Obesity has been associated with upper gastrointestinal cancers; however, there are limited prospective data on associations by subtype/subsite. Obesity can impact hormonal factors, which have been hypothesized to play a role in these cancers. We investigated anthropometric and reproductive factors in relation to esophageal and gastric cancer by subtype and subsite for 476,160 participants from the European Prospective Investigation into Cancer and Nutrition cohort. Multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox models. During a mean follow-up of 14 years, 220 esophageal adenocarcinomas (EA), 195 esophageal squamous cell carcinomas, 243 gastric cardia (GC) and 373 gastric noncardia (GNC) cancers were diagnosed. Body mass index (BMI) was associated with EA in men (BMI ≥30 vs. 18.5-25 kg/m2 : HR = 1.94, 95% CI: 1.25-3.03) and women (HR = 2.66, 95% CI: 1.15-6.19); however, adjustment for waist-to-hip ratio (WHR) attenuated these associations. After mutual adjustment for BMI and HC, respectively, WHR and waist circumference (WC) were associated with EA in men (HR = 3.47, 95% CI: 1.99-6.06 for WHR >0.96 vs. <0.91; HR = 2.67, 95% CI: 1.52-4.72 for WC >98 vs. <90 cm) and women (HR = 4.40, 95% CI: 1.35-14.33 for WHR >0.82 vs. <0.76; HR = 5.67, 95% CI: 1.76-18.26 for WC >84 vs. <74 cm). WHR was also positively associated with GC in women, and WC was positively associated with GC in men. Inverse associations were observed between parity and EA (HR = 0.38, 95% CI: 0.14-0.99; >2 vs. 0) and age at first pregnancy and GNC (HR = 0.54, 95% CI: 0.32-0.91; >26 vs. <22 years); whereas bilateral ovariectomy was positively associated with GNC (HR = 1.87, 95% CI: 1.04-3.36). These findings support a role for hormonal pathways in upper gastrointestinal cancers.
Some oral verrucal lesions may constitute parts of the clinicopathological spectrum of proliferative verrucous leukoplakia (PVL). Because of its idiopathic yet sinister nature, it is possible that PVL may exist in other populations. The aim of this study was to review the clinicopathological features of persistent, multifocal, oral verrucal lesions in Malaysian population.
Since its recognition about 150 years ago, there has been much progress in the understanding of the pathogenesis, prevention, early detection and management of carcinoma of the uterine cervix. Important historical landmarks include the (1) recognition of pre-invasive and pre-clinical lesions, and the devise of various systems for reporting these lesions, (2) improvements in diagnostic techniques particularly colposcopy, (3) advent of therapeutic procedures (electrocoagulation, cryotherapy, laser therapy and loop electrosurgical excision), and (4) recognition of the aetiological relationship between the human papillomavirus and cervical neoplasia. The susceptibility of the cervical transformation zone to malignant change is now well recognised. The WHO classification system remains the one most commonly utilised for histological reporting of cervical cancers. In the recent 1994 update, cervical carcinoma is divided into 3 main categories: squamous cell carcinoma, adenocarcinoma and other epithelial tumours. Squamous cell carcinoma (60-80%) predominates among invasive cervical carcinoma. Recognised variants include verrucous, warty (condylomatous), papillary squamous (transitional) and lymphoepithelioma-like carcinoma. Adenocarcinoma (5-15% of invasive carcinomas) shows an increasing trend in young females. Like its squamous counterpart, preinvasive and microinvasive versions are known. Variants such as mucinous, endometrioid, clear cell, mesonephric, serous, villoglandular and minimal deviation carcinoma are now defined. Adenosquamous carcinoma (5-25%), adenoid-cystic, adenoid-basal, neuroendocrine and undifferentiated carcinomas constitute other epithelial tumours of the cervix. The management of invasive cervical carcinoma remains heavily dependent on its stage. The FIGO staging system remains the most widely used. The 1995 update provides more definite criteria in subdividing stage IA tumours by delimiting stromal invasion of stage IA1 lesions to a maximum depth of 3 mm and a horizontal axis of 7 mm. In Malaysia, an appreciation of the cervical carcinoma problem has to take into consideration the population at risk, its multi-ethnicity, its socio-economic and geographical diversities and the constraints of the health care system. Females form 48.9% of the Malaysian population. 52.9% of them are in the sexually active age group of 15-50 years, indicating a significant population at risk for cervical carcinoma. Cervical carcinoma was the third most common cause of death due to solid tumours among Malaysian females in 1995 following carcinoma of the breast and respiratory tract. East Malaysia is predominantly rural with many communities having limited modern facilities. Such areas imply a lower educational and socio-economic status, raising the worry of a population at higher risk for developing cervical carcinoma. The population: doctor for Malaysia of 2153:1 compares poorly with nearby Singapore. Besides a shortage of doctors, there is also an uneven distribution of doctors, resulting in a ratio in East Malaysia of > 4000:1. Although Malaysia does not have a national cervical cancer-screening programme, many action plans and cancer awareness campaigns have been launched throughout the years, which appear to have made an impact as evidenced by the decreasing mortality rates from cervical carcinoma. Another interesting feature of cervical carcinoma in Malaysia relates to its multiethnic population. In Malaysian Chinese and Malay females, the prevalence of cervical carcinoma ranks second to breast cancer whereas the pattern is reversed in Malaysian Indian females. Studies into its aetiology and pathogenesis are being undertaken and may shed more light on this matter.
