Search

Purpose: The integration of patient-reported outcomes (PROs) into electronic health records (EHRs) has enabled systematic collection of symptom data to manage post-treatment symptoms. The use and integration of PRO data into routine care are associated with overall treatment success, adherence, and satisfaction. Clinical trials have demonstrated the prognostic value of PROs including physical function and global health status in predicting survival. It is unknown to what extent routinely collected PRO data are used in the development of risk prediction models (RPMs) in oncology care. The objective of the scoping review is to assess how PROs are used to train risk RPMs to predict patient outcomes in oncology care., Methods: Using the scoping review methodology outlined in the Joanna Briggs Institute Manual for Evidence Synthesis, we searched four databases (MEDLINE, CINAHL, Embase, and Web of Science) to locate peer-reviewed oncology articles that used PROs as predictors to train models. Study characteristics including settings, clinical outcomes, and model training, testing, validation, and performance data were extracted for analyses., Results: Of the 1,254 studies identified, 18 met inclusion criteria. Most studies performed retrospective analyses of prospectively collected PRO data to build prediction models. Post-treatment survival was the most common outcome predicted. Discriminative performance of models trained using PROs was better than models trained without PROs. Most studies did not report model calibration., Conclusion: Systematic collection of PROs in routine practice provides an opportunity to use patient-reported data to develop RPMs. Model performance improves when PROs are used in combination with other comprehensive data sources.

Precision oncology tailors treatment strategies to a patient's molecular and health data. Despite the essential clinical value of current diagnostic methods, hematoxylin and eosin morphology, immunohistochemistry, and gene panel sequencing offer an incomplete characterization. In contrast, highly multiplexed tissue imaging allows spatial analysis of dozens of markers at single-cell resolution enabling analysis of complex tumor ecosystems; thereby it has the potential to advance our understanding of cancer biology and supports drug development, biomarker discovery, and patient stratification. We describe available highly multiplexed imaging modalities, discuss their advantages and disadvantages for clinical use, and potential paths to implement these into clinical practice. Significance: This review provides guidance on how high-resolution, multiplexed tissue imaging of patient samples can be integrated into clinical workflows. It systematically compares existing and emerging technologies and outlines potential applications in the field of precision oncology, thereby bridging the ever-evolving landscape of cancer research with practical implementation possibilities of highly multiplexed tissue imaging into routine clinical practice., (©2024 The Authors; Published by the American Association for Cancer Research.)

The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment of the work to date in this field, focusing on diagnostic AI models of key genomic markers, predictive AI models of response before and after therapy, and differentiation of true disease progression from treatment-related changes, which is a considerable challenge based on current clinical care in neuro-oncology. Furthermore, promising future directions, including the use of AI for automated response assessment in neuro-oncology, are discussed., Competing Interests: Declaration of interests JML received grants from the National Institutes of Health (NIH; P01CA118816), Department of Defense, and GE Healthcare. WLB reported receiving an honorarium from Stryker. PL received a grant from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation; 428090865/SPP 2177). TCB received consulting fees from Microvention; is on speakers bureaus for Siemens Healthineers, Bayer, and Medtronic; and received grants from the Medical Research Council (MR/W021684/1) and the Wellcome Engineering and Physical Sciences Research Council Centre for Medical Engineering (WT 203,148/Z/16/Z). HJWLA received grants from the NIH (U24CA194354, U01CA190234, U01CA209414, R35CA22052, and U54CA27451), the European Research Council (866504), and the US Department of Veterans Affairs; and consulting fees from Onc.AI, Sphera, and Love Health. JCT received grants from Novocure and Munich Surgical Imaging; royalties from Springer Publishing; consulting fees from Novartis; an honorarium from the Italian Society for Neurology; and support to attend meetings of the Belgian Association for Neurooncology and Glioma Meeting Athens 2023. RJ received a grant from AIRS Medical. MAV received grants from Infuseon Therapeutics, Oncosynergy, and DeNovo Pharma; consulting fees from Servier Pharma and BioDexa Pharma; and holds patents and received royalties for drug delivery devices. RYH reported consulting fees from Nuvation Bio and Vysioneet. NG received a grant from the DFG (428090865/SPP 2177); honorarium from Blue Earth Diagnostics; and participated on an advisory board for Telix Pharmaceuticals. CD received grants from the NIH (U24CA189523, UL1TR001878, and R01NS042645). SB received grants from the NIH (U01CA242871 and UL1TR001878). RRC received grants from the NIH. MI received grants from the Musella Foundation Grant and the R&D Pilot Award from the University of Wisconsin-Madison. PT received grants from the NIH (U01CA248226, R01CA264017, and U01CA248226), the Veterans Affairs (VA) Merit Award (1I01BX005842-01A2), the DOD/PRCRP Career Development Award (W81XWH-18-1-0404), the Dana Foundation David Mahoney Neuroimaging Program, the V Foundation Translational Research Award, the Johnson & Johnson WiSTEM2D Award, the Ohio Third Frontier Technology Validation Fund, the Musella Foundation Grant, and the R&D Pilot Award from the University of Wisconsin-Madison. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Cognitive dysfunction is common in cancers and their treatments. Factors that can contribute to cognitive dysfunction include direct and indirect effects of cancer, surgery, radiation, systemic therapy, as well as comorbidities, fatigue, and mood disturbance. Using objective, validated measures, a neuropsychological evaluation can provide information regarding patterns of cognitive function. Emphasis of cognitive domains assessed may vary depending on disease and treatment history. Cognitive interventions can minimize the effects of cancer-related cognitive dysfunction on daily life., Competing Interests: Disclosure The authors do not have any commercial or financial conflicts of interests with this work. J. Wefel received consulting fees from Bayer and Intra-Cellular Therapies, and research funding (paid directly to institution) from Bayer, Germany, GT Medical Technologies, and Novocure, Israel., (Copyright © 2024 Elsevier Inc. All rights reserved.)

As cancer has become better understood on the molecular level with the evolution of gene sequencing techniques, considerations for individualized therapy using predictive biomarkers (those associated with a treatment's effect) have shifted to a new level. In the last decade or so, randomized "adaptive enrichment" clinical trials have become increasingly utilized to strike a balance between enrolling all patients with a given tumor type, versus enrolling only a subpopulation whose tumors are defined by a potential predictive biomarker related to the mechanism of action of the experimental therapy. In this review article, we review recent innovative design extensions and adaptations to adaptive enrichment designs proposed during the last few years in the clinical trial methodology literature, both from Bayesian and frequentist perspectives., (© 2024. The Author(s).)

