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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The Radiation Biology Ontology: A New Tool Supporting FAIR Principles Across Radiation Biology Facilitating Data Discovery and Integration

Development of the Radiation Biology Ontology (RBO) was motivated by the need for a comprehensive, well-structured ontology for encoding radiation biology metadata. The primary use-cases were archiving data in the STORE database (https://www.storedb.org/), the repository for the RadoNorm Project, and in GeneLab (https://genelab.nasa.gov), NASA’s ‘omics database. The scope of radiobiology research ranges from physics to radiation oncology to socio-legal studies; no existing ontology has the necessary breadth or depth. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR radiation biology data.

ontology↗
NASA NTRSDate not supplied

Data Sharing in Radiobiology; Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally „Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗
NASA NTRS2023

Data Sharing in Radiation Biology: Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally "Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗
DOE OSTI2026

Discovery of BBO-11818, a Potent and Selective Noncovalent Inhibitor of (ON) and (OFF) KRAS with Activity against Multiple Oncogenic Mutants

Although KRAS G12C -specific inhibitors have been introduced, no approved targeted therapies exist for other clinically significant KRAS mutants, including KRAS G12D and KRAS G12V . We discovered BBO-11818, a potent, selective, orally bioavailable noncovalent pan-KRAS inhibitor capable of targeting multiple KRAS mutants in both the inactive GDP-bound (OFF) and active GTP-bound (ON) states. BBO-11818 binds in the Switch-II/Helix 3 pocket, inducing conformational changes incompatible with effector binding, and demonstrates high-affinity binding to mutant KRAS with strong selectivity over NRAS and HRAS. BBO-11818 potently inhibited MAPK signaling and cellular viability specifically in KRAS-driven lines and produced tumor regressions in KRAS-mutant xenograft models. Combination studies with anti–PD-1, anti-EGFR antibodies, and a RAS:PI3Kα breaker compound showed enhanced efficacy. BBO-11818 has entered phase I clinical trials for patients with various KRAS mutations in colorectal, pancreatic, and lung cancers (NCT06917079).

Stahlhut, Carlos [BridgeBio Oncology Therapeutics,↗
DOE OSTI2025

BBO-10203 inhibits tumor growth without inducing hyperglycemia by blocking RAS-PI3Kα interaction

BBO-10203 is an orally available drug that covalently and specifically binds to the rat sarcoma (RAS)–binding domain of phosphoinositide 3-kinase α (PI3Kα), preventing its activation by HRAS, NRAS, and KRAS. Here, it inhibited PI3Kα activation in tumors with oncogenic mutations in KRAS or PIK3CA and in tumors with human epidermal growth factor receptor 2 (HER2) amplification or overexpression. In preclinical models, BBO-10203 caused significant tumor growth inhibition across multiple tumor types and showed enhanced efficacy in combination with inhibitors of cyclin-dependent kinase 4/6 (CDK4/6), estrogen receptor (ER), HER2, and KRAS-G12C mutant, including in tumors harboring mutations in Kelch-like ECH-associated protein 1 (KEAP1) and serine/threonine kinase 11 (STK11). Notably, these antitumor effects occurred without inducing hyperglycemia, because insulin signaling does not depend on RAS-mediated PI3Kα activation to promote glucose uptake.

Simanshu, Dhirendra K. [Frederick National Laborat↗
DOE OSTI2025

Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model

Abstract Background Accurate delineation of the clinical target volume (CTV) is essential in the radiotherapy treatment of soft tissue sarcomas. However, this process is subject to inter‐reader variability due to the need for clinical assessment of risk and extent of potential microscopic spread. This can lead to inconsistencies in treatment planning, potentially impacting treatment outcomes. Most existing automatic CTV delineation methods do not account for this variability and can only generate a single CTV for each case. Purpose This study aims to develop a deep learning‐based technique to generate multiple CTV contours for each case, simulating the inter‐reader variability in the clinical practice. Methods We employed a publicly available dataset consisting of fluorodeoxyglucose positron emission tomography (FDG‐PET), x‐ray computed tomography (CT), and pre‐contrast T1‐weighted magnetic resonance imaging (MRI) scans from 51 patients with soft tissue sarcoma, along with an independent validation set containing five additional patients. An experienced reader drew a contour of the gross tumor volume (GTV) for each patient based on multi‐modality images. Subsequently, two additional readers, together with the first one, were responsible for contouring three CTVs in total based on the GTV. We developed a diffusion model‐based deep learning method that is capable of generating arbitrary number of different and plausible CTVs to mimic the inter‐reader variability in CTV delineation. The proposed model incorporates a separate encoder to extract features from the GTV masks, leveraging the critical role of GTV information in accurate CTV delineation. Results The proposed diffusion model demonstrated superior performance with the highest Dice Index (0.902 compared to values below 0.881 for state‐of‐the‐art models) and the best generalized energy distance (GED) (0.209 compared to values exceeding 0.221 for state‐of‐the‐art models). It also achieved the second‐highest recall and precision metrics among the compared ambiguous image segmentation models. Results from both datasets exhibited consistent trends, reinforcing the reliability of our findings. Additionally, ablation studies exploring different model structures and input configurations highlighted the significance of incorporating prior GTV information for accurate CTV delineation. Conclusions The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter‐reader variability in CTV delineation.

