Kidney Neoplasms

This study will investigate the genetic cause of Birt Hogg-Dube (BHD) syndrome and the relationship of this disorder to kidney cancer. BHD is a rare inherited condition characterized by papules, or bumps-benign tumors involving hair follicles-on the head and neck. People with BHD are at increased risk of developing kidney cancer. Scientists have identified the chromosome (strand of genetic material in the cell nucleus) that contains the BHD gene and the region of the gene on the chromosome. This study will try to learn more about: * The characteristics and type of kidney tumors associated with BHD * The risk of kidney cancer in people with BHD * Whether more than one gene causes BHD * The genetic mutations (changes) responsible for BHD Individuals with known or suspected Birt Hogg-Dube syndrome, and their family members, may be eligible for this study. Candidates will be screened with a family history and review of medical records, including pathology reports for tumors, and films of computed tomography (CT) and magnetic resonance imaging (MRI) scans. Participants may undergo various tests and procedures, including the following: * Physical examination * Review of personal and family history with a cancer doctor, cancer nurses, kidney surgeon, and genetic counselor * Chest and other x-rays * Ultrasound (imaging study using sound waves) * MRI (imaging study using radiowaves and a magnetic field) * CT scans of the chest and abdomen (imaging studies using radiation) * Blood tests for blood chemistries and genetic testing * Skin evaluation, including a skin biopsy (surgical removal of a small skin tissue sample for microscopic evaluation) * Cheek swab or mouthwash to collect cells for genetic analysis * Lung function studies * Medical photography of skin lesions These tests will be done on an outpatient basis in either one day or over 3 to 4 days. When the studies are complete, participants will receive counseling about the findings and recommendations. Individuals with kidney lesions may be asked to return periodically, such as every 3 to 36 months, based on their individual condition, to document the rate of progression of the lesions.

BEACON (Benchmarking AI for Clinical Oncology decisioNmaking) is a prospective, multicentre, comparative, blinded, non-interventional benchmark comparing the treatment recommendations of six frontier large language models (LLMs) with those of multidisciplinary tumour boards (RCP) in oncology treatment planning. One hundred standardised synthetic cases (20 per localisation, across breast, lung, urological, digestive and gynaecological cancers) are submitted as identical structured input to two independent tumour boards per localisation and to six frontier LLMs. Every recommendation, human or model, is decomposed into five predefined decision domains (intent, surgery, radiotherapy, systemic therapy with its line, work-up and biomarkers). For each domain, concordance between two recommendations is scored 2 when the same options are selected, 1 when at least one option is shared, and 0 when none is shared; the score is computed automatically from the recommendation forms, without human scoring. The primary endpoint is the mean domain score between each LLM and each tumour board, read against the same score computed between the two tumour boards of the same case, so that humans and models are measured by an identical rule and no respondent contributes to its own reference. A co-primary safety endpoint captures the proportion of recommendations carrying serious harm potential, because concordance alone can conceal dangerous errors. Where the two boards select different options, the case-domain is classified EQUIPOISE and, like every discordance, is adjudicated by an independent panel blinded to the source of the recommendation. Tumour boards record their recommendations during the meeting itself, on a dedicated platform (https://etude-beacon.fr) that reveals a case only once it is presented and time-stamps that reveal, so that no board can read a case in advance. BEACON is designed as reusable, openly licensed, pre-registered infrastructure: all synthetic cases, evaluation rubrics, scoring algorithms, verbatim prompts and raw model outputs are released for full reproducibility.

The purpose of this trial is to evaluate a new drug, HTL0039732, that will be administered on its own (as a monotherapy) and in combination with atezolizumab or with other approved anti-cancer therapies, in participants with advanced solid tumours.

