffer from overfitting and poor generalizability, our research introduces a novel deep learning framework that synergistically combines the Xception and MobileNet architectures. This innovative ensemble model aims to enhance feature extraction, improve model robustness, and reduce overfitting.Our methodology involves training the hybrid model on a comprehensive dataset of histopathological images, followed by validation against a balanced test set. The results demonstrate an impressive classification accuracy of 99.44%, with perfect precision and recall in identifying certain cancerous and non-cancerous tissues, marking a significant improvement over traditional approach.The practical implications of these findings are profound. By integrating Gradient-weighted Class Activation Mapping (Grad-CAM), the model offers enhanced interpretability, allowing clinicians to visualize the diagnostic reasoning process. This transparency is vital for clinical acceptance and enables more personalized, accurate treatment planning. Our study not only pushes the boundaries of medical imaging technology but also sets the stage for future research aimed at expanding these techniques to other types of cancer diagnostics., (© 2024. The Author(s).)

Colonic polyp refers to lesions that exhibit a protrusion of the mucosa, regardless of histology. The most recent WHO classification is based on a better understanding of these lesions; however, its application in daily practice could be subject to interobserver variability biases that could have clinical implications., Objectives: To determine the interobserver variability in the histopathological reporting and grading of dysplasia of samples obtained from elevated colon lesions in a private laboratory in the city of Lima., Materials and Methods: Observational, descriptive, and prospective study: Case series type. All biopsies of elevated colon lesions received over a period of 3 months were evaluated by two observers without clinical information of the cases, to diagnose the lesions according to the WHO classification. In cases of diagnostic differences, the cases were evaluated together to reach a consensus., Results: A Kappa coefficient value of 0.458 was obtained in the diagnostic classification of elevated colon lesions, while a Kappa value of 0.416 in the evaluation of dysplasia; indicating moderate agreement., Conclusions: Despite achieving moderate agreement between evaluators, this work demonstrates the importance of not only relying on morphological criteria for diagnostic classification, but also including criteria of location and size of these lesions to increase diagnostic accuracy.

Over the past decade, our understanding of the diversity of colorectal cancer has expanded significantly, raising hopes of tailoring treatments more precisely for individual patients. A key achievement in this direction was the establishment of the consensus molecular classification, particularly identifying the challenging consensus molecular subtype (CMS) CMS4 associated with poor prognosis. Because of its aggressive nature, extensive research is dedicated to the CMS4 subgroup. Recent years have unveiled molecular and microenvironmental features at the tissue level specific to CMS4 colorectal cancer. This has paved the way for mechanistic studies and the development of preclinical models. Simultaneously, efforts have been made to easily identify patients with CMS4 colorectal cancer. Reassessing clinical trial results through the CMS classification lens has improved our understanding of the therapeutic challenges linked to this subtype. Exploration of the biology of CMS4 colorectal cancer is yielding potential biomarkers and novel treatment approaches. This overview aims to provide insights into the clinico-biological characteristics of the CMS4 subgroup, the molecular pathways driving this subtype, and available diagnostic options. We also emphasize the therapeutic challenges associated with this subtype, offering potential explanations. Finally, we summarize the current tailored treatments for CMS4 colorectal cancer emerging from fundamental and preclinical studies., (©2024 The Authors; Published by the American Association for Cancer Research.)

Advancements in the field of next generation sequencing (NGS) have generated vast amounts of data for the same set of subjects. The challenge that arises is how to combine and reconcile results from different omics studies, such as epigenome and transcriptome, to improve the classification of disease subtypes. In this study, we introduce sCClust (sparse canonical correlation analysis with clustering), a technique to combine high-dimensional omics data using sparse canonical correlation analysis (sCCA), such that the correlation between datasets is maximized. This stage is followed by clustering the integrated data in a lower-dimensional space. We apply sCClust to gene expression and DNA methylation data for three cancer genomics datasets from the Cancer Genome Atlas (TCGA) to distinguish between underlying subtypes. We evaluate the identified subtypes using Kaplan-Meier plots and hazard ratio analysis on the three types of cancer-GBM (glioblastoma multiform), lung cancer and colon cancer. Comparison with subtypes identified by both single- and multi-omics studies implies improved clinical association. We also perform pathway over-representation analysis in order to identify up-regulated and down-regulated genes as tentative drug targets. The main goal of the paper is twofold: the integration of epigenomic and transcriptomic datasets followed by elucidating subtypes in the latent space. The significance of this study lies in the enhanced categorization of cancer data, which is crucial to precision medicine.

Background: Existing colorectal cancer subtyping methods were generated without much consideration of potential differences in expression profiles between colon and rectal tissues. Moreover, locally advanced rectal cancers at resection often have received neoadjuvant chemoradiotherapy which likely has a significant impact on gene expression., Methods: We collected mRNA expression profiles for rectal and colon cancer samples (n = 2121). We observed that (i) Consensus Molecular Subtyping (CMS) had a different prognosis in treatment-naïve rectal vs. colon cancers, and (ii) that neoadjuvant chemoradiotherapy exposure produced a strong shift in CMS subtypes in rectal cancers. We therefore clustered 182 untreated rectal cancers to find rectal cancer-specific subtypes (RSSs)., Results: We identified three robust subtypes. We observed that RSS1 had better, and RSS2 had worse disease-free survival. RSS1 showed high expression of MYC target genes and low activity of angiogenesis genes. RSS2 exhibited low regulatory T cell abundance, strong EMT and angiogenesis signalling, and high activation of TGF-β, NF-κB, and TNF-α signalling. RSS3 was characterised by the deactivation of EGFR, MAPK and WNT pathways., Conclusions: We conclude that RSS subtyping allows for more accurate prognosis predictions in rectal cancers than CMS subtyping and provides new insight into targetable disease pathways within these subtypes., (© 2024. The Author(s).)

Aim: Log Odds of Positive Lymph Nodes (LODDS) have a better predictive ability than N stage for colon cancer. However, the prognostic value of developing a novel prognostic classification by combining T stage and LODDS (TLODDS) for colon cancer remains unknown. Therefore, in the present study, we aimed to develop a TLODDS classification for colon cancer, and assess whether or not the novel TLODDS classification could improve survival stratification by comparing its discrimination, model-fitting, and net benefits, with the American Joint Committee on Cancer (AJCC) Tumor/Node/Metastasis (TNM) classification., Methods: 45,558 Western colon cancers were identified in the Surveillance, Epidemiology, and End Results database as a training set. A novel LODDS stage was established and patients with similar survival rates were grouped by combining T and LODDS stages to develop a novel TLODDS classification. The TLODDS classification was further assessed in a Chinese validation set of 3,515 colon cancers and an application set of 3,053 rectal cancers., Results: We developed a novel TLODDS classification that incorporated 7 stages: stage I (T1LODDS1), IIA (T2LODDS1, T1LODDS2, T1LODDS3), IIB (T2LODDS2-3, T3LODDS1, T1LODDS4), IIC (T3LODDS2, T2LODDS4, T4aLODDS1), IIIA (T3LODDS3, T1-2LODDS5, T4bLODDS1, T4aLODDS2), IIIB (T3LODDS4-5, T4aLODDS3-4, T4bLODDS2) and IIIC (T4bLODDS3-5, T4aLODDS5). In the training set, it showed significantly better discrimination (area under the receiver operating characteristic (ROC) curve, 0.691 vs. 0.664, P < 0.001), better model-fitting (Akaike information criteria, 265,644 vs. 267,410), and superior net benefits, than the latest AJCC TNM classification. The predictive performance of the TLODDS classification was further validated in colon cancers and was successfully applied in rectal cancers with regards to both overall and disease-free survival., Conclusions: The TLODDS classification has better discriminatory ability, model-fitting, and net benefits than the existing TNM classification, and represents an alternative to the current TNM classifications for colon and rectal cancers., Competing Interests: Declaration of competing interest The authors declare no potential conflicts of interest regarding this work., (Copyright © 2021 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.)

