Precision Medicine: An Optimal Approach to Patient Care in Renal Cell Carcinoma

Low Serum Alanine Aminotransferase Blood Activity Is Associated with Shortened Survival of Renal Cell Cancer Patients and Survivors: Retrospective Analysis of 1830 Patients

Background: Sarcopenia is characterized by a loss of muscle mass and function and is often associated with frailty, a syndrome linked to physical disability and shortened survival in various patient populations, including cancer patients. Low serum alanine aminotransferase (ALT) values, serving as a biomarker for sarcopenia, were previously associated with frailty and shortened survival in several cancers. In the current study, we aimed to test the association between low ALT and shorter survival in renal cell carcinoma (RCC) patients and survivors. Methods: This was a retrospective analysis of RCC patients and survivors, both in- and outpatients. We defined patients with sarcopenia as those presenting with ALT < 17 IU/L. Results: We identified records of 3012 RCC patients. The cohort included 1830 patients (mean age 65.6 ± 13.3 years, 68% were men) of whom only 179 underwent surgical treatment. Out of the eligible cohort, 811 patients (44.3%) had ALT < 17 IU/L, with a mean ALT value of patients within the low-ALT group of 11.79 IU/L, while the mean value in the higher ALT level group was 24.44 IU/L (p < 0.001). Patients in the low-ALT group were older (67.9 vs. 63.7 years; p < 0.001) and had lower BMIs (26.6 vs. 28; p < 0.001). In addition, patients with low ALT had lower hemoglobin values (12.14 vs. 12.91 g/dL; p < 0.001), higher serum creatinine (1.49 vs. 1.14; p < 0.001) and higher platelet to lymphocyte ratios (178 vs. 156; p < 0.001). In a univariate analysis, low ALT levels were associated with a 72% increase in mortality (95% CI 1.46-2.02, p < 0.001). In a multivariate model controlled for age, gender, hemoglobin, platelets, LDH, neutrophil to lymphocyte ratios and platelet to lymphocyte ratios, low ALT levels were still associated with a 27% increase in mortality (HR = 1.27, 95% CI 1.08-1.51; p = 0.005). Conclusion. Low ALT values, associated with sarcopenia and frailty, are also associated with shortened survival in RCC patients, and survivors and could potentially be applied for optimizing individual treatment decisions.

Strategic Developments in Polymer-Functionalized Liposomes for Targeted Colon Cancer Therapy: An Updated Review of Clinical Trial Data and Future Horizons

Liposomes, made up of phospholipid bilayers, are efficient nanocarriers for drug delivery because they can encapsulate both hydrophilic and lipophilic drugs. Conventional cancer treatments sometimes involve considerable toxicities and adverse drug reactions (ADRs), which limits their clinical value. Despite liposomes' promise in addressing these concerns, clinical trials have revealed significant limitations, including stability, targeted distribution, and scaling challenges. Recent clinical trials have focused on enhancing liposome formulations to increase therapeutic efficacy while minimizing negative effects. Notably, the approval of liposomal medications like Doxil demonstrates their potential in cancer treatment. However, the intricacy of liposome preparation and the requirement for comprehensive regulatory approval remain substantial impediments. Current clinical trial updates show continued efforts to improve liposome stability, targeting mechanisms, and payload capacity in order to address these issues. The future of liposomal drug delivery in cancer therapy depends on addressing these challenges in order to provide patients with more effective and safer treatment alternatives.

Barriers and facilitators of the application of precision medicine to the genitourinary cancer care pathway: Perspective from a low- and middle- income country in sub-Saharan Africa

The benefit of the delivery of the right form of cancer care, tailored to the right patient, at the right time is increasingly being recognized in the global oncology community. Information on the role and feasible potential of precision oncology during the management of genitourinary cancer in Nigeria, the most populous country in Africa, is limited. This article, therefore, describes the present application of personalized medicine in Nigeria and its barriers and facilitators. It provided granular details on manpower distribution and epidemiological disparities. It also explored the use of clinical and biological markers for screening and early diagnosis, the application of team science to support genomic profiling, cost-effective approaches for image-based phenotypic precision oncology, the emerging role of molecular imaging, access to clinical trials; and their potential to support data driven diagnosis, treatment decision and care availability in order to address gaps in genitourinary cancer management in the country.

