Polymorphisms in BMP2/BMP4, with estimates of mean lung dose, predict radiation pneumonitis among patients receiving definitive radiotherapy for non-small cell lung cancer

Integrative prediction model for radiation pneumonitis incorporating genetic and clinical-pathological factors using machine learning

Purpose

We aimed to develop a machine learning-based prediction model for severe radiation pneumonitis (RP) by integrating relevant clinicopathological and genetic factors, considering the associations of clinical, dosimetric parameters, and single nucleotide polymorphisms (SNPs) of genes in the TGF-β1 pathway with RP.

Methods

We prospectively enrolled 59 primary lung cancer patients undergoing radiotherapy and analyzed pretreatment blood samples, clinicopathological/dosimetric variables, and 11 functional SNPs in TGFβ pathway genes. Using the Synthetic Minority Over-sampling Technique (SMOTE) and nested cross-validation, we developed a machine learning-based prediction model for severe RP (grade ≥ 2). Feature selection was conducted using four methods (filtered-based, wrapper-based, embedded, and logistic regression), and performance was evaluated using three machine learning models.

Results

Severe RP occurred in 20.3 % of patients with a median follow-up of 39.7 months. In our final model, age (>66 years), smoking history, PTV volume (>300 cc), and AG/GG genotype in BMP2 rs1979855 were identified as the most significant predictors. Additionally, incorporating genomic variables for prediction alongside clinicopathological variables significantly improved the AUC compared to using clinicopathological variables alone (0.822 vs. 0.741, p = 0.029). The same feature set was selected using both the wrapper-based method and logistic model, demonstrating the best performance across all machine learning models (AUC: XGBoost 0.815, RF 0.805, SVM 0.712, respectively).

Conclusion

We successfully developed a machine learning-based prediction model for RP, demonstrating age, smoking history, PTV volume, and BMP2 rs1979855 genotype as significant predictors. Notably, incorporating SNP data significantly enhanced predictive performance compared to clinicopathological factors alone.

Radiogenomics in lung cancer: Where are we?

Huge technological and biomedical advances have improved the survival and quality of life of lung cancer patients treated with radiotherapy. However, during treatment planning, a probability that the patient will experience adverse effects is assumed. Radiotoxicity is a complex entity that is largely dose-dependent but also has important intrinsic factors. One of the most studied is the genetic variants that may be associated with susceptibility to the development of adverse effects of radiotherapy. This review aims to present the current status of radiogenomics in lung cancer, integrating results obtained in association studies of SNPs (single nucleotide polymorphisms) related to radiotherapy toxicities. We conclude that despite numerous publications in this field, methodologies and endpoints vary greatly, making comparisons between studies difficult. Analyzing SNPs from the candidate gene approach, together with the study in cohorts limited by the sample size, has complicated the possibility of having validated results. All this delays the incorporation of genetic biomarkers in predictive models for clinical application. Thus, from all analysed SNPs, only 12 have great potential as esophagitis genetic risk factors and deserve further exploration. This review highlights the efforts that have been made to date in the radiogenomic study of radiotoxicity in lung cancer.

Circ 003390/Eukaryotic translation initiation factor 4A3 promoted cell migration and proliferation in endometrial cancer via vascular endothelial growth factor signaling by miR-195-5p

The differential expression of circRNA in different biological samples renders it as an ideal biomarker for disease diagnosis and identification of tissue development. In addition, the gradual clarification of the mode of action of circRNA in disease makes it as a potential therapeutic target. The purpose of this study is to investigate the role and regulating mechanism of circular RNA has circ 003390 (circWEE1) on Endometrial cancer (EC) genesis. To estimate clinical values of circWEE1 on cell migration and proliferation in EC, and its possible mechanisms. The expression of circWEE1 and EIF4A3in EC cells have been evaluated using qPCR and Western blot. The expression of circWEE1 and EIF4A3 levels were increased in patients with EC. Over-expression of circWEE1 or down-regulation of miR-195-5p promoted cell migration and proliferation in EC. Next, we verified that eIF4A3 binds to the circWEE1 mRNA transcript, circWEE1 served as a sponge that directly targeted miR-195-5p. Bioinformatics prediction forecast that miR-195-5p directly targeted VEGF at 3'-UTR, which was confirmed by luciferase reporter assay. Our findings indicate that Circular RNA hsa circWEE1/EIF4A3 promoted cell migration and proliferation in EC via VEGF signaling by miR-195-5p, which could provide pivotal potential therapeutic targets for the treatment of EC.

