Principal component analysis identifies patterns of cytokine expression in non-small cell lung cancer patients undergoing definitive radiation therapy

Baseline Cytokine Profile Identifies a Favorable Outcome in a Subgroup of Colorectal Cancer Patients Treated with Regorafenib

Metastatic colorectal cancer is frequently associated with poor clinical conditions that may limit therapeutic options. Regorafenib is a small molecule approved for the treatment of metastatic colorectal cancer, but it is hampered by significative toxicities. Moreover, only a relatively limited number of patients benefit from the treatment. Therefore, the identification of reliable markers for response is an unmet need. Eighteen cytokines, selected based on their prevalent Th1 or Th2 effects, were collected. Peripheral blood samples were gathered at baseline in 25 metastatic colorectal cancer patients treated with regorafenib. Data extracted have been linked to progression-free survival. ROC identified the best cytokines associated with outcome. The relative value of the selected cytokines was determined by PCA. Data analysis identified 8 cytokines (TGF-β, TNF-α, CCL-2, IL-6, IL-8, IL-10, IL-13 and IL-21), used to create a signature (TGF-β, TNF-α high; CCL-2, IL-6, IL-8, IL-10, IL-13 and IL-21 low) corresponding to patients with a significantly longer progression-free survival. This report suggests that the analysis of multiple cytokines might identify a cytokine signature related to a patient's outcome that is able to recognize patients who will benefit from treatment. If confirmed, future studies, also based on different drugs, using this approach and including larger patient populations, might identify a signature allowing the a priori identification of patients to be treated.

A Comprehensive Analysis of Cytokine Network in Centenarians

Cytokines have been investigated extensively in elderly people, with conflicting results. We performed a comprehensive analysis of the plasma levels of 62 cytokines and growth factors involved in the regulation of the immune system, in healthy centenarians, and middle-aged controls. We confirmed the previously observed increase in the levels of several pro-inflammatory cytokines, such as TNF-α and IL-6, and found that several other cytokines, directly or indirectly involved in inflammation (such as IFN-α, IL-23, CCL-5), were present at higher levels in centenarians. We did not observe any increase in the levels of anti-inflammatory cytokines, with the notable exception of the Th2-shifting cytokine IL-19. No relevant difference was observed in cytokines regulating T cell immunity. Several growth factors having a role in regulating immunity, such as G-CSF, GM-CSF, EGF, and VEGF, were upregulated in centenarians, too. Principal component analysis of the cytokine dataset showed that pro and anti-inflammatory cytokines were the variables that contributed the most to the variability of the data we observed.

Standardized Whole Blood Assay and Bead-Based Cytokine Profiling Reveal Commonalities and Diversity of the Response to Bacteria and TLR Ligands in Cattle

Recent developments in multiplex technologies enable the determination of a large nu\mber of soluble proteins such as cytokines in various biological samples. More than a one-by-one determination of the concentration of immune mediators, they permit the establishment of secretion profiles for a more accurate description of conditions related to infectious diseases or vaccination. Cytokine profiling has recently been made available for bovine species with the development of a Luminex^® technology-based 15-plex assay. Independently from the manufacturer, we evaluated the bovine cytokine/chemokine multiplex assay for limits of detection, recovery rate, and reproducibility. Furthermore, we assessed cytokine secretion in blood samples from 107 cows upon stimulation with heat-killed bacteria and TLR2/4 ligands compared to a null condition. Secretion patterns were analyzed either using the absolute concentration of cytokines or using their relative concentration with respect to the overall secretion level induced by each stimulus. Using Partial Least Square-Discriminant Analysis, we show that the 15-cytokine profile is different under Escherichia coli, Staphylococcus aureus, and Streptococcus uberis conditions, and that IFN-γ, IL-1β, and TNF-α contribute the most to differentiate these conditions. LPS and E. coli induced largely overlapping biological responses, but S. aureus and S. uberis were associated with distinct cytokine profiles than their respective TLR ligands. Finally, results based on adjusted or absolute cytokine levels yielded similar discriminative power, but led to different stimuli-related signatures.

Biological Adaptations of Tumor Cells to Radiation Therapy

Radiation therapy has been used worldwide for many decades as a therapeutic regimen for the treatment of different types of cancer. Just over 50% of cancer patients are treated with radiotherapy alone or with other types of antitumor therapy. Radiation can induce different types of cell damage: directly, it can induce DNA single- and double-strand breaks; indirectly, it can induce the formation of free radicals, which can interact with different components of cells, including the genome, promoting structural alterations. During treatment, radiosensitive tumor cells decrease their rate of cell proliferation through cell cycle arrest stimulated by DNA damage. Then, DNA repair mechanisms are turned on to alleviate the damage, but cell death mechanisms are activated if damage persists and cannot be repaired. Interestingly, some cells can evade apoptosis because genome damage triggers the cellular overactivation of some DNA repair pathways. Additionally, some surviving cells exposed to radiation may have alterations in the expression of tumor suppressor genes and oncogenes, enhancing different hallmarks of cancer, such as migration, invasion, and metastasis. The activation of these genetic pathways and other epigenetic and structural cellular changes in the irradiated cells and extracellular factors, such as the tumor microenvironment, is crucial in developing tumor radioresistance. The tumor microenvironment is largely responsible for the poor efficacy of antitumor therapy, tumor relapse, and poor prognosis observed in some patients. In this review, we describe strategies that tumor cells use to respond to radiation stress, adapt, and proliferate after radiotherapy, promoting the appearance of tumor radioresistance. Also, we discuss the clinical impact of radioresistance in patient outcomes. Knowledge of such cellular strategies could help the development of new clinical interventions, increasing the radiosensitization of tumor cells, improving the effectiveness of these therapies, and increasing the survival of patients.