Many clinical trials evaluating cancer treatments require patients to undergo testing for specific molecular markers as part of eligibility screening, typically using immunohistochemistry or sequencing. Because relatively few patients may carry a required marker, trial investigators often test large numbers of patients to identify the few who may ultimately qualify for enrollment. Pathology laboratories routinely produce hematoxylin-and-eosin (H\&E) slides during cancer diagnosis. Pathology foundation models-large neural networks pretrained on millions of histology images-have shown promise in predicting molecular characteristics from these slides. Researchers can use these models to build classifiers that predict specific molecular markers and prioritize patients for confirmatory testing. This study evaluates FATHOM (Facilitating Accrual through Tumor Histology and Omics Matching), an autonomous research system powered by large multimodal models. Its agents read registered clinical trial records, identify molecular markers used as enrollment criteria, build prediction models using pathology foundation models, select the individual models or model combinations that best meet prespecified criteria, set their decision thresholds, and determine whether to deploy them. Together, a prediction model, its decision threshold, and the decision to deploy it constitute an AI prediction policy. Before FATHOM runs, the investigators preregister the clinical trial records that its agents may read, the cutoff date that defines which trial information they may use, the rules governing the agents, and the analysis plan. The system timestamps and locks each policy immediately after an agent produces it. The investigators then apply the policies to archived patient slides and compare their predictions with existing molecular marker results. The primary outcome is the proportion of prespecified evaluation scenarios in which an agent-generated policy, compared with universal molecular testing, either enriches the population selected for confirmatory testing with marker-positive patients or safely spares patients from confirmatory testing while meeting prespecified performance criteria. This study analyzes existing pathology images and clinical trial records only. It does not enroll or contact patients, influence patient care, or affect participation in any clinical trial.

This is a 4-arm, single-center study involving 40 participants. Ten healthy volunteers will be enrolled for system imaging optimization, and thirty (30) patients with previously identified lesions in the breast, liver, or kidney-based on prior ultrasound or cross-sectional imaging-will be imaged. Recruitment will be conducted such that ten patients are included from each anatomic region. The fourth arm will consist of 10 healthy volunteers who will be imaged to allow optimization of imaging parameters. Optimization is is required again due to the use of a different ultrasound system employing a new imaging technique. Parameters such as frame rate, power, depth of imaging, and linear translation rate will be adjusted during this process. The primary objectives of the study are to assess the sensitivity and specificity of Contrast Enhanced Super-Resolution (CESR) imaging in evaluating known lesions in the breast, liver, and kidney. These results will be compared with pathological findings. The secondary objectives are to compare the sensitivity and specificity of CESR imaging with those of traditional B-mode ultrasound in differentiating malignant from benign lesions in these same organs.

The aim of this study is to establish and optimize the \[18F\]RCCB6 PET/CT imaging method, and its physiological and pathological distribution characteristics, on the basis of which the diagnostic efficacy of the above imaging agent in renal cancer (especially clear cell renal cell carcinoma) wil be evaluated.

This is a multicenter real world study (RWS) initiated by the investigator. Eligible patients will be selected for treatment with second-line treatment including vorolanib and followed up. The real survival data of patients after medication will be collected and compared with the data of CONCEPT study, and multi-factor stratified analysis of the efficacy of voronib will be conducted.

To conduct prospective studies to confirm the value of circulating tumor DNA and its abnormal methylation in longitudinal monitoring of patients undergoing kidney cancer surgery.

Pheochromocytomas and paragangliomas are neural crest-derived tumors of the nervous system that are often inherited and genetically heterogeneous. Genetic screening is recommended for patients and their relatives, and can guide clinical decisions. However, a mutation is not found in all cases. The aims of this proposal are to: 1) to map gene(s) involved in pheochromocytoma, and 2) identify genotype-phenotype correlations in patients with pheochromocytoma/paraganglioma of various genetic origins.

A proposed new tool ('DIPLANN-tool' - Digital Planning in Nephrectomy) for predicting kidney perfusion zones on a segmented 3D model during robot-assisted partial nephrectomy (RAPN) for localized renal cancer demonstrated high accuracy when planning selective clamping (SC) for RAPN. However, the tool's clinical added value still needs to be confirmed. Therefore, a randomized controlled trial using a study and control group is the preferred study design. Experimental group: the use of the DIPLANN-tool + conventional computed tomography (CT) imaging for preoperative planning and perioperative guidance during RAPN. Control group: the use of only conventional CT imaging for preoperative planning and perioperative guidance during RAPN (= current standard of care). The primary endpoint is planning and performing as planned a SC strategy. Secondary endpoints include patients' health, patients' insight and surgeons' benefits.

Zero ischemia laparoscopic radio frequency ablation assisted tumor enucleation has been proved to enable tumor excision with relatively better renal function preservation comparing with conventional laparoscopic partial nephrectomy for T1a renal cell carcinoma (RCC) in a randomized clinical trial in single center. The investigators want to explore this technique to robotic surgery and add suture-less technique to T1 RCC patients in randomized clinical trial.

Patients with renal masses eligible to partial nephrectomy often require arterial ischemia to control or prevent blood loss during this surgical procedure. This study aims to determine the safety and efficacy of renal cryoablation at the tumor bed, as a substitute measure or technique vs total or selective arterial renal ischemia.