Background: Adjuvant chemotherapy reduces the risk of recurrence of stage III colon cancer (CC). However, more effective prognostic and predictive biomarkers are needed for better treatment stratification of affected patients. Here, we constructed a 55-gene classifier (55GC) and investigated its utility for classifying patients with stage III CC., Methods: We retrospectively identified patients aged 20-79 years, with stage III CC, who received adjuvant chemotherapy with or without oxaliplatin, between the years 2009 and 2012., Results: Among 938 eligible patients, 203 and 201 patients who received adjuvant chemotherapy with and without oxaliplatin, respectively, were selected by propensity score matching. Of these, 95 patients from each group were analyzed, and their 5-year relapse-free survival (RFS) rates with and without oxaliplatin were 73.7 and 77.1%, respectively. The hazard ratios for 5-year RFS following adjuvant chemotherapy (fluoropyrimidine), with and without oxaliplatin, were 1.241 (95% CI, 0.465-3.308; P = 0.67) and 0.791 (95% CI, 0.329-1.901; P = 0.60), respectively. Stratification using the 55GC revealed that 52 (27.3%), 78 (41.1%), and 60 (31.6%) patients had microsatellite instability (MSI)-like, chromosomal instability (CIN)-like, and stromal subtypes, respectively. The 5-year RFS rates were 84.3 and 72.0% in patients treated with and without oxaliplatin, respectively, for the MSI-like subtype (HR, 0.495; 95% CI, 0.145-1.692; P = 0.25). No differences in RFS rates were noted in the CIN-like or stromal subtypes. Stratification by cancer sidedness for each subtype showed improved RFS only in patients with left-sided primary cancer treated with oxaliplatin for the MSI-like subtype (P = 0.007). The 5-year RFS rates of the MSI-like subtype in left-sided cancer patients were 100 and 53.9% with and without oxaliplatin, respectively., Conclusions: Subclassification using 55GC and tumor sidedness revealed increased RFS in patients within the MSI-like subtype with stage III left-sided CC treated with fluoropyrimidine and oxaliplatin compared to those treated without oxaliplatin. However, the predictive power of 55GC subtyping alone did not reach statistical significance in this cohort, warranting larger prospective studies., Trial Registration: The study protocol was registered in the University Hospital Medical Education Network (UMIN) clinical trial registry (UMIN study ID: 000023879 )., (© 2021. The Author(s).)

Colon cancer is the third cause of cancer death in the developed countries. Some environmental factors are involved in its pathogenesis, including viral infections. The possible involvement of human polyomaviruses (HPyVs) in colon cancer pathogenesis has been previously reported, leading to inconsistent conclusions. Clinical specimens were collected from 125 colon cancer patients. Specifically, 110 tumor tissues, 55 negative surgical margins, and 39 peripheral blood samples were analyzed for the presence of six HPyVs: JC polyomavirus (JCPyV), BK polyomavirus (BKPyV), Merkel cell PyV (MCPyV), HPyV -6, -7, and -9 by means of DNA isolation and subsequent duplex Real Time quantitative polymerase chain reaction. HPyVs genome was detected in 33/204 samples (16.2%): the significant higher positivity was found in tumor tissues (26/110, 23.6%), followed by negative surgical margins (3/55, 5.5%, p < .05), and peripheral blood mononuclear cells (PBMCs) (4/39; 10.3%). HPyVs load was statistically higher only in the tumor tissues compared to negative surgical margins (p < .05). Specifically, MCPyV was detected in 19.1% (21/110) of tumor tissues, 3.6% (2/55) of negative surgical margins (p < .05), and 7.7% (3/39) of PBMCs; HPyV-6 in 2.7% (3/110) of tumor tissues, and 1.8% (1/55) of negative surgical margins; one tumor tissue (1/110, 0.9%) and one PBMCs sample (1/39, 2.6%) were positive for BKPyV; JCPyV was present in 0.9% (1/110) of tumor tissues. HPyV-7 and 9 were not detected in any sample. High prevalence and load of MCPyV genome in the tumor tissues might be indicative of a relevant rather than bystander role of the virus in the colon tumorigenesis., (© 2021 Wiley Periodicals LLC.)

Background: In transitioning from the 7th edition of the tumor-node-metastasis classification (TNM-7) to the 8th edition (TNM-8), colorectal cancer with peritoneal metastasis was newly categorized as M1c. In the 9th edition of the Japanese Classification of colorectal, appendiceal, and anal carcinoma (JPC-9), M1c is further subdivided into M1c1 (without other organ involvement) and M1c2 (with other organ involvement). This study aimed to compare the model fit and discriminatory ability of the M category of these three classification systems, as no study to date has made this comparison., Methods: The study population consisted of stage IV colorectal cancer patients who were referred to the National Cancer Center Hospital from 2000 to 2017. The Akaike information criterion (AIC), Harrell's concordance index (C-index), and time-dependent receiver operating characteristic (ROC) curves were used to compare the three classification systems. Subgroup analyses, stratified by initial treatment year, were also performed., Results: According to TNM-8, 670 (55%) patients had M1a, 273 (22%) had M1b, and 279 (23%) had M1c (87 M1c1 and 192 M1c2 using JPC-9) tumors. Among the three classification systems, JPC-9 had the lowest AIC value (JPC-9: 10546.3; TNM-7: 10555.9; TNM-8: 10585.5), highest C-index (JPC-9: 0.608; TNM-7: 0.598; TNM-8: 0.599), and superior time-dependent ROC curves throughout the observation period. Subgroup analyses were consistent with these results., Conclusions: While the revised M category definition did not improve model fit and discriminatory ability from TNM-7 to TNM-8, further subdivision of M1c in JPC-9 improved these parameters. These results support further revisions to M1 subcategories in future editions of the TNM classification system., (© 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Purpose: The consensus molecular subtypes (CMS) represent a significant advance in the understanding of intertumor heterogeneity in colon cancer. Intratumor heterogeneity (ITH) is the new frontier for refining prognostication and understanding treatment resistance. This study aims at deciphering the transcriptomic ITH of colon cancer and understanding its potential prognostic implications., Experimental Design: We deconvoluted the transcriptomic profiles of 1,779 tumors from the PETACC8 trial and 155 colon cancer cell lines as weighted sums of the four CMSs, using the Weighted In Silico Pathology (WISP) algorithm. We assigned to each tumor and cell line a combination of up to three CMS subtypes with a threshold above 20%., Results: Over 55% of tumors corresponded to mixtures of at least two CMSs, demonstrating pervasive ITH in colon cancer. Of note, ITH was associated with shorter disease-free survival (DFS) and overall survival, [HR, 1.34; 95% confidence interval (CI; 1.12-1.59), 1.40, 95% CI (1.14-1.71), respectively]. Moreover, we uncovered specific combinations of CMS associated with dismal prognosis. In multivariate analysis, ITH represents the third parameter explaining DFS variance, after T and N stages. At a cellular level, combined WISP and single-cell transcriptomic analysis revealed that most colon cancer cell lines are a mixture of cells falling into different CMSs, indicating that ITH may correspond to distinct functional statuses of colon cancer cells., Conclusions: This study shows that CMS-based transcriptomic ITH is frequent in colon cancer and impacts its prognosis. CMS-based transcriptomic ITH may correspond to distinct functional statuses of colon cancer cells, suggesting plasticity between CMS-related cell populations. Transcriptomic ITH deserves further assessment in the context of personalized medicine., (©2021 The Authors; Published by the American Association for Cancer Research.)