Transcriptomic and microRNA Expression Profiles Identify Biomarkers for Predicting Neo-Chemoradiotherapy Response in Esophageal Squamous Cell Carcinomas (ESCC)

Neo-chemoradiotherapy (nCRT) before surgery is a standard treatment for locally advanced esophageal cancers. However, the treatment outcome of nCRT varied with different patients. This study aimed to identify potential biomarkers for prediction of nCRT-response in patients with esophageal squamous cell carcinoma (ESCC). Microarray datasets of nCRT responder and non-responder samples (access number GSE45670 and GSE59974) of patients with ESCC were downloaded from Gene Expression Omnibus (GEO) database. The mRNA expression profiles of cancer biopsies from four ESCC patients were analyzed before and after nCRT. Differentially expressed genes (DEGs) and miRNAs were screened between nCRT responder and non-responder ESCC samples. Functional enrichment analysis was conducted for these DEGs followed by construction of protein-protein interaction (PPI) network and miRNA-mRNA regulatory network. Finally, univariate survival analysis was performed to identify candidate biomarkers with prognostic values in ESCC. We identified numerous DEGs and differentially expressed miRNAs from nCRT responder group. GO and KEGG analysis showed that the dysregulated genes were mainly involved in biological processes and pathways, including "response to stimulus", "cellular response to organic substance", "regulation of signal transduction", "AGE-RAGE signaling pathway in diabetic complications", and "steroid hormone biosynthesis". After integration of PPI network and miRNA-mRNA network analysis, we found eight genes, TNF, AKR1C1, AKR1C2, ICAM1, GPR68, GNB4, SERPINE1 and MMP12, could be candidate genes associated with disease progression. Univariate cox regression analysis showed that there was no significant correlation between dysregulated miRNAs (such as hsa-miR-34b-3p, hsa-miR-127-5p, hsa-miR-144-3p, and hsa-miR-486-5p, et al.) and overall survival of ESCC patients. Moreover, abnormal expression of MMP12 was significantly correlated with pathological degree, TNM stage, lymph nodes metastasis, and overall survival of ESCC patients (p < 0.05). Taken together, our study identified that MMP12 might be a useful tumor biomarker and therapeutic target for ESCC.

Weighted-Support Vector Machine Learning Classifier of Circulating Cytokine Biomarkers to Predict Radiation-Induced Lung Fibrosis in Non-Small-Cell Lung Cancer Patients

Background

Radiation-induced lung fibrosis (RILF) is an important late toxicity in patients with non-small-cell lung cancer (NSCLC) after radiotherapy (RT). Clinically significant RILF can impact quality of life and/or cause non-cancer related death. This study aimed to determine whether pre-treatment plasma cytokine levels have a significant effect on the risk of RILF and investigate the abilities of machine learning algorithms for risk prediction.

Methods

This is a secondary analysis of prospective studies from two academic cancer centers. The primary endpoint was grade≥2 (RILF2), classified according to a system consistent with the consensus recommendation of an expert panel of the AAPM task for normal tissue toxicity. Eligible patients must have at least 6 months’ follow-up after radiotherapy commencement. Baseline levels of 30 cytokines, dosimetric, and clinical characteristics were analyzed. Support vector machine (SVM) algorithm was applied for model development. Data from one center was used for model training and development; and data of another center was applied as an independent external validation.

Results

There were 57 and 37 eligible patients in training and validation datasets, with 14 and 16.2% RILF2, respectively. Of the 30 plasma cytokines evaluated, SVM identified baseline circulating CCL4 as the most significant cytokine associated with RILF2 risk in both datasets (P = 0.003 and 0.07, for training and test sets, respectively). An SVM classifier predictive of RILF2 was generated in Cohort 1 with CCL4, mean lung dose (MLD) and chemotherapy as key model features. This classifier was validated in Cohort 2 with accuracy of 0.757 and area under the curve (AUC) of 0.855.

Conclusions

Using machine learning, this study constructed and validated a weighted-SVM classifier incorporating circulating CCL4 levels with significant dosimetric and clinical parameters which predicts RILF2 risk with a reasonable accuracy. Further study with larger sample size is needed to validate the role of CCL4, and this SVM classifier in RILF2.