While AI holds immense potential for accelerating advances in oncology, we must be intentional in developing and applying these technologies responsibly, equitably, and ethically. One path forward is for cancer care providers and researchers to be among the architects of AI and its adoption in medicine. Given the limitations of traditional top-down, hypothesis-driven design in an exponentially expanding data universe, on one hand, and the danger of spiraling into artificial ignorance (ai) from rushing into a purely 'synthetic' method on the other, this article proposes a 'scienthetic' method that synergizes AI with human wisdom. Tracing philosophical underpinnings of the scientific method from Socrates, Plato, and Aristotle to the present, it examines the critical juncture at which AI stands to either augment or undermine new knowledge. The scienthetic method seeks to harness the power and capabilities of AI responsibly, equitably, and ethically to transcend the limitations of both the traditional scientific method and purely synthetic methods, by intentionally weaving machine intelligence together with human wisdom., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Introduction: Use of placebo in oncology randomized controlled trials (RCT) is ethically controversial. Placebo may introduce bias, as toxicity profiles of treatment arms can inadvertently unblind subjects and investigators. We investigated the use of placebo in urologic oncology RCTs, hypothesizing that most placebo-controlled trials are effectively unblinded, either explicitly with open-label design or implicitly due to large differences in adverse events (AE) or oncologic outcomes., Methods: Urologic oncology RCTs utilizing placebo were identified via ClinicalTrials.gov. Interventional prostate, bladder/urothelial, and renal cancer trials from 2014 to 2024 were included. Subject incompletion, all-cause mortality, AE rates, and serious AE (SAE) rates were identified and compared between placebo and active arms using χ 2 and Fisher's exact tests., Results: Sixty studies met inclusion criteria and included 66 placebo arms with 12,918 subjects and 81 active arms with 16,098 subjects. There was no significant difference in incompletion rates between placebo and active arms. Subjects enrolled in active arms reported statistically significant higher SAE and AE rates compared to those in placebo arms across the majority of physiological domains, including 18/24 domains for SAEs and 13/24 for AEs. This relationship persisted in sensitivity analyses where unblinded trials were excluded., Conclusions: In urologic oncology placebo-controlled RCTs, active arms are associated with significantly higher rates of AEs and SAEs compared with placebo arms. These findings indicate a strong possibility that true blinding is not possible in oncology RCTs, even with optimal study design, and serve to better inform future clinical trial design and implementation challenges in employing placebo control.

Background: Genomic tumour profiling has a crucial role in the management of patients with solid cancers, as it helps selecting and prioritising therapeutic interventions based on prognostic and predictive biomarkers, as well as identifying markers of hereditary cancers. Harmonised approaches to interpret the results of genomic testing are needed to support physicians in their decision making, prevent inequalities in precision medicine and maximise patient benefit from available cancer management options., Methods: The European Society for Medical Oncology (ESMO) Translational Research and Precision Medicine Working Group assembled a group of international experts to propose recommendations for preparing clinical genomic reports for solid cancers. These recommendations aim to foster best practices in integrating genomic testing within clinical settings. After review of available evidence, several rounds of surveys and focused discussions were conducted to reach consensus on the recommendation statements. Only consensus recommendations were reported. Recommendation statements were graded in two tiers based on their clinical importance: level A (required to maintain common standards in reporting) and level B (optional but necessary to achieve ideal practice)., Results: Genomics reports should present key information in a front page(s) followed by supplementary information in one or more appendices. Reports should be structured into sections: (i) patient and sample details; (ii) assay and data analysis characteristics; (iii) sample-specific assay performance and quality control; (iv) genomic alterations and their functional annotation; (v) clinical actionability assessment and matching to potential therapy indications; and (vi) summary of the main findings. Specific recommendations to prepare each of these sections are made., Conclusions: We present a set of recommendations aimed at structuring genomics reports to enhance physician comprehension of genomic profiling results for solid cancers. Communication between ordering physicians and professionals reporting genomic data is key to minimise uncertainties and to optimise the impact of genomic tests in patient care., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

In recent years, the incorporation of new strategies to the therapeutic armamentarium has completely changed the outcomes of epithelial ovarian cancer (EOC). The identification of new predictive and prognostic biomarkers has also enabled the selection of those patients more likely to respond to targeted agents. Nevertheless, EOC is still a highly lethal disease and resistance to many of these new agents is common. The objective of this guideline is to summarize the most relevant strategies to manage EOC, to help the clinician throughout the challenging diagnostic and therapeutic processes and to provide evidence-based recommendations., (© 2024. The Author(s).)

This systematic review examines shared care networks (SCNs) in pediatric oncology as a strategic response to the healthcare challenges in low- and middle-income countries. SCNs integrate specialized hubs with local satellite centers to enhance accessibility and quality of care. Our methodology included a search of PubMed, Embase, Google Scholar, and Scopus, selecting peer-reviewed articles from the last 20 years. We analyzed nine studies, focusing on SCN definitions, models, and outcomes. Findings reveal that SCNs improve clinical outcomes and patient satisfaction, while reducing economic and emotional burdens through standardized protocols and efficient referral systems. Despite the benefits, challenges remain in maintaining consistent care quality and communication across centers. The review underscores the need for further research to quantify benefits, examine long-term outcomes, and refine operational practices to optimize SCNs' effectiveness in pediatric oncology., (© 2024 Wiley Periodicals LLC.)

Background: Advances in precision oncology led to approval of tumour-agnostic molecularly guided treatment options (MGTOs). The minimum requirements for claiming tumour-agnostic potential remain elusive., Methods: The European Society for Medical Oncology (ESMO) Precision Medicine Working Group (PMWG) coordinated a project to optimise tumour-agnostic drug development. International experts examined and summarised the publicly available data used for regulatory assessment of the tumour-agnostic indications approved by the US Food and Drug Administration and/or the European Medicines Agency as of December 2023. Different scenarios of minimum objective response rate (ORR), number of tumour types investigated, and number of evaluable patients per tumour type were assessed for developing a screening tool for tumour-agnostic potential. This tool was tested using the tumour-agnostic indications approved during the first half of 2024. A taxonomy for MGTOs and a framework for tumour-agnostic drug development were conceptualised., Results: Each tumour-agnostic indication had data establishing objective response in at least one out of five patients (ORR ≥ 20%) in two-thirds (≥4) of the investigated tumour types, with at least five evaluable patients in each tumour type. These minimum requirements were met by tested indications and may serve as a screening tool for tumour-agnostic potential, requiring further validation. We propose a conceptual taxonomy classifying MGTOs based on the therapeutic effect obtained by targeting a driver molecular aberration across tumours and its modulation by tumour-specific biology: tumour-agnostic, tumour-modulated, or tumour-restricted. The presence of biology-informed mechanistic rationale, early regulatory advice, and adequate trial design demonstrating signs of biology-driven tumour-agnostic activity, followed by confirmatory evidence, should be the principles for tumour-agnostic drug development., Conclusion: The ESMO Tumour-Agnostic Classifier (ETAC) focuses on the interplay of targeted driver molecular aberration and tumour-specific biology modulating the therapeutic effect of MGTOs. We propose minimum requirements to screen for tumour-agnostic potential (ETAC-S) as part of tumour-agnostic drug development. Definition of ETAC cut-offs is warranted., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Testicular germ cell tumors are the most common tumors in adolescent and young men. They are curable malignancies that should be treated with curative intent, minimizing acute and long-term side effects. Inguinal orchiectomy is the main diagnostic procedure, and is also curative for most localized tumors, while patients with unfavorable risk factors for recurrence, or those who are unable or unwilling to undergo close follow-up, may require adjuvant treatment. Patients with persistent markers after orchiectomy or advanced disease at diagnosis should be staged and classified according to the IGCCCG prognostic classification. BEP is the most recommended chemotherapy, but other schedules such as EP or VIP may be used to avoid bleomycin in some patients. Efforts should be made to avoid unnecessary delays and dose reductions wherever possible. Insufficient marker decline after each cycle is associated with poor prognosis. Management of residual masses after chemotherapy differs between patients with seminoma and non-seminoma tumors. Patients at high risk of relapse, those with refractory tumors, or those who relapse after chemotherapy should be managed by multidisciplinary teams in experienced centers. Salvage treatment for these patients includes conventional-dose chemotherapy (TIP) and/or high-dose chemotherapy, although the best regimen and strategy for each subgroup of patients is not yet well established. In late recurrences, early complete surgical resection should be performed when feasible. Given the high cure rate of TGCT, oncologists should work with patients to prevent and identify potential long-term side effects of the treatment. The above recommendations also apply to extragonadal retroperitoneal and mediastinal tumors., (© 2024. The Author(s).)

