Diabetes alone should not be a reason for withholding adjuvant chemotherapy for stage III colon cancer

Background: With increasing prevalence of diabetes mellitus and colon cancer, the number of patients suffering from both diseases is growing, and physicians are being faced with complicated treatment decisions. Objective: To investigate the association between diabetes and treatment/course of stage III colon cancer and the association between colon cancer and course of diabetes. Materials and Methods: Additional information was collected from the medical records of all patients with both stage III colon cancer and diabetes (n=201) and a random sample of stage III colon cancer patients without diabetes (n=206) in the area of the population-based Eindhoven Cancer Registry (1998–2007). Results: Colon cancer patients without diabetes were more likely to receive adjuvant chemotherapy compared with diabetic colon cancer patients (OR 1.8; 95% CI 1.2–2.7). After adjustment for age, this difference was borderline significant (OR 1.6; 95% CI 1.0–2.6). Diabetic patients did not have: significantly more side-effects from surgery or adjuvant chemotherapy; more recurrence from colon cancer; significantly shorter time interval until recurrence; or a poorer disease-free survival or overall survival. Age and withholding of adjuvant chemotherapy were most predictive of all-cause mortality. After colon cancer diagnosis, the dose of antiglycaemic medications was increased in 22% of diabetic patients, resulting in significantly lower glycaemic indexes than before colon cancer diagnosis. Conclusions: Since diabetic patients did not have more side-effects of adjuvant chemotherapy, and adjuvant chemotherapy had a positive effect on survival for both patients with and without diabetes, diabetes alone should not be a reason for withholding adjuvant chemotherapy.Journal of Comorbidity 2011;1(1):19–2

High-efficacy targeting of colon-cancer liver metastasis with Salmonella typhimurium A1-R via intra-portal-vein injection in orthotopic nude-mouse models.

Liver metastasis is the main cause of colon cancer-related death and is a recalcitrant disease. We report here the efficacy and safety of intra-portal-vein (iPV) targeting of Salmonella typhimurium A1-R on colon cancer liver metastasis in a nude-mouse orthotopic model. Nude mice with HT29 human colon cancer cells, expressing red fluorescent protein (RFP) (HT29-RFP), growing in the liver were administered S. typhimurium A1-R by either iPV (1×104 colony forming units (CFU)/100 μl) or, for comparison, intra-venous injection (iv; 5×107 CFU/100 μl). Similar amounts of bacteria were delivered to the liver with the two doses, indicating that iPV delivery is 5×103 times more efficient than iv delivery. Treatment efficacy was evaluated by tumor fluorescent area (mm2) and total fluorescence intensity. Tumor fluorescent area and fluorescence intensity highly correlated (p<0.0001). iPV treatment was more effective compared to both untreated control and iv treatment (p<0.01 and p<0.05, respectively with iPV treatment with S. typhimurium arresting metastatic growth). There were no significant differences in body weight between all groups. The results of this study suggest that S. typhimurium A1-R administered iPV has potential for peri-operative adjuvant treatment of colon cancer liver metastasis

Machine learning approach for segmenting glands in colon histology images using local intensity and texture features

Colon Cancer is one of the most common types of cancer. The treatment is planned to depend on the grade or stage of cancer. One of the preconditions for grading of colon cancer is to segment the glandular structures of tissues. Manual segmentation method is very time-consuming, and it leads to life risk for the patients. The principal objective of this project is to assist the pathologist to accurate detection of colon cancer. In this paper, the authors have proposed an algorithm for an automatic segmentation of glands in colon histology using local intensity and texture features. Here the dataset images are cropped into patches with different window sizes and taken the intensity of those patches, and also calculated texture-based features. Random forest classifier has been used to classify this patch into different labels. A multilevel random forest technique in a hierarchical way is proposed. This solution is fast, accurate and it is very much applicable in a clinical setup

Survival disparities in Indigenous and non-Indigenous New Zealanders with colon cancer: the role of patient comorbidity, treatment and health service factors