Association of pro-inflammatory soluble cytokine receptors early during hepatocellular carcinoma stereotactic radiotherapy with liver toxicity

Plasma levels of soluble factors early during hepatocellular carcinoma (HCC) stereotactic body radiotherapy (SBRT) were evaluated in relation to radiation liver injury, tumor response, and risk of early death. No significant differences were found in baseline plasma levels of AFP, CXCL1, and HGF amongst HCC patients with different Child Pugh scores. Higher levels of sTNFRII (P < 0.001), and lower levels of sCD40L (P < 0.001) and CXCL1 (P = 0.01) following one to two fractions of SBRT were noted in patients who developed liver toxicity vs. those who did not. High circulating levels of AFP (HR 2.16, P = 0.04), sTNFRII (HR 2.27, P = 0.01), and sIL-6R (HR 1.99, P = 0.03) early during SBRT were associated with increased risk of death 3 months post treatment. Plasma levels of the studied factors early during SBRT were not associated with tumor response. A pro-inflammatory systemic environment is associated with development of liver toxicity and increased risk of early death following SBRT.

Irradiated Bladder Cancer Cells Expressing both GM-CSF and IL-21 versus Either GM-CSF or IL-21 Alone as Tumor Vaccine in a Mouse Xenograft Model

Previous studies have established the efficacy of irradiated cancer cells overexpressing GM-CSF or IL-21 as a vaccine. Here we examined whether the vaccine efficacy was greater when both factors were overexpressed together. MB49 bladder cancer cells were transfected with expression plasmid pT7TS encoding mouse GM-CSF and human IL-21, and then irradiated with 100 Gy at 4 days later. The cells (1×10⁷ per animal) were injected subcutaneously into C57BL/6 mice at 0, 4, 8, and 12 days after inoculation with MB49 tumor xenografts. Control animals were injected with MB49 cells transfected with pT7TS encoding GM-CSF or IL-21 on its own. Tumor growth was monitored for 45 days and compared among the groups using repeated-measures ANOVA. Vaccination with irradiated MB49 cells did not affect xenograft growth. Vaccination with irradiated cells overexpressing GM-CSF or IL-21 alone significantly inhibited tumor growth and led to significantly more CD4⁺ CD8⁺ T cells and fewer CD4⁺ Foxp3⁺ T cells in the spleen and xenograft. These effects were even greater following vaccination with irradiated cells overexpressing both GM-CSF and IL-21. Irradiated bladder cancer cells overexpressing both GM-CSF and IL-21 are more effective than cells expressing either factor alone as a vaccine against bladder cancer.

Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer

PURPOSE

Radiation pneumonitis is an important adverse event in patients with non-small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypothesized that inflammatory cytokines or the dynamic changes during radiotherapy can improve predictive accuracy for RP2.

EXPERIMENTAL DESIGN

Levels of 30 inflammatory cytokines and clinical information in patients with stages I-III NSCLC treated with radiotherapy were from our prospective studies. Statistical analysis was used to select predictive cytokine candidates and clinical covariates for adjustment. Machine learning algorithm was used to develop the generalized linear model for predicting risk RP2.

RESULTS

A total of 131 patients were eligible and 17 (13.0%) developed RP2. IL8 and CCL2 had significantly (Bonferroni) lower expression levels in patients with RP2 than without RP2. But none of the changes in cytokine levels during radiotherapy was significantly associated with RP2. The final predictive GLM model for RP2 was established, including IL8 and CCL2 at baseline level and two clinical variables. Nomogram was constructed based on the GLM model. The model's predicting ability was validated in the completely independent test set (AUC = 0.863, accuracy = 80.0%, sensitivity = 100%, specificity = 76.5%).

CONCLUSIONS

By machine learning, this study has developed and validated a comprehensive model integrating inflammatory cytokines with clinical variables to predict RP2 before radiotherapy that provides an opportunity to guide clinicians.

Cytokines and radiation-induced pulmonary injuries

Radiation therapy is one of the most common treatment strategies for thorax malignancies. One of the considerable limitations of this therapy is its toxicity to normal tissue. The lung is the major dose-limiting organ for radiotherapy. That is because ionizing radiation produces reactive oxygen species that induce lesions, and not only is tumor tissue damaged, but overwhelming inflammatory lung damage can occur in the alveolar epithelium and capillary endothelium. This damage may result in radiation-induced pneumonitis and/or fibrosis. While describing the lung response to irradiation generally, the main focus of this review is on cytokines and their roles and functions within the individual stages. We discuss the relationship between radiation and cytokines and their direct and indirect effects on the formation and development of radiation injuries. Although this topic has been intensively studied and discussed for years, we still do not completely understand the roles of cytokines. Experimental data on cytokine involvement are fragmented across a large number of experimental studies; hence, the need for this review of the current knowledge. Cytokines are considered not only as molecular factors involved in the signaling network in pathological processes, but also for their diagnostic potential. A concentrated effort has been made to identify the significant immune system proteins showing positive correlation between serum levels and tissue damages. Elucidating the correlations between the extent and nature of radiation-induced pulmonary injuries and the levels of one or more key cytokines that initiate and control those damages may improve the efficacy of radiotherapy in cancer treatment and ultimately the well-being of patients.