Gastric cancer (GC) is the fifth most common cancer worldwide with a varied geographic distribution and an aggressive behavior. In Spain, the incidence is lower and GC represents the tenth most frequent tumor and the seventh cause of cancer mortality. Molecular biology knowledge allowed to better profile patients for a personalized therapeutic approach. In the localized setting, the multidisciplinary team discussion is fundamental for planning the therapeutic approach. Endoscopic resection in very early stage, perioperative chemotherapy in locally advanced tumors, and chemoradiation + surgery + adjuvant immunotherapy for the GEJ are current standards. For the metastatic setting, biomarker profiling including Her2, PD-L1, MSS status is needed. Chemotherapy in combination with checkpoint inhibitors had improved the outcomes for patients with PD-L1 expression. Her2 positive patients should receive antiHer2 therapy added to chemotherapy. We describe the different evidences and recommendations based on the literature., (© 2024. The Author(s).)

Background: The Dutch Committee for the Evaluation of Oncological Drugs evaluates the effectiveness of new oncological treatments. The committee compares survival endpoints to the so-called PASKWIL-2023 criteria for palliative treatments, which define if treatment effects are considered clinically relevant. A positive recommendation depends on whether the median overall survival (OS) is below or above 12 months in the comparator arm. If the former applies, an OS benefit of at least 12 weeks, and a hazard ratio (HR) smaller than 0.7 are required. If the latter applies, an OS or progression free survival (PFS) benefit of at least 16 weeks, and an HR smaller than 0.7 are required. Nonetheless, the median survival time may not be reached and the proportional hazards (PH) assumption, quantified by the HR, is likely violated for immuno-oncology (IO) therapies, deeming these criteria inappropriate., Methods: We conducted a systematic literature review to identify statistical methods used to represent the clinical effectiveness of IO therapies based on trial data. We searched MEDLINE and EMBASE databases from inception to August 31, 2022, limited to English papers. Methodological studies, randomized controlled trials, and discussion papers recognising key issues of survival data analysis of IO therapies were eligible for inclusion., Results: A total of 1,035 unique references were identified. After full paper screening, 17 publications were included in the review. Additionally, 43 papers were identified through 'snowballing'. We conclude that the current PASKWIL-2023 criteria are methodologically incorrect under non-PH. In that case, single summary statistics fail to capture the treatment effect and any measure should be interpreted in combination with the Kaplan-Meier curves. We recommend 'parameter-free' measures, such as the difference in restricted mean survival time, avoiding assumptions on the underlying survival., Conclusions: The HR is commonly used to assess treatment effectiveness, without investigating the validity of the PH assumption. This happens with the application of the PASKWIL-2023 criteria for palliative oncology treatments, which can only be valid under a PH setting. Under non-PH, alternative treatment effect measures are suggested. We propose a step-by-step approach supporting the choice of the most appropriate methods to quantify treatment effectiveness that can be used to redefine the PASKWIL-2023 criteria, or similar criteria in other clinical areas., (© 2024. The Author(s).)

Immuno-oncology has transformed the treatment of cancer, with several immunotherapies becoming the standard treatment across histologies. Despite these advancements, the majority of patients do not experience durable clinical benefits, highlighting the imperative for ongoing advancement in immuno-oncology. Computational immuno-oncology emerges as a forefront discipline that draws on biomedical data science and intersects with oncology, immunology, and clinical research, with the overarching goal to accelerate the development of effective and safe immuno-oncology treatments from the laboratory to the clinic. In this review, we outline 10 critical challenges and opportunities in computational immuno-oncology, emphasizing the importance of robust computational strategies and interdisciplinary collaborations amid the constantly evolving interplay between clinical needs and technological innovation., Competing Interests: Competing interests: RB declares PCT/US15/612657 (Cancer Immunotherapy), PCT/US18/36052 (Microbiome Biomarkers for Anti-PD-1/PD-L1 Responsiveness: Diagnostic, Prognostic and Therapeutic Uses Thereof), PCT/US63/055227 (Methods and Compositions for Treating Autoimmune and Allergic Disorders). AM is an equity holder in Picture Health, Elucid Bioimaging, and Inspirata. Currently, he serves on the advisory board of Picture Health, and SimBioSys. He currently consults for Takeda; He also has sponsored research agreements with AstraZeneca and Bristol Myers-Squibb; his technology has been licensed to Picture Health and Elucid Bioimaging; he is also involved in two different R01 grants with Inspirata; he also serves as a member for the Frederick National Laboratory Advisory Committee.VDJ has performed consulting for VincerX Pharmaceuticals, Providence St. John, Los Angeles; she is a founder of Bioinformatica. JSB-S, EK, DM are full time, paid employees of NCI/NIH. EJF is on the Scientific Advisory Board of Resistance Bio, a consultant for Mestag and Merck, and receives research funding from AbbVie. SG reports current and past research funding from Regeneron Pharmaceuticals, Boehringer Ingelheim, BMS (Celgene), Genentech, EMD Serono, Pfizer, and Takeda. ER is a co-founder of MedAware, Metabomed and Pangea Biomed (divested), and an unpaid member of Pangea Biomed’s and GSK Oncology scientific advisory boards. DVV is a co-founder and chief scientist of Barrier Biosciences and holds equity in the company. NV is on the Consulting/Advisory Boards of Sanofi/Genzyme (2022), Oncocyte (2021), Eli Lilly (2021), Regeneron (2022), Amgen (2023), Xencor (2023), AstraZeneca (2023), Tempus (2023), Pfizer (2024), Summit Therapeutics (2024), OncoHost (2024); she reports travel reimbursement from Regeneron; research grants from Oncocyte (2022–), Circulogene and Mirati, funding from Circulogene, and honoraria from Nebraska Oncology Society, Scienomics Group, Grace, OncLive and OMNI-Oncology. EMVA reports personal fees from Tango Therapeutics, Genome Medical, Genomic Life, Monte Rosa Therapeutics, Manifold Bio, Enara Bio, Riva Therapeutics, Foaley & Hoag, and Serinus Bio, grants and personal fees from Novartis Institute for Biomedical Research, and grants from BMS, Janssen, and Sanofi outside the submitted work; in addition, EMVA has a patent for institutional patents filed on chromatin mutations and immunotherapy response and methods for clinical interpretation pending., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

