Exploring machine learning tools in a retrospective case-study of patients with metastatic non-small cell lung cancer treated with first-line immunotherapy: A feasibility single-centre experience.

Background: Artificial intelligence (AI) models are emerging as promising tools to identify predictive features among data coming from health records. Their application in clinical routine is still challenging, due to technical limits and to explainability issues in this specific setting. Response to standard first-line immunotherapy (ICI) in metastatic Non-Small-Cell Lung Cancer (NSCLC) is an interesting population for machine learning (ML), since up to 30% of patients do not benefit.

Single-Nuclei Transcriptome Profiling Reveals Intra-Tumoral Heterogeneity and Characterizes Tumor Microenvironment Architecture in a Murine Melanoma Model.

Malignant melanoma is an aggressive cancer, with a high risk of metastasis and mortality rates, characterized by cancer cell heterogeneity and complex tumor microenvironment (TME). Single cell biology is an ideal and powerful tool to address these features at a molecular level. However, this approach requires enzymatic cell dissociation that can influence cellular coverage.

CTC-derived pancreatic cancer models serve as research tools and are suitable for precision medicine approaches.

Pancreatic ductal adenocarcinoma (PDAC) poses significant clinical challenges, often presenting as unresectable with limited biopsy options. Here, we show that circulating tumor cells (CTCs) offer a promising alternative, serving as a "liquid biopsy" that enables the generation of in vitro 3D models and highly aggressive in vivo models for functional and molecular studies in advanced PDAC. Within the retrieved CTC pool (median 65 CTCs/5 mL), we identify a subset (median content 8.

From Tumor Macroenvironment to Tumor Microenvironment: The Prognostic Role of the Immune System in Oral and Lung Squamous Cell Carcinoma.

Background: The interplay between cancer cells and the immune system is crucial in cancer progression and treatment. In this regard, the tumor immune microenvironment and macroenvironment, marked by systemic inflammation markers and TILs, could be considered key prognostic factors in tumors, including oral and lung squamous cell carcinoma.

Methods: We conducted a retrospective clinical study on patients with Oral Squamous Cell Carcinoma (OSCC) and Lung Squamous Cell Carcinoma (LUSCC), examining stages, comorbidities, treatments, and outcomes.

Unlocking the future of cancer diagnosis - promises and challenges of ctDNA-based liquid biopsies in non-small cell lung cancer.

The advent of liquid biopsies has brought significant changes to the diagnosis and monitoring of non-small cell lung cancer (NSCLC), presenting both promise and challenges. Molecularly targeted drugs, capable of enhancing survival rates, are now available to around a quarter of NSCLC patients. However, to ensure their effectiveness, precision diagnosis is essential.