Chemotherapy- and immunotherapy-induced peripheral neuropathies (PNP) are common and often dose-limiting side effects of cancer treatment. Patients often experience pain, numbness, and tingling in their extremities. Pharmacological options such as duloxetine, which is recommended for chemotherapy-induced PNP (CIPN), offer limited relief [1]. Consequently, neuromuscular training incorporating sensorimotor elements is a promising non-pharmacological alternative. However, its effect on symptoms in the upper extremities remains unexplored. This study investigates the feasibility of combined sensorimotor and vibration training for the upper extremities before and during cancer treatment.

The VISCIPH A study is a two-arm, prospective, randomized controlled proof-of-principle trial. Within the overarching VISCIPH A/B research framework, this is an independently designed sub-study. The primary outcome was feasibility; secondary outcomes included patient-reported outcome measures (PROMs). Participants were randomized to either a sensorimotor and vibration training group (PNPEX) or a moderate resistance exercise group (MREX). Both interventions were supervised and performed twice weekly over 12 weeks. Fine motor skills, depth sensitivity, and temperature sensation were assessed pre- and post-intervention. PROMs (EORTC-QLQ-C30, FACT/GOG-Ntx, NRS (pain)) were collected at baseline, week 4, week 8, and week 12.

Of 50 enrolled cancer patients, 40 completed the study (32.5% male; mean age = 50.8 years). A total of 874 out of 960 planned sessions (91%) were completed. The dropout rate was 20%, with high patient adherence (98%) and successful implementation of the extensive test battery, exhibit feasibility of the study (proof of principle). Thirteen participants reported no numbness or tingling in the hands, and 18 reported no discomfort over the 12-week period. Both groups showed significant improvements in global health status (EORTC-QLQ-C30) at T3 (p = 0.001). However, the MREX group showed significant deterioration in depth sensitivity at 2 of 4 bone points after 12 weeks (I CP: p = 0.01; III CP: p = 0.046), whereas PNPEX outcomes remained stable.

While prior research has mainly focused on lower extremities, this study demonstrates the feasibility and potential protective effects of a combined vibration and sensorimotor training protocol for the upper limbs during neurotoxic cancer therapy. Given the limited efficacy of current pharmacological approaches, further research is warranted to explore the therapeutic potential of structured exercise interventions in the management of PNP.

DNAJB4 plays a crucial role in tumor suppression and proteostasis across various cancers. However, a comprehensive pan-cancer analysis of DNAJB4 remains lacking. We performed an extensive pan-cancer analysis to assess DNAJB4 expression and its clinical value. Analyses included competing endogenous RNA, protein-protein interaction networks, tumor purity, genomic profiling, immune microenvironment evaluation, and drug sensitivity. Gene set enrichment analysis was used to identify key pathways associated with DNAJB4. Additionally, DNAJB4 expression was evaluated in a cohort of 370 kidney neoplasm patients using immunohistochemistry to explore its clinical significance. DNAJB4 expression was significantly lower in tumor tissues compared to normal tissues in pan-cancer analysis. Reduced expression of DNAJB4 correlated with clinical outcomes, tumor purity, genomic alterations, immune microenvironment features, and drug sensitivity. In kidney neoplasm patients, DNAJB4 expression was significantly lower in tumor tissues (P value < 0.001) and was associated with poor prognosis, including progression-free survival (P value < 0.01) and overall survival (P value < 0.05). Higher DNAJB4 levels were linked to advanced tumor stages (P value < 0.001 for T2b-T4, P value < 0.01 for stages 3-4). DNAJB4 serves as a multifunctional biomarker in pan-cancer, particularly in kidney neoplasm, and is closely related to tumorigenesis, staging, and prognosis. Targeting DNAJB4 could provide new therapeutic avenues for cancer treatment.

Meningioma resection constitutes a substantial portion of neurosurgical practice, with a variety of patient-factors playing a role in outcomes. This study aims to assess the role of frailty in elderly patients undergoing resection of primary intracranial meningiomas.

This is a retrospective study of patients undergoing resection for primary intracranial meningiomas at our institution between 2004-2024. Patients were ≥ 65 years, and were required to have ≥ 1 year of follow-up. The modified frailty index (mFI) was used to identify degree of frailty, categorising patients into the non-frail (NF, mFI = 0), pre-frail (PF, mFI = 1/2), and frail (F, mFI ≥ 3) groups. The Shapiro-Wilk test, paired T-test, and ANOVA were used to identify statistical significance. Propensity-score matching (PSM) was performed based on a multinomial logistic regression model and 1:1 nearest-neighbour matching algorithm. Kaplan-Meier analysis using Log-rank tests were used to compare overall (OS) and progression-free (PFS) survival.