This study aims to develop explainable AI methods for matching patients with phase 1 oncology clinical trials using Natural Language Processing (NLP) techniques to address challenges in patient recruitment for improved efficiency in drug development. A prototype system based on modern NLP techniques has been developed to match patient records with phase 1 oncology clinical trial protocols. Four criteria are considered for the matching: cancer type, performance status, genetic mutation, and measurable disease. The system outputs a summary matching score along with explanations of the evidence. The outputs of the AI system were evaluated against the ground truth matching results provided by the domain expert on a dataset of twelve synthesized dummy patient records and six clinical trial protocols. The system achieved a precision of 73.68%, sensitivity/recall of 56%, accuracy of 77.78%, and specificity of 89.36%. Further investigation into the misclassified cases indicated that ambiguity of abbreviation and misunderstanding of context are significant contributors to errors. The system found evidence of no matching for all false positive cases. To the best of our knowledge, no system in the public domain currently deploys an explainable AI-based approach to identify optimal patients for phase 1 oncology trials. This initial attempt to develop an AI system for patients and clinical trial matching in the context of phase 1 oncology trials showed promising results that are set to increase efficiency without sacrificing quality in patient-trial matching., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ghosh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Purpose: Despite suffering from the same disease, each patient exhibits a distinct microbiological profile and variable reactivity to prescribed treatments. Most doctors typically use a standardized treatment approach for all patients suffering from a specific disease. Consequently, the challenge lies in the effectiveness of this standardized treatment and in adapting it to each individual patient. Personalized medicine is an emerging field in which doctors use diagnostic tests to identify the most effective medical treatments for each patient. Prognosis, disease monitoring, and treatment planning rely on manual, error-prone methods. Artificial intelligence (AI) uses predictive techniques capable of automating prognostic and monitoring processes, thus reducing the error rate associated with conventional methods., Methods: This paper conducts an analysis of current literature, encompassing the period from January 2015 to 2023, based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)., Results: In assessing 25 pertinent studies concerning predicting neoadjuvant treatment (NAT) response in breast cancer (BC) patients, the studies explored various imaging modalities (Magnetic Resonance Imaging, Ultrasound, etc.), evaluating results based on accuracy, sensitivity, and area under the curve. Additionally, the technologies employed, such as machine learning (ML), deep learning (DL), statistics, and hybrid models, were scrutinized. The presentation of datasets used for predicting complete pathological response (PCR) was also considered., Conclusion: This paper seeks to unveil crucial insights into the application of AI techniques in personalized oncology, particularly in the monitoring and prediction of responses to NAT for BC patients. Finally, the authors suggest avenues for future research into AI-based monitoring systems., (© 2024. The Author(s).)

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches., Competing Interests: Declaration of interests W.L.H. has received grant funding from Akoya Biosciences and conference travel reimbursements from Nanostring Technologies related to spatial oncology studies. W.L.H. is an inventor on U.S. Provisional Patent Application No. 63/069,035 and No. 63/346,670, as well as International Patent Application No. PCT/US2021/047041 and No. PCT/US2023/067607., (Copyright © 2024 Elsevier Inc. All rights reserved.)

In March 2024, 12 European Network of Young Gynae Oncologists- International Journal of Gynaecological Cancer (ENYGO-IJGC) Editorial Fellows conducted 10 interviews with senior opinion leaders on original and controversial topics in the field of gynecologic oncology presented during the 25th European Society of Gynaecological Oncology (ESGO) Congress in Barcelona, Spain. This article provides a summary and overview of the content of these discussions summarizing key points presented at the meeting. These selected interviews were chosen by consensus by the ENYGO-IJGC Editorial Fellows based on novelty and relevance to the field of gynecologic oncology., Competing Interests: Competing interests: None declared., (© IGCS and ESGO 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Real-world research on cancer care in the community should address social determinants of health (SDOH) to advance health equity in cancer diagnosis, treatment, and survivorship. We sought patient and stakeholder perspectives to co-develop research principles to guide researchers when using patient record data to address health equity in their research protocols., Materials and Methods: Key informant interviews with 13 individuals elicited perspectives and insights related to health equity and SDOH when conducting research using data from community-based oncology care. Interviews included a brief overview of a prior scoping review and related questions in the interview guide. Key informants included experts in health equity and SDOH, and patient and community advisory board members. Rapid qualitative analysis was used to identify key themes, patterns, and insights from the interview data. Principles were developed based on the results of the analysis., Results: Three overarching categories for promoting health equity were (1) education; (2) community engagement; and (3) research design and implementation. Education principles highlight the necessity of training in relevant skills to address health equity. Community engagement principles highlight various actions that researchers can take to conduct research inclusive of community concerns regarding health equity. The research design and implementation category provides practical guidelines for researchers in planning, conducting, and disseminating community-based oncology research to address health equity., Conclusion: Our principles guide oncology real-world research protocols to address SDOH in community settings and promote health equity. These principles should be tailored to specific cancer topics and communities., (© The Author(s) 2024. Published by Oxford University Press.)

