Renal cell carcinoma (RCC) associated with anaplastic lymphoma kinase (ALK) gene rearrangements (ALK-RCC) is currently considered an “emerging or provisional” tumor entity by the last World Health Organization classification published in 2016. Although several studies assessing ALK-RCC’s clinical and histological characteristics have been published in recent years, only a few publications have evaluated the activity of ALK inhibitors (ALK-i) in this subgroup of patients. Considering the well-recognized efficacy of this evolving class of targeted therapies in other ALK-positive tumors, we conducted a systematic review to evaluate the reported activity of ALK-i in the ALK-RCC subtype. MEDLINE was searched from its inception to 7 January 2022 for case reports and case series on adult metastatic ALK-RCC patients treated with ALK-i whose therapeutic outcomes were available. A virtual cohort of ALK-RCC patients was created. Our results showed a favorable activity of first- and second-generation ALK-i in pretreated ALK-RCC patients in terms of either radiological response or performance status improvement. We hope that the present work will prompt the creation of large, multi-institutional clinical trials to confirm these promising early data.

The approval of larotrectinib and entrectinib for cancer patients harboring an NTRK gene fusion has represented a milestone in the era of “histology-agnostic” drugs. Among the clinical trials that led to the approval of these two drugs, most of the enrolled patients were affected by soft tissue sarcomas, lung, and salivary gland cancer. However, as next-generation sequencing assays are increasingly available in the clinical setting, health care professionals may be able to detect NTRK gene fusions in patients affected by tumor types under or not represented in the clinical trials. To this aim, we systematically reviewed MEDLINE from its inception to 31 August 2022 for case reports and case series on patients with NTRK gene fusion-positive tumors treated with TRK inhibitors. A virtual cohort of 43 patients was created, excluding those enrolled in the above-mentioned clinical trials. Although our results align with those existing in the literature, various cases of central nervous system tumors were registered in our cohort, confirming the benefit of these agents in this subgroup of patients. Large, multi-institutional registries are needed to provide more information about the efficacy of TRK inhibitors in cancer patients affected by tumor types under or not represented in the clinical trials.

Background: Artificial intelligence is increasingly being applied to many workflows. Large language models (LLMs) are publicly accessible platforms trained to understand, interact with, and produce human-readable text; their ability to deliver relevant and reliable information is also of particular interest for the health care providers and the patients. Hematopoietic stem cell transplantation (HSCT) is a complex medical field requiring extensive knowledge, background, and training to practice successfully and can be challenging for the nonspecialist audience to comprehend. Objective: We aimed to test the applicability of 3 prominent LLMs, namely ChatGPT-3.5 (OpenAI), ChatGPT-4 (OpenAI), and Bard (Google AI), in guiding nonspecialist health care professionals and advising patients seeking information regarding HSCT. Methods: We submitted 72 open-ended HSCT–related questions of variable difficulty to the LLMs and rated their responses based on consistency—defined as replicability of the response—response veracity, language comprehensibility, specificity to the topic, and the presence of hallucinations. We then rechallenged the 2 best performing chatbots by resubmitting the most difficult questions and prompting to respond as if communicating with either a health care professional or a patient and to provide verifiable sources of information. Responses were then rerated with the additional criterion of language appropriateness, defined as language adaptation for the intended audience. Results: ChatGPT-4 outperformed both ChatGPT-3.5 and Bard in terms of response consistency (66/72, 92%; 54/72, 75%; and 63/69, 91%, respectively; P=.007), response veracity (58/66, 88%; 40/54, 74%; and 16/63, 25%, respectively; P<.001), and specificity to the topic (60/66, 91%; 43/54, 80%; and 27/63, 43%, respectively; P<.001). Both ChatGPT-4 and ChatGPT-3.5 outperformed Bard in terms of language comprehensibility (64/66, 97%; 53/54, 98%; and 52/63, 83%, respectively; P=.002). All displayed episodes of hallucinations. ChatGPT-3.5 and ChatGPT-4 were then rechallenged with a prompt to adapt their language to the audience and to provide source of information, and responses were rated. ChatGPT-3.5 showed better ability to adapt its language to nonmedical audience than ChatGPT-4 (17/21, 81% and 10/22, 46%, respectively; P=.03); however, both failed to consistently provide correct and up-to-date information resources, reporting either out-of-date materials, incorrect URLs, or unfocused references, making their output not verifiable by the reader. Conclusions: In conclusion, despite LLMs’ potential capability in confronting challenging medical topics such as HSCT, the presence of mistakes and lack of clear references make them not yet appropriate for routine, unsupervised clinical use, or patient counseling. Implementation of LLMs’ ability to access and to reference current and updated websites and research papers, as well as development of LLMs trained in specialized domain knowledge data sets, may offer potential solutions for their future clinical application.

Precision medicine has opened up a new era in the development of anti-cancer agents that is focused on identifying biomarkers predictive of treatment response regardless of tumor histology. Since 2017, the Food and Drug Administration has approved six drugs with histology-agnostic indications: pembrolizumab (both for tumors with the mismatch-repair deficiency (dMMR)/high microsatellite instability (MSI-H) phenotype and for those with the high tumor mutational burden (TMB-H) phenotype), dostarlimab (for dMMR tumors), larotrectinib and entrectinib (for tumors harboring neurotrophic tyrosine receptor kinase (NTRK) fusions), and the combination of dabrafenib plus trametinib (for BRAF V600E-mutated tumors). The genomic alterations targeted by these antineoplastic agents are rare in metastatic castration-resistant prostate cancer (mCRPC). Furthermore, only a small number of mCRPC patients were enrolled in the clinical trials that led to the approval of the above-mentioned drugs. Therefore, we critically reviewed the literature on the efficacy of histology-agnostic drugs in mCRPC patients. Although the available evidence derives from retrospective studies and case reports, our results confirmed the efficacy of pembrolizumab in dMMR/MSI-H mCRPC. In contrast, few data are available for dostarlimab, larotrectinib, entrectinib, and dabrafenib-trametinib in this subset of patients. Large, multi-institutional registries aimed at collecting real-world data are needed to better comprehend the role of tissue-agnostic drugs in mCRPC patients.

Antibody–drug conjugates (ADCs) are complex chemical structures composed of a monoclonal antibody, serving as a link to target cells, which is conjugated with a potent cytotoxic drug (i.e., payload) through a chemical linker. Inspired by Paul Ehrlich’s concept of the ideal anticancer drug as a “magic bullet”, ADCs are also highly specific anticancer agents, as they have been demonstrated to recognize, bind, and neutralize cancer cells, limiting injuries to normal cells. ADCs are among the newest pharmacologic breakthroughs in treating solid and hematologic malignancies. Indeed, in recent years, various ADCs have been approved by the Food and Drug Administration and European Medicines Agency for the treatment of several cancers, resulting in a “practice-changing” approach. However, despite these successes, no ADC is approved for treating patients affected by renal cell carcinoma (RCC). In the present paper, we thoroughly reviewed the current literature and summarized preclinical studies and clinical trials that evaluated the activity and toxicity profile of ADCs in RCC patients. Moreover, we scrutinized the potential causes that, until now, hampered the therapeutical success of ADCs in those patients. Finally, we discussed novel strategies that would improve the development of ADCs and their efficacy in treating RCC patients.