Drug resistance is a hot topic issue in cancer research and therapy. Although cancer therapy including radiotherapy and anti‐cancer drugs can kill malignant cells within the tumor, cancer cells can develop a wide range of mechanisms to resist the toxic effects of anti‐cancer agents. Cancer cells may provide some mechanisms to resist oxidative stress and escape from apoptosis and attack by the immune system. Furthermore, cancer cells may resist senescence, pyroptosis, ferroptosis, necroptosis, and autophagic cell death by modulating several critical genes. The development of these mechanisms leads to resistance to anti‐cancer drugs and also radiotherapy. Resistance to therapy can increase mortality and reduce survival following cancer therapy. Thus, overcoming mechanisms of resistance to cell death in malignant cells can facilitate tumor elimination and increase the efficiency of anti‐cancer therapy. Natural‐derived molecules are intriguing agents that may be suggested to be used as an adjuvant in combination with other anticancer drugs or radiotherapy to sensitize cancer cells to therapy with at least side effects. This paper aims to review the potential of triptolide for inducing various types of cell death in cancer cells. We review the induction or resistance to different cell death mechanisms such as apoptosis, autophagic cell death, senescence, pyroptosis, ferroptosis, and necrosis following the administration of triptolide. We also review the safety and future perspectives for triptolide and its derivatives in experimental and human studies. The anticancer potential of triptolide and its derivatives may make them effective adjuvants for enhancing tumor suppression in combination with anticancer therapy.
Cancer is one of the dangerous diseases that afflict a person through injury to cells and tissues in the body, where a person is vulnerable to infection in any age group, and it is not easy to control and multiply between cells and spread to the body. In spite of the great progress in medical studies interested in this aspect, the options for those with this disease are few and difficult, as they require significant financial costs for health services and for treatment that is difficult to provide.
This study dealt with the determinants of liver cancer by relying on the data of cancerous tumours taken from the Iraqi Center for Oncology in the Ministry of Health 2017. Survival analysis has been used as a m
... Show MoreThe current study was conducted in the period extending from November 2018 to October 2019 and designed as a case-control study and aimed to assess the seroprevalence of HCMV. However, a total number of 91serum specimens were collected to fulfill this purpose from females (71 breast cancer patients, and control group of 20 females) attending Al-Amal hospital for cancer management and Baghdad teaching hospital and the practical part was performed in College of Science, University of Baghdad. The study protocol was approved by the Ethics Committee at the Department of Biology (Reference: BEC/0220/0011). The immunological part for evaluation of seroprevalence of HCMV was accomplished by ELISA technique which revealed that anti-HCMV IgG was sco
... Show MoreBackground: Moringa peregrina is widely used in the traditional medicine of the Arabian Peninsula to treat various ailments, because it has many pharmacologically active components with several therapeutic effects. Objective: This study aimed to investigate the inhibitory effect of Moringa peregrina seed ethanolic extract (MPSE) against key enzymes involved in human pathologies, such as angiogenesis (thymidine phosphorylase), diabetes (α-glucosidase), and idiopathic intracranial hypertension (carbonic anhydrase). In addition, the anticancer properties were tested against the SH-SY5Y(human neuroblastoma). Results: MPSE extract significantly inhibited α-glucosidase, thymidine phosphorylase, and carbonic anhydrase with half-maximal i
... Show MoreBreast cancer is the most repeatedly detected cancer category and the second reason cause of cancer-linked deaths among women worldwide. Tumor bio-indictor is a term utilized to describe possible indicators for carcinoma diagnosis, development and progression. The goal of this study is to evaluate part of some cytokines and biomarkers for both serum and saliva samples in breast cancer then estimate their potential value in the early diagnosis of breast cancer by doing more researches in saliva, and utilizing saliva instead of blood (serum and plasma) in sample collection from patients. Serum and salivary samples were taken from 72 patients with breast cancer and 45 healthy controls, in order to investigate the following
... Show MoreAbstract A descriptive study to assess the quality of life (QOL) for patients with colorectal cancer. The study was conducted from Baghdad Teaching Hospital, Al-Yarmouk Teaching Hospital and Radiation Hospital and Nuclear medicine for the period from 1st July/2004 to 1st September/2004. The sample selected by purposive random of (50) patients diagnosed with colorectal cancer and all of them who were under chemotherapy treatment. A questionnaire was prepared for the purpose of the study and comprised of three parts including: 1- Socio-demographical characteristics. 2- Clinical characteristics. 3- and QOL
Breast cancer is one of the most common cancers in females. In Iraq there are noticeable elevation in incidence rates and prevalence of advanced stages of breast cancer. Ferritin is intracellular iron storage protein abundant in circulation and its main application in differential diagnosis of anemia.
The level of serum ferritin was found raised in various cancers including breast cancer. The aim of this study was to assess whether the serum ferritin concentration would be altered in Iraqi women with breast cancer and it could be related to progression of disease.
Sixty eight females participated in this study. The mean age of these females was 53.25± 9.52 .The level of serum ferritin was measured in 24
... Show MoreBackground: The transcriptional control of various cell types, especially in the development or functioning of immune system cells involved in either promoting or inhibiting the immune response against cancer, is significantly influenced by DNA or RNA methylation. Multifaceted interconnections exist between immunological or cancer cell populations in the tumor's microenvironment (TME). TME alters the fluctuating DNA (as well as RNA) methylation sequences in these immunological cells to change their development into pro- or anti-cancer cell categories (such as T cells, which are regulatory, for instance). Objective: This review highlights the impact of DNA and RNA methylation on myeloid and lymphoid cells, unraveling their intricate
... Show MoreAmygdalin (d-Mandelonitrile 6-O-β-d-glucosido-β-d-glucoside) and its semi synthetic product is Laetrile ( also called vitamin B17): a natural cyanogenic glycoside occurring in the seeds of some edible plants, such as bitter almonds and peaches. Early in the 19th century, Amygdalin was first isolated in 1830 by two French chemists, Robiquet and Boutron-Charlard, as active components in various fruit pits and raw nuts. However, the systematized study of vitamin B17 started when chemist Bohn (1802) discovered that a hydrocyanic acid is released during distillation of the water from bitter almonds. The various pharmacological effects of Laetrile include antiatherogenic, activity in renal fibrosis, pulmonary fibrosis, immune regulation, ant
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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