Gene expression profiles can be utilized in the diagnosis of critical diseases such as cancer. The selection of biomarker genes from these profiles is significant and crucial for cancer detection. This paper presents a framework proposing a two-stage multifilter hybrid model of feature selection for colon cancer classification. Colon cancer is being extremely common nowadays among other types of cancer. There is a need to find fast and an accurate method to detect the tissues, and enhance the diagnostic process and the drug discovery. This paper reports on a study whose objective has been to improve the diagnosis of cancer of the colon through a two-stage, multifilter model of feature selection. The model described deals with feature selection using a combination of Information Gain and a Genetic Algorithm. The next stage is to filter and rank the genes identified through this method using the minimum Redundancy Maximum Relevance (mRMR) technique. The final phase is to further analyze the data using correlated machine learning algorithms. This two-stage approach, which involves the selection of genes before classification techniques are used, improves success rates for the identification of cancer cells. It is found that Decision Tree, K-Nearest Neighbor, and Naïve Bayes classifiers had showed promising accurate results using the developed hybrid framework model. It is concluded that the performance of our proposed method has achieved a higher accuracy in comparison with the existing methods reported in the literatures. This study can be used as a clue to enhance treatment and drug discovery for the colon cancer cure., Competing Interests: The authors have declared that no competing interests exist.

The eighth edition of the American Joint Committee on Cancer (AJCC) Staging Manual attempts to address ambiguity in the pT category assignment for colon cancer from prior editions. Despite modifications, the distinction between the pT3 and pT4a categories continues to be a source of diagnostic confusion. In this study, we assessed interobserver agreement among pathologists from different institutions in the application of AJCC eighth edition criteria for categorizing deeply invasive colonic adenocarcinomas. We identified morphologic patterns that produce diagnostic confusion. We assessed 47 colon cancers that closely approached the serosal surface. Six pathologists with interest in gastrointestinal pathology and 4 focused in other subspecialties classified each case as pT3 or pT4a, based on examination of low-magnification and high-magnification images of the most deeply invasive area. Interobserver agreement was assessed using Fleiss' κ. Cases displayed 3 morphologic patterns at the advancing tumor edge, namely, (1) continuous invasion through an inflammatory focus, (2) pushing border, and (3) infiltrative glands and cell clusters with serosal reaction. Gastrointestinal pathologists achieved slight (κ=0.21) or moderate (κ=0.46) and (κ=0.51) agreement in each category, whereas agreement among nongastrointestinal pathologist was fair (0.31) and (0.39), or moderate (0.57) for each category, respectively. In 10 (21%) cases, the distinction between pT3 and pT4a would have changed the overall clinical stage. We conclude that histologic criteria for serosal penetration is a persistent source of diagnostic ambiguity for gastrointestinal and general pathologists in the pT categorization of colon cancers. Clarification of these criteria will help ensure uniform reporting of pathologic and clinical stage.

Background/aim: As of 2020, adenocarcinoma arising in the ileocecal valve (ICV-A) has been examined along with cecal and right colon cancer (RCC) under the collective heading "ileocecal" tumor. We propose a new classification system for this cancer., Patients and Methods: We retrospectively analyzed RCC patients from 2003 to 2019. The scheme was: i) Type I cancer for adenocarcinomas residing in ICV; ii) Type II, if they reside 1 to 5 mm from ICV; iii) Type III, 6 mm to 10 mm from ICV; iv) Type IV, at 1,1 to 5 cm; v) Type V, at more than 5 cm (ascending colon cancer)., Results: Of 689 hemicolectomized patients, there were 91 (13.2%) Type I, 87 Type II (12.6%), 38 (5.5%) Type III, 157 (22.8%) Type IV and 314 (45.6%) Type V. Each type was associated with at least one clinicopathologic feature., Conclusion: ICV-A was classified into five types (I-V) according to the distance from ICV. Further studies are needed in order to corroborate our findings., (Copyright© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Histopathological classification of gastric and colonic epithelial tumours is one of the routine pathological diagnosis tasks for pathologists. Computational pathology techniques based on Artificial intelligence (AI) would be of high benefit in easing the ever increasing workloads on pathologists, especially in regions that have shortages in access to pathological diagnosis services. In this study, we trained convolutional neural networks (CNNs) and recurrent neural networks (RNNs) on biopsy histopathology whole-slide images (WSIs) of stomach and colon. The models were trained to classify WSI into adenocarcinoma, adenoma, and non-neoplastic. We evaluated our models on three independent test sets each, achieving area under the curves (AUCs) up to 0.97 and 0.99 for gastric adenocarcinoma and adenoma, respectively, and 0.96 and 0.99 for colonic adenocarcinoma and adenoma respectively. The results demonstrate the generalisation ability of our models and the high promising potential of deployment in a practical histopathological diagnostic workflow system.

Introduction: Probe-based confocal laser endomicroscopy (pCLE) is a promising modality for classifying polyp histology in vivo, but decision making in real-time is hampered by high-magnification targeting and by the learning curve for image interpretation. The aim of this study is to test the feasibility of a system combining the use of a low-magnification, wider field-of-view pCLE probe and a computer-assisted diagnosis (CAD) algorithm that automatically classifies colonic polyps., Methods: This feasibility study utilized images of polyps from 26 patients who underwent colonoscopy with pCLE. The pCLE images were reviewed offline by two expert and five junior endoscopists blinded to index histopathology. A subset of images was used to train classification software based on the consensus of two GI histopathologists. Images were processed to extract image features as inputs to a linear support vector machine classifier. We compared the CAD algorithm's prediction accuracy against the classification accuracy of the endoscopists., Results: We utilized 96 neoplastic and 93 non-neoplastic confocal images from 27 neoplastic and 20 non-neoplastic polyps. The CAD algorithm had sensitivity of 95%, specificity of 94%, and accuracy of 94%. The expert endoscopists had sensitivities of 98% and 95%, specificities of 98% and 96%, and accuracies of 98% and 96%, while the junior endoscopists had, on average, a sensitivity of 60%, specificity of 85%, and accuracy of 73%., Conclusion: The CAD algorithm showed comparable performance to offline review by expert endoscopists and improved performance when compared to junior endoscopists and may be useful for assisting clinical decision making in real time.

Purpose: The gold standard for colorectal cancer metastases detection in the peritoneum is histological evaluation of a removed tissue sample. For feedback during interventions, real-time in vivo imaging with confocal laser microscopy has been proposed for differentiation of benign and malignant tissue by manual expert evaluation. Automatic image classification could improve the surgical workflow further by providing immediate feedback., Methods: We analyze the feasibility of classifying tissue from confocal laser microscopy in the colon and peritoneum. For this purpose, we adopt both classical and state-of-the-art convolutional neural networks to directly learn from the images. As the available dataset is small, we investigate several transfer learning strategies including partial freezing variants and full fine-tuning. We address the distinction of different tissue types, as well as benign and malignant tissue., Results: We present a thorough analysis of transfer learning strategies for colorectal cancer with confocal laser microscopy. In the peritoneum, metastases are classified with an AUC of 97.1, and in the colon the primarius is classified with an AUC of 73.1. In general, transfer learning substantially improves performance over training from scratch. We find that the optimal transfer learning strategy differs for models and classification tasks., Conclusions: We demonstrate that convolutional neural networks and transfer learning can be used to identify cancer tissue with confocal laser microscopy. We show that there is no generally optimal transfer learning strategy and model as well as task-specific engineering is required. Given the high performance for the peritoneum, even with a small dataset, application for intraoperative decision support could be feasible.

