Prognostic value of primary tumor location in colorectal cancer: an updated meta-analysis

Stage-based colorectal cancer prediction on uncertain dataset using rough computing and LSTM models

Artificial intelligence (AI) is an attractive field of Computer Science that helps to classify and to predict various real-time applications. Perhaps AI has a major role in predicting diseases at an early stage based on history. As cancer is one of the most harmful diseases where the mortality rate is high, it is now essential to utilize the benefits of AI to have an early diagnosis of cancer. Among various cancers, Colorectal cancer (CRC) is a common form of gastrointestinal cancer, and its treatment is lengthy and costly, with a high recurrence rate and high fatality rate. Initial disease analysis and prognosis are required to improve the patient's treatment with a better survival analysis. However, the disease prediction process depends on the collected data, where the data may contain uncertainty. Uncertain data leads to wrong predictions. Thus, it is essential to utilize rough computing, a mathematical tool to deal with uncertainty. This paper has made an effort, to handle uncertainty using a rough set of fuzzy approximation space as pre-processing and utilized Unidirectional and Bidirectional LSTM for the classification and prediction process. Thus, to demonstrate improved predictive accuracy, the proposed model adapted the optimizers and evaluated using benchmarking techniques in predicting stage-based survival rate. The comparative analysis shows that the proposed model performs well against the state-of-the-art models and can help the medical practitioner to detect CRC at an early stage and reduce the mortality rate among human beings.

Pegylated nanoliposomal cisplatin ameliorates chemotherapy-induced peripheral neuropathy

BACKGROUND

Chemotherapy-induced peripheral neuropathy (CIPN) is a serious adverse effect of cisplatin. The current study aimed to determine whether PEGylated nanoliposomal cisplatin can limit CIPN in an animal model.

METHODS

Cisplatin-loaded PEGylated liposome nanoparticles (Cis-PL) were produced as a combination of lecithin, cholesterol, and DSPE-mPEG2000 in a molar ratio of 50:45:5 and were characterized by polydispersity index (PDI), zeta potential, Field emission scanning electron microscopy (FESEM) analysis, as well as encapsulation efficiency (EE). Fifteen male rats were provided and randomly divided into 3 groups including Cis-PL group, cisplatin group, and control group. Behavioural tests (hot-plate test and acetone drop test) were used for evaluating CIPN. Moreover, oxidative stress markers and histopathological analysis were applied. Treatment-related toxicity was assessed by haematological analysis as well as liver and renal function tests.

RESULTS

Cis-PL had an average particle size of 125.4, PDI of 0.127, and zeta potential of -40.9 mV. Moreover, the Cis-PL exhibited a high EE as well as low levels of leakage rate at 25 °C. In a hot-plate test, paw withdrawal latency was longer in Cis-PL group in comparison to rats treated with cisplatin. A lower number of withdrawal responses was detected during acetone drop test in Cis-PL group than in cisplatin-treated rats. Assessment of oxidative stress markers showed that Cis-PL could improve oxidative stress. Additionally, histopathological assessment demonstrated that the number of satellite cells was significantly reduced in the dorsal root ganglion (DRG) of Cis-PL-treated rats compared with those treated with cisplatin. The cisplatin group had elevated white blood cells counts, reduced platelet counts, and higher levels of bilirubin, ALT (alanine aminotransferase, and AST (aspartate aminotransferase), and creatinine compared with the control group, which was ameliorated in Cis-PL group.

CONCLUSIONS

Data from the current study support the previous hypothesis that Cisplatin-loaded PEGylated liposome could be a promising solution for CIPN in the future by modulating oxidative stress and preventing glial cell activation in DRG, suggesting further clinical studies to investigate the efficacy of this agent and its potential application in clinical practice.

Prognostic Factors Influencing Survival in Stage II and Stage III Colorectal Cancer Patients

Background Colorectal cancer (CRC) is a global health concern with rising incidence. This study analyzed demographic and clinicopathological factors influencing overall survival (OS) and disease-free survival (DFS) in Jordanian CRC patients. Methodology This retrospective, single-center study collected data from CRC patients at the Royal Medical Services, Jordan, from January 2018 to June 2020. Patient variables included disease stage, stage risk, tumor location, history of chemotherapy, and metastasis status. OS and DFS were defined as the time from surgery to death, last follow-up, or metastasis confirmation. Kaplan-Meier curves and Cox models were used for survival analysis. Results Of 127 CRC patients, 33.3% died during the follow-up period. Most patients were males (55.1%), diagnosed with stage III (55.9%), and classified as high risk (59.2%). Metastasis occurred in 24.4%, and 65.4% received chemotherapy. OS at one, two, and end of the follow-up years was 85.2%, 75.6%, and 66.9%, respectively. Metastasis-free rates were 85%, 78.5%, and 71%, respectively. Multivariate analysis showed that stage III (hazard ratio (HR) = 2.968) and high-risk stage (HR = 2.966) were associated with shorter OS and increased metastasis risk. Right-sided tumors (HR = 2.183) had shorter OS, while chemotherapy recipients (HR = 0.430) had longer OS. Stage III and high-risk stages were strong predictors of mortality, while only stage III and high-risk stages were robust predictors of metastasis. Demographic variables (sex and age) showed no significant associations with survival outcomes. Conclusions Our findings highlight the prognostic significance of disease stage, stage risk, tumor location, and chemotherapy in CRC survival among Jordanian patients. Understanding these factors can guide tailored treatment and improve outcomes.

Extracellular vesicles: Emerging mediators of cell communication in gastrointestinal cancers exhibiting metabolic abnormalities

There is a complex interaction between pro-tumoural and anti-tumoural networks in the tumour microenvironment (TME). Throughout tumourigenesis, communication between malignant cells and various cells of the TME contributes to metabolic reprogramming. Tumour Dysregulation of metabolic pathways offer an evolutional advantage in the TME and enhance the tumour progression, invasiveness, and metastasis. Therefore, understanding these interactions within the TME is crucial for the development of innovative cancer treatments. Extracellular vesicles (EVs) serve as carriers of various materials that include microRNAs, proteins, and lipids that play a vital role in the communication between tumour cells and non-tumour cells. EVs are actively involved in the metabolic reprogramming process. This review summarized recent findings regarding the involvement of EVs in the metabolic reprogramming of various cells in the TME of gastrointestinal cancers. Additionally, we highlight identified microRNAs involved in the reprogramming process in this group of cancers and explained the abnormal tumour metabolism targeted by exosomal cargos as well as the novel potential therapeutic approaches.