Technology in Cancer Research & Treatment最新文献

Lymphoma is a highly heterogeneous malignancy, demanding accurate and precise diagnosis to guide the selection of the appropriate treatment for optimal outcome. Copy number aberration (CNA) has been suggested to play an important role in the occurrence and development of lymphoma and thus can be explored as biomarker to improve disease management. It is believed that CNAs in variable forms and complexities can be triggered by both exogenous (eg viral infection and ionizing radiation) and endogenous factors (eg genetic predisposition and evolutionary forces). However, conventional cytogenetic methods have limitations to detect all types of CNAs with accuracy and adequate details. The emergence of new technologies, including fluorescence in situ hybridization (FISH), chromosome microarray analysis (CMA), and especially next-generation sequencing (NGS) has made significant progress in the identification and characterization of CNAs or CNA-related genomic aberrations. Accumulating data addressing molecular insights and clinical implications have provided us more theoretical and experimental support for its clinical translation. Currently, while only limited number of CNAs or CNA-related genomic variation, such as deletion/amplification of DNA segments, have been documented in major guidelines or consensus for their clinical potential in lymphoma, more CNAs remain to be further characterized and/or discovered for their clinical relevance. Taking together, with available and upcoming evidence, CNA should play an important role as a diagnostic and prognostic biomarker while integrated with the current settings in lymphoma.

IntroductionLung cancer has the highest mortality rate among all cancer types globally, largely due to delayed or ineffective diagnosis and treatment. Radiomics is commonly used to diagnose lung cancer, especially in later stages or during routine screenings. However, frequent radiological imaging poses health risks, and while advanced diagnostic alternatives exist, they are often costly and accessible only to a limited, privileged population. Leveraging clinical data using machine learning (ML) and artificial intelligence (AI) enables a safer, more inclusive, and affordable solution. Due to a lack of interpretability, AI-based models for cancer diagnosis are less adopted by clinicians.MethodsThis study introduces a safe, inclusive, and cost-effective lung cancer diagnostic method using an explainable AI (XAI) model built on routine clinical data. It employs a stacking ensemble of Artificial Neural Network (ANN) and Deep Neural Network (DNN) to match the diagnostic performance of clean-data DNN models. By incorporating rare medical cases through Adaptive Synthetic Sampling (ADASYN), the model reduces the risk of missing challenging, rare-case diagnoses.ResultsThe proposed XAI model demonstrates strong performance with an accuracy of 0.8558, AUC of 0.8600, precision of 0.8092, recall of 0.9282, and F1-score of 0.8646, notably improving rare case detection by over 50%. SHapley additive exPlanations(SHAP)-based interpretability highlights Erythrocyte sedimentation rate(ESR), intoxication-related factors, hemoglobin levels, and neutrophil counts as key features. The model also reveals associations, such as a link between heavy tobacco use and elevated ESR. Counterfactual explanations help identify features contributing to misdiagnoses by exposing sources of confusion in the model's decisions.ConclusionGiven the limited dataset size and geographic constraints, this research should be viewed as a prototype and in its current form, the model is best suited as a pre-screening tool to support early detection. With training on larger and more diverse datasets, the model has strong potential to evolve into a robust and scalable diagnostic solution.

Development of the Bharat Cancer Genome Atlas (BCGA) is poised to be a comprehensive genomic database which will not only deepen our scientific understanding of the unique molecular landscape of cancers prevalent in India but also provide the essential foundation required to facilitate the development of targeted therapies, enable personalized treatment strategies, and foster the creation of more effective early detection methods specifically tailored for the Indian population. The open-access nature of the BCGA is a core strength, designed to democratize access to this vital information, thereby empowering researchers to make new discoveries, enabling clinicians to provide more precise care, and allowing patients and their families to engage more fully in their health journey.

Early detection of skin cancer is crucial for effective treatment and improved patient outcomes. Recent advancements in oncologic imaging, particularly molecular imaging techniques, have revolutionized cancer diagnostics and treatment by enabling the visualization of tumors and cellular activities at the molecular level. These techniques facilitate the identification of early-stage cancers that might remain undetectable through traditional imaging methods. Innovative technologies such as reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) which visualize skin at near-histologic detail and skin fluorescent imaging (SFI), which targets αvβ3 integrin expression, are promising for non-invasive early detection of melanoma. By integrating in vivo molecular imaging with tumor biomarkers, clinicians can gain more precise insights into processes integral to cancer biology, leading to improved diagnosis, prognosis and the development of personalized treatment strategies. This review explores imaging modalities used in skin cancer diagnosis, highlighting their advantages and limitations, with an emphasis on molecular imaging, stressing its potential to improve early detection, personalize treatment and monitor therapeutic responses.