Aim: To investigate whether differences in histotype in colon cancer correlate with clinical presentation and if they might influence oncological outcomes and survival., Methods: Data regarding colon cancer patients operated both electively or in emergency between 2009 and 2014 were retrospectively collected from a prospectively maintained database and analyzed for the purpose of this study. Rectal cancer was excluded from this analysis. Statistical univariate and multivariate analyses were performed to investigate possible significant variables influencing clinical presentation, as well as oncological outcomes and survival., Results: Data from 219 patients undergoing colorectal resection for cancer of the colon only were retrieved. One hundred seventy-four patients had an elective procedure and forty-five had an emergency colectomy. Emergency presentation was more likely to occur in mucinous (p < 0.05) and signet ring cell (p < 0.01) tumors. No definitive differences in 5-year overall (44.7% vs. 60.6%, p = 0.078) and disease-free (51.2% vs. 64.4%, p = 0.09) survival were found between the two groups as a whole, but the T3 emergency patients showed worse prognosis than the elective (p < 0.03). Lymph node invasion, laparoscopy, histology, and blood transfusions were independent variables found to influence survival. Distribution assessed for pTNM stage showed T3 cancers were more common in emergency (p < 0.01)., Conclusions and Discussion: Mucinous and signet ring cell tumors are related to emergency presentation, pT3 stage, poorest outcomes, and survival. Disease-free survival in patients who had emergency surgery for T3 colon cancer seems related to the histotype.

We utilize deep neural networks to develop prediction models for patient survival and conditional survival of colon cancer. Our models are trained and validated on data obtained from the Surveillance, Epidemiology, and End Results Program. We provide an online outcome calculator for 1, 2, and 5 years survival periods. We experimented with multiple neural network structures and found that a network with five hidden layers produces the best results for these data. Moreover, the online outcome calculator provides conditional survival of 1, 2, and 5 years after surviving the mentioned survival periods. In this article, we report an approximate 0.87 area under the receiver operating characteristic curve measurements, higher than the 0.85 reported by Stojadinovic et al.

Background: The American Joint Commission on Cancer, the European Neuroendocrine Tumor Society, and the North American Neuroendocrine Tumor Society all classify colon neuroendocrine tumor (NET) nodal metastasis as N0 or N1. This binary classification does not allow for further prognostication by the total number of positive lymph nodes. This study aimed to evaluate whether the total number of positive lymph nodes affects the overall survival for patients with colon NET., Methods: The National Cancer Database was used to identify patients with colon NET. Nearest-neighborhood grouping was performed to classify patients by survival to create a new nodal staging system. The Surveillance, Epidemiology, and End Results database was used to validate the new nodal staging classification., Results: Colon NETs were identified in 2472 patients. Distinct 5-year survival rates were estimated for the patients with N0 (no positive lymph nodes; 69.8%; 95% confidence interval [CI], 66.7-72.7%), N1a (1 positive lymph node; 63.9%; 95% CI, 59.6-68.0%), N1b (2-9 positive lymph nodes; 38.9%; 95% CI, 35.4-42.3%), and N2 (≥ 10 positive lymph nodes; 15.7%; 95% CI, 11.9-20.0%; p < 0.001) nodal classifications. The validation population showed distinct 5-year survival rates with the new nodal staging. In multivariable Cox regression, the new nodal stage was a significant independent predictor of overall survival., Conclusions: The number of positive locoregional lymph nodes in colon NETs is an independent prognostic factor. For patients with colon NETs, N0, N1a, N1b, and N2 classifications for nodal metastasis more accurately predict survival than current staging systems.

Background: The risk of cancers is well characterized in Lynch syndrome (LS) families but has been less studied in familial colorectal cancer type X (FCCTX) families., Methods: In this article, we compare the risk estimates of first and second colorectal cancers (CRCs) in 168 FCTTX and 780 LS families recruited through the Colon Cancer Family Registry as well as the risk of cancer-related deaths and disease-free survival (DFS) after a first CRC. Our methodology is based on a survival analysis approach, developed specifically to model the occurrence of successive cancers (ie, first and second CRCs) in the presence of competing risk events (ie, death from any causes)., Results: We found an excess risk of first and second CRC in individuals with LS compared to FCCTX family members. However, for an average age at first CRC of 60 years in FCCTX families and 50 years in LS families, the DFS rates were comparable in men but lower in women from FCCTX vs LS families, eg , 75.1% (95% confidence interval [CI] = 69.0% to 80.9%) vs 78.9% (95% CI = 76.3% to 81.3%) for the 10-year DFS. The 10-year risk of cancer-related death was higher in FCCTX families vs LS families, eg, 15.4% in men (95% CI = 10.9% to 19.8%) and 19.3% in women (95% CI = 13.6% to 24.7%) vs 8.9% (95% CI = 7.5% to 11.4%) and 8.7% (95% CI = 7.1% to 10.8%), respectively., Conclusions: Individuals with CRCs arising in the context of FCCTX do not experience the same improved DFS and overall survival of those with LS, and that difference may be relevant in management decisions., (© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Benign lipomatous lesions of the colon are generally asymptomatic. A few histologic subtypes are appreciable, but this is poorly studied. We categorized 404 benign colonic lipomatous lesions as vascular lipoma, fibrolipoma, mucosal lipoma, or lipoma not otherwise specified (NOS). We compared patient age and sex, tumor site and size, symptoms, whether the lesion was flat or pedunculated, and whether an overlying epithelial lesion was present. Symptomatic cases (4%) were larger on average than non-symptomatic ones (mean 3.70 cm vs. 1.30 cm, P < 0.0001). Lipoma NOS was commonly right-sided (P < 0.001) and commonly had an associated epithelial proliferation (P = 0.0004). Vascular lipomas were larger (mean 1.93 cm, P < 0.0001) than other types; they were the most commonly symptomatic, though this was not statistically significant. Mucosal lipomas were smallest on average (mean 0.48 cm) and were not associated with any clinical syndromes. Some colonic lipomas are non-incidental. Vascular lipomas are more often large, while lipomas NOS more often have an associated epithelial proliferation. Colonic lipomas are generally sporadic.

Background: Characterization of colonic lesions in inflammatory bowel disease (IBD) remains challenging. We developed an endoscopic classification of visual characteristics to identify colitis-associated neoplasia using multimodal advanced endoscopic imaging (Frankfurt Advanced Chromoendoscopic IBD LEsions [FACILE] classification)., Methods: The study was conducted in three phases: 1) development - an expert panel defined endoscopic signs and predictors of dysplasia in IBD and, using multivariable logistic regression created the FACILE classification; 2) validation - using 60 IBD lesions from an image library, two assessments of diagnostic accuracy for neoplasia were performed and interobserver agreement between experts using FACILE was determined; 3) reproducibility - the reproducibility of the FACILE classification was tested in gastroenterologists, trainees, and junior doctors after completion of a training module., Results: The experts initially selected criteria such as morphology, color, surface, vessel architecture, signs of inflammation, and lesion border. Multivariable logistic regression confirmed that nonpolypoid lesion, irregular vessel architecture, irregular surface pattern, and signs of inflammation within the lesion were predictors of dysplasia. Area under the curve of this logistic model using a bootstrapped estimate was 0.76 (0.73 - 0.78). The training module resulted in improved accuracy and kappa agreement in all nonexperts, though in trainees and junior doctors the kappa agreement was still moderate and poor, respectively., Conclusion: We developed, validated, and demonstrated reproducibility of a new endoscopic classification (FACILE) for the diagnosis of dysplasia in IBD using all imaging modalities. Flat shape, irregular surface and vascular patterns, and signs of inflammation predicted dysplasia. The diagnostic performance of all nonexpert participants improved after a training module., Competing Interests: Dr Iacucci has received an unrestricted research grant from Pentax USA. Dr. Sanduleanu has received an unrestricted research grant from Pentax Europe., (© Georg Thieme Verlag KG Stuttgart · New York.)

