Prognostic Value of KRAS Gene Mutation on Survival of Patients with Peritoneal Metastases of Colorectal Adenocarcinoma

Detecting colorectal cancer using genetic and epigenetic biomarkers: screening and diagnosis

Colorectal cancer (CRC) is one of the most frequent types of cancer, with high incidence rates and mortality globally. The extended timeframe for developing CRC allows for the potential screening and early identification of the disease. Furthermore, studies have shown that survival rates for patients with cancer are increased when diagnoses are made at earlier stages. Recent research suggests that the development of CRC, including its precancerous lesion, is influenced not only by genetic factors but also by epigenetic variables. Studies suggest epigenetics plays a significant role in cancer development, particularly CRC. While this approach is still in its early stages and faces challenges due to the variability of CRC, it shows promise as a potential method for understanding and addressing the disease. This review examined the current evidence supporting genetic and epigenetic biomarkers for screening and diagnosis. In addition, we also discussed the feasibility of translating these methodologies into clinical settings. Several markers show promising potential, including the methylation of vimentin (VIM), syndecan-2 (SDC2), and septin 9 (SEPT9). However, their application as screening and diagnostic tools, particularly for early-stage CRC, has not been fully optimized, and their effectiveness needs validation in large, multi-center patient populations. Extensive trials and further investigation are required to translate genetic and epigenetic biomarkers into practical clinical use. biomarkers, diagnostic biomarkers.

Single metachronous bone metastasis following rectal adenocarcinoma: A case report

Colorectal cancer (CRC) ranks as the third leading cause of cancer-related mortality in developed countries. While its incidence in early stages has increased due to screening programs, a significant number of patients experience the development of metastases either at the time of diagnosis or during follow-ups. Unlike certain other types of cancer, such as breast, prostate, or lung cancer, where bone tissue is a common site for secondary dissemination, CRC primarily spreads to the lymph nodes, liver and lungs. The occurrence of bone metastases from CRC is rare and usually coincides with tumor involvement in other locations. Risk factors for bone metastases include the location of the primary tumor, the age of the patients, KRAS mutations and the degree of tumor differentiation. Unlike metastases to the liver and lungs, bone metastases tend to be symptomatic, affecting the patient's quality of life and resulting in a poorer prognosis with shorter survival rates. The approach to patient management needs to be personalized. The present study describes the of a patient who underwent surgery for stage IV rectal adenocarcinoma and later developed a metastasis in the costal wall 79 months post-intervention, with no evidence of recurrence at other sites.

Nanoparticles and convergence of artificial intelligence for targeted drug delivery for cancer therapy: Current progress and challenges

Cancer is a life-threatening disease, resulting in nearly 10 million deaths worldwide. There are various causes of cancer, and the prognostic information varies in each patient because of unique molecular signatures in the human body. However, genetic heterogeneity occurs due to different cancer types and changes in the neoplasms, which complicates the diagnosis and treatment. Targeted drug delivery is considered a pivotal contributor to precision medicine for cancer treatments as this method helps deliver medication to patients by systematically increasing the drug concentration on the targeted body parts. In such cases, nanoparticle-mediated drug delivery and the integration of artificial intelligence (AI) can help bridge the gap and enhance localized drug delivery systems capable of biomarker sensing. Diagnostic assays using nanoparticles (NPs) enable biomarker identification by accumulating in the specific cancer sites and ensuring accurate drug delivery planning. Integrating NPs for cancer targeting and AI can help devise sophisticated systems that further classify cancer types and understand complex disease patterns. Advanced AI algorithms can also help in biomarker detection, predicting different NP interactions of the targeted drug, and evaluating drug efficacy. Considering the advantages of the convergence of NPs and AI for targeted drug delivery, there has been significantly limited research focusing on the specific research theme, with most of the research being proposed on AI and drug discovery. Thus, the study's primary objective is to highlight the recent advances in drug delivery using NPs, and their impact on personalized treatment plans for cancer patients. In addition, a focal point of the study is also to highlight how integrating AI, and NPs can help address some of the existing challenges in drug delivery by conducting a collective survey.

Prognostic Factors of Survival in Patients with Peritoneal Metastasis from Colorectal Cancer

Objectives: The aim of this study was to analyze the prognostic factors of survival in patients with peritoneal metastasis (PM) from colorectal cancer (CRC). The type of relationship between survival and the PM time of detection was used to determine whether it was synchronous with the primary tumor or metachronous. Patients and Methods: Retrospective observational study. It included patients treated for colorectal adenocarcinoma diagnosed between January 2005 and December 2019 who presented PM at the time of diagnosis or during follow-up. Variables, such as sex, age, differentiation grade, positive adenopathy (pN+), tumor size (pT), tumor location, mucinous component, peritoneal carcinomatosis index (PCI), and KRAS mutational status, were analyzed. Results: During the study period, 1882 patients were surgically treated for CRC in our hospital. Of these, 240 patients (12.8%) were included in the study after evidence of PM. The mean age was 67 ± 12 years (range: 32−92 years), and 114 patients were female (47.5%). The mean follow-up was 20 ± 13 months (median 12 months). The Kaplan−Meier survival at 36 months was higher in patients with metachronous PM (24% vs. 8%; p = 0.002), WT-KRAS tumors (31% vs. 15%; p < 0.001), N0 stage (30% vs. 19%; p < 0.001), T3 stage tumors (18% vs. 19% in T4A and 3% in T4B; p > 0.001), and tumors with classic adenocarcinoma histology (18% vs. 8%; p = 0.011). Patients with a PCI of 1−10 showed a likelihood of survival at 36 months of 56%, which was longer than that found in patients with a PCI of 11−20 (8%) or a PCI of >20 (0%) (p < 0.001). In the multiple regression analysis, the factors with an independent prognostic value were: poor grade of differentiation (HR 1.995; 95% CI: 1.294−3.077), KRAS mutation (HR 1.751; 95% CI: 1.188−2.581), PCI 11−20 (HR: 9.935; 95% CI: 5.204−18.966) and PCI > 20 (HR: 4.011; 95% CI: 2.291−7.023). Conclusions: PCI should continue as the as the most useful prognostic indicator in order to assess prognostic estimations as well as therapeutic and surgical decisions, but tumor grade and KRAS mutational status may help in the treatment decision process by providing complementary information. The time of PM detection did not achieve statistical significance in the multiple regression analysis.