The microbiota and renal cell carcinoma

Renal cell carcinoma (RCC) accounts for about 2% of cancer diagnoses and deaths worldwide. Recent studies emphasized the critical involvement of microbial populations in RCC from oncogenesis, tumor growth, and response to anticancer therapy. Microorganisms have been shown to be involved in various renal physiological and pathological processes by influencing the immune system function, metabolism of the host and pharmaceutical reactions. These findings have extended our understanding and provided more possibilities for the diagnostic or therapeutic development of microbiota, which could function as screening, prognostic, and predictive biomarkers, or be manipulated to prevent RCC progression, boost anticancer drug efficacy and lessen the side effects of therapy. This review aims to present an overview of the roles of microbiota in RCC, including pertinent mechanisms in microbiota-related carcinogenesis, the potential use of the microbiota as RCC biomarkers, and the possibility of modifying the microbiota for RCC prevention or treatment. According to these scientific findings, the clinical translation of microbiota is expected to improve the diagnosis and treatment of RCC.

Sequential treatment of metastatic renal cell carcinoma patients after first-line vascular endothelial growth factor targeted therapy in a real-world setting: epidemiologic, noninterventional, retrospective-prospective cohort multicentre study

PURPOSE

The purpose of our study was to determine whether data on the clinical effectiveness of second-line therapy collected in a real-world setting provide additional valuable information on the optimal sequence of metastatic renal cell carcinoma (mRCC) treatment.

METHODS

Patients diagnosed with mRCC who were treated with at least one dose of first-line vascular endothelial growth factor (VEGF)-targeted therapy with either sunitinib or pazopanib and with at least one dose of second-line everolimus, axitinib, nivolumab, or cabozantinib were included. The efficacy of different treatment sequences was analyzed based on the time to the second objective disease progression (PFS2) and the time to the first objective disease progression (PFS).

RESULTS

Data from 172 subjects were available for analysis. PFS2 was 23.29 months. The 1-year PFS2 rate was 85.3%, and the 3-year PFS2 rate was 25.9%. The 1-year overall survival rate was 97.0%, and the 3-year overall survival rate was 78.6%. Patients with a lower IMDC prognostic risk group had a significantly (p < 0.001) longer PFS2. Patients with metastases in the liver had a shorter PFS2 than patients with metastases in the other sites (p = 0.024). Patients with metastases in the lungs and lymph nodes (p = 0.045) and patients with metastases in the liver and bones (p = 0.030) had lower PFS2 rates than patients with metastases in other sites.

CONCLUSIONS

Patients with a better IMDC prognosis have a longer PFS2. Metastases in the liver lead to a shorter PFS2 than metastases in other sites. One metastasis site means a longer PFS2 than 3 or more metastasis sites. Nephrectomy performed in an earlier stage of disease or metastatic setting means higher PFS and higher PFS2. No PFS2 difference was found between different treatment sequences of TKI-TKI or TKI-immune therapy.

