Introduction: Nutritional care is a cornerstone of cancer treatment, with the potential to significantly improve patient outcomes by addressing malnutrition and enhancing recovery. Despite growing awareness, the integration of evidence-based nutritional strategies into oncology remains inconsistent. Following a 2020 survey that highlighted critical gaps, the NutriOnc Research Group launched targeted initiatives to raise awareness and improve practices. This study reassesses progress in integrating nutritional care and identifies persistent challenges. Methods: A 29-question survey was conducted in 2024 among 73 early-career oncologists, surgeons, radiation oncologists, and nutrition specialists across Italy. Respondents provided insights into clinical nutrition program availability, multidisciplinary team composition, screening practices, and educational needs. Results: Encouraging advancements were noted, with 80.8% of respondents reporting the presence of clinical nutrition programs, compared to fewer structured efforts in 2020. However, only 26.0% included nutrition specialists in multidisciplinary teams, and barriers such as financial constraints, limited product availability, and the absence of trained professionals persisted. While 82.2% performed nutritional screening, variability in tools and practices highlighted the need for standardization. Strikingly, 98.6% expressed a strong demand for advanced education on clinical nutrition, emphasizing the need for innovative and accessible training programs. Conclusions: This study reveals a landscape of progress tempered by persistent inequities. To close the gap, oncology must embrace standardized protocols, expand access to trained nutrition specialists, and invest in educational initiatives. The findings offer actionable insights for transforming cancer care through nutrition, underscoring its potential to improve survival, quality of life, and overall treatment success.

Background: Radiomics can provide quantitative features from medical imaging that can be correlated with various biological features and diverse clinical endpoints. Delta radiomics, on the other hand, consists in the analysis of feature variation at different acquisition time points, usually before and after therapy. The aim of this study was to provide a systematic review of the different delta radiomics approaches. Methods: Eligible articles were searched in Embase, Pubmed, and ScienceDirect using a search string that included free text and/or Medical Subject Headings (MeSH) with 3 key search terms: 'radiomics,' 'texture,' and 'delta.' Studies were analyzed using QUADAS-2 and the RQS tool. Results: Forty-eight studies were finally included. The studies were divided into preclinical/methodological (5 studies, 10.4%); rectal cancer (6 studies, 12.5%); lung cancer (12 studies, 25%); sarcoma (5 studies, 10.4%); prostate cancer (3 studies, 6.3%), head and neck cancer (6 studies, 12.5%); gastrointestinal malignancies excluding rectum (7 studies, 14.6%) and other disease sites (4 studies, 8.3%). The median RQS of all studies was 25% (mean 21% ± 12%), with 13 studies (30.2%) achieving a quality score < 10% and 22 studies (51.2%) < 25%. Conclusions: Delta radiomics shows potential benefit for several clinical endpoints in oncology, such asdifferential diagnosis, prognosis and prediction of treatment response, evaluation of side effects. Nevertheless, the studies included in this systematic review suffer from the bias of overall low methodological rigor, so that the conclusions are currently heterogeneous, not robust and hardly replicable. Further research with prospective and multicenter studies is needed for the clinical validation of delta radiomics approaches.

The integration of multidisciplinary tumor boards (MTBs) is fundamental in delivering state-of-the-art cancer treatment, facilitating collaborative diagnosis and management by a diverse team of specialists. Despite the clear benefits in personalized patient care and improved outcomes, the increasing burden on MTBs due to rising cancer incidence and financial constraints necessitates innovative solutions. The advent of artificial intelligence (AI) in the medical field offers a promising avenue to support clinical decision-making. This review explores the perspectives of clinicians dedicated to the care of cancer patients—surgeons, medical oncologists, and radiation oncologists—on the application of AI within MTBs. Additionally, it examines the role of AI across various clinical specialties involved in cancer diagnosis and treatment. By analyzing both the potential and the challenges, this study underscores how AI can enhance multidisciplinary discussions and optimize treatment plans. The findings highlight the transformative role that AI may play in refining oncology care and sustaining the efficacy of MTBs amidst growing clinical demands.

Tumor immunologic microenvironment is strongly involved in tumor progression and the presence of tumor infiltrating lymphocytes (TIL) with different phenotypes has been demonstrated to be of prognostic relevance in different malignancies. We investigated whether TIL infiltration of tumor tissues could also predict the outcome of prostate cancer patients. To this end, we carried out a retrospective analysis correlating the outcome of locally advanced prostate cancer patients undergone salvage radiotherapy upon relapse after radical surgery with the infiltration by different TIL populations. Twenty-two patients with resectable prostate cancer, with a mean age of 67 (+/−3.93) years, who received salvage radiotherapy with a mean of 69.66 (+/− 3.178) Gy in 8 weeks, between June 1999 and January 2009 and with a median follow up of 123 (+/− 55.82) months, were enrolled in this study. We evaluated, by immunohistochemistry, the intratumoral (^t) and peripheral stroma (^p) infiltration by CD45, CD3, CD4, CD8, CCR7, FoxP3 or PD-1-positive cells on tumor samples taken at the diagnosis (^d) and relapse times (^R). We correlated these variables with patients' biochemical progression free survival (bPFS), post-radiotherapy progression free survival (PFS), and overall survival (OS). Substantial changes in the rate of TIL subsets were found between the first and the second biopsy with progressive increase in CD4, CCR7, FoxP3, PD-1⁺ cells. Our analysis revealed that higher CD8^p,R+ and lower PD-1^R+ TIL scores correlated to a longer bPFS. Higher CD8^p,R+ and CCR7^t,R+ TIL scores and lower CD45^p,R+ and FoxP3^p,R+ TIL scores correlated to a prolonged PFS and OS. These results suggest that the immunological microenvironment of primary tumor is strictly correlated with patient outcome and provide the rationale for immunological treatment of prostate cancer.

The evaluation of the efficacy of different therapies is of paramount importance for the patients and the clinicians in oncology, and it is usually possible by performing imaging investigations that are interpreted, taking in consideration different response evaluation criteria. In the last decade, texture analysis (TA) has been developed in order to help the radiologist to quantify and identify parameters related to tumor heterogeneity, which cannot be appreciated by the naked eye, that can be correlated with different endpoints, including cancer prognosis. The aim of this work is to analyze the impact of texture in the prediction of response and in prognosis stratification in oncology, taking into consideration different pathologies (lung cancer, breast cancer, gastric cancer, hepatic cancer, rectal cancer). Key references were derived from a PubMed query. Hand searching and clinicaltrials.gov were also used. This paper contains a narrative report and a critical discussion of radiomics approaches related to cancer prognosis in different fields of diseases.