Leptomeningeal metastases (LM) are increasingly becoming recognized as a treatable, yet generally incurable, complication of advanced cancer. As modern cancer therapeutics have prolonged the lives of patients with metastatic cancer, specifically in patients with parenchymal brain metastases, treatment options, and clinical research protocols for patients with LM from solid tumors have similarly evolved to improve survival within specific populations. Recent expansions in clinical investigation, early diagnosis, and drug development have given rise to new unanswered questions. These include leptomeningeal metastasis biology and preferred animal modeling, epidemiology in the modern cancer population, ensuring validation and accessibility of newer leptomeningeal metastasis diagnostics, best clinical practices with multimodality treatment options, clinical trial design and standardization of response assessments, and avenues worthy of further research. An international group of multi-disciplinary experts in the research and management of LM, supported by the Society for Neuro-Oncology and American Society of Clinical Oncology, were assembled to reach a consensus opinion on these pressing topics and provide a roadmap for future directions. Our hope is that these recommendations will accelerate collaboration and progress in the field of LM and serve as a platform for further discussion and patient advocacy., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Purpose: Rapidly expanding medical literature challenges oncologists seeking targeted cancer therapies. General-purpose large language models (LLMs) lack domain-specific knowledge, limiting their clinical utility. This study introduces the LLM system Medical Evidence Retrieval and Data Integration for Tailored Healthcare (MEREDITH), designed to support treatment recommendations in precision oncology. Built on Google's Gemini Pro LLM, MEREDITH uses retrieval-augmented generation and chain of thought ., Methods: We evaluated MEREDITH on 10 publicly available fictional oncology cases with iterative feedback from a molecular tumor board (MTB) at a major German cancer center. Initially limited to PubMed -indexed literature (draft system), MEREDITH was enhanced to incorporate clinical studies on drug response within the specific tumor type, trial databases, drug approval status, and oncologic guidelines. The MTB provided a benchmark with manually curated treatment recommendations and assessed the clinical relevance of LLM-generated options (qualitative assessment). We measured semantic cosine similarity between LLM suggestions and clinician responses (quantitative assessment)., Results: MEREDITH identified a broader range of treatment options (median 4) compared with MTB experts (median 2). These options included therapies on the basis of preclinical data and combination treatments, expanding the treatment possibilities for consideration by the MTB. This broader approach was achieved by incorporating a curated medical data set that contextualized molecular targetability. Mirroring the approach MTB experts use to evaluate MTB cases improved the LLM's ability to generate relevant suggestions. This is supported by high concordance between LLM suggestions and expert recommendations (94.7% for the enhanced system) and a significant increase in semantic similarity from the draft to the enhanced system (from 0.71 to 0.76, P = .01)., Conclusion: Expert feedback and domain-specific data augment LLM performance. Future research should investigate responsible LLM integration into real-world clinical workflows.

Purpose: Therapeutic compliance, or adherence, is critical in oncology because of the complexity and duration of cancer treatment regimens. Nonadherence can lead to suboptimal therapeutic outcomes, increased disease progression, higher mortality rates, and elevated health care costs. Traditional methods to enhance compliance, such as patient education and regular follow-ups, have shown limited success., Materials and Methods: This review examines the potential of digital health technologies to improve adherence in oncology. Various studies and trials are analyzed to assess the effectiveness of these technologies in supporting patients with cancer., Results: mHealth applications have been shown to improve medication adherence through features like medication reminders and symptom tracking. Telemedicine facilitates continuous care and reduces the need for travel, significantly improving adherence and patient satisfaction. Patient-reported outcome measures enhance clinical decision making and personalized treatment plans by incorporating patient feedback. Electronic medical records and patient portals improve compliance by providing easy access to medical information and fostering better patient-provider communication. Connected pillboxes aid in consistent medication intake and reduce dispensing errors., Conclusion: Digital health technologies offer significant benefits in oncology by enhancing patient engagement, improving adherence to treatment protocols, and enabling comprehensive cancer care management. However, challenges such as the digital divide, data privacy concerns, and the need for tailored interventions must be addressed. Future research should focus on evaluating the effectiveness of digital interventions and developing personalized digital health tools to maximize therapeutic compliance.

Background: Children and young people with cancer face barriers when engaging with exercise, such as treatment-related side effects, psychosocial burdens and lack of individualised provisions. Digital health tools, such as smartphone applications, have emerged as a promising driver to support healthcare provisions in exercise prescription among patients. It is vital to explore how such technologies can be developed more effectively in order to strengthen the evidence supporting their use and for more appropriate implementation within healthcare. This study aims to explore user experiences, preferences and suggested improvements from healthy children and young people aged 9-21 years. Methods: An augmented reality (AR) application was specifically developed for children and young people aged 9-21 years undergoing cancer treatment and a protocol for a pilot study was designed. The target sample of this pilot study is 90 healthy children and young people aged 9-21 years. Practical 30-min workshops will be conducted encouraging participants to engage with the smartphone app. Focus groups will explore participant experiences, preferences, and suggested improvements. Data will be analysed deductively with apriori themes derived from the semi-structured interviews. Discussion: Obtaining user experiences, preferences and suggested improvements is especially important for the development of novel apps, such as those prescribing exercise and using algorithms and augmented reality software. Results from this study will directly influence the development of an augmented reality application, which will also be applied within a long-term trial in paediatric oncology., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Introduction: Clinical decision-making in oncology is a complex process, with the primary goal of identifying the most effective treatment tailored to individual cancer patients. Many factors influence the treatment decision: disease- and patient-specific criteria, the increasingly complex treatment landscape, market authorization and drug availability, financial aspects, and personal treatment expertise. In the domain of genitourinary cancers, particularly prostate cancer, decision-making is challenging. Despite the prevalence of this malignancy, there are few in-depth explorations of these factors within real-world scenarios. Understanding and refining this intricate decision-making process is essential for future successful clinical decisions and the integration of computerized decision support into clinicians' workflows., Aim: The objective of this study is to improve the current knowledge base and evidence of the factors that influence treatment decision-making for patients with genitourinary cancers., Methods: Assessment of how routine treatment decisions are made for genitourinary cancers was performed by a mixed-methods study, encompassing field observations and focus group discussions., Results: In total, we identified 59 factors that influence clinical decision-making in oncology, specifically for genitourinary and prostate cancer. Of these, 23 criteria can be classified as decision-maker-related criteria encompassing personal, cognitive, and emotional attributes and factors of both, healthcare professionals and patients. Moreover, 20 decision-specific criteria have been identified that refer to clinical and disease-related factors, followed by 16 contextual decision factors that describe the relevant criteria introduced by the specific circumstances and environment in which the treatment decision is made., Conclusion: By presenting an exhaustive set of decision factors and providing specific examples for genitourinary cancers, this observational study establishes a possible framework for a better understanding of decision-making. Moreover, we specify and expand the set of decision factors, while emphasizing the importance of cognitive, emotional, and human factors, as well as the quality and accessibility of decision-relevant information., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

