Abscopal Effects in Metastatic Cancer: Is a Predictive Approach Possible to Improve Individual Outcomes?
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SUBMITTER: Link B
PROVIDER: S-EPMC8584726 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In this paper, we summarize published articles and experiences related to the attempt to improve radiotherapy outcomes and, thus, to personalize the radiation treatment according to the individual characteristics of each patient. The evolution of ideas and the study of successively published data have led us to envisage new biophysical models for the interpretation of tumor and healthy normal tissue response to radiation. In the development of the model, we have shown that when mesenchymal stem cells (MSCs) and radiotherapy are administered simultaneously in experimental radiotherapy on xenotumors implanted in a murine model, the results of the treatment show the existence of a synergic mechanism that is able to enhance the local and systemic actions of the radiation both on the treated tumor and on its possible metastasis. We are convinced that, due to the physical hallmarks that characterize the neoplastic tissues, the physical-chemical tropism of MSCs, and the widespread functions of macromolecules, proteins, and exosomes released from activated MSCs, the combination of radiotherapy plus MSCs used intratumorally has the effect of counteracting the pro-tumorigenic and pro-metastatic signals that contribute to the growth, spread, and resistance of the tumor cells. Therefore, we have concluded that MSCs are appropriate for therapeutic use in a clinical trial for rectal cancer combined with radiotherapy, which we are going to start in the near future.
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Project description:ObjectivesColorectal cancer (CRC) is one of the most common solid tumors worldwide, but its diagnosis and treatment are limited. The objectives of our study were to compare the metabolic differences between CRC patients and healthy controls (HC), and to identify potential biomarkers in the serum that can be used for early diagnosis and as effective therapeutic targets. The aim was to provide a new direction for CRC predictive, preventive, and personalized medicine (PPPM).MethodsIn this study, CRC patients (n = 30) and HC (n = 30) were recruited. Serum metabolites were assayed using an ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technology. Subsequently, CRC cell lines (HCT116 and HCT8) were treated with metabolites to verify their function. Key targets were identified by molecular docking, thermal shift assay, and protein overexpression/inhibition experiments. The inhibitory effect of celastrol on tumor growth was also assessed, which included IC50 analysis, nude mice xenografting, molecular docking, protein overexpression/inhibition experiments, and network pharmacology technology.ResultsIn the CRC group, 15 serum metabolites were significantly different in comparison with the HC group. The level of glycodeoxycholic acid (GDCA) was positively correlated with CRC and showed high sensitivity and specificity for the clinical diagnostic reference (AUC = 0.825). In vitro findings showed that GDCA promoted the proliferation and migration of CRC cell lines (HCT116 and HCT8), and Poly(ADP-ribose) polymerase-1 (PARP-1) was identified as one of the key targets of GDCA. The IC50 of celastrol in HCT116 cells was 121.1 nM, and the anticancer effect of celastrol was supported by in vivo experiments. Based on the potential of GDCA in PPPM, PARP-1 was found to be significantly correlated with the anticancer functions of celastrol.ConclusionThese findings suggest that GDCA is an abnormally produced metabolite of CRC, which may provide an innovative molecular biomarker for the predictive identification and targeted prevention of CRC. In addition, PARP-1 was found to be an important target of GDCA that promotes CRC; therefore, celastrol may be a potential targeted therapy for CRC via its effects on PARP-1. Taken together, the pathophysiology and progress of tumor molecules mediated by changes in metabolite content provide a new perspective for predictive, preventive, and personalized medical of clinical cancer patients based on the target of metabolites in vivo.Clinical trials registration number: ChiCTR2000039410.Supplementary informationThe online version contains supplementary material available at 10.1007/s13167-021-00269-8.
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Project description:Immunotherapy holds tremendous promise for improving cancer treatment. To administer radiotherapy with immunotherapy has been shown to improve immune responses and can elicit the 'abscopal effect'. Unfortunately, response rates for this strategy remain low. Herein we report an improved cancer immunotherapy approach that utilizes antigen-capturing nanoparticles (AC-NPs). We engineered several AC-NP formulations and demonstrated that the set of protein antigens captured by each AC-NP formulation is dependent on the NP surface properties. We showed that AC-NPs deliver tumour-specific proteins to antigen-presenting cells (APCs) and significantly improve the efficacy of αPD-1 (anti-programmed cell death 1) treatment using the B16F10 melanoma model, generating up to a 20% cure rate compared with 0% without AC-NPs. Mechanistic studies revealed that AC-NPs induced an expansion of CD8+ cytotoxic T cells and increased both CD4+T/Treg and CD8+T/Treg ratios (Treg, regulatory T cells). Our work presents a novel strategy to improve cancer immunotherapy with nanotechnology.