Background Ethnic disparities in cancer survival have been documented in many populations and cancer types. The causes of these inequalities are not well understood but may include disease and patient characteristics, treatment differences and health service factors. Survival was compared in a cohort of Maori ( Indigenous) and non-Maori New Zealanders with colon cancer, and the contribution of demographics, disease characteristics, patient comorbidity, treatment and healthcare factors to survival disparities was assessed. Methods Maori patients diagnosed as having colon cancer between 1996 and 2003 were identified from the New Zealand Cancer Registry and compared with a randomly selected sample of non-Maori patients. Clinical and outcome data were obtained from medical records, pathology reports and the national mortality database. Cancer-specific survival was examined using Kaplane-Meier survival curves and Cox hazards modelling with multivariable adjustment. Results 301 Maori and 328 non-Maori patients with colon cancer were compared. Maori had a significantly poorer cancer survival than non-Maori ( hazard ratio (HR) 1.33, 95% CI 1.03 to 1.71) that was not explained by demographic or disease characteristics. The most important factors contributing to poorer survival in Maori were patient comorbidity and markers of healthcare access, each of which accounted for around a third of the survival disparity. The final model accounted for almost all the survival disparity between Maori and non-Maori patients ( HR 1.07, 95% CI 0.77 to 1.47). Conclusion Higher patient comorbidity and poorer access and quality of cancer care are both important explanations for worse survival in Maori compared with non-Maori New Zealanders with colon cancer

Validation of a modified clinical risk score to predict cancer-specific survival for stage II colon cancer

Many patients with stage II colon cancer will die of their disease despite curative surgery. Therefore, identification of patients at high risk of poor outcome after surgery for stage II colon cancer is desirable. This study aims to validate a clinical risk score to predict cancer-specific survival in patients undergoing surgery for stage II colon cancer. Patients undergoing surgery for stage II colon cancer in 16 hospitals in the West of Scotland between 2001 and 2004 were identified from a prospectively maintained regional clinical audit database. Overall and cancer-specific survival rates up to 5 years were calculated. A total of 871 patients were included. At 5 years, cancer-specific survival was 81.9% and overall survival was 65.6%. On multivariate analysis, age ≥75 years (hazard ratio (HR) 2.11, 95% confidence intervals (CI) 1.57–2.85; P<0.001) and emergency presentation (HR 1.97, 95% CI 1.43–2.70; P<0.001) were independently associated with cancer-specific survival. Age and mode of presentation HRs were added to form a clinical risk score of 0–2. The cancer-specific survival at 5 years for patients with a cumulative score 0 was 88.7%, 1 was 78.2% and 2 was 65.9%. These results validate a modified simple clinical risk score for patients undergoing surgery for stage II colon cancer. The combination of these two universally documented clinical factors provides a solid foundation for the examination of the impact of additional clinicopathological and treatment factors on overall and cancer-specific survival

Anticancer Activities of Meroterpenoids Isolated from the Brown Alga Cystoseira usneoides against the Human Colon Cancer Cells HT-29

Colorectal cancer (CRC) is one of the most common types of cancers and a leading cause of cancer death worldwide. The current treatment for CRC mainly involves surgery, radiotherapy, and chemotherapy. However, due to the side effects and the emergence of drug resistance, the search for new anticancer agents, pharmacologically safe and effective, is needed. In the present study, we have investigated the anticancer effects of eight algal meroterpenoids (AMTs, 1-8) isolated from the brown seaweed Cystoseira usneoides and their underlying mechanisms of action using HT-29, a highly metastatic human colon cancer cell line. All the tested meroterpenoids inhibited the growth of HT-29 malignant cells and were less toxic towards non-cancer colon cells, with the AMTs 1 and 5 exhibiting selectivity indexes of 5.26 and 5.23, respectively. Treatment of HT-29 cells with the AMTs 1, 2, 3, 4, 5, and 7 induced cell cycle arrest in G2/M phase and, in some instances, apoptosis (compounds 2, 3, and 5). Compounds 1-8 also exhibited significant inhibitory effects on the migration and/or invasion of colon cancer cells. Mechanistic analysis demonstrated that the AMTs 1, 2, 5, 6, 7, and 8 reduced phosphorylation levels of extracellular signal-regulated kinase (ERK) and the AMTs 2, 3, 4, 5, 7, and 8 decreased phosphorylation of c-JUN N-terminal kinase (JNK). Moreover, the AMTs 1, 2, 3, 4, 7, and 8 inhibited phosphorylation levels of protein kinase B (AKT) in colon carcinoma cells. These results provide new insights into the mechanisms and functions of the meroterpenoids of C. usneoides, which exhibit an anticancer effect on HT-29 colon cancer cells by inducing cell cycle arrest and apoptosis via the downregulation of ERK/JNK/AKT signaling pathways

Adjuvant treatment with tumor-targeting Salmonella typhimurium A1-R reduces recurrence and increases survival after liver metastasis resection in an orthotopic nude mouse model.