Dong, Yafei [Yale Biomedical Imaging Institute Yal↗
DOE OSTI2023

Practical Understanding of Cancer Model Identifiability in Clinical Applications

Mathematical models are a core component in the foundation of cancer theory and have been developed as clinical tools in precision medicine. Modeling studies for clinical applications often assume an individual’s characteristics can be represented as parameters in a model and are used to explain, predict, and optimize treatment outcomes. However, this approach relies on the identifiability of the underlying mathematical models. In this study, we build on the framework of an observing-system simulation experiment to study the identifiability of several models of cancer growth, focusing on the prognostic parameters of each model. Our results demonstrate that the frequency of data collection, the types of data, such as cancer proxy, and the accuracy of measurements all play crucial roles in determining the identifiability of the model. We also found that highly accurate data can allow for reasonably accurate estimates of some parameters, which may be the key to achieving model identifiability in practice. As more complex models required more data for identification, our results support the idea of using models with a clear mechanism that tracks disease progression in clinical settings. For such a model, the subset of model parameters associated with disease progression naturally minimizes the required data for model identifiability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Cancer Incidence Trends in Successive Social Generations in the US

Importance: The incidence of some cancers in the US is increasing in younger age groups, but underlying trends in cancer patterns by birth year remain unclear. Objective: To estimate cancer incidence trends in successive social generations. Design, Setting, and Participants: In this cohort study, incident invasive cancers were ascertained from the Surveillance, Epidemiology, and End Results (SEER) program’s 13-registry database (November 2020 submission, accessed August 14, 2023). Invasive cancers diagnosed at ages 35 to 84 years during 1992 to 2018 within 152 strata were defined by cancer site, sex, and race and ethnicity. Exposure: Invasive cancer. Main Outcome and Measures: Stratum-specific semiparametric age-period-cohort (SAGE) models were fitted and incidence per 100 000 person-years at the reference age of 60 years was calculated for single-year birth cohorts from 1908 through 1983 (fitted cohort patterns [FCPs]). The FCPs and FCP incidence rate ratios (IRRs) were compared by site for Generation X (born between 1965 and 1980) and Baby Boomers (born between 1946 and 1964). Results: A total of 3.8 million individuals with invasive cancer (51.0% male; 8.6% Asian or Pacific Islander, 9.5% Hispanic, 10.4% non-Hispanic Black, and 71.5% non-Hispanic White) were included in the analysis. In Generation X vs Baby Boomers, FCP IRRs among women increased significantly for thyroid (2.76; 95% CI, 2.41-3.15), kidney (1.99; 95% CI, 1.70-2.32), rectal (1.84; 95% CI, 1.52-2.22), corpus uterine (1.75; 95% CI, 1.40-2.18), colon (1.56; 95% CI, 1.27-1.92), and pancreatic (1.39; 95% CI, 1.07-1.80) cancers; non-Hodgkins lymphoma (1.40; 95% CI, 1.08-1.82); and leukemia (1.27; 95% CI, 1.03-1.58). Among men, IRRs increased for thyroid (2.16; 95% CI, 1.87-2.50), kidney (2.14; 95% CI, 1.86-2.46), rectal (1.80; 95% CI, 1.52-2.12), colon (1.60; 95% CI, 1.32-1.94), and prostate (1.25; 95% CI, 1.03-1.52) cancers and leukemia (1.34; 95% CI, 1.08-1.66). Lung (IRR, 0.60; 95% CI, 0.50-0.72) and cervical (IRR, 0.71; 95% CI, 0.57-0.89) cancer incidence decreased among women, and lung (IRR, 0.51; 95% CI, 0.43-0.60), liver (IRR, 0.76; 95% CI, 0.63-0.91), and gallbladder (IRR, 0.85; 95% CI, 0.72-1.00) cancer and non-Hodgkins lymphoma (IRR, 0.75; 95% CI, 0.61-0.93) incidence decreased among men. For all cancers combined, FCPs were higher in Generation X than for Baby Boomers because gaining cancers numerically overtook falling cancers in all groups except Asian or Pacific Islander men. Conclusions and Relevance: In this model-based cohort analysis of incident invasive cancer in the general population, decreases in lung and cervical cancers in Generation X may be offset by gains at other sites. Generation X may be experiencing larger per-capita increases in the incidence of leading cancers than any prior generation born in 1908 through 1964. On current trajectories, cancer incidence could remain high for decades.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The PI3K/mTOR inhibitor Gedatolisib eliminates dormant breast cancer cells in organotypic culture, but fails to prevent metastasis in preclinical settings