The current research study is concerned with the automated differentiation between histopathological slides from colon tissues with respect to four classes (healthy tissue and cancerous of grades 1, 2 or 3) through an optimized ensemble of predictors. Six distinct classifiers with prediction accuracies ranging from 87% to 95% are considered for the task. The proposed method of combining them takes into account the probabilities of the individual classifiers for each sample to be assigned to any of the four classes, optimizes weights for each technique by differential evolution and attains an accuracy that is significantly better than the individual results. Moreover, a degree of confidence is defined that would allow the pathologists to separate the data into two distinct sets, one that is correctly classified with a high level of confidence and the rest that would need their further attention. The tandem is also validated on other benchmark data sets. The proposed methodology proves to be efficient in improving the classification accuracy of each algorithm taken separately and performs reasonably well on other data sets, even with default weights. In addition, by establishing a degree of confidence the method becomes more viable for use by actual practitioners., Competing Interests: DL is employed by Wolfram Research, Inc. and received research materials in that his employer permitted the use of his desktop computer in this work. There are no patents, products in development or marketed products associated with this research to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: pN stage in the TNM classification has been the "gold standard" for lymph node staging of colorectal carcinomas, but this system recommends collecting at least 12 lymph nodes for the staging to be reliable. However, new prognostic staging systems have been devised, such as the ganglion quotients or lymph node ratios and natural logarithms of the lymph node odds methods. The aim of this study was to establish and validate the predictive and prognostic ability of the lymph node ratios and natural logarithms of the lymph node odds staging systems and to compare them to the pN nodal classification of the TNM system in a population sample of patients with colon cancer., Methods: A multicentric population study between January 2004 and December 2007. The inclusion criteria were that the patients were: diagnosed with colon cancer, undergoing surgery with curative intent, and had a complete anatomopathological report. We excluded patients with cancer of the rectum or caecal appendix with metastases at diagnosis. Survival analysis was performed using the Kaplan-Meier actuarial method and the Log-Rank test was implemented to estimate the differences between groups in terms of overall survival and disease-free survival. Multivariate survival analysis was performed using Cox regression., Results: We analysed 548 patients. For the overall survival, the lymph node ratios and natural logarithms of the lymph node odds curves were easier to discriminate because their separation was clearer and more balanced. For disease-free survival, the discrimination between the pN0 and pN1 groups was poor, but this phenomenon was adequately corrected for the lymph node ratios and natural logarithms of the lymph node odds curves which could be sufficiently discriminated to be able to estimate the survival prognosis., Conclusions: Lymph node ratios and natural logarithms of the lymph node odds techniques can more precisely differentiate risk subgroups from within the pN groups. Of the three methods tested in this study, the natural logarithms of the lymph node odds was the most accurate for staging non-metastatic colon cancer. Thus helping to more precisely adjust and individualise the indication for adjuvant treatments in these patients.

Goblet cell carcinoid tumors are amphicrine tumors whose biological behavior ranges from indolent to highly aggressive, depending on tumor grade. Current grading systems for these tumors are based on identifying an adenocarcinoma arising in the setting of a goblet cell carcinoid tumor, which distinguishes this tumor from other gastrointestinal tract adenocarcinomas. Because goblet cell tumors are predominantly tumors of mucin secreting cells, we propose that they be classified as goblet cell adenocarcinomas, and graded using a methodology that has parallels in colorectal adenocarcinoma grading. We graded a large series of goblet cell adenocarcinomas by assessing the proportion of the tumor that demonstrates tubular or clustered growth. Histologic grade correlated with overall survival independent of stage, with median overall survival of 204, 86, and 29 months for low-grade, intermediate-grade, and high-grade goblet cell adenocarcinomas, respectively. Tumor stage also correlated with overall survival. We also graded the tumors according to previously proposed grading systems, and found that these systems are valid, in that they segregate patients according to prognosis.

Background: The estimation of risk of recurrence for patients with colon carcinoma must be improved. A robust immune score quantification is needed to introduce immune parameters into cancer classification. The aim of the study was to assess the prognostic value of total tumour-infiltrating T-cell counts and cytotoxic tumour-infiltrating T-cells counts with the consensus Immunoscore assay in patients with stage I-III colon cancer., Methods: An international consortium of 14 centres in 13 countries, led by the Society for Immunotherapy of Cancer, assessed the Immunoscore assay in patients with TNM stage I-III colon cancer. Patients were randomly assigned to a training set, an internal validation set, or an external validation set. Paraffin sections of the colon tumour and invasive margin from each patient were processed by immunohistochemistry, and the densities of CD3+ and cytotoxic CD8+ T cells in the tumour and in the invasive margin were quantified by digital pathology. An Immunoscore for each patient was derived from the mean of four density percentiles. The primary endpoint was to evaluate the prognostic value of the Immunoscore for time to recurrence, defined as time from surgery to disease recurrence. Stratified multivariable Cox models were used to assess the associations between Immunoscore and outcomes, adjusting for potential confounders. Harrell's C-statistics was used to assess model performance., Findings: Tissue samples from 3539 patients were processed, and samples from 2681 patients were included in the analyses after quality controls (700 patients in the training set, 636 patients in the internal validation set, and 1345 patients in the external validation set). The Immunoscore assay showed a high level of reproducibility between observers and centres (r=0·97 for colon tumour; r=0·97 for invasive margin; p<0·0001). In the training set, patients with a high Immunoscore had the lowest risk of recurrence at 5 years (14 [8%] patients with a high Immunoscore vs 65 (19%) patients with an intermediate Immunoscore vs 51 (32%) patients with a low Immunoscore; hazard ratio [HR] for high vs low Immunoscore 0·20, 95% CI 0·10-0·38; p<0·0001). The findings were confirmed in the two validation sets (n=1981). In the stratified Cox multivariable analysis, the Immunoscore association with time to recurrence was independent of patient age, sex, T stage, N stage, microsatellite instability, and existing prognostic factors (p<0·0001). Of 1434 patients with stage II cancer, the difference in risk of recurrence at 5 years was significant (HR for high vs low Immunoscore 0·33, 95% CI 0·21-0·52; p<0·0001), including in Cox multivariable analysis (p<0·0001). Immunoscore had the highest relative contribution to the risk of all clinical parameters, including the American Joint Committee on Cancer and Union for International Cancer Control TNM classification system., Interpretation: The Immunoscore provides a reliable estimate of the risk of recurrence in patients with colon cancer. These results support the implementation of the consensus Immunoscore as a new component of a TNM-Immune classification of cancer., Funding: French National Institute of Health and Medical Research, the LabEx Immuno-oncology, the Transcan ERAnet Immunoscore European project, Association pour la Recherche contre le Cancer, CARPEM, AP-HP, Institut National du Cancer, Italian Association for Cancer Research, national grants and the Society for Immunotherapy of Cancer., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Traditionally, carcinoma classifications have been based on clinical or pathological features. However, with the development of molecular biology in recent decades, more tumors are increasingly being genetically studied and, in several of them, molecular classifications have been created (the most widely studied and used is that for breast cancer). Colon and rectum cancer are no exception. In this short review, the evolution of colon and rectum cancer molecular classification is explained and the consensus conclusions on the subject are addressed., (Copyright: © 2018 SecretarÍa de Salud.)