362 patients were included, with 69, 207, and 86 patients in the NF, PF, and F groups respectively. Preoperatively, the F group was found to have a significantly higher age vs. the NF group (76.17 vs. 71.57, p = 0.0002), alongside reporting a significantly lower median KPS vs. the PF and NF groups (70 vs. 80, p < 0.0001) respectively. The PF group was found to have a significantly lower duration of surgery (309 min, p = 0.0048) vs. the F group, which reported significantly higher mean length-of-stay (17.68 days, p < 0.0001), higher frequencies of medical complications (11.6%, p = 0.0317), and lower postoperative KPS (70, p < 0.0001) vs. other groups. Despite PSM, the F group was found to have significantly reduced median OS (p = 0.0106) and PFS (p = 0.0101) compared to other groups.

Frailty was significantly associated with higher length-of-stay, frequent medical complications, and worse OS and PFS following surgery vs. other groups. Frailty is hence a crucial consideration in preoperative planning for elderly populations undergoing meningioma resection.

Cancer remains one of the most formidable global health challenges, with conventional therapies often limited by off-target toxicity, drug resistance, and the inability to target key oncogenic drivers. In recent years, de novo protein and peptide binder engineering has emerged as an approach to overcome these barriers, offering precise and customizable solutions for cancer diagnosis and treatment. By leveraging computational design, directed evolution, and artificial intelligence, researchers can now engineer binding molecules with high specificity, stability, and therapeutic potential, unconstrained by the limitations of natural protein scaffolds. This review explores methodologies in de novo binder design, from computational algorithms like Rosetta and AlphaFold (although, with limitations such as their accuracy for disordered regions and conformational dynamics) to innovative scaffold optimization strategies. It highlights groundbreaking applications, including direct tumor inhibition, targeted drug delivery, immune modulation, and diagnostic biosensing, while showcasing case studies such as Designed Ankyrin Repeat Proteins (DARPins) and PD-1/PD-L1 mini-protein inhibitors. Looking ahead, the field promises to improve personalized medicine through tumor-specific binders, synthetic biology circuits, and next-generation delivery systems. As a convergence of biotechnology, computational modeling, and translational medicine, de novo binder engineering represents a powerful frontier in cancer therapy, with the potential to redefine precision oncology and address unmet clinical needs. The insights presented herein underscore its growing relevance in shaping future therapeutic strategies against cancer's complexity.

Colorectal cancer (CRC) is a significant health challenge in the world, with incidence being increasingly reported among the young population. Machine learning, therefore, is revolutionizing care in CRC, including providing advancements in early detection, staging, recurrence prediction, and individualized medicine. Techniques for analysis include support vector machines, random forests, and neural networks, which allow complex analyses of datasets, including genetic profiles and imaging data, with an improvement in diagnostic accuracy and treatment outcomes. Machine learning-driven personalized treatment strategies empower clinicians to tailor therapies to individual patients, optimizing efficacy while reducing side effects. However, integration of Machine learning (ML) in CRC management faces challenges like data quality, validation, and smooth adaptation into clinical workflow. Overcoming these barriers through multi-institutional collaboration and strong validation frameworks will be essential to unlock the full potential of ML. Advancement in research will enable the transformation of CRC care to provide more accurate diagnoses and targeted treatments, ultimately changing patient outcomes. Insight box This review examines the transformative impact of machine learning (ML) in colorectal cancer (CRC) research and care. By integrating multi-omics, radiomics, and clinical data, ML models outperform traditional diagnostic and prognostic methods, enabling precise risk prediction, personalized treatment, and early recurrence detection. The amalgamation of supervised learning, neural networks, and deep learning yields actionable insights that improve patient outcomes and address unmet needs in CRC management. The review also discusses solutions to challenges such as data standardization, ethics, and clinical workflow integration, offering a roadmap for real-world ML adoption. This work highlights the synergy between computational advances and oncology, providing a forward-thinking framework for CRC care.