PI3K/AKT/mTOR Dysregulation and Reprogramming Metabolic Pathways in Renal Cancer: Crosstalk with the VHL/HIF Axis

Renal cell carcinoma (RCC) represents 85-95% of kidney cancers and is the most frequent type of renal cancer in adult patients. It accounts for 3% of all cancer cases and is in 7th place among the most frequent histological types of cancer. Clear cell renal cell carcinoma (ccRCC), accounts for 75% of RCCs and has the most kidney cancer-related deaths. One-third of the patients with ccRCC develop metastases. Renal cancer presents cellular alterations in sugars, lipids, amino acids, and nucleic acid metabolism. RCC is characterized by several metabolic dysregulations including oxygen sensing (VHL/HIF pathway), glucose transporters (GLUT 1 and GLUT 4) energy sensing, and energy nutrient sensing cascade. Metabolic reprogramming represents an important characteristic of the cancer cells to survive in nutrient and oxygen-deprived environments, to proliferate and metastasize in different body sites. The phosphoinositide 3-kinase-AKT-mammalian target of the rapamycin (PI3K/AKT/mTOR) signaling pathway is usually dysregulated in various cancer types including renal cancer. This molecular pathway is frequently correlated with tumor growth and survival. The main aim of this review is to present renal cancer types, dysregulation of PI3K/AKT/mTOR signaling pathway members, crosstalk with VHL/HIF axis, and carbohydrates, lipids, and amino acid alterations.

Artificial Intellgence in the Era of Precision Oncological Imaging

Rapid-paced development and adaptability of artificial intelligence algorithms have secured their almost ubiquitous presence in the field of oncological imaging. Artificial intelligence models have been created for a variety of tasks, including risk stratification, automated detection, and segmentation of lesions, characterization, grading and staging, prediction of prognosis, and treatment response. Soon, artificial intelligence could become an essential part of every step of oncological workup and patient management. Integration of neural networks and deep learning into radiological artificial intelligence algorithms allow for extrapolating imaging features otherwise inaccessible to human operators and pave the way to truly personalized management of oncological patients.Although a significant proportion of currently available artificial intelligence solutions belong to basic and translational cancer imaging research, their progressive transfer to clinical routine is imminent, contributing to the development of a personalized approach in oncology. We thereby review the main applications of artificial intelligence in oncological imaging, describe the example of their successful integration into research and clinical practice, and highlight the challenges and future perspectives that will shape the field of oncological radiology.

Effects and Prognostic Values of Circadian Genes CSNK1E/GNA11/KLF9/THRAP3 in Kidney Renal Clear Cell Carcinoma via a Comprehensive Analysis

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent and deadly types of renal cancer in adults. Recent research has identified circadian genes as being involved in the development and progression of KIRC by altering their expression. This study aimed to identify circadian genes that are differentially expressed in KIRC and assess their role in KIRC progression. In KIRC, there were 553 differentially expressed rhythm genes (DERGs), with 300 up-regulated and 253 down-regulated DERGs. Functional enrichment analyses showed that DERGs were greatly enriched in the circadian rhythm and immune response pathways. Survival analyses indicated that higher expression levels of CSNK1E were related to shorter overall survival of KIRC patients, whereas lower expression levels of GNA11, KLF9, and THRAP3 were associated with shorter overall survival of KIRC patients. Through cell assay verification, the mRNA level of CSNK1E was significantly up-regulated, whereas the mRNA levels of GNA11, KLF9, and THRAP3 were dramatically down-regulated in KIRC cells, which were consistent with the bioinformatics analysis of KIRC patient samples. Age, grade, stage, TM classification, and CSNK1E expression were all shown to be high-risk variables, whereas GNA11, KLF9, and THRAP3 expression were found to be low-risk factors in univariate Cox analyses. Multivariate Cox analyses showed that CSNK1E and KLF9 were also independently related to overall survival. Immune infiltration analysis indicated that the proportion of immune cells varied greatly between KIRC tissues and normal tissue, whereas CSNK1E, GNA11, KLF9, and THRAP3 expression levels were substantially linked with the infiltration abundance of immune cells and immunological biomarkers. Moreover, interaction networks between CSNK1E/GNA11/KLF9/THRAP3 and immune genes were constructed to explore the stream connections. The findings could help us better understand the molecular mechanisms of KIRC progression, and CSNK1E/GNA11/KLF9/THRAP3 might be used as molecular targets for chronotherapy in KIRC patients in the near future.