Genetic Variations in the Transforming Growth Factor-β1 Pathway May Improve Predictive Power for Overall Survival in Non-small Cell Lung Cancer

Purpose: Transforming growth factor-β1 (TGF-β1), a known immune suppressor, plays an important role in tumor progression and overall survival (OS) in many types of cancers. We hypothesized that genetic variations of single nucleotide polymorphisms (SNPs) in the TGF-β1 pathway can predict survival in patients with non-small cell lung cancer (NSCLC) after radiation therapy. Materials and Methods: Fourteen functional SNPs in the TGF-β1 pathway were measured in 166 patients with NSCLC enrolled in a multi-center clinical trial. Clinical factors, including age, gender, ethnicity, smoking status, stage group, histology, Karnofsky Performance Status, equivalent dose at 2 Gy fractions (EQD2), and the use of chemotherapy, were first tested under the univariate Cox's proportional hazards model. All significant clinical predictors were combined as a group of predictors named "Clinical." The significant SNPs under the Cox proportional hazards model were combined as a group of predictors named "SNP." The predictive powers of models using Clinical and Clinical + SNP were compared with the cross-validation concordance index (C-index) of random forest models. Results: Age, gender, stage group, smoking, histology, and EQD2 were identified as significant clinical predictors: Clinical. Among 14 SNPs, BMP2:rs235756 (HR = 0.63; 95% CI:0.42-0.93; p = 0.022), SMAD9:rs7333607 (HR = 2.79; 95% CI 1.22-6.41; p = 0.015), SMAD3:rs12102171 (HR = 0.68; 95% CI: 0.46-1.00; p = 0.050), and SMAD4: rs12456284 (HR = 0.63; 95% CI: 0.43-0.92; p = 0.016) were identified as powerful predictors of SNP. After adding SNP, the C-index of the model increased from 84.1 to 87.6% at 24 months and from 79.4 to 84.4% at 36 months. Conclusion: Genetic variations in the TGF-β1 pathway have the potential to improve the prediction accuracy for OS in patients with NSCLC.

Low dose ionizing radiation effects on the immune system

Ionizing radiation interacts with the immune system in many ways with a multiplicity that mirrors the complexity of the immune system itself: namely the need to maintain a delicate balance between different compartments, cells and soluble factors that work collectively to protect, maintain, and restore tissue function in the face of severe challenges including radiation damage. The cytotoxic effects of high dose radiation are less relevant after low dose exposure, where subtle quantitative and functional effects predominate that may go unnoticed until late after exposure or after a second challenge reveals or exacerbates the effects. For example, low doses may permanently alter immune fitness and therefore accelerate immune senescence and pave the way for a wide spectrum of possible pathophysiological events, including early-onset of age-related degenerative disorders and cancer. By contrast, the so called low dose radiation therapy displays beneficial, anti-inflammatory and pain relieving properties in chronic inflammatory and degenerative diseases. In this review, epidemiological, clinical and experimental data regarding the effects of low-dose radiation on the homeostasis and functional integrity of immune cells will be discussed, as will be the role of immune-mediated mechanisms in the systemic manifestation of localized exposures such as inflammatory reactions. The central conclusion is that ionizing radiation fundamentally and durably reshapes the immune system. Further, the importance of discovery of immunological pathways for modifying radiation resilience amongst other research directions in this field is implied.

Precision radiotherapy for non-small cell lung cancer

Precision medicine is becoming the standard of care in anti-cancer treatment. The personalized precision management of cancer patients highly relies on the improvement of new technology in next generation sequencing and high-throughput big data processing for biological and radiographic information.

Systemic precision cancer therapy has been developed for years. However, the role of precision medicine in radiotherapy has not yet been fully implemented. Emerging evidence has shown that precision radiotherapy for cancer patients is possible with recent advances in new radiotherapy technologies, panomics, radiomics and dosiomics.

This review focused on the role of precision radiotherapy in non-small cell lung cancer and demonstrated the current landscape.

Validation study of the association between genetic variant of IL4 and severe radiation pneumonitis in lung cancer patients treated with radiation therapy

BACKGROUND AND PURPOSE

Recent researches demonstrated that single nucleotide polymorphisms (SNPs) of genes involving inflammation, DNA repair, etc. were associated with risk of radiation pneumonitis (RP). However, these studies were single-centered, from single ethnic origin, without validation from independent cohort studies from other populations. In order to identify clinical valuable SNPs for RP, in this study we selected 19 RP-related SNPs candidates previously published before 2016 for validation in our cohort.

MATERIAL AND METHODS

359 lung cancer patients with radiotherapy were included in our prospective study (NCT02490319). Peripheral blood samples from these patients were genotyped by MassArray and Sanger Sequence method. Multivariate Cox hazard and other analyses were applied to estimate the hazard ratio (HR) and 95% confidence intervals (CIs) of all factors possibly related to the risk of RP.

RESULTS

Patients with elder age, MLD ≥15 Gy, V₂₀ ≥24% had higher risk of RP ≥grade 3 compared with their counterparts (HR = 2.020, 95% CI: 1.045-3.906, P = 0.037; HR = 2.502, 95% CI: 1.346-4.652, P = 0.004; HR = 2.256, 95% CI: 1.191-4.272, P = 0.013, respectively). Moreover, patients receiving IMRT were associated with decreased incidence of RP (HR = 0.520, 95% CI: 0.280-0.963, P = 0.037). Importantly, CT + TT genotype of IL4: rs2243250 was strongly related to decreased risk of RP ≥grade 3 (HR = 0.195, 95% CI: 0.090-0.424, P = 0.000037, P_c = 0.0006).