Background: Sessile serrated adenomas/polyps are distinguished from hyperplastic colonic polyps subjectively by their endoscopic appearance and histological morphology. However, hyperplastic and sessile serrated polyps can have overlapping morphological features resulting in sessile serrated polyps diagnosed as hyperplastic. While sessile serrated polyps can progress into colon cancer, hyperplastic polyps have virtually no risk for colon cancer. Objective measures, differentiating these types of polyps would improve cancer prevention and treatment outcome., Methods: RNA-seq training data set and Affimetrix, Illumina testing data sets were obtained from Gene Expression Omnibus (GEO). RNA-seq single-end reads were filtered with FastX toolkit. Read mapping to the human genome, gene abundance estimation, and differential expression analysis were performed with Tophat-Cufflinks pipeline. Background correction, normalization, and probe summarization steps for Affimetrix arrays were performed using the robust multi-array method (RMA). For Illumina arrays, log 2 -scale expression data was obtained from GEO. Pathway analysis was implemented using Bioconductor package GSAR. To build a platform-independent molecular classifier that accurately differentiates sessile serrated and hyperplastic polyps we developed a new feature selection step. We also developed a simple procedure to classify new samples as either sessile serrated or hyperplastic with a class probability assigned to the decision, estimated using Cantelli's inequality., Results: The classifier trained on RNA-seq data and tested on two independent microarray data sets resulted in zero and three errors. The classifier was further tested using quantitative real-time PCR expression levels of 45 blinded independent formalin-fixed paraffin-embedded specimens and was highly accurate. Pathway analyses have shown that sessile serrated polyps are distinguished from hyperplastic polyps and normal controls by: up-regulation of pathways implicated in proliferation, inflammation, cell-cell adhesion and down-regulation of serine threonine kinase signaling pathway; differential co-expression of pathways regulating cell division, protein trafficking and kinase activities., Conclusions: Most of the differentially expressed pathways are known as hallmarks of cancer and likely to explain why sessile serrated polyps are more prone to neoplastic transformation than hyperplastic. The new molecular classifier includes 13 genes and may facilitate objective differentiation between two polyps.

Background: Recent studies have disclosed novel histological phenotypes of colon tumours in carcinogen-treated rats. The aim of this study was to update the current histological classification of colonic neoplasias in Sprague-Dawley (SD) rats., Materials and Methods: Archival sections from 398 SD rats having 408 neoplasias in previous experiments were re-evaluated., Results: Of the 408 colonic neoplasias, 11% (44/408) were adenomas without invasive growth and 89% (364/408) invasive carcinomas. Out of the 44 adenomas, 82% were conventional (tubular or villous), 14% traditional serrated (TSA; with unlocked serrations or with closed microtubules) and 5% gut-associated lymphoid tissue (GALT)-associated adenomas. Out of 364 carcinomas, 57% were conventional carcinomas, 26% GALT carcinomas, 8% undifferentiated, 6% signet-ring cell carcinomas, and 4% traditional serrated carcinomas (TSC). Thus, conventional adenomas, conventional carcinomas and GALT-associated carcinomas predominated (p<0.05)., Conclusion: The updated classification of colonic tumours in SD rats includes conventional adenomas, TSA, GALT-associated adenomas, conventional carcinomas, TSC, GALT-associated carcinomas, signet-ring cell carcinomas and undifferentiated carcinomas. Several of the histological phenotypes reported here are not included in any of the current classifications of colonic tumours in rodents. This updated classification fulfils the requirements for an animal model of human disease, inasmuch as similar histological phenotypes of colon neoplasias have been documented in humans., (Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Purpose: Preclinical imaging offers a useful tool for monitoring cancer biological behavior and therapy in vivo without the necessity of animal surgery. The following paper describes our examination of tumor progress and anti-angiogenic therapy with Bevacizumab on colon cancer subtypes (SW480 and SW620) by using different non-invasive real-time in vivo imaging techniques., Procedures: Color Doppler ultrasound imaging (CDUI) was used to observe the formation of new blood vessels; a homemade fluorescence reflectance imaging (FRI) apparatus was mainly used to test the difference in VEGFR2 expression between the tumor subtypes. Briefly, 15 Balb/c nude mice bearing subcutaneous SW480 and SW620 xenografts were randomly divided into Control and Drug groups. Bevacizumab treatment lasted for 3 weeks. All images were captured pre- and post-treatment. At the end of experiment, all mice were euthanized, and tumor tissue was collected and analyzed by immunohistochemical staining., Results: Expression of VEGFR2 was found to be slightly (10 %) but significantly higher for the SW620 cells than for SW480 cells. In addition, SW620 has shown to be more vascularized than SW480 subtype. After 3-week Bevacizumab therapy, no blood vessels were found within 83 % of SW620, while it was 67 % in SW480; the increase of SW620 tumor volume post-treatment was only 3.17-fold compared with the tumor volume pre-treatment, and 4.51-fold higher in SW480., Conclusion: Our data suggest that SW480 and SW620 cell lines respond differently to Bevacizumab therapy in vivo. Because of higher vascularization, and subsequently higher reduction by drug of new blood vessels and tumor growth rate, xenografts derived from the metastatic SW620 cell line have a better chance of being successfully treated with Bevacizumab compared with those derived from the primary tumor SW480 cell line.

The WHO published a new classification of colonic polyps in 2010, including the group of serrated polyps, which can be divided into hyperplastic polyps (HP), traditional serrated adenomas, and sessile serrated adenomas (SSA) or polyps. To assess the rate of re-diagnosis of HP to SSA and to look for possible predictors for changing the diagnosis. English Medical literature searches were performed for 'reassessment' OR 'reclassification' AND 'hyperplastic polyp' OR 'sessile serrated adenoma' till 31 January 2017. PRISMA guidelines for systematic reviews were followed. Studies that included a precise re-diagnosis of HP into SSA were included. We also looked for predictors of SSA diagnosis such as polyp location and size, patient sex and age, and synchronous advanced adenoma. Altogether, we found 220 eligible studies; 212 were excluded as they did not fulfill the inclusion criteria and we were left with eight studies including 2625 patients. The odds ratio for the number of polyps with changed pathological diagnosis from HP to SSA was 0.112 with 95% confidence interval (CI): 0.099-0.126 (P<0.0001) or 11.2%. Heterogeneity between studies was significant with Q=199.4, d.f. (Q)=9, P<0.0001, and I=95.486%. The odds ratio for changing the pathological diagnosis from HP to SSA for polyp proximal location and polyp size more than 5 mm were 4.401, 95% CI: 2.784-6.958, P<0.0001, and 8.336, 95% CI: 4.963-15.571, P<0.0001, respectively. Endoscopists and pathologists should be aware of the SSA diagnosis when finding HPs larger than 5 mm in the right colon. The diagnosis of HP in these cases should be reassessed by experienced gastrointestinal pathologists.

Background: Consensus molecular subtype 4 (CMS4) is a recently identified aggressive colon cancer subtype for which platelet-derived growth factor receptors (PDGFRs) and KIT are potential therapeutic targets. We aimed to develop a clinically applicable CMS4 reverse transcription polymerase chain reaction (RT-qPCR) test to select patients for PDGFR/KIT-targeted therapy., Methods: We used logistic regression to develop a CMS4 prediction rule based on microarray expression values of PDGFRA , PDGFRB , PDGFC , and KIT (566 training and 1259 test samples, using the 273-gene random forest classifier as CMS4 reference standard). We next translated the prediction rule into a single-sample RT-qPCR test, which we independently validated in 29 fresh tumor samples. To study intratumor CMS4 heterogeneity, we used the RT-qPCR test to analyze five random regions of 20 colon tumors., Results: The microarray-based prediction rule diagnosed CMS4-type tumors extremely well in both training and independent test samples (training: area under the curve [AUC] = 0.95, 95% confidence interval [CI] = 0.94 to 0.97; test: AUC = 0.95, 95% CI = 0.94 to 0.96), with excellent calibration and approximately 80% overall net benefit over a large threshold range. Translation into an RT-qPCR test did not affect discrimination (AUC = 0.97, 95% CI = 0.93 to 1.00, independent validation). RT-qPCR analysis of five random tumor regions revealed extensive intratumor CMS4 heterogeneity in nine out of 20 tumors. At least two regions likely have to be analyzed to identify patients that are predominantly CMS4 positive (>50% average CMS4 chance)., Conclusion: The CMS4 RT-qPCR test is a promising clinical tool for selecting individual patients for CMS4-subtype-targeted therapy., (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Background and Aims: The diagnosis of irritable bowel syndrome (IBS) is based mainly on clinical evaluation. The reported incidence of misclassification of significant organic diseases in previously diagnosed IBS patients differs between studies. The aim of this study was to examine the incidence and risk factors for the misclassification of significant organic disease [colon cancer, inflammatory bowel disease (IBD), Celiac disease, and thyroid dysfunction] in a cohort of young patients with symptoms attributed to IBS., Methods: In this population-based cohort study, we examined the incidence and risk factors for the diagnosis of a new significant organic diseases in a cohort of 2645 IBS patients., Results: During follow-up, organic disease was diagnosed in 27 subjects (1.03%): IBD in 23, Celiac disease in 2, IBD and Celiac disease in 1, and hypothyroidism in1. The mean interval from the diagnosis of IBS to the diagnosis of an organic disorder was 13.08±8.51 months. Increased symptom severity was the only significant risk factor for the misclassification of an organic disease (hazard ratio, 2.26; 95% confidence interval, 1.01-5.05; P=0.047). The risk ratio for misclassification of organic diseases in moderate to severe IBS was increased by 2.575 (95% confidence interval, 1.10-6.51; P=0.027) as compared with mild IBS., Conclusions: The incidence of misclassification of major organic disease in IBS patients was low. Increased symptoms severity was the only significant risk factor for the misclassification of organic disorders. Further gastrointestinal evaluation should be considered in patients with moderate to severe symptoms attributed to IBS.