Background Multi-b-value diffusion MRI models have been used to predict pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) for breast cancer. However, there is a lack of longitudinal comparative research. Purpose To compare the performance of various diffusion MRI-derived longitudinal parameters during NAC for prediction of pCR in breast cancer. Materials and Methods This prospective study included consecutive women with breast cancer enrolled between February 2021 and June 2023 and treated with six or eight cycles of NAC. Each woman underwent intravoxel incoherent motion (IVIM) imaging and diffusion kurtosis imaging (DKI) before NAC (time point T₁) and after two, four, and six cycles of NAC (T₂, T₃, and T₄, respectively). The apparent diffusion coefficient (ADC) and IVIM and DKI parameters were compared using repeated-measures analysis of variance. Backward stepwise multivariable logistic regression analysis was used to identify parameters associated with pCR. Model performance was assessed using the area under the receiver operating characteristic curve (AUC) and was compared using the DeLong test. Results Among 160 women (mean age, 49.73 years ± 8.39 [SD]), 36 had pCR. ADC, tissue diffusion coefficient, and non-Gaussian ADC (D_app) demonstrated significant differences between the pCR group and non-pCR group (P = .04, .02, and .01, respectively). At T₂, progesterone receptor positivity (odds ratio [OR], 0.10 [95% CI: 0.02, 0.48]; P = .004) was associated with lower odds of pCR, while human epidermal growth factor receptor 2 positivity (OR, 4.51 [95% CI: 1.64, 12.45]; P = .004), higher D_app (OR, 8.44 [95% CI: 3.28, 21.72]; P < .001), and higher apparent kurtosis coefficient (OR, 7.69 [95% CI: 3.03, 19.53]; P < .001) were associated with higher odds of pCR. The clinicopathologic-DKI model integrating these parameters exhibited an AUC of 0.90 (95% CI: 0.84, 0.94) in predicting pCR, outperforming the clinicopathologic model (AUC, 0.79 [95% CI: 0.72, 0.85]; P < .001) and clinicopathologic-IVIM model (AUC, 0.84 [95% CI: 0.77, 0.89]; P = .04). Conclusion A model combining clinicopathologic variables and DKI parameters after early NAC showed excellent performance in predicting pCR to NAC for breast cancer. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Thakur and Bitencourt in this issue.

Background Patients with stage T3 non-small cell lung cancer (NSCLC) with separate nodules (SNs) have been reported to have better outcomes than those with T3 tumors with other descriptors, but heterogeneity may exist depending on nodule characteristics. Purpose To identify prognostic factors based on the imaging features of SNs among patients with pathologically confirmed SNs in the same lobe. Materials and Methods This retrospective study included patients with pT2b-pT3 NSCLC who underwent lobectomy or pneumonectomy between January 2010 and December 2021. Radiologic features of the SNs were evaluated. Recurrence-free survival (RFS) and overall survival (OS) were evaluated with Cox proportional hazards regression. Results A total of 1107 patients were evaluated (mean age, 64.8 years ± 9.8 [SD]; 766 male; 498 with pT2b; 141 with SNs; 468 with pT3-other descriptors). In patients with SNs, subsolid SNs were an independent negative prognostic factor for both RFS (hazard ratio [HR], 0.26 [95% CI: 0.12, 0.57]; P = .001) and OS (HR, 0.11 [95% CI: 0.04, 0.32]; P < .001). The number of SNs was an independent positive prognostic factor for RFS (HR, 2.40 [95% CI: 1.24, 4.64]; P = .009). In patients with solid SNs, a nonregional location was the only prognostic factor for shorter OS (HR, 1.92 [95% CI: 1.04, 3.56]; P = .04). No difference was identified between patients with subsolid SNs and those with pT2b tumors for RFS or OS (P > .99). Patients with subsolid SNs had better survival than those with solid SNs (P < .001 for RFS and OS) or pT3-other descriptor tumors (P = .002 for RFS; P < .001 for OS). No survival difference was detected between patients with solid SNs and those with pT3-other descriptor tumors (P > .99). Conclusion In patients with surgically resected NSCLC and pathologic SNs in the same lobe, the presence of ground-glass opacity was associated with outcome. Only subsolid SNs were associated with higher survival rates compared with pT3-other descriptor tumors. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Goo in this issue.

Splicing factor 3b subunit 1 (SF3B1) mutations have been implicated in hematologic malignancies, but the clinical significance of distinct SF3B1 mutation variants remain unclear.

The objective of this study was to evaluate clinicopathologic features, mutational profiles, and outcomes of 1691 patients with hematologic malignancies, including myelodysplastic syndromes (MDS; n = 402), acute myeloid leukemia (AML; n = 758), and chronic lymphocytic leukemia (CLL; n = 531).