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Project description: Not available
| S-EPMC9280999 | biostudies-literature
Project description:To investigate the effects soy isoflavones in established cancers, the role of genistein, daidzein, and combined soy isoflavones was studied on progression of subcutaneous tumors in nude mice created from green fluorescent protein (GFP) tagged-MDA-MB-435 cells. Following tumor establishment, mice were gavaged with vehicle or genistein or daidzein at 10 mg/kg body weight (BW) or a combination of genistein (10 mg/kg BW), daidzein (9 mg/kg BW), and glycitein (1 mg/kg BW) three times per week. Tumor progression was quantified by whole body fluorescence image analysis followed by microscopic image analysis of excised organs for metastases. Results show that daidzein increased while genistein decreased mammary tumor growth by 38 and 33% respectively, compared to vehicle. Daidzein increased lung and heart metastases while genistein decreased bone and liver metastases. Combined soy isoflavones did not affect primary tumor growth but increased metastasis to all organs tested, which include lung, liver, heart, kidney, and bones. Phosphoinositide-3-kinase (PI3-K) pathway real time PCR array analysis and western blotting of excised tumors demonstrate that genistein significantly downregulated 10/84 genes, including the Rho GTPases RHOA, RAC1, and CDC42 and their effector PAK1. Daidzein significantly upregulated 9/84 genes that regulate proliferation and protein synthesis including EIF4G1, eIF4E, and survivin protein levels. Combined soy treatment significantly increased gene and protein levels of EIF4E and decreased TIRAP gene expression. Differential regulation of Rho GTPases, initiation factors, and survivin may account for the disparate responses of breast cancers to genistein and daidzein diets. This study indicates that consumption of soy foods may increase metastasis.
| S-EPMC2944964 | biostudies-literature
Project description:Identifying genetic variants associated with complex disease in high-dimensional data is a challenging problem, and complicated etiologies such as gene-gene interactions are often ignored in analyses. The data-mining method Random Forests (RF) can handle high-dimensions; however, in high-dimensional data, RF is not an effective filter for identifying risk factors associated with the disease trait via complex genetic models such as gene-gene interactions without strong marginal components. Here we propose an extension called Weighted Random Forests (wRF), which incorporates tree-level weights to emphasize more accurate trees in prediction and calculation of variable importance. We demonstrate through simulation and application to data from a genetic study of addiction that wRF can outperform RF in high-dimensional data, although the improvements are modest and limited to situations with effect sizes that are larger than what is realistic in genetics of complex disease. Thus, the current implementation of wRF is unlikely to improve detection of relevant predictors in high-dimensional genetic data, but may be applicable in other situations where larger effect sizes are anticipated.
| S-EPMC3912194 | biostudies-literature
Project description:BackgroundTo determine if tuberculosis (TB) screening improves patient outcomes, we conducted two systematic reviews to investigate the effect of TB screening on diagnosis, treatment outcomes, deaths (clinical review assessing 23 outcome indicators); and patient costs (economic review).MethodsPubmed, EMBASE, Scopus and the Cochrane Library were searched between 1/1/1980-13/4/2020 (clinical review) and 1/1/2010-14/8/2020 (economic review). As studies were heterogeneous, data synthesis was narrative.FindingsClinical review: of 27,270 articles, 18 (n=3 trials) were eligible. Nine involved general populations. Compared to passive case finding (PCF), studies showed lower smear grade (n=2/3) and time to diagnosis (n=2/3); higher pre-treatment losses to follow-up (screened 23% and 29% vs PCF 15% and 14%; n=2/2); and similar treatment success (range 68-81%; n=4) and case fatality (range 3-11%; n=5) in the screened group. Nine reported on risk groups. Compared to PCF, studies showed lower smear positivity among those culture-confirmed (n=3/4) and time to diagnosis (n=2/2); and similar (range 80-90%; n=2/2) treatment success in the screened group. Case fatality was lower in n=2/3 observational studies; both reported on established screening programmes. A neonatal trial and post-hoc analysis of a household contacts trial found screening was associated with lower all-cause mortality. Economic review: From 2841 articles, six observational studies were eligible. Total costs (n=6) and catastrophic cost prevalence (n=4; range screened 9-45% vs PCF 12-61%) was lower among those screened.InterpretationWe found very limited patient outcome data. Collecting and reporting this data must be prioritised to inform policy and practice.FundingWHO and EDCTP.