The field of neuro-oncology has seen significant advances that have allowed the expansion of the therapeutic armamentarium. Nevertheless, overall outcomes have not improved significantly particularly for high-grade tumors. The relative rarity of these pathologies in the pediatric population limits the capacity to design large-scale, multicenter, randomized clinical trials. The emergence of precision medicine as a direct result of better, more widespread genetic and molecular testing affords clinicians the possibility of envisioning new clinical trial paradigms. Each patient becomes their own singular trial receiving the most tailored treatment at every stage of their disease while serving as their own controls. Although limitations still exist for the widespread adoption of these technologies and incorporation into standard clinical care, the prospect of being able to offer directed therapies and monitor disease progression based on single-patient testing represents a much-needed paradigm shift in neuro-oncology., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The NCCN Guidelines for Ovarian Cancer/Fallopian Tube Cancer/Primary Peritoneal Cancer provide multidisciplinary diagnostic workup, staging, and treatment recommendations for this disease. These NCCN Guidelines Insights detail how the evolution of the use of PARP inhibitors as maintenance and single-agent regimens for the treatment of ovarian cancer informed panel recommendations in the guidelines.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for acute lymphoblastic leukemia (ALL) provide recommendations for management of ALL, with a focus on the classification of ALL subtypes based on immunophenotype and cytogenetic/molecular markers; risk assessment and stratification for risk-adapted therapy; treatment strategies for Philadelphia chromosome (Ph)-positive and Ph-negative ALL for both adolescent and young adult and adult patients; and supportive care considerations. This selection from the NCCN Guidelines for ALL focuses on treatment recommendations for adults with newly diagnosed Ph-negative ALL based on current evidence.

Background: Extravasation (EV), or the leakage of anticancer drugs into perivascular and subcutaneous tissues during intravenous administration, can cause serious conditions that may require surgical intervention. Therefore, updated guidelines for EV based on systematic review are needed. Additionally, classifications for anticancer drugs that cause EV are not standardized across the current guidelines, and some novel drugs have not been classified. Therefore, this study aimed to formulate guidelines using evidence-based information for shared decision making on prevention, early detection, treatment, and care for EV in Japan and provide additional classification for tissue injury based on systematic review., Materials and Methods: The members of the Japanese Society of Cancer Nursing (JSCN), Japanese Society of Medical Oncology (JSMO), and Japanese Society of Pharmaceutical Oncology (JASPO) were surveyed about significant clinical challenges related to EV, and 17 clinical questions (CQs) were formulated. PubMed and ICHUSHI Web were searched using the Patient, Intervention, Comparison, and Outcomes terms listed in each CQ as key words. For the classification of new drugs, articles published through February 2021 were selected using the search terms 'extravasation', 'injection-site reaction', 'adverse events', and the names of individual drugs as key words., Results: Recommendations based on the results of randomized controlled trials (RCTs) were made with regard to the selection of central venous (CV) devices (CQ2, CQ3a, CQ3b, and CQ3c), regular replacement of peripheral venous catheters (CQ5), and use of fosaprepitant (CQ7). These CQs are novel and were not mentioned in previous guidelines. Warm compression monotherapy (CQ10b) and local injection of steroids (CQ12) are discouraged for the management of EV. Ten new drugs were classified for EV tissue injury., Conclusions: This study provides updated guidelines for the prevention and treatment of EV, which can be used to help health care providers and patients and their families practice better EV management., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: The primary results of phase III oncology trials may be challenging to interpret, given that results are generally based on P value thresholds. The probability of whether a treatment is beneficial, although more intuitive, is not usually provided. Here, we developed and released a user-friendly tool that calculates the probability of treatment benefit using trial summary statistics., Methods: We curated 415 phase III randomized trials enrolling 338,600 patients published between 2004 and 2020. A phase III prior probability distribution for the treatment effect was developed on the basis of a three-component zero-mean mixture distribution of the observed z-scores. Using this prior, we computed the probability of clinically meaningful benefit (hazard ratio [HR] <0.8). The distribution of signal-to-noise ratios and power of phase III oncology trials were compared with that of 23,551 randomized trials from the Cochrane Database., Results: The signal-to-noise ratios of phase III oncology trials tended to be much larger than randomized trials from the Cochrane Database. Still, the median power of phase III oncology trials was only 49% (IQR, 14%-95%), and the power was <80% in 65% of trials. Using the phase III oncology-specific prior, only 53% of trials claiming superiority (114 of 216) had a ≥90% probability of clinically meaningful benefits. Conversely, the probability that the experimental arm was superior to the control arm (HR <1) exceeded 90% in 17% of trials interpreted as having no benefit (34 of 199)., Conclusion: By enabling computation of contextual probabilities for the treatment effect from summary statistics, our robust, highly practical tool, now posted on a user-friendly webpage, can aid the wider oncology community in the interpretation of phase III trials.

With more treatment options in oncology lead to better outcomes and more favorable side effect profiles, patients are living longer-with higher quality of life-than ever, with a growing survivor population. As the needs of patients and providers evolve, and technology advances, cancer care is subject to change. This review explores the myriad of changes in the current oncology landscape with a focus on the patient perspective and patient-centered care., (Copyright © 2024. Published by Elsevier Inc.)

Competing Interests: Disclosures David E. Fisher reports grants from the NIH (R01AR072304, R01AR043369, and P01CA163222); the Department of Defense (DoD W81XWH2220052 and DoD W81XWH2110981); and the Dr Miriam and Sheldon G. Adelson Medical Research Foundation; and a financial interest in Soltego, a company developing salt-inducible kinase inhibitors for topical skin-darkening treatments that might be used for a broad set of human applications. David E. Fisher also serves as a consultant for Coherent Medicines, Pierre Fabre, Tasca, Torqur, and Biocoz Inc. The interests of David E. Fisher were reviewed and are managed by Massachusetts General Hospital and Partners HealthCare in accordance with their conflict-of-interest policies. The author gratefully acknowledges the Lancer Family for support of the Lancer Professorship at Harvard Medical School.

Novel clinical trial designs are conducted in the precision medicine era. This study aimed to evaluate biomarker-driven, adaptive phase II trials in precision oncology, focusing on infrastructure, efficacy, and safety. We systematically reviewed and analyzed the target studies. EMBASE and PubMed searches from 2015 to 2023 generated 29 eligible trials. Data extraction included infrastructure, biomarker screening methodologies, efficacy, and safety profiles. Government agencies, cancer hospitals, and academic societies with accumulated experiences led investigator-initiated precision oncology clinical trials (IIPOCTs), which later guided sponsor-initiated precision oncology clinical trials (SIPOCTs). Most SIPOCTs were international studies with basket design. IIPOCTs primarily used the central laboratory for biomarker screening, but SIPOCTs used both central and local laboratories. Most of the studies adapted next-generation sequencing and/or immunohistochemistry for biomarker screening. Fifteen studies included an independent central review committee for outcome investigation. Efficacy assessments predominantly featured objective response rate as the primary endpoint, with varying results. Nine eligible studies contributed to the United States Food and Drug Administration's marketing authorization. Safety monitoring was rigorous, but reporting formats lacked uniformity. Health-related quality of life and patient-reported outcomes were described in some protocols but rarely reported. Our results reveal that precision oncology trials with adaptive design rapidly and efficiently evaluate anticancer drugs' efficacy and safety, particularly in specified biomarker-driven cohorts. The evolution from IIPOCT to SIPOCT has facilitated fast regulatory approval, providing valuable insights into the precision oncology landscape.