The frequency of SF3B1-mutated (SF3B1^MUT) MDS, AML, and CLL was 70 of 402 patients (17.4%), 23 of 758 patients (3.0%), and 45 of 531 patients (8.5%), respectively. p.K700E was the most prevalent SF3B1^MUT variant and was identified in 43 of 70 of patients with MDS (61.4%), in seven of 23 patients with AML (30.4%), and in 19 of 45 patients with CLL (42.2%). In MDS and AML, TET2 was the most frequent co-mutated gene in patients with SF3B1^MUT disease (20 of 70 patients with MDS [28.6%]; 11 of 23 patients with AML [47.8%]). For patients with SF3B1^MUT CLL, the most common co-mutated genes were ATM (11 of 45; 24.4%) and TP53 (11 of 45; 24.4%). Kaplan-Meier analysis indicated that the SF3B1 p.K700E variant was significantly associated with improved overall survival (OS) and progression-free survival (PFS) in patients who had MDS (p < .001 and p = .016, respectively) but with worse OS and PFS in those who had AML (p = .006 and p = .006, respectively) compared with those who had wild-type SF3B1. In patients who had CLL, p.I704F was associated with reduced OS (p < .001) and p.K700E was associated with a shorter time-to-first treatment (p = .028) compared with those who had wild-type SF3B1. Multivariable analysis identified p.K700E as an independent protective factor for OS in patients with MDS (p = .048) but as an independent risk factor for both OS and PFS in patients with AML (p = .036 and p = .035, respectively) and for the time to first treatment in patients with CLL (p = .033).

Specific SF3B1 variants should be incorporated into prognostic stratification for hematologic malignancies.

BACKGROUND: Tinnitus is a common symptom in patients with vestibular schwannoma (VS). The impact of Gamma Knife radiosurgery (GKRS) on tinnitus and the health-related quality of life (HRQoL) of patients with VS remains unclear. This study evaluated the effect of GKRS on HRQoL affected by tinnitus. METHODS: From December 2020 to April 2022, spontaneous VS patients who had no prior history of treatment and underwent their first GKRS in this period were analyzed. Subjective distress from tinnitus was measured by the Tinnitus Handicap Inventory (THI) and their HRQoL by 36-Item Short Form Survey Version 2 (SF-36v2). Pre-GKRS THI and SF-36v2 were obtained, and after GKRS, consecutive THI and SF-36v2 were obtained during the follow-up period. Bowker's test, paired Student's t-test, and Spearman's correlation were used to analyze the changes in THI grade, SF-36v2 score, and the correlation between THI grade and SF-36v2 score. Factors affecting the THI grade change and SF-36v2 score were evaluated through univariate and multivariate models. RESULTS: Twenty of 34 patients showed serviceable hearing before GKRS. The median radiation dose of GKRS was 12.75 Gy (range, 12-21 Gy). Twenty-two of 33 patients demonstrated no change or worse THI grade after GKRS, but the change was not statistically significant (P =.34). However, with age, the odds ratio of THI improvement is 0.905 (95% CI 0.83-0.98, P=.02). Patients with serviceable hearing before GKRS displayed THI grade improvement (OR = 6.721; P = .03). Compared to those with pre-GKRS THI grade 1, grades 3 and 4 exhibited lower odds of THI improvement (OR =0.095; P=.0449). No significant change was noted in SF-36v2 scores after GKRS. A high THI grade was correlated with a low physical component score (P =.03) and mental component score (P=.0002) of SF-36v2. CONCLUSION: Although THI grade and SF-36v2 change before and after GKRS did not show statistical significance, several factors affected THI grade change. Moreover, the THI grade and SF-36v2 score had a significant negative correlation. Factors that may aggravate tinnitus and further impact HRQoL of VS patients should be taken into account when planning treatment and providing counseling to VS patients.

Osteosarcoma (OS) is a type of bone tumour characterized by high risk of metastatic progression and recurrence after therapy. Traditional tumour treatment methods such as radiotherapy and chemotherapy can lead to the accumulation of senescent cells in tumours. Treatment-induced senescence (TIS) can lead to incomplete tumour clearance and potential recurrence. Recently, the combination of chemotherapy drugs and senolytics drugs ('one-two punch' therapy) has become a promising strategy for improved tumour treatment, but this method also faces challenges in terms of safety and targeting specificity. In order to further improve the efficacy of chemotherapy on OS, here we developed a senolytic drug delivery system based on engineered Natural killer (NK) cell-derived extracellular vesicles (EVs) that can target OS cells. EVs were engineered to contain doxorubicin (Dox), termed iRGD-EVs-Dox, and used to induce cellular senescence in OS cells, followed by delivery of the Bcl-2 family inhibitor ABT-263 in similar engineered EVs (iRGD-EVs-ABT-263), to specifically eliminate the senescent OS cells induced by Dox. Our results demonstrate that iRGD-EVs have efficient targeting ability to OS cells and iRGD-EVs-ABT-263 effectively induced senolysis of Dox-induced senescent OS cells in vitro and repressed tumour growth in OS cell xenograft mouse models. Taken together, our results demonstrate the therapeutic efficiency of using engineered EVs from NK cells to deliver first a chemotherapeutic agent to induce senescent OS cells followed by a senolytic drug to eliminate chemotherapy-induced senescent OS cells, providing a novel strategy for more effective cancer treatment.