Methodology: The antimicrobial activity of synthesized 2MBI derivatives were evaluated against Gram positive and Gram negative bacterial species as well as fungal species by tube dilution technique whereas their anticancer activity was assessed against human colorectal carcinoma cell line (HCT116) by Sulforhodamine B (SRB) assay. They were also structurally characterized by IR, NMR, MS and elemental analyses.
Results discussion and conclusion: The antimicrobial activity findings revealed that compound N1 (MIC
bs,st,
ca
= 1.27, 2.54, 1.27 µM), N8 (MIC
ec
= 1.43 µM), N22 (MIC
kp,an
= 2.60 µM), N23 and N25 (MIC
sa
= 2.65 µM) exhibited significant antimicrobial effects against tested strains, i.e. Gram-positive, Gram-negative (bacterial) and fungal strains. The anticancer screening results demonstrated that compounds N9, N18 (IC50 = 5.85, 4.53 µM) were the most potent compounds against cancer cell line (HCT116) even more than 5-FU, the standard drug (IC50 = 9.99 µM).
METHODS: The findings for a few outcome indicators, ranging from the iFOBT uptake to the CRC and polyp detection rates, were generated from the data contributed by 583 public health clinics between 2014 and 2018. The trends in their changes were also evaluated.
RESULTS: The iFOBT uptake constantly increased over the years (p < 0.001), totaling 2.29 % (n = 127,957) as at 2018. Nearly 10 % (n = 11,872) of the individuals screened had a positive test result. Of those who underwent colonoscopy (n = 6,491), 4.04 % (n = 262) and 13.93 % (n = 904) were found to have CRC and polyps, respectively.
CONCLUSION: An uptrend in the CRC screening uptake was witnessed following the introduction of the iFOBT in public health clinics.
METHODS AND FINDINGS: The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
CONCLUSIONS: These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
Case presentation: We present a case of 15-year-old boy from rural area, presented with chronic diarrhea and per rectal bleeding for 3 months. The diagnosis was determined by colonoscope which revealed a fungating mass identified at 10cm from anal verge. Histological examination confirmed diagnosis of signet ring cell adenocarcinoma. CT scan of the abdomen showed thickening involving the recto-sigmoid colon and rectal mass, without evidence of distant metastatic disease. The patient's carcinoembryonic antigen level was within the normal range. He underwent a colostomy and was subjected to neoadjuvant CCRT and surgery.
Discussion: This CASE highlights the importance and challenges in achieving early diagnosis and surgical intervention of signet-ring cell carcinoma in adolescents, as most cases are detected at an advanced stage coupled with the scarcity of information on these rarer subtypes which leads to a poor prognosis.
Conclusion: In managing Signet cell carcinoma of the colorectal, physician have to know that it has a poor prognosis in patients of any age. However, in young teenagers delayed diagnosis and treatment option are narrowed to palliative management. Genetic profiling of family members and similar environment population may be a key to early detection.
Methods: A multi-centred matched case control study was conducted in five local hospitals. A total of 140 histologically confirmed CRC cases were matched with 280 cancer free controls. Mean value and prevalence of the components of metabolic syndrome between cases and controls were measured based on the three definitions. A multiple variable analysis using Cox regression was conducted to measure the strength of the association between the definitions of MetS, components of MetS and risk of CRC.
Results: Multiple variable analyses showed that metabolic syndrome significantly and independently increased the risk of CRC, with an odds ratio ranging from 1.79 to 2.61. This study identified that the definition of metabolic syndrome by the International Diabetes Federation is the most sensitive in predicting the risk of CRC, compared to metabolic syndrome as defined by the World Health Organization and National Cholesterol Education Program Adults Treatment Panel III. Abdominal obesity, low HDL-cholesterol, and hypertension were identified as the three core risk factors, which promote inflammatory signals that contribute to metabolic syndrome and an increased risk of CRC.
Conclusions: These data hypothesized that simple measurement of abdominal obesity, abnormal BP and HDL-cholesterol especially using International Diabetes Federation (IDF) definition of MetS for South Asians for to detect individuals at CRC risk may have higher clinical utility than applying other universal complex MetS definitions.
OBJECTIVE: The objective of this study was to determine the relationship between obesity and blood lipids with a risk of colorectal cancer (CRC).
METHODOLOGY: Histologically confirmed CRC patients from five local hospitals were matched with cancer-free controls for age, gender, and ethnicity (n = 140: 280). The study participants underwent physical assessment for the presence of obesity and 10 mL of fasting blood was drawn for blood lipid analysis.
RESULTS: In this study, abdominal obesity significantly doubled the risk of CRC (adjusted odds ratio [AOR] =1.69, 95% confidence interval [CI] = 1-2.83). Hypercholesterolemia and low high-density lipoprotein cholesterol (HDL) increased the risk of CRC more than twofolds (AOR = 2.6, 95% CI = 1.7-3.9 and AOR = 3.8, 95% CI = 2.3-6.3, respectively). Abdominal obesity and hypercholesterolemia synergically doubled the risk of CRC (AOR = 2.0, 95% CI = 1-4). Low-HDL has shown no synergic association with other dyslipidemic states with an increased CRC risk.
CONCLUSION: Improving abdominal obesity, hypercholesterolemia, and low HDL may be a clinically relevant strategy to reduce the risk of CRC among Malaysians.
PATIENTS AND METHODS: Formalin-fixed, paraffin-embedded tissue samples of 47 CRCs surgically resected at the Kuala Lumpur Hospital (KLH) between 1999 and 2000 were used. Immunohistochemical staining with monoclonal antibodies against cyclin-D1 and survivin and polyclonal antibodies against Wnt-1 and WISP-1 was performed. Results of immunohistochemistry were analysed for correlation between biomolecules and histopathological data of the patients.
RESULTS: Of the 47 CRCs, 26 (55.3%), 15 (31.9%), 5 (10.6%) and 28 (59.6%) of the tumours exhibited positivity for Wnt-1, WISP-1, cyclin D1 and survivin, respectively. A lower percentage of the 40 apparently normal adjacent tissues were found to be positive for Wnt-1 (7, 17.5%), WISP-1 (+/-5, 12.5%) and survivin (13, 32.5%), but cyclin D1 was not detected in any of them. Interestingly, the total scores of Wnt-1, WISP-1 and survivin were significantly higher in CRC tissues (p=0.001, 0.034 and 0.044, respectively). Using the Spearman rank correlation test, a positive linear relationship was found between total Wnt-1 score with total WISP-1 score (rho=0.319, p=0.003) and total survivin score (rho=0.609, p=or<0.001). The expression of WISP-1 in the CRC tissues was found to be positively correlated with patients older than 60 years old (p=0.011). In addition, nuclear cyclin-D1 expression was found to be associated with poorly differentiated CRC tissues (p<0.001, Table 5) and right-sided CRC tumour (p=0.019, Table 6). Total WISP-1 score was associated with well-differentiated CRC tissues (p=0.029).
CONCLUSIONS: Overexpression and interplay between Wnt-1, WISP-1, survivin and cyclin-D1 may play a role in tumorigenesis, possibly by promoting cell cycle checkpoint progression, accelerating cell growth and inhibiting apoptosis. Our data may provide useful information towards the search for potent therapeutic targets towards the development of novel treatment strategies for CRC.