Dormant, disseminated tumor cells (DTCs) are thought to be the source of breast cancer metastases several years or even decades after initial treatment. To date, a selective therapy that leads to their elimination has not been discovered. While dormant DTCs resist chemotherapy, evidence suggests that this resistance is driven not by their lack of proliferation, but by their engagement of the surrounding microenvironment, via integrin-β1-mediated interactions. Because integrin-β1-targeted agents have not been translated readily to the clinic, signaling nodes downstream of integrin-β1 could serve as attractive therapeutic targets in order to sensitize dormant DTCs to therapy. By probing a number of kinases downstream of integrin-β1, we determined that PI3K inhibition with either a tool compounds or a compound (PF-05212384; aka Gedatolisib) in clinical trials robustly sensitizes quiescent breast tumor cells seeded in organotypic bone marrow cultures to chemotherapy. These results motivated the preclinical study of whether Gedatolisib—with or without genotoxic therapy—would reduce DTC burden and prevent metastases. Despite promising results in organotypic culture, Gedatolisib failed to reduce DTC burden or delay, reduce or prevent metastasis in murine models of either triple-negative or estrogen receptor-positive breast cancer dissemination and metastasis. This result held true whether analyzing Gedatolisib on its own (vs. vehicle-treated animals) or in combination with dose-dense doxorubicin and cyclophosphamide (vs. animals treated only with dose-dense chemotherapies). These data suggest that PI3K is not the node downstream of integrin-β1 that confers chemotherapeutic resistance to DTCs. More broadly, they cast doubt on the strategy to target PI3K in order to eliminate DTCs and prevent breast cancer metastasis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

COVID ‐19 outcomes in patients with cancer: Findings from the University of California health system database

Abstract Background The interaction between cancer diagnoses and COVID‐19 infection and outcomes is unclear. We leveraged a state‐wide, multi‐institutional database to assess cancer‐related risk factors for poor COVID‐19 outcomes. Methods We conducted a retrospective cohort study using the University of California Health COVID Research Dataset, which includes electronic health data of patients tested for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) at 17 California medical centers. We identified adults tested for SARS‐CoV‐2 from 2/1/2020–12/31/2020 and selected a cohort of patients with cancer. We obtained demographic, clinical, cancer type, and antineoplastic therapy data. The primary outcome was hospitalization within 30d after the first positive SARS‐CoV‐2 test. Secondary outcomes were SARS‐CoV‐2 positivity and severe COVID‐19 (intensive care, mechanical ventilation, or death within 30d after the first positive test). We used multivariable logistic regression to identify cancer‐related factors associated with outcomes. Results We identified 409,462 patients undergoing SARS‐CoV‐2 testing. Of 49,918 patients with cancer, 1781 (3.6%) tested positive. Patients with cancer were less likely to test positive (RR 0.70, 95% CI: 0.67–0.74, p < 0.001). Among the 1781 SARS‐CoV‐2‐positive patients with cancer, BCR/ABL‐negative myeloproliferative neoplasms (RR 2.15, 95% CI: 1.25–3.41, p = 0.007), venetoclax (RR 2.96, 95% CI: 1.14–5.66, p = 0.028), and methotrexate (RR 2.72, 95% CI: 1.10–5.19, p = 0.032) were associated with greater hospitalization risk. Cancer and therapy types were not associated with severe COVID‐19. Conclusions In this large, diverse cohort, cancer was associated with a decreased risk of SARS‐CoV‐2 positivity. Patients with BCR/ABL‐negative myeloproliferative neoplasm or receiving methotrexate or venetoclax may be at increased risk of hospitalization following SARS‐CoV‐2 infection. Mechanistic and comparative studies are needed to validate findings.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Pan‐Cancer Survival Impact of Immune Checkpoint Inhibitors in a National Healthcare System