The fifth chapter of the upcoming fifth edition of the 2022 World Health Organization Classification of Tumours of the Head and Neck titled Tumours of the oral cavity and mobile tongue, has had some modifications from the 2017 fourth edition. A new section "Non-neoplastic Lesions", introduces two new entries: necrotizing sialometaplasia and melanoacanthoma. The combined Oral potentially malignant disorders and Oral epithelial dysplasia section in the 2015 WHO has now been separated and submucous fibrosis and HPV-associated dysplasia are also discussed in separate sections. Carcinoma cuniculatum and verrucous carcinoma are described in dedicated sections, reflecting that the oral cavity is the most common location in the head and neck for both these entities which have distinct clinical and histologic features from conventional squamous cell carcinoma. This review summarizes the changes in Chapter 5 with special reference to new additions, deletions, and sections that reflect current clinical, histological, and molecular advances.
Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. The purpose is benefitting from the synergies obtained from combining these technologies for the development of classification models. Such a combination creates an opportunity to invest in the strength of each algorithm, and is an approach to make up for their deficiencies. To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. Furthermore, the statistical analysis was performed using the Friedman test followed by post-hoc tests. The experimental findings indicated that the novel proposed hybrid model resulted in significantly better classification performance compared with all 13 classification methods. Finally, the performance results of the proposed model was benchmarked against the best ones reported as the state-of-the-art classifiers in terms of classification accuracy for the same data sets. The substantial findings of the comprehensive comparative study revealed that performance of the proposed model in terms of classification accuracy is desirable, promising, and competitive to the existing state-of-the-art classification models.
Matched MeSH terms: Breast Neoplasms/classification
Tympanojugular paragangliomas (TJPs) with intradural extension can be successfully treated by a single or staged procedure with low surgical morbidity.
Matched MeSH terms: Skull Base Neoplasms/classification
Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test.
Gene expression data are expected to be of significant help in the development of efficient cancer diagnoses and classification platforms. In order to select a small subset of informative genes from the data for cancer classification, recently, many researchers are analyzing gene expression data using various computational intelligence methods. However, due to the small number of samples compared to the huge number of genes (high dimension), irrelevant genes, and noisy genes, many of the computational methods face difficulties to select the small subset. Thus, we propose an improved (modified) binary particle swarm optimization to select the small subset of informative genes that is relevant for the cancer classification. In this proposed method, we introduce particles' speed for giving the rate at which a particle changes its position, and we propose a rule for updating particle's positions. By performing experiments on ten different gene expression datasets, we have found that the performance of the proposed method is superior to other previous related works, including the conventional version of binary particle swarm optimization (BPSO) in terms of classification accuracy and the number of selected genes. The proposed method also produces lower running times compared to BPSO.