With the continuous development of genetics in healthcare, there has been a significant contribution to the development of precision medicine, which is ultimately aimed at improving the care of patients. Generally, drug treatments used in Oncology are characterized by a narrow therapeutic range and by their potential toxicity. Knowledge of pharmacogenomics and pharmacogenetics can be very useful in the area of Oncology, as they constitute additional tools that can help to individualize patients' treatment. This work includes a description of some genes that have been revealed to be useful in the field of Oncology, as they play a role in drug prescription and in the prediction of treatment response., (© 2024 British Pharmacological Society.)

Sleep concerns are common during pediatric cancer treatment and can last into survivorship. The current systematic review sought to identify intervention studies that addressed sleep as a primary or secondary outcome during pediatric cancer treatment up to 5 years after completing treatment. Quality assessment was rated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. The review identified 16 studies with a total of 943 participants that tested a wide range of interventions including psycho-educational, stress management techniques, medications, and physical activity. Most studies included tested interventions in small samples. None of the included studies had a high risk of bias for all domains, but all included studies had a high risk of bias for at least two risk domains. Several feasible pilot studies were identified that warrant further research to test efficacy. Implications for future research and clinical practice to manage sleep concerns are discussed., (© 2024 The Author(s). Pediatric Blood & Cancer published by Wiley Periodicals LLC.)

Objectives: Pancreatic ductal adenocarcinoma (PDAC) is the most pervasive sort of pancreatic malignant growth. Due to the lack of early symptoms and effective methods for early detection and screening, the majority of patients (80% to 85%) are diagnosed with advanced metastatic or locally advanced disease, resulting in a low 5-year survival rate of 12%. The case study represents a comprehensive investigation into the intricate landscape of pancreatic cancer diagnosis within the Korean population., Methods: Grounded in epidemiological bits of knowledge, the review plans to disentangle the particular examples, commonness, and segment attributes of PDAC in Korea. By scrutinizing current diagnostic modalities, including conventional imaging techniques, molecular markers, and emerging technologies, the research seeks to evaluate the strengths and limitations of existing approaches within the Korean clinical context. Central to the study is an exploration of the collaborative initiatives spearheaded by the Association of Clinical Oncology in Korea in the domain of PDAC early detection. Analysing research projects, clinical trials, and interdisciplinary collaborations, the case study sheds light on the association's pivotal role in driving innovation and progress in oncology., Results: The goal is to offer a detailed analysis of how the association helps in furthering knowledge and enhancing results in the management of PDAC. The case study delves into the implications of early PDAC detection for patient outcomes, emphasizing the significance of timely interventions and tailored treatment strategies. By outlining the potential benefits and challenges associated with early diagnosis, the study aims to inform health care policies, shape clinical guidelines, and guide future research priorities., Conclusion: Through a holistic approach, the case study endeavours to offer important experiences into the multifaceted landscape of PDAC early detection within the Korean health care system, contributing to the broader discourse on effective oncological practices and patient care., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: To update the ASCO-Oncology Nursing Society (ONS) standards for antineoplastic therapy administration safety in adult and pediatric oncology and highlight current standards for antineoplastic therapy for adult and pediatric populations with various routes of administration and location., Methods: ASCO and ONS convened a multidisciplinary Expert Panel with representation of multiple organizations to conduct literature reviews and add to the standards as needed. The evidence base was combined with the opinion of the ASCO-ONS Expert Panel to develop antineoplastic safety standards and guidance. Public comments were solicited and considered in preparation of the final manuscript., Results: The standards presented here include clarification and expansion of existing standards to include home administration and other changes in processes of ordering, preparing, and administering antineoplastic therapy; the advent of immune effector cellular therapy; the importance of social determinants of health; fertility preservation; and pregnancy avoidance. In addition, the standards have added a fourth verification., Standards: Standards are provided for which health care organizations and those involved in all aspects of patient care can safely deliver antineoplastic therapy, increase the quality of care, and reduce medical errors.Additional information is available at www.asco.org/standards and www.ons.org/onf.

Objectives: Some therapeutic strategy questions in oncology could be answered with studies using observational data. Target trial emulation is the application of design principles from randomized controlled trials (RCTs) to the analysis of observational data, to reduce design-induced biases. Our objective was to determine which type of study physicians would preferably plan to answer a comparative effectiveness question lacking evidence in oncology., Methods: We launched an online survey among physicians specialized in oncology. We constructed a vignette-based inquiry where vignettes described study scenarios which could be conducted to answer the predefined question. We designed six vignettes described by study design (RCT or observational study with a trial emulation framework), main study characteristics, probability of the study succeeding and anticipated delay before results availability. Participants randomly assessed five pair-wise comparisons of the vignettes and were asked which study they would preferably plan by using a Likert scale ranging from -5 to 5. The main outcome was the evaluation of clinicians' preferences for each pairwise comparison. Mean and median preference scores were calculated., Results: Two hundred thirteen participants, specialized in many tumor types, assessed at least one comparison with 82% reporting France as their country of affiliation. The interquartile range was -4 to 4 across pairwise comparisons. The median preference score was in disfavor of the monocentric RCT for the five comparisons where it appeared. The median preference score was strongly in favor of the multicentric national emulated trial when compared to the monocentric emulated trial 4 [IQR 2.5-4]. The mean preference score was the highest for the large European observational study 1.14 (SD 3.33), while the mean preference score was the lowest for the monocentric RCT -1.86 (SD 2.93)., Conclusion: No study design was strongly preferred, but the monocentric RCT was the least favored study in pair-wise comparisons. The planification of the new research is a compromise between scientific soundness, feasibility, cost, and time before obtaining results. We need to have the right answers to the right questions at the right time., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The continuous generation of multi-omics and phenotype data is propelling advancements in precision oncology. UCSCXenaShiny was developed as an interactive tool for exploring thousands of cancer datasets available on UCSC Xena. However, its capacity for comprehensive and personalized pan-cancer data analysis is being challenged by the growing demands. Here, we introduce UCSCXenaShiny v2, a milestone update through a variety of improvements. Firstly, by integrating multidimensional data and implementing adaptable sample settings, we create a suite of robust TPC (TCGA, PCAWG, CCLE) analysis pipelines. These pipelines empower users to conduct in-depth analyses of correlation, comparison, and survival in three modes: Individual, Pan-cancer and Batch screen. Additionally, the tool includes download interfaces that enable users to access diverse data and outcomes, several features also facilitate the joint analysis of drug sensitivity and multi-omics of cancer cell lines. UCSCXenaShiny v2 is an open-source R package and a web application, freely accessible at https://github.com/openbiox/UCSCXenaShiny ., (© 2024. The Author(s).)