| S-EPMC8473670 | biostudies-literature
Project description:Perinatal asphyxia occurs still with great incidence whenever delivery is prolonged, despite improvements in perinatal care. After asphyxia, infants can suffer from short- to long-term neurological sequelae, their severity depend upon the extent of the insult, the metabolic imbalance during the re-oxygenation period and the developmental state of the affected regions. Significant progresses in understanding of perinatal asphyxia pathophysiology have achieved. However, predictive diagnostics and personalised therapeutic interventions are still under initial development. Now the emphasis is on early non-invasive diagnosis approach, as well as, in identifying new therapeutic targets to improve individual outcomes. In this review we discuss (i) specific biomarkers for early prediction of perinatal asphyxia outcome; (ii) short and long term sequelae; (iii) neurocircuitries involved; (iv) molecular pathways; (v) neuroinflammation systems; (vi) endogenous brain rescue systems, including activation of sentinel proteins and neurogenesis; and (vii) therapeutic targets for preventing or mitigating the effects produced by asphyxia.
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Project description:BackgroundThere are no accepted universal biomarkers capable to accurately predict response to immuno-checkpoint inhibitors (ICI). Although recent literature has been flooded with studies on ICI predictive biomarkers, available data show that currently approved companion diagnostics either leave out many possible responders, as in the case of PD-L1 testing for first-line metastatic lung cancer, or apply to a small subset of patients, such as the recently approved treatment for microsatellite instability-high or mismatch repair deficiency tumors. In this study, we conducted a survey of the available data on ICI trials with matched genomic or transcriptomic datasets in order to cross-validate the proposed biomarkers, to assess whether their prediction power was confirmed and, mainly, to investigate if their combination was able to generate a better predictive tool.MethodsWe extracted clinical information and sequencing data details from publicly available datasets, along with a list of possible biomarkers obtained from the recent literature. After an operation of data harmonization, we validated the performance of all the biomarkers taken individually. Furthermore, we tested two strategies to combine the best performing biomarkers in order to improve their predictive value.ResultsWhen considered individually, some of the biomarkers, such as the ImmunoPhenoScore, and the IFN-? signature, did not confirm their originally proposed predictive power. The best absolute scoring biomarkers are TIDE, one of the ICB resistance signatures and CTLA4 with a mean AUC?>?0.66. Among the combinations tested, generalized linear models showed the best performance with an AUC of 0.78.ConclusionsWe confirmed that the available biomarkers, taken individually, fail to provide a satisfactory predictive value. Unfortunately, also combination of some of them only provides marginal improvements. Hence, in order to generate a more robust way to predict ICI efficacy it is necessary to analyze and combine additional biomarkers and interrogate a wider set of clinical data.
| S-EPMC6480695 | biostudies-literature
Project description:Despite that the impact of immune checkpoint inhibitors on malignancies treatment is unprecedented, a lack of response to these molecules is observed in several cases. Differently from melanoma and non-small cell lung cancer, where the use of immune checkpoint inhibitors results in a high efficacy, the response rate in other tumors, such as gastrointestinal cancers, breast cancer, sarcomas, and part of genitourinary cancers remains low. The first strategy evaluated to improve the response rate to immune checkpoint inhibitors is the use of predictive factors for the response such as PD-L1 expression, tumor mutational burden, and clinical features. In addition to the identification of the patients with a higher expression of immune checkpoint molecules, another approach currently under intensive investigation is the use of therapeutics in a combinatory manner with immune checkpoint inhibitors in order to obtain an enhancement of efficacy through the modification of the tumor immune microenvironment. In addition to the abscopal effect induced by radiotherapy, a lot of studies are evaluating several drugs able to improve the response rate to immune checkpoint inhibitors, including microbiota modifiers, drugs targeting co-inhibitory receptors, anti-angiogenic therapeutics, small molecules, and oncolytic viruses. In view of the rapid and extensive development of this research field, we conducted a systematic review of the literature identifying which of these drugs are closer to achieving validation in the clinical practice.
| S-EPMC6521062 | biostudies-literature