Breast cancer may be classified into luminal A, luminal B, HER2+/ER-, basal-like and normal-like subtypes based on gene expression profiling or immunohistochemical (IHC) characteristics. The main aim of the present study was to classify breast cancer into molecular subtypes based on immunohistochemistry findings and correlate the subtypes with clinicopathological factors. Two hundred and seventeen primary breast carcinomas tumor tissues were immunostained for ER, PR, HER2, CK5/6, EGFR, CK8/18, p53 and Ki67 using tissue microarray technique. All subtypes were significantly associated with Malay ethnic background (p=0.035) compared to other racial origins. The most common subtypes of breast cancers were luminal A and was significantly associated with low histological grade (p<0.000) and p53 negativity (p=0.003) compared to HER2+/ER-, basal-like and normal-like subtypes with high histological grade (p<0.000) and p53 positivity (p=0.003). Luminal B subtype had the smallest mean tumor size (p=0.009) and also the highest mean number of lymph nodes positive (p=0.032) compared to other subtypes. All markers except EGFR and Ki67 were significantly associated with the subtypes. The most common histological type was infiltrating ductal carcinoma, NOS. Majority of basal-like subtype showed comedo-type necrosis (68.8%) and infiltrative margin (81.3%). Our studies suggest that IHC can be used to identify the different subtypes of breast cancer and all subtypes were significantly associated with race, mean tumor size, mean number of lymph node positive, histological grade and all immunohistochemical markers except EGFR and Ki67.
Matched MeSH terms: Breast Neoplasms/classification*
The classification of the cancer tumors based on gene expression profiles has been extensively studied in numbers of studies. A wide variety of cancer datasets have been implemented by the various methods of gene selection and classification to identify the behavior of the genes in tumors and find the relationships between them and outcome of diseases. Interpretability of the model, which is developed by fuzzy rules and linguistic variables in this study, has been rarely considered. In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. The results show that fuzzy classifier can classify the tumors with high performance while presenting the relationships between the genes by linguistic variables.
Meningioma, is the second most frequent intracranial tumor in Malaysia and are classified according to the World Health Organization classification. The relationship of p53 protein in the determination of meningioma grading and their influencing factors were studied via immunohistochemistry studies on 77 intracranial meningiomas (67 benign, 10 atypical). The higher the p53 reaction was correlated to the poorer the histological grade (19.4% in benign and 90% in atypical meningioma) (p < 0.001). Other variables like age, sex, ethnicity, demographic location, surgical clearance, midline shift and contrast enhancement of CT Scan Brain and clinical features were found not to be significant.
OBJECTIVE: To examine the fine needle aspiration cytologic features of invasive lobular carcinoma of breast and to discuss problems that may occur in cytodiagnosis.
STUDY DESIGN: Fine needle aspiration cytologic smears from 21 cases of invasive lobular carcinoma (ILC) of breast were subjected to detailed cytomorphologic analysis. Features studied included pattern of cells, size of cells, nuclear placement, pleomorphism, presence of intracytoplasmic lumina (ICL) and signet ring cells.
RESULTS: Cellularity was generally moderate or high, and the pattern was predominantly or partly dissociated in 86% of cases. Rosettelike pattern was discerned in alveolar-type ILC. Cell size was usually small or intermediate, with nuclei placed eccentrically in most cases. ICLs with or without signet ring cells were present in 12 cases (57%).
CONCLUSION: A cytologic picture consisting of predominantly dissociated small or intermediate-sized tumor cells with eccentric nuclei, with some of the cells showing ICLs, is highly suggestive of ILC. Indian file pattern, another characteristic feature of ILC, is, however, focal and inconsistent. Variant patterns of ILC may show other cytologic features, such as rosettelike pattern (alveolar variant of ILC) or large cell pattern (pleomorphic variant of ILC) and may consequently be difficult to categorize on cytologic smears.
Matched MeSH terms: Breast Neoplasms/classification
Emerging evidence suggests that a metabolic profile associated with obesity may be a more relevant risk factor for some cancers than adiposity per se. Basal metabolic rate (BMR) is an indicator of overall body metabolism and may be a proxy for the impact of a specific metabolic profile on cancer risk. Therefore, we investigated the association of predicted BMR with incidence of 13 obesity-related cancers in the European Prospective Investigation into Cancer and Nutrition (EPIC). BMR at baseline was calculated using the WHO/FAO/UNU equations and the relationships between BMR and cancer risk were investigated using multivariable Cox proportional hazards regression models. A total of 141,295 men and 317,613 women, with a mean follow-up of 14 years were included in the analysis. Overall, higher BMR was associated with a greater risk for most cancers that have been linked with obesity. However, among normal weight participants, higher BMR was associated with elevated risks of esophageal adenocarcinoma (hazard ratio per 1-standard deviation change in BMR [HR1-SD ]: 2.46; 95% CI 1.20; 5.03) and distal colon cancer (HR1-SD : 1.33; 95% CI 1.001; 1.77) among men and with proximal colon (HR1-SD : 1.16; 95% CI 1.01; 1.35), pancreatic (HR1-SD : 1.37; 95% CI 1.13; 1.66), thyroid (HR1-SD : 1.65; 95% CI 1.33; 2.05), postmenopausal breast (HR1-SD : 1.17; 95% CI 1.11; 1.22) and endometrial (HR1-SD : 1.20; 95% CI 1.03; 1.40) cancers in women. These results indicate that higher BMR may be an indicator of a metabolic phenotype associated with risk of certain cancer types, and may be a useful predictor of cancer risk independent of body fatness.