ABSTRACT Background The cumulative, health system‐wide survival benefit of immune checkpoint inhibitors (ICIs) is unclear, particularly among real‐world patients with limited life expectancies and among subgroups poorly represented on clinical trials. We sought to determine the health system‐wide survival impact of ICIs. Methods We identified all patients receiving PD‐1/PD‐L1 or CTLA‐4 inhibitors from 2010 to 2023 in the national Veterans Health Administration (VHA) system (ICI cohort) and all patients who received non‐ICI systemic therapy in the years before ICI approval (historical control). ICI and historical control cohorts were matched on multiple cancer‐related prognostic factors, comorbidities, and demographics. The effect of ICI on overall survival was quantified with Cox regression incorporating matching weights. Cumulative life‐years gained system‐wide were calculated from the difference in adjusted 5‐year restricted mean survival times. Results There were 27,322 patients in the ICI cohort and 69,801 patients in the historical control cohort. Among ICI patients, the most common cancer types were NSCLC (46%) and melanoma (10%). ICI demonstrated a large OS benefit in most cancer types with heterogeneity across cancer types (NSCLC: adjusted HR [aHR] 0.56, 95% confidence interval [CI] 0.54–0.58,p < 0.001; urothelial: aHR 0.91, 95% CI 0.83–1.01,p = 0.066). The relative benefit of ICI was stable across patient age, comorbidity, and self‐reported race subgroups. Across VHA, 15,859 life‐years gained were attributable to ICI within 5‐years of treatment, with NSCLC contributing the most life‐years gained. Conclusion We demonstrated substantial increase in survival due to ICIs across a national health system, including in patient subgroups poorly represented on clinical trials.

Oncology↗
DOE OSTI2021

Floor and ceiling effects in the EORTC QLQ-C30 Physical Functioning subscale among patients with advanced or metastatic breast cancer

The European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 Physical Functioning subscale is a widely used patient-reported outcome measure that quantifies cancer patients' physical functioning. Strong floor/ceiling effects can affect a scale's sensitivity to change. The aim of this study was to characterize floor/ceiling effects of the physical functioning domain in patients with advanced/metastatic breast cancer enrolled in commercial clinical trials and a community-based trial. The clinical trial cohort comprised patients from 5 registrational trials submitted to the Food and Drug Administration for review (2010-2017). The community cohort comprised a subgroup of patients from the Alliance Patient Reported Outcomes to Enhance Cancer Treatment (PRO-TECT) trial. The distribution of patient responses to Physical Functioning items and the summed score were assessed at the baseline and 3-month follow-up for both cohorts. Descriptive statistics were used to determine floor/ceiling effects at the item and scale levels. The clinical trial cohort and the community cohort consisted of 2407 and 178 patients, respectively. Twenty-four percent or more of the respondents reported “not at all” for having trouble/needing help with each Physical Functioning item across both cohorts and measurement time points. Fourteen to twenty percent of the patients scored perfectly (100 of 100) on the Physical Functioning subscale summary measure (where higher scores indicated better physical functioning) across both cohorts and time points. Minor floor effects and notable ceiling effects were found at the item and scale levels of the Physical Functioning subscale, regardless of cohort, and this creates some uncertainty about its ability to detect changes in physical functioning among high-functioning patients. In conclusion, investigators may consider adding additional high-functioning items from the EORTC's item library to more accurately describe the impact of anticancer treatment on patients' physical functioning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Human–mouse comparison of the multistage nature of radiation carcinogenesis in a mathematical model