IntroductionAccurate beam modeling is essential for ensuring safe and effective proton therapy delivery. Before clinical implementation, pencil beam scanning systems require thorough validation to confirm that calculated dose distributions reliably reflect measured performance. This work outlines a practical approach to achieving comprehensive and efficient validation.MethodsThe beam model for a pencil beam scanning system was configured in the treatment planning system (TPS). Beam data including integrated depth dose, lateral profiles in air, and absolute outputs for various energies were measured and entered into the TPS following vendor recommendations. Validation tests were performed according to AAPM TG 185 and insights from other proton centers, adapted to our clinical requirements, time constraints, and regulations. The validation incorporated test cases from AAPM TG 350 draft report and included: 1) rectangular field dose distributions in water, 2) PDD measurements, 3) planar dose measurements using the DigiPhant detector with TG 350 test plans and clinical cases, and 4) end-to-end tests in animal tissue. TPS-calculated dose distributions, obtained using either the proton convolution superposition or Acuros Protons algorithms, were compared with corresponding measurements. A peer review from an institute with a similar proton treatment machine validated the machine output and our validation process.ResultsFor rectangular targets with various ranges and modulation widths in water based on TG 185, TG 350 test plans, and clinical plans, ionization chamber and MatriXX PT planar dose measurements agreed with TPS calculations (point dose difference < 3%, planar dose 3%/3 mm > 95%). Range differences for animal tissues were within 3%. Independent peer output measurements agreed with our results within 1%.ConclusionTPS-calculated range and dose were in good agreement with measurements across multiple validation tests. The beam model for both PCS and Acuros PT has been validated and used clinically. Incorporating practical considerations is essential for achieving comprehensive and efficient beam commissioning and validation.

The battle against cancer remains a top priority for society, with an urgent need to develop therapies capable of targeting challenging tumours while preserving patient's quality of life. Hadron Therapy (HT), which employs accelerated beams of protons, carbon ions, and other charged particles, represents a significant frontier in cancer treatment. This modality offers superior precision and efficacy compared to conventional methods, delivering therapeutic the dose directly to tumours while sparing healthy tissue. Even though 350,000 patients have already been treated worldwide with protons and 50,000 with carbon ions, HT is still a relatively young field and more research as well as novel, cost-effective and compact accelerator technologies are needed to make this treatment more readily available globally. Interestingly the very first patient was irradiated with protons in September 1954, the same month and year CERN was founded. Both of these endeavours are embedded in cutting edge technologies and multidisciplinary collaboration. HT is finally gaining ground and, even after 70 years, the particle therapy field continues innovating and improving for the benefits of patients globally. Developing technologies that are both affordable and easy to use is key and would allow access to more patients. Advances in accelerator-driven Boron Neutron Capture Therapy (BNCT), image-guided hadron beams delivery, clinical trials and immunotherapy, together with the recent interest and advances in FLASH therapy, which is currently an experimental treatment modality that involves ultrahigh-dose rate delivery, are just a few examples of innovation that may eventually help to provide access to a larger number of patients.

Long non-coding RNAs (lncRNAs) are known to play vital roles in human cancers. LncRNA TRPM2-AS has been found to be upregulated in various types of cancers. The elevated levels of TRPM2-AS are associated with important clinicopathological parameters such as tumor size, tumor stage, and lymph node metastasis, revealing that TRPM2-AS could be a potential target for cancer diagnosis, prognosis and treatment. Moreover, TRPM2-AS is involved in regulating the cell proliferation, migration, invasion, apoptosis, drug or radio resistance by serving as a competing endogenous RNA, directly bounding to proteins and regulating multiple signaling pathways. In this review, we comprehensively summarize the latest knowledge on the aberrant expression of TRPM2-AS, the relationship between TRPM2-AS and clinical features, and the detailed mechanisms of potential functions of TRPM2-AS in various cancer types. The current study highlights the potential of TRPM2-AS as a prognostic and therapeutic target in cancers.

