Breast cancer is one of the most common and alarming diseases for women. With early detection and diagnosis, the chances of successful treatment and survival would improve. The diagnosis includes classification or staging of the breast cancer, which plays an important role in the prognosis of the disease hence determining the best treatment for the disease. Breast cancer staging is a way of describing the size of a cancer and how far it has grown. One of the staging numbering systems is the Tumour-Node-Metastasis (TNM) system, which categories cancer into several stages. Most types of cancer have four stages, numbered from I to IV. Normally, staging is determined by doctors by examining the pathology information which describes the spreading area of the cancer. In this study, a series of computer algorithms is applied to produce the area information of the cancerous region. The methodology consists of four phases which are image gathering; image pre-processing using Median filter and PCA; image segmentation using FCM; and staging using the area of the primary tumour as a representation of size in the TNM system. From thirty-five randomly selected mammography images of Malaysian women with malignant tumour, 14.3% is in stage I, 5.7% is in stage II and 80% in stage III. Experimental results also shows that 96.4% accuracy is obtained for stage III but higher errors occur at the boundaries of the staging scale.
: The advancements in cancer treatment have no significant effect on ovarian cancer [OC]. The lethality of the OC remains on the top list of the gynecological cancers. The long term survival rate of the OC patients with the advanced stage is less than 30%. The only effective measure to increase the survivability of the patient is the detection of disease in stage I. The earlier the diagnosis, the more will be the chances of survival of the patient. But due to the absence of symptoms and effective diagnosis, only a few % of OC are detected in stage I. A valid, reliable having a high acceptance test is imperative to detect OC in its early stages. Currently, the most used approach for the detection of OC is the screening of CA-125 and transvaginal ultrasonography together. This approach has an efficacy of only 30-45%. A large number of biomarkers are also being explored for their potential use in early screening of OC but no success has been obtained so far. This review provides an overview of the biomarkers being explored for early-stage diagnosis of OC as well to increase the current long-term survival rates of OC patients.
Number of studies has demonstrated the relationship of interleukin 10 gene polymorphism with risk of prostate cancer. This research aimed to evaluate the effect of single nucleotide polymorphism in the promoter region rs1800896 of IL-10 -1082A >G on the incidence of benign prostate hyperplasia and prostate cancer in Iraqi patients. In this study, we studied IL-10 gene polymorphism in two groups of patients, thirty of whom have benign prostate hyperplasia and thirty have prostate cancer, as well as in thirty healthy subjects who were the control group. Relevant primers were used for the amplification by the polymerase chain reaction of the promoter region IL-10 rs1800896. Restriction fragment length polymorphism has been used to determine the frequencies of the alleles associated with each group of subjects studied. The amplified products of PCR were sequenced using the forward primer. The result of restriction fragment length polymorphism showed that AG, AA alleles were not found and GG allele was detected in all of the controls and patients, leading to a conclusion that AA, GG homozygotes and AG heterozygote alleles were not associated with both benign prostate hyperplasia and prostate cancer.
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