Colon cancer liver metastasis is often the lethal aspect of this disease. Well-isolated metastases are candidates for surgical resection, but recurrence is common. Better adjuvant treatment is therefore needed to reduce or prevent recurrence. In the present study, HT-29 human colon cancer cells expressing red fluorescent protein (RFP) were used to establish liver metastases in nude mice. Mice with a single liver metastasis were randomized into bright-light surgery (BLS) or the combination of BLS and adjuvant treatment with tumor-targeting S. typhimurium A1-R. Residual tumor fluorescence after BLS was clearly visualized at high magnification by fluorescence imaging. Adjuvant treatment with S. typhimurium A1-R was highly effective to increase survival and disease-free survival after BLS of liver metastasis. The results suggest the future clinical potential of adjuvant S. typhimurium A1-R treatment after liver metastasis resection

Combination of capecitabine and ludartin inhibits colon cancer growth in mice

Purpose: To investigate the efficacy of capecitabine and ludartin in the treatment of colon cancer in mice.Methods: Mice model of colon cancer was used in this study. Quantitative real-time polymerase chain reaction (Qrt-PCR) was used to quantify the expression of vascular endothelial growth factor (VEGF) mRNA. Micro-vessel density was assessed using immunohistochemical analysis.Results: When administered separately, capecitabine and ludartin treatments significantly suppressed tumor growth in the mice model of colon cancer for 4 weeks, compared to control group. Coadministration of capecitabine and ludartin significantly inhibited tumor growth for 6 weeks (p < 0.05). Symptoms of colon cancer such as weight loss, skin discoloration and leukopenia were observed in untreated control group. However, these symptoms were completely absent in the group treated with combination of capecitabine and ludartin. The combined treatment also prevented colon cancer-induced increase in white blood cell (WBC) count, and increased median survival time of colon cancer mice from 38 to 55 days. Expression of VEGF in combination (capecitabine + ludartin) treatment group was significantly lower than in the control, i.e., untreated group (p ˂ 0.05). The combination treatment group also had significantly lower micro-vessel density in the tumor tissues, compared to the  ntreated control mice (p < 0.05).Conclusion: These results show that a combination treatment of capecitabine and ludartin effectively inhibits colon tumor growth and angiogenesis in mice via a mechanism involving suppression of VEGF expression. Thus, capecitabine and ludartin combination is a potentially  uitable treatment for colon cancer.Keywords: Colon cancer, Mice, Ludartin, Leukopenia, VEGF expression, Angiogenesi

Combining conventional chemotherapy and γδ T cell-based immunotherapy to target cancer-initiating cells.

Colon cancer comprises a small population of cancer initiating stem cells (CIC) that is responsible for tumor maintenance and resistance to anti-cancer therapies, possibly allowing for tumor recapitulation once treatment stops. Combinations of immune-based therapies with chemotherapy and other anti-tumor agents may be of significant clinical benefit in the treatment of colon cancer. However, cellular immune-based therapies have not been experimented yet in the population of colon CICs. Here, we demonstrate that treatment with low concentrations of commonly used chemotherapeutic agents, 5-fluorouracyl and doxorubicin, sensitize colon CICs to Vγ9Vδ2 T cell cytotoxicity. Vγ9Vδ2 T cell cytotoxicity was largely mediated by TRAIL interaction with DR5, following NKG2D-dependent recognition of colon CIC targets. We conclude that in vivo activation of Vγ9Vδ2 T cells or adoptive administration of ex-vivo expanded Vγ9Vδ2 T cells at suitable intervals after chemotherapy may substantially increase anti-tumor activities and represent a novel strategy for colon cancer immunotherapy

A Comparative Study for Methodologies and Algorithms Used In Colon Cancer Diagnoses and Detection

Colon cancer is also referred to as colorectal cancer; it is a kind of cancer that starts with colon damage to the large intestine in the last section of the digestive tract. Elderly people typically suffer from colon cancer, but this may occur at any age. It normally starts as a little, noncancerous (benign) mass of cells named polyps that structure within the colon. After a period of time these polyps can turn into advanced malignant tumors that attack the human body and some of these polyps can become colon cancers. So far, no concrete causes have been identified and the complete cancer treatment is very difficult to be detected by doctors in the medical field. Colon cancer often has no symptoms in an early stage so detecting it at this stage is curable but colorectal cancer diagnosis in the final stages (stage IV), gives it the opportunity to spread into different pieces of the body, which are difficult to treat successfully, and the person\u27s opportunities of survival become much lower. False diagnosis of colorectal cancer which means wrong treatment for patients with long-term infections and they will be suffering from colon cancer this causing the death for these patients. Also, cancer treatment needs more time and a lot of money. This paper provides a comparative study for methodologies and algorithms used in the colon cancer diagnoses and detection this can help for proposing a prediction for risk levels of colon cancer disease using CNN algorithm of deep learning (Convolutional Neural Networks Algorithm)