CONCLUSION

IL4: rs2243250 was validated to be significantly related to RP of grade ≥3 in our cohort. Our results further emphasized the prevalence and clinical value of IL4: rs2243250 on RP, and may thus be one of the important predictors of severe RP before radiotherapy.

The single nucleotide variant rs2868371 associates with the risk of mortality in non-small cell lung cancer patients: A multicenter prospective validation

BACKGROUND AND PURPOSE

Definitive radiation therapy (RT) with or without chemotherapy has become the standard treatment for non-metastatic unresectable non-small cell lung cancer (NSCLC). However, treatment outcomes can differ substantially and patients' genetic background could play a crucial role. Potential associations between single-nucleotide polymorphisms (SNP) in Heat shock protein beta-1 (HSPB1) and survival have been reported in prior single-institution retrospective reports.

MATERIALS AND METHODS

The current assay aims to validate such connection in a prospective multicenter study in a European cohort including 181 NSCLC patients. Median follow-up time for all patients was 13 months (range, 3-57 months).

RESULTS

The results obtained show an association between the rs2868371 GG genotype and better overall survival (HR: 0.35; 95%CI: 0.13-0.96; p = 0.042) in multivariate analysis. Two-year overall survival rate was 72% for patients carrying the rs2868371 GG genotype versus 36% for those patients harboring the rs2868371 CC/CG genotypes (p = 0.013). Additionally, the rs2868371 GG genotype was found to be associated with better disease-free survival in the multivariate analysis (HR: 0.36; 95%CI: 0.13-0.99; p = 0.048). In silico analysis of the potential functional SNP suggested significant difference in the affinity of the Glucocorticoid Receptor binding site between alternative allelic variants, confirmed by chromatin immunoprecipitation analysis displaying stronger affinity for the risk allele (C). Furthermore, our findings indicate that the rs2868371 influences (mRNA) HSPB1 expression, offering insight into the regulation of HSPB1 transcription.

CONCLUSION

The functional HSPB1 rs2868371 promoter variant may affect lung cancer survival by regulation of HSPB1 expression levels through glucocorticoid receptor interaction.

Nomograms incorporating genetic variants in BMP/Smad4/Hamp pathway to predict disease outcomes after definitive radiotherapy for non-small cell lung cancer

Hepcidin is crucial in regulating iron metabolism, and increased serum levels were strongly linked with poor outcomes in various malignancies. Thus, we investigated if genetic variants in the BMP/Smad4/Hamp hepcidin-regulating pathway were associated with outcomes in patients receiving definitive radiotherapy for NSCLC. Subjects were 664 NSCLC patients who received ≥60 Gy radiotherapy for NSCLC retrospectively identified from a single-institution database. Potentially, functional and tagging single nucleotide polymorphisms (SNPs) of BMP2 (rs170986, rs1979855, rs1980499, rs235768, and rs3178250), BMP4 (rs17563, rs4898820, and rs762642), Smad4 (rs12456284), and Hamp (rs1882694, rs10402233, rs10421768, and rs12971321) were genotyped by TaqMan real-time polymerase chain reaction. Cox proportional hazard's analyses were used to assess potential influences of SNPs on overall survival (OS), local-regional progression-free survival (LRPFS), progression-free survival (PFS), and distant metastasis-free survival (DMFS). Nomogram of each endpoint model was developed using R project. The median patient age was 66 years. Most (488 [73.2%]) had stage III NSCLC. Age, disease stage, receipt of concurrent chemotherapy, and gross tumor volume were independent factors of OS. Hamp rs1882694 AC/CC genotypes were associated with poor OS, LRPFS, PFS, and DMFS in multivariate analyses. Besides, BMP2 rs1979855, rs3178250, and rs1980499 associated with PFS; Hamp rs10402233 and BMP2 rs1979855 associated with LRPFS; BMP2 rs3178250 associated with DMFS after adjustment for clinical factors. After adding SNPs to each model, all the likelihood ratios were increased; the nomograms were improved significantly to predict LRPFS (P < 0.001) and PFS (P < 0.001), and marginally to predict OS (P = 0.056) and DM (P = 0.057). Our nomograms incorporating significant SNPs in the BMP/Smad4/Hamp hepcidin-regulating pathway could improve the prediction of outcomes in patients given definitive radiotherapy for NSCLC. Intensified follow-ups would be recommended for patients with unfavorable outcomes identified in nomograms. Due to the rapid developments of targeted therapies and immunotherapies for NSCLC, it is necessary to further validate our findings in patients receiving such treatments.