Multi-omics data play a crucial role in precision medicine, mainly to understand the diverse biological interaction between different omics. Machine learning approaches have been extensively employed in this context over the years. This review aims to comprehensively summarize and categorize these advancements, focusing on the integration of multi-omics data, which includes genomics, transcriptomics, proteomics and metabolomics, alongside clinical data. We discuss various machine learning techniques and computational methodologies used for integrating distinct omics datasets and provide valuable insights into their application. The review emphasizes both the challenges and opportunities present in multi-omics data integration, precision medicine and patient stratification, offering practical recommendations for method selection in various scenarios. Recent advances in deep learning and network-based approaches are also explored, highlighting their potential to harmonize diverse biological information layers. Additionally, we present a roadmap for the integration of multi-omics data in precision oncology, outlining the advantages, challenges and implementation difficulties. Hence this review offers a thorough overview of current literature, providing researchers with insights into machine learning techniques for patient stratification, particularly in precision oncology. Contact:  anirban@klyuniv.ac.in., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Combination of immunotherapy with radiotherapy is under active investigation. The PACIFIC trial firmly established the treatment paradigm of consolidation immunotherapy following definitive chemoradiotherapy, inspiring a series of similar or exploratory combination regimens. This summary highlighted six reports updated in the 2024 ASCO Annual Meeting., (© 2024. The Author(s).)

Background: The Multidisciplinary Tumor Board (MTB) is a collaborative platform involving specialists in oncology, surgery, radiology, pathology, and radiotherapy, and aims to optimize diagnostics and treatments. Despite MTB's widespread benefits, limited literature addresses its application in pediatric neuro-oncology. After a literature revision on pediatric neuro-oncology MTB, our study describes our institute's pediatric neuro-oncology MTB, focuses on evaluating its impact and the neuroradiologist's role in patient-centric approaches, considering recent genetic insights into pediatric brain tumors., Materials and Methods: Literature Review concerning pediatric neuro-oncology MTB from January 2002 to June 2024., Clinical Data: retrospective study of all patient files presented in the pediatric neuro-oncology MTB (pnMTB) between 2019 and 2022. Statistical analysis was mainly carried out by directly comparing the absolute or relative values of the respective parameters examined; qualitative variables compared mainly with the chi-square test, quantitative variables mainly with the t-test., Results: Literature Review: 7 papers encompass a multidisciplinary approach for the pediatric CNS tumors., Clinical Data: A total of 236 discussions were analyzed representing 107 patients. Median age was 14,3 years (range: 6 months - 17 years). The requests for case evaluations primarily came from the pediatric oncologists (83%) and neurosurgeons (14.8%), and they were mainly addressed to the neuroradiologists (70.3%). Proposals during pnMTB mainly involved imaging follow-up (47.8%) and management with chemotherapy (34.7%). Changes in patient treatment (CPT) occurred in 115 cases, and pediatric neuroradiologist intervention contributed to 72.4% of these changes., Conclusion: Thanks to their multidisciplinarity, high number of cases discussed, and usual respect for their proposals, the pnMTB has made it possible to improve the coordination among specialties involved in patient management, to apply the recent protocols, and to exchange knowledge among teams managing pediatric CNS tumors., (© 2024. The Author(s).)

The characterization of somatic genomic variation associated with the biology of tumors is fundamental for cancer research and personalized medicine, as it guides the reliability and impact of cancer studies and genomic-based decisions in clinical oncology. However, the quality and scope of tumor genome analysis across cancer research centers and hospitals are currently highly heterogeneous, limiting the consistency of tumor diagnoses across hospitals and the possibilities of data sharing and data integration across studies. With the aim of providing users with actionable and personalized recommendations for the overall enhancement and harmonization of somatic variant identification across research and clinical environments, we have developed ONCOLINER. Using specifically designed mosaic and tumorized genomes for the analysis of recall and precision across somatic SNVs, insertions or deletions (indels), and structural variants (SVs), we demonstrate that ONCOLINER is capable of improving and harmonizing genome analysis across three state-of-the-art variant discovery pipelines in genomic oncology., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Precision oncology endeavors to tailor therapies based on individual patient and tumor characteristics. This rapidly evolving field has transformed cancer treatment across all age groups. In this commentary, we review the application of precision oncology across different age groups, specifically in children, adolescents, and young adults, and emphasize that precision medicine is age and tissue agnostic., Competing Interests: Declaration of interests V.S. reports grants/contracts from AbbVie, Inc., Agenus, Amgen, Bayer HealthCare Pharmaceuticals Inc., Blueprint Medicines, Berghealth, Boston Biomedical, Boston Pharmaceuticals, Celgene Corporation, Dragonfly Therapeutics, Exelixis Inc., F. Hoffmann-La Roche AG, FUJIFILM Medical Systems USA, Inc., Genentech USA, Inc., GlaxoSmithKline, LLC, Idera Pharma, Incyte Corporation, Inhibrx, LOXO Oncology, MedImmune, LLC, Multivir, Nanocarrier, the National Comprehensive Cancer Network, the National Cancer Institute, Novartis Pharma, OncLive, Oncusp, PERS, Pfizer, PharmaMar, Relay Therapeutics, and Takeda Oncology; personal/consulting fees from AbbVie, Bayer HealthCare Pharmaceuticals Inc., F. Hoffmann-La Roche AG, Illumina, Incyte Corporation, Jazz Pharmaceuticals Inc., LabCorp (aka Lab Corporation), Regeneron Pharmaceuticals, Inc., and Relay Therapeutics; support for other professional activities from Aadi Biosciences, Clinical Care Communications, Illumina, Jazz Pharmaceuticals Inc., Med Learning Group, Medscape, and Pheon Therapeutics; and travel support from the American Society of Clinical Oncology, the European Society of Medical Oncology, Helsinn Healthcare SA, and Incyte Corporation outside the submitted work. R.K. has received research funding from Biological Dynamics, Boehringer, Caris, Datar Genomics, Ingelheim, Debiopharm, Foundation Medicine, Genentech, Grifols, Guardant, Incyte, Konica Minolta, Medimmune, Merck Serono, Omniseq, Pfizer, Sequenom, Takeda, and TopAlliance; as well as consultant and/or speaker fees and/or advisory board for Actuate Therapeutics, AstraZeneca, Bicara Therapeutics, Biological Dynamics, Caris, Daiichi Sankyo, Inc., EISAI, EOM Pharmaceuticals, Iylon, Merck, NeoGenomics, Neomed, Pfizer, Prosperdtx, Roche, TD2/Volastra, Turning Point Therapeutics, X-Biotech; has an equity interest in CureMatch Inc., CureMetrix, and IDbyDNA; serves on the Board of CureMatch and CureMetrix; and is a co-founder of CureMatch., (Copyright © 2024 Elsevier Inc. All rights reserved.)