Background: Caudal-type homeobox transcription factor 2 (CDX2) is involved in colon cancer (CC) oncogenesis and has been proposed as a prognostic biomarker in patients with stage II or III CC., Patients and Methods: We analyzed CDX2 expression in a series of 469 CC typed for the new international consensus molecular subtype (CMS) classification, and we confirmed results in a series of 90 CC., Results: Here, we show that lack of CDX2 expression is only present in the mesenchymal subgroup (CMS4) and in MSI-immune tumors (CMS1) and not in CMS2 and CMS3 colon cancer. Although CDX2 expression was a globally independent prognostic factor, loss of CDX2 expression is not associated with a worse prognosis in the CMS1 group, but is highly prognostic in CMS4 patients for both relapse free and overall survival. Similarly, lack of CDX2 expression was a bad prognostic factor in MSS patients, but not in MSI., Conclusions: Our work suggests that combination of the consensual CMS classification and lack of CDX2 expression could be a useful marker to identify CMS4/CDX2-negative patients with a very poor prognosis., (© The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background/aims: This study evaluated and compared the clinical and prognostic values of the grading criteria used by the World Health Organization (WHO) and the European Neuroendocrine Tumors Society (ENETS). Moreover, this work assessed the current best prognostic model for colorectal neuroendocrine tumors (CRNETs)., Results: The 2010 WHO classifications and the ENETS systems can both stratify the patients into prognostic groups, although the 2010 WHO criteria is more applicable to CRNET patients. Along with tumor location, the 2010 WHO criteria are important independent prognostic parameters for CRNETs in both univariate and multivariate analyses through Cox regression (P<0.05)., Methods: Data from 192 consecutive patients histopathologically diagnosed with CRNETs and had undergone surgical resection from January 2009 to May 2016 in a single center were retrospectively analyzed., Conclusions: Findings suggest that the WHO classifications are superior over the ENETS classification system in predicting the prognosis of CRNETs. Additionally, the WHO classifications can be widely used in clinical practice.

Aims: Despite almost pathognomonic status of ectopic crypt foci (ECF) in the diagnosis of traditional serrated adenoma (TSA), there are few systematic studies on their prevalence in other types of colon polyps or in adenomas adjacent to colorectal cancer (CRC)., Methods: We calculated ECF in all the polyps (n=922) removed in the colonoscopy in Oulu University Hospital in 2001. Moreover, to study ECF in precursor lesions next to CRCs, we re-examined a previously described cohort of 148 CRCs., Results: ECF were seen in 53 (5.7%) polyps representing 28 (6.5%) tubular adenomas (TAs), 14 (53.8%) tubulovillous adenomas (TVAs), 2 (100.0%) villous adenomas (VAs) and 9 (100.0%) TSAs. In all TSAs and VAs, the density of ECF was higher than in TVAs and TAs. An adjacent precursor lesion was recognised in 28 of 148 (18.9%) CRCs. Twenty-four (85.7%) of these contained ECF., Conclusions: ECF can most frequently be observed in TSAs but also in many TVAs, VAs and TAs, reflecting a histological overlap between serrated and conventional polyps. Especially, precursor lesions adjacent to CRC frequently contain ECF., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Multiple gene-expression-based subtypes have been proposed for the molecular subdivision of colon cancer in the last decade. We aimed to cross-validate these classifiers to explore their concordance and their power to predict survival. A gene-chip-based database comprising 2,166 samples from 12 independent datasets was set up. A total of 22 different molecular subtypes were re-trained including the CCHS, CIN25, CMS, ColoGuideEx, ColoGuidePro, CRCassigner, MDA114, Meta163, ODXcolon, Oncodefender, TCA19, and V7RHS classifiers as well as subtypes established by Budinska, Chang, DeSousa, Marisa, Merlos, Popovici, Schetter, Yuen, and Watanabe (first authors). Correlation with survival was assessed by Cox proportional hazards regression for each classifier using relapse-free survival data. The highest efficacy at predicting survival in stage 2-3 patients was achieved by Yuen (p = 3.9e-05, HR = 2.9), Marisa (p = 2.6e-05, HR = 2.6) and Chang (p = 9e-09, HR = 2.35). Finally, 61 colon cancer cell lines from four independent studies were assigned to the closest molecular subtype.

Laparoscopic surgery for colorectal cancer in Sweden has previously been performed infrequently but is presently increasing, and in 2014 more than one fourth of all patients with colorectal cancer underwent laparoscopic resection. Regional differences are decreasing but substantial variation persists with regard to individual hospitals and the use of laparoscopy. All Swedish patients undergoing resection for cancer in the ascending and sigmoid colon between 2012-2014 (n=8269; laparoscopic resection 17%) were assessed with regard to patient demography and short-term outcome. The present investigation demonstrated that open surgery was more often performed in patients with locally advanced cancer or with metastatic disease and that laparoscopically operated patients were slightly younger and had less comorbidity. Short term surgical outcome was better in patients who underwent laparoscopy, a difference which may be attributed to a certain patient selection demonstrated in the present investigation. The number of retrieved lymph nodes was comparable and hospital stay was two days shorter in patients with laparoscopic resection.

BRAF(V600E) mutant colon cancers (CCs) have a characteristic gene expression signature that is also found in some tumors lacking this mutation. Collectively, they are referred to as "BRAF-like" tumors and represent some 20% of CCs. We used a shRNA-based genetic screen focused on genes upregulated in BRAF(V600E) CCs to identify vulnerabilities of this tumor subtype that might be exploited therapeutically. Here, we identify RANBP2 (also known as NUP358) as essential for survival of BRAF-like, but not for non-BRAF-like, CC cells. Suppression of RANBP2 results in mitotic defects only in BRAF-like CC cells, leading to cell death. Mechanistically, RANBP2 silencing reduces microtubule outgrowth from the kinetochores, thereby inducing spindle perturbations, providing an explanation for the observed mitotic defects. We find that BRAF-like CCs display far greater sensitivity to the microtubule poison vinorelbine both in vitro and in vivo, suggesting that vinorelbine is a potential tailored treatment for BRAF-like CCs., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: Mucinous carcinoma is often independently classified as a histological type of colon cancer, but there are currently no established diagnostic criteria. The relationship between the proportions of mucinous components to the oncological outcomes was examined to determine whether mucinous carcinoma should be classified as an independent histological type., Methods: The study group comprised 1,038 patients with colon cancer. The relationships between the survival rates and recurrence patterns with the mucinous component area ratio (MC area ratio) and clinical variables were evaluated., Results: Tumors were classified into three groups: Group 1 (MC area ratio, 0 %), Group 2 (1-49 %), and Group 3 (≥50 %). Of the 1038 tumors studied, 877 (84 %) were classified as Group 1, 123 (12 %) as Group 2, and 38 (4 %) as Group 3. The tumor size was significantly larger in Group 3, and an increased MC area ratio was significantly related to a higher proportion of right-sided tumors. Among patients with stage II or III disease, stage III disease, poorly differentiated adenocarcinoma, and no adjuvant chemotherapy were poor prognostic factors. There was no relationship between the MC area ratio and the survival or recurrence pattern., Conclusion: Mucinous carcinoma does not need to be classified as a separate histological type from ordinary differentiated adenocarcinoma.