BackgroundExtensive-stage small cell lung cancer (ES-SCLC) is a highly aggressive malignancy with poor prognosis. This study aimed to assess the efficacy of combining immunotherapy (IT) with Anlotinib in ES-SCLC patients.MethodsThis study was a multicenter retrospective cohort analysis. Survival outcomes were evaluated using Kaplan-Meier curves and Cox proportional hazards regression models.ResultsA total of 147 patients were included in the analysis. The median overall survival (mOS) for the cohort was 15.5 months (95% CI: 13.9-17.1). Patients in the chemotherapy(CT) plus IT group had an mOS of 17.8 months, compared to 12.6 months in the CT-alone group (p = 0.055). When stratified into CT + IT + Anlotinib, CT + IT, and CT-alone groups, the mOS were 18.5, 16.3, and 12.6 months, respectively, with the CT + IT + Anlotinib group demonstrating significantly improved OS compared to CT-alone (p = 0.044). The ORR and DCR for the entire cohort were 71.4% and 85.7%, respectively. Subgroup analysis revealed ORRs of 74.1% (CT + IT + Anlotinib), 73.9% (CT + IT), and 70.1% (CT-alone), with corresponding DCRs of 92.6%, 91.3%, and 82.5%. Multivariate analysis revealed that radiotherapy (RT, p = 0.003) and IT (p = 0.021) were independent prognostic factors for OS, while liver metastasis (p = 0.023) and RT (p = 0.018) were associated with PFS. Patients receiving RT in combination with CT showed markedly improved OS (17.5 vs 12.5 months; p = 0.002) and PFS (7.3 vs 6.3 months; p = 0.004). The incidence of adverse events was comparable across all groups (p = 0.721).ConclusionThe combined application of Anlotinib with IT and the combination of CT with RT both significantly improved survival outcomes in patients with ES-SCLC while maintaining a favorable safety profile. These findings warrant further investigation in future studies.

IntroductionThe OCRA Tabletop MRI System is a compact, low-field (0.24T) magnetic resonance platform originally developed as an educational device to teach MR physics using chemical test tube-sized samples. Given its capabilities, we explored its diagnostic potential by performing relaxometric analysis on freshly resected human tissue specimens.MethodsMatched pairs of histologically confirmed tumor and non-tumor samples were analyzed with the OCRA MRI system to determine T1 and T2 relaxation times via NMR spectroscopy. In parallel, mRNA expression levels of ZEB1, a key transcription factor involved in WNT signaling, stem cell maintenance and tumor-stroma interactions were quantified for each sample.ResultsThe measured T1 and T2 relaxation times showed distinct profiles between tumor and non-tumor tissues. These biophysical properties were correlated with ZEB1 mRNA expression, revealing preliminary associations between tissue relaxation behavior and molecular signatures relevant to tumor microenvironment dynamics.ConclusionAlthough this pilot study does not yet confirm clinical diagnostic utility, it offers initial biophysical insights into tumor-associated tissue alterations and provides a foundation for future validation studies in larger patient cohorts.

IntroductionHistorically, the management of relapsed or refractory diffuse large B-cell lymphoma (r/r-DLBCL) involved chemotherapy and autologous stem cell transplant, though outcomes were often suboptimal. Chimeric antigen receptor T-cell (CAR-T) therapy has transformed the therapeutic landscape for r/r-DLBCL, achieving high response rates and improving progression-free and overall survival. However, a significant proportion of patients relapse after CAR-T, and optimal treatment strategies for post-CAR-T relapse remain unclear. Radiotherapy (RT), a highly effective treatment for lymphoma, is increasingly recognized for its potential role as both a bridging therapy and a salvage option following CAR-T relapse.MethodsA comprehensive literature review was conducted using databases including PubMed, Scopus, EMBASE, and Cochrane Library, with search terms combining "radiotherapy," "radiation therapy," "lymphoma," and "CAR T-cell." A total of 690 records were screened, and 14 studies were included in the analysis after applying inclusion and exclusion criteria.ResultsRT demonstrates high response rates in CAR-T relapsed DLBCL, with overall response rates (ORR) ranging from 35% to 82.4% and complete response rates (CRR) from 17% to 59%. One-year local control rates ranged between 62% and 84%. Salvage RT showed comparable or superior outcomes to systemic therapies in multiple studies, particularly in patients with localized relapses. The toxicity profile of RT was favorable, particularly when modern techniques such as IMRT were employed. Case reports and retrospective series highlighted its effectiveness in achieving durable responses and controlling localized disease progression.ConclusionsRadiotherapy is a safe and effective treatment option for patients with DLBCL relapsed or refractory after CAR-T therapy. It achieves high local control rates and favorable outcomes, particularly in patients with localized relapse. Incorporating RT into the therapeutic workflow may enhance the management of this challenging population. Further prospective studies are needed to define its role and optimize treatment sequencing.