Notch signaling has been implicated in cell fate decisions during odontogenesis and tumorigenesis of some odontogenic neoplasms; however, its role in solid/multicystic (SA), unicystic (UA), and recurrent (RA) ameloblastoma remains unclear. The aim of this study was to determine Notch receptor and ligand expressions in these subtypes and to speculate on their significance.
OBJECTIVES: We evaluated the feasibility of using chemical shift gradient-echo (GE) in- and opposed-phase (IOP) imaging to grade glioma.
METHODS: A phantom study was performed to investigate the correlation of (1)H MRS-visible lipids with the signal loss ratio (SLR) obtained using IOP imaging. A cross-sectional study approved by the institutional review board was carried out in 22 patients with different glioma grades. The patients underwent scanning using IOP imaging and single-voxel spectroscopy (SVS) using 3T MRI. The brain spectra acquisitions from solid and cystic components were obtained and correlated with the SLR for different grades.
RESULTS: The phantom study showed a positive linear correlation between lipid quantification at 0.9 parts per million (ppm) and 1.3 ppm with SLR (r = 0.79-0.99, p
Mucins are produced by both benign and malignant gastric epithelium. In general, mucins can be classified into neutral and acidic mucins. The latter are of 2 major types, sulphated (sulphomucins) and carboxylated (sialomucins). A retrospective study was initiated at the Department of Pathology, University Hospital, Kuala Lumpur to histochemically study the mucin profiles of cases of intestinal (IGC) and diffuse (DGC) types of gastric carcinoma in Malaysian patients to determine whether a significant change of mucin type occurs in the event of malignant transformation. 42 IGC and 37 DGC were subjected to alcian blue-periodic acid Schiff and high iron diamine-alcian blue histochemical staining. In addition, 18 cases of gastrectomies performed for benign lesions in the stomach served as normal controls. The number of cases of IGC and DGC which exhibited sulphomucin production was significantly increased (p < 0.001) compared to normal controls. Also, the number of cases of DGC which produced neutral mucin were significantly less (p < 0.05) than the control group. However, there was no significant difference between the number of IGC and DGC cases which demonstrated sialomucin production and normal controls. It appears that while not pathognomonic, a lack of neutral mucin production should alert the pathologist to the possibility of a gastric malignancy, in particular DGC. The likelihood of a malignant lesion would be further supported if there is an increased sulphomucin production.
Hormone receptor (HR) negative breast cancers are relatively more common in low-risk than high-risk countries and/or populations. However, the absolute variations between these different populations are not well established given the limited number of cancer registries with incidence rate data by breast cancer subtype. We, therefore, used two unique population-based resources with molecular data to compare incidence rates for the 'intrinsic' breast cancer subtypes between a low-risk Asian population in Malaysia and high-risk non-Hispanic white population in the National Cancer Institute's surveillance, epidemiology, and end results 18 registries database (SEER 18). The intrinsic breast cancer subtypes were recapitulated with the joint expression of the HRs (estrogen receptor and progesterone receptor) and human epidermal growth factor receptor-2 (HER2). Invasive breast cancer incidence rates overall were fivefold greater in SEER 18 than in Malaysia. The majority of breast cancers were HR-positive in SEER 18 and HR-negative in Malaysia. Notwithstanding the greater relative distribution for HR-negative cancers in Malaysia, there was a greater absolute risk for all subtypes in SEER 18; incidence rates were nearly 7-fold higher for HR-positive and 2-fold higher for HR-negative cancers in SEER 18. Despite the well-established relative breast cancer differences between low-risk and high-risk countries and/or populations, there was a greater absolute risk for HR-positive and HR-negative subtypes in the US than Malaysia. Additional analytical studies are sorely needed to determine the factors responsible for the elevated risk of all subtypes of breast cancer in high-risk countries like the United States.
Matched MeSH terms: Breast Neoplasms/classification*
Disease-related malnutrition is highly prevalent in hospital patients and varies from 25-40%. Early nutritional screening of patients at admission helps to improve recognition of malnourished patients to allow early interventions and enhance clinical outcomes.