Nature Cancer, Год журнала: 2025, Номер unknown
Опубликована: Март 7, 2025
Язык: Английский
Algorithms, Год журнала: 2024, Номер 17(6), С. 254 - 254
Опубликована: Июнь 10, 2024
The introduction of machine learning in digital pathology has deeply impacted the field, especially with advent whole slide image (WSI) analysis. In this review, we tried to elucidate role algorithms diagnostic precision, efficiency, and reproducibility results. First, discuss some most used tools, including QuPath, HistoQC, HistomicsTK, provide an updated overview approaches their application pathology. Later, report how these tools may simplify automation WSI analyses, also reducing manual workload inter-observer variability. A novel aspect review is its focus on open-source presented a way that help adoption process for pathologists. Furthermore, highlight major benefits technologies, aim making practical guide clinicians seeking implement learning-based solutions specific workflows. Moreover, emphasizes crucial limitations related data quality interpretability models, giving insight into future directions research. Overall, work tries bridge gap between more recent technological progress computer science traditional clinical practice, supporting broader, yet smooth,
Язык: Английский
Процитировано
5
npj Precision Oncology, Год журнала: 2025, Номер 9(1)
Опубликована: Март 11, 2025
Abstract There are no current stratified medicine options for STK11-deficient NSCLC. STK11 loss mediates mTORC activation, GLUT1 up-regulation and increased glycolysis. This metabolic reprogramming might represent a therapeutic vulnerability targetable with mTORC1/2 inhibition. In arm B2 of the National Lung Matrix Trial 54 patients NSCLC received vistusertib, which 49 were (30 KRAS mutation (B2D), 19 without (B2S)). Objective response (OR) durable clinical benefit (DCB) rates 95% credible intervals (CrI) estimated from posterior probability distributions generated using Bayesian beta-binomial conjugate analysis. B2D, 2 per-protocol obtained OR (estimated true rate (95%CrI) 9.8% (2.4–24.3). Estimates DCB (95%CrI): B2D 24.4% (11.1–42.3), B2S 14.6% (3.6–34.7). Overall, vistusertib cannot be recommended in this context. Longitudinal ctDNA analysis demonstrates enrichment SMARCA4 mutations post-treatment. vitro studies show adaptive resistance to inhibition via AKT reactivation. (NCT02664935, ISRCTN38344105, EudraCT 2014-000814-73, 10 June 2015)
Язык: Английский
Процитировано
0
Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, Год журнала: 2025, Номер 1880(3), С. 189298 - 189298
Опубликована: Март 13, 2025
Язык: Английский
Процитировано
0
Annual Review of Cancer Biology, Год журнала: 2025, Номер 9(1), С. 285 - 305
Опубликована: Апрель 11, 2025
Preclinical models have played a pivotal role in the development of immunotherapies that now become standard treatment option for numerous cancer types. This review examines strengths and weaknesses various mouse advancing our understanding immunology responses to immunotherapy. Furthermore, we explore how emerging technologies such as humanized models, integration CRISPR/Cas9 systems, advanced vitro systems are helping us deepen insights into cancer–immune interactions dictate response therapies. Integrating these diverse with cutting-edge genetic genomic tools will be crucial tackle challenges immunotherapy resistance design next generation drugs.
Язык: Английский
Процитировано
0
European Radiology, Год журнала: 2025, Номер unknown
Опубликована: Апрель 11, 2025
Язык: Английский
Процитировано
0
Chinese Medical Journal, Год журнала: 2025, Номер unknown
Опубликована: Апрель 10, 2025
Процитировано
0
Translational Oncology, Год журнала: 2024, Номер 45, С. 101968 - 101968
Опубликована: Май 7, 2024
Killer cell lectin like receptor G1 (KLRG1) is identified as a co-inhibitory for NK cells and antigen-experienced T cells. The role of KLRG1 in immune regulation patients with non-small lung cancer (NSCLC) remains poorly understood.
Язык: Английский
Процитировано
4
Briefings in Bioinformatics, Год журнала: 2024, Номер 25(5)
Опубликована: Июль 25, 2024
Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of data with unparalleled spatial resolution. This type collection, namely, proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms evolved manage the increasing dimensionality proteomics inherent this progress. Numerous imaging-based frameworks, such as pathology, been proposed for research and clinical applications. However, development these fields demands diverse domain expertise, creating barriers their integration further application. review seeks bridge divide by presenting a comprehensive guideline. We consolidate prevailing methods outline roadmap from image processing data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives field moves toward interfacing other quantitative domains, holding significant promise precision care immuno-oncology.
Язык: Английский
Процитировано
4
Personalized Medicine, Год журнала: 2025, Номер unknown, С. 1 - 14
Опубликована: Янв. 7, 2025
Efforts have been made to leverage technology accurately identify tumor characteristics and predict how each cancer patient may respond medications. This involves collecting data from various sources such as genomic data, histological information, functional drug profiling, metabolism using techniques like polymerase chain reaction, sanger sequencing, next-generation fluorescence in situ hybridization, immunohistochemistry staining, patient-derived xenograft models, organoid therapeutic monitoring. The utilization of diverse detection technologies clinical practice has "individualized treatment" possible, but the desired level accuracy not fully attained yet. Here, we briefly summarize conventional state-of-the-art contributing individualized medication settings, aiming explore therapy options enhancing outcomes.
Язык: Английский
Процитировано
0
Clinical Cancer Research, Год журнала: 2025, Номер unknown
Опубликована: Янв. 13, 2025
Abstract Background: KRAS inhibitors are revolutionizing the treatment of NSCLC, but clinico-genomic determinants efficacy warrant continued exploration. Methods: Patients with advanced KRASG12C-mutant NSCLC treated adagrasib (KRYSTAL-1-NCT03785249) were included in analysis. Pre-treatment NGS data collected per protocol. HTG EdgeSeq Transcriptome Panel was used for gene expression profiling. Clinical endpoints objective response, progression-free and overall survival. cell lines xenograft models sensitivity analyses combination drug screens. Results: KEAP1MUT STK11MUT associated shorter survival to (KEAP1: PFS 4.1m vs 9.9m, HR 2.7, p<0.01; OS 5.4m 19.0m, 3.6, STK11: 4.2m 11.0m, 2.2, 9.8m NR, 2.6, p<0.01). KEAP1WT/STK11WT status identified adagrasib-treated patients significantly longer (16.9m) (NR). Pre-clinical further validate association between KEAP1 loss-of-function resistance. Adagrasib mTOR inhibitor combinations produced higher harboring STK11 co-mutations. NRF2HIGH signaling (PFS: 8.4m, 2.0, p=0.02; OS: 6.5m 2.8, p<0.01) even KEAP1WTNSCLC patients. KEAP1WT/STK11WT/NRF2LOW - 32% (PFS 12.0m 4.2m, 0.2, NR 8.0m, 0.1, Conclusions: KEAP1, NRF2 define markedly distinct outcomes adagrasib. These results support use genomic features – mutational non-mutational selection
Язык: Английский
Процитировано
0