Abstract Mouse models are vital for assessing risk from environmental carcinogens, including ionizing radiation, yet the interspecies difference in the dose response precludes direct application of experimental evidence to humans. Herein, we take a mathematical approach to delineate the mechanism underlying the human–mouse difference in radiation‐related cancer risk. We used a multistage carcinogenesis model assuming a mutational action of radiation to analyze previous data on cancer mortality in the Japanese atomic bomb survivors and in lifespan mouse experiments. Theoretically, the model predicted that exposure will chronologically shift the age‐related increase in cancer risk forward by a period corresponding to the time in which the spontaneous mutational process generates the same mutational burden as that the exposure generates. This model appropriately fitted both human and mouse data and suggested a linear dose response for the time shift. The effect per dose decreased with increasing age at exposure similarly between humans and mice on a per‐lifespan basis (0.72‐ and 0.71‐fold, respectively, for every tenth lifetime). The time shift per dose was larger by two orders of magnitude in humans (7.8 and 0.046 years per Gy for humans and mice, respectively, when exposed at ~35% of their lifetime). The difference was mostly explained by the two orders of magnitude difference in spontaneous somatic mutation rates between the species plus the species‐independent radiation‐induced mutation rate. Thus, the findings delineate the mechanism underlying the interspecies difference in radiation‐associated cancer mortality and may lead to the use of experimental evidence for risk prediction in humans.

Oncology↗
DOE OSTI2025

Cohort-based pan-cancer analysis and experimental studies reveal ISG15 gene as a novel biomarker for prognosis and immunotherapy efficacy prediction

Abstract ISG15, an interferon-stimulated ubiquitin-like protein, plays a multifaceted role in tumorigenesis and immune regulation. This study comprehensively evaluates ISG15 as a prognostic biomarker and predictor of immunotherapy response through pan-cancer bioinformatics analysis and experimental validation. By integrating multiomics data from TCGA, GEO, and clinical cohorts, we found that ISG15 is significantly overexpressed in multiple cancers and generally correlates with poor prognosis. Elevated ISG15 expression is associated with increased immune checkpoint gene expression, particularly PD-L1, and immune infiltration, notably M2-like tumor-associated macrophages. Immunohistochemistry and multiplexed immunofluorescence confirmed a strong positive correlation between ISG15, PD-L1, and M2-TAM infiltration in lung and gastric cancer samples. Functional analysis at the single-cell level revealed significant associations between ISG15 and tumor proliferation, angiogenesis, and immune suppression. Immunotherapy cohort analysis demonstrated that tumors with high ISG15 expression responded favorably to PD-L1 inhibitors but exhibited resistance to CTLA-4 blockade, findings further validated in lung cancer patients receiving anti-PD-1 therapy. These results suggest that ISG15 is a promising biomarker for prognosis and immunotherapy response prediction across cancers. Its integration into clinical decision-making may enhance personalized treatment strategies, improve immunotherapy outcomes, and provide new insights into the tumor immune microenvironment, cancer progression, and potential therapeutic targets for future drug development.

Immunology↗
DOE OSTI2022

Dietary B group vitamin intake and the bladder cancer risk: a pooled analysis of prospective cohort studies

Abstract Purpose Diet may play an essential role in the aetiology of bladder cancer (BC). The B group complex vitamins involve diverse biological functions that could be influential in cancer prevention. The aim of the present study was to investigate the association between various components of the B group vitamin complex and BC risk. Methods Dietary data were pooled from four cohort studies. Food item intake was converted to daily intakes of B group vitamins and pooled multivariate hazard ratios (HRs), with corresponding 95% confidence intervals (CIs), were obtained using Cox-regression models. Dose–response relationships were examined using a nonparametric test for trend. Results In total, 2915 BC cases and 530,012 non-cases were included in the analyses. The present study showed an increased BC risk for moderate intake of vitamin B1 (HR B1 : 1.13, 95% CI: 1.00–1.20). In men, moderate intake of the vitamins B1, B2, energy-related vitamins and high intake of vitamin B1 were associated with an increased BC risk (HR (95% CI): 1.13 (1.02–1.26), 1.14 (1.02–1.26), 1.13 (1.02–1.26; 1.13 (1.02–1.26), respectively). In women, high intake of all vitamins and vitamin combinations, except for the entire complex, showed an inverse association (HR (95% CI): 0.80 (0.67–0.97), 0.83 (0.70–1.00); 0.77 (0.63–0.93), 0.73 (0.61–0.88), 0.82 (0.68–0.99), 0.79 (0.66–0.95), 0.80 (0.66–0.96), 0.74 (0.62–0.89), 0.76 (0.63–0.92), respectively). Dose–response analyses showed an increased BC risk for higher intake of vitamin B1 and B12. Conclusion Our findings highlight the importance of future research on the food sources of B group vitamins in the context of the overall and sex-stratified diet.

60 APPLIED LIFE SCIENCES↗