Background and Aim: Sessile serrated adenoma/polyps (SSAPs) are suspected to have a high malignant potential, although few reports have evaluated the incidence of carcinomas derived from SSAPs using the new classification for serrated polyps (SPs). The aim of study was to compare the frequency of cancer coexisting with the various SP subtypes including mixed polyps (MIXs) and conventional adenomas (CADs)., Methods: A total of 18,667 CADs were identified between April 2005 and December 2011, and 1858 SPs (re-classified as SSAP, hyperplastic polyp (HP), traditional serrated adenoma (TSA), or MIX) were removed via snare polypectomy, endoscopic mucosal resection, or endoscopic sub-mucosal dissection., Results: Among 1160 HP lesions, 1 (0.1%) coexisting sub-mucosal invasive carcinoma (T1) was detected. Among 430 SSAP lesions, 3 (0.7%) high-grade dysplasia (HGD/Tis) and 1 (0.2%) T1 were detected. All of the lesions were detected in the proximal colon, with a mean tumor diameter of 18 mm (SD 9 mm). Among 212 TSA lesions, 3 (1%) HGD/Tis were detected but no T1 cancer. Among 56 MIX lesions, 9 (16%) HGD/Tis and 1 (2%) T1 cancers were detected, and among 18,677 CAD lesions, 964 (5%) HGD/Tis and 166 (1%) T1 cancers were identified., Conclusions: Among the resected lesions that were detected during endoscopic examination, a smaller proportion (1%) of SSAPs harbored HGD or coexisting cancer, compared to CAD or MIX lesions. Therefore, more attention should be paid to accurately identifying lesions endoscopically for intentional resection and the surveillance of each SP subtype.

Introduction: A substantial interobserver variation in the differential diagnosis of hyperplastic polyps (HPs) and sessile or traditional serrated adenomas (SSAs/TSAs) has been described., Methods: The aim of this study is to determine the magnitude of reclassification of HPs and associated factors after pathological reassessment of specimens from screening and surveillance colonoscopies, and to estimate its consequences for follow-up recommendations., Results: Among 1694 screening and surveillance colonoscopies, a total of 536 polyps were initially diagnosed as HPs and remained unchanged in 88.5% (n = 474), whereas 7.6 (n = 41) and 1.1% (n = 6) were reclassified as SSA and TSA, respectively. Compared to definite HPs, SSAs were found more frequently in men than in women (82.9 vs. 61.2%, p < 0.05), and in individuals ≥65.0 years (51.2 vs. 31.6%, p = 0.05). Also, more SSAs were >5 mm in size (36.6 vs. 6.3%, p < 0.05) and were localized in the proximal colon (31.7 vs. 11.8%, p < 0.05). In a mixed model analysis, age ≥65.0 years (OR 4.13, 95% CI 1.22-14.2), snare polypectomy (OR 23.6, 95% CI 4.86-115), and coincident advanced adenomas (OR 7.56, 95% CI 1.31-43.5) were significantly (p < 0.05) associated with reclassification to SSAs. Only 0.53% of patients had received false recommendations for follow-up visits based on the incorrect HP diagnosis. A c.1799T>A, p.V600E BRAF mutation was detected in 21.9 % (n = 9) of reclassified SSAs., Conclusion: Considering these factors may be helpful in serrated lesions that are difficult to allocate. Incorrect recommendations regarding control colonoscopy intervals due to misdiagnosed HPs can explain only a small fraction of interval colorectal cancers.

Based on gene expression, we have classified 53 colon cancer patients with UICC II into two groups: relapse and no relapse. Samples were taken from each patient, and gene information was extracted. Of the 53 samples examined, 500 genes were considered proper through analyses by S-Kohonen, BP, and SVM neural networks. Classification accuracy obtained by S-Kohonen neural network reaches 91%, which was more accurate than classification by BP and SVM neural networks. The results show that S-Kohonen neural network is more plausible for classification and has a certain feasibility and validity as compared with BP and SVM neural networks.

In order to ascertain the relationship between gene expression and colon cancer localization, a classification method based on random gene selection and a self-organizing map network is proposed. Different numbers of genes were selected randomly from 54,675 genes of 53 colon cancer patients in stage union for international cancer control II. These patients were then divided into two sets: a training set of 36 and a validation set of 17 patients. In this study, we randomly selected 1000, 100, 50, 30, 10, 5, and 3 genes, 1000 times, respectively. The minimum misclassification ratio of each gene group was 3/17 to 4/17, and the percentage of gene groups that were less than 0.25 was approximately 1-7%. Moreover, the misclassification ratio of most gene groups (about 82-89%) was lower than 0.4. Through the analysis of these low misclassification ratio gene groups, we found that there were few common genes between them. This revealed that colon cancer localization is not associated with a single gene group but with many gene groups. Furthermore, K-fold cross validation was used to test the reliability of the possible informative genes, and the results indicated that using gene expression to classify colon tumor localization was not feasible.

The histopathological examination of tissue specimens is necessary for the diagnosis and grading of colon cancer. However, the process is subjective and leads to significant inter/intra observer variation in diagnosis as it mainly relies on the visual assessment of histopathologists. Therefore, a reliable computer-aided technique, which can automatically classify normal and malignant colon samples, and determine grades of malignant samples, is required. In this paper, we propose a novel colon cancer diagnostic (CCD) system, which initially classifies colon biopsy images into normal and malignant classes, and then automatically determines the grades of colon cancer for malignant images. To this end, various novel structural descriptors, which mathematically model and quantify the variation among the structure of normal colon tissues and malignant tissues of various cancer grades, have been employed. Radial basis function (RBF) kernel of support vector machines (SVM) has been employed as classifier in order to classify/grade colon samples based on these descriptors. The proposed system has been tested on 92 malignant and 82 normal colon biopsy images. The classification performance has been measured in terms of various performance measures, and quite promising performance has been observed. Compared with previous techniques, the proposed system has demonstrated better cancer detection (classification accuracy=95.40%) and grading (classification accuracy=93.47%) capability. Therefore, the proposed CCD system can provide a reliable second opinion to the histopathologists., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Several types of colorectal cancers are associated with a prominent lymphoid component, which is considered a positive prognostic factor. We report a case of a dome-type carcinoma of the cecum in a 57 year old female. The sessile, non-polypoid lesion histologically consisted of a tubulovillous adenoma with low-grade dysplasia. The submucosal invasive component showed low-grade architectural features that included cystically dilated glands containing eosinohilic debris. Immunohistochemical studies displayed retention of the four mistmach repair proteins, consistent with a stable phenotype. After 3 years, the patient remains free of recurrence. A literature review highlighted striking similarities between dome-type carcinoma and the gut-associated lymphoid tissue carcinoma, the two sharing an intimate association with the gut associated lymphoid tissue.The two variants might therefore be grouped into a unified category.