An evaluation of nivolumab for the treatment of metastatic renal cell carcinoma

Artificial Intelligence in Urooncology: What We Have and What We Expect

INTRODUCTION

Artificial intelligence is transforming healthcare by driving innovation, automation, and optimization across various fields of medicine. The aim of this study was to determine whether artificial intelligence (AI) techniques can be used in the diagnosis, treatment planning, and monitoring of urological cancers.

METHODOLOGY

We conducted a thorough search for original and review articles published until 31 May 2022 in the PUBMED/Scopus database. Our search included several terms related to AI and urooncology. Articles were selected with the consensus of all authors.

RESULTS

Several types of AI can be used in the medical field. The most common forms of AI are machine learning (ML), deep learning (DL), neural networks (NNs), natural language processing (NLP) systems, and computer vision. AI can improve various domains related to the management of urologic cancers, such as imaging, grading, and nodal staging. AI can also help identify appropriate diagnoses, treatment options, and even biomarkers. In the majority of these instances, AI is as accurate as or sometimes even superior to medical doctors.

CONCLUSIONS

AI techniques have the potential to revolutionize the diagnosis, treatment, and monitoring of urologic cancers. The use of AI in urooncology care is expected to increase in the future, leading to improved patient outcomes and better overall management of these tumors.

Wandering Cancer Cells: Metastatic Renal Cell Carcinoma Without Evidence of a Primary Tumor

Renal cell carcinoma (RCC) usually presents clinically in the advanced stage including bone metastasis. However metastatic RCC without evidence of a primary tumor in the kidney is extremely rare. We herein report a case of a 70-year-old male initially evaluated for bone lesion and diagnosed with biopsy-proven metastatic clear cell RCC without a renal primary. Given the rare nature of the disease, there is no standardized course of treatment that has yet been established. We believe that our case will add to the body of knowledge about uncommon oncologic instances and consolidate the information that has already been published.

A Network Meta-Analysis of the Differences in Effectiveness and Safety between Nivolumab and Targeted Drug Therapy in Metastatic Renal Cell Carcinoma

Objective. Nivolumab plus other drugs have provided significant benefits in patients with metastatic renal cell carcinoma (mRCC), but most of the available comparisons were conducted with sunitinib, and differences in efficacy with targeted drugs were marginally reported. Thus, this study used a network meta-analysis to compare the difference in efficacy between nivolumab combination therapy and other targeted agents. Methods. In this systematic review and network meta-analysis, we searched PubMed, Embase, and Cochrane Library databases for randomized controlled trials (RCTs) with the time set from database establishment to December 10, 2021, using programmed death factor 1 (PD-1) inhibitors, nivolumab, and sunitinib in the treatment of mRCC. Progression-free survival (PFS), overall survival (OS), response rate (RR), and adverse events (AEs) were collated and analyzed using the gemtc package in the R language. Results. A total of ten studies satisfied the inclusion criteria, including 6568 RCC cases, 10 drugs, and 11 treatment protocols. The Ate_Axi protocol obtained similar PFS to the Niv_Cab protocol, which outperformed that of all other protocols. The Niv_Cab regimen showed better PFS benefits than the Niv_Ipi regimen (HR < 1, $P<0.05$ ), and Niv_Ipi had superior PFS compared to the Ate, Eve, Paz, Sor, and Sun scheme. The regimens Cab, Niv_Cab, and Niv_Ipi were associated with the best PFS benefits, while Eve is the least favorable drug in terms of PFS. Niv_Cab showed better OS than Ate_Bev, Eve, Paz, Sor, and Sun. The patients given Ate_Bev, Eve, Paz, Sor, and Sun had inferior OS to those given Niv_Ipi. The Pem_Axi, Niv_Cab, and Niv_Ipi regimens had the best OS, and that of Eve is considered least promising. The Niv_Cab protocol showed significantly better RRs than the Eve, Paz, Sor, and Sun protocols, and the Ate_Bev, Eve, Paz, Sor, and Sun protocols presented superior RRs compared to the Niv_Ipi protocol. The Ate, Eve, and Niv_Ipi regimens had the lowest incidence of AEs, and the Sor regimen had the highest incidence of AEs. Conclusion. Among the targeted treatment options for mRCC, both Niv_Cab and Niv_Ipi yield better efficacy and safety in the treatment of mRCC, with Niv_Cab providing more survival benefit but with a less favorable safety profile.

From Anti-PD-1/PD-L1 to CTLA-4 and to MUC1-Is the Better Response to Treatment in Smokers of Cancer Patients Drug Specific?

Whether smokers respond to anti-cancer drugs differently than non-smokers remains controversial. The objective of this study is to explore whether the better response of the smokers is specific to therapy of anti-PD-1/PD-L1, anti-checkpoint inhibitor, individual drugs on the cell surface, or lung cancer. Our results showed that among all non-small cell lung cancer (NSCLC) patients, when the data from anti-PD-1/PD-L1, anti-CTLA-4, and anti-MUC1 drugs are combined, the mean hazard ratios (HR) of smokers and non-smokers were 0.751 and 1.016, respectively. A meta-analysis with a fixed effect (FE) model indicated that the smokers have an HR value of 0.023 lower than that of the non-smokers. A stratified subgroup meta-analysis indicated that when treated with anti-CTLA-4 drugs, smokers had reduced HR values of 0.152 and 0.165 on average and FE model meta-analysis, respectively. When treated with an anti-MUC1 drug, smokers had reduced HR values of 1.563 and 0.645, on average and FE model meta-analysis, respectively. When treated with a combination of nivolumab and ipilimumab drugs, smokers had, on average, reduced HR and FE model meta-analysis values (0.257 and 0.141), respectively. Smoking is a clinical response predictor for anti-PD/PD-L1 monotherapy or first-line treatment in lung, urothelial carcinoma, and head and neck cancer. Smokers treated with other drugs have shown worse responses in comparison to non-smokers. These data suggest that, along with the progress in the development of new drugs for cancer, drugs acting on specific genotypes of smokers likely will arise.

Impact of inflammation and immunotherapy in renal cell carcinoma

Substantial research attention has been directed at exploring the mechanisms and treatment of renal cell carcinoma (RCC). Indeed, the association between inflammation and tumor phenotypes has been at the center of cancer research. Concomitant with research on the inflammation response and inflammatory molecules involved in RCC, new breakthroughs have emerged. A large body of knowledge now shows that treatments targeting inflammation and immunity in RCC provide substantial clinical benefits. Adequate analysis and a better understanding of the mechanisms of inflammatory factors in the occurrence and progression of RCC are highly desirable. Currently, numerous RCC treatments targeted at inflammation and immunotherapy are available. The current review describes in detail the link between inflammation and RCC.