Pneumonitis with combined immune checkpoint inhibitors and chemoradiotherapy in locally advanced non-small-cell lung cancer: a systematic review and meta-analysis.

Aims: This study systematically evaluated cases of pneumonitis following combined immune checkpoint inhibitors (ICI) and chemoradiotherapy (CRT) for locally advanced non-small-cell lung cancer (LA-NSCLC). Methods: Studies from Embase, PubMed and the Cochrane Library on patients with LA-NSCLC who received CRT and ICIs were reviewed. The primary outcomes were rates of all-grade, grade 3-5 and grade 5 pneumonitis. Results: Overall, 35 studies involving 5000 patients were enrolled. The pooled rates of all-grade, grade 3-5 and grade 5 pneumonitis were 33.0% (95% CI: 23.5-42.6), 6.1% (95% CI: 4.7-7.4) and 0.8% (95% CI: 0.3-1.2), respectively, with 7.6% of patients discontinuing ICIs because of pneumonitis. Conclusion: The incidence rates of pneumonitis following combined CRT and ICIs for LA-NSCLC were acceptable. However, the pulmonary toxicity of concurrent CRT and nivolumab plus ipilimumab should be noted.

Combined immune checkpoint inhibitors (ICI) and chemoradiotherapy (CRT) may cause severe pneumonitis due to overlapped pulmonary toxicity. However, the safety data on pneumonitis are limited to a small number of prospective clinical trials and retrospective studies with limited evidence. Thus we conducted a systematic review of pneumonitis in relation to the combination treatment. A total of 35 studies, involving 5000 patients, were included for the final analysis. The pooled rates of all-grade, grade 3­5 and grade 5 pneumonitis were 33.0, 6.1 and 0.8%, respectively, and 7.6% of patients stopped taking ICIs because of pneumonitis. The pneumonitis rates following combined CRT and ICIs for LA-NSCLC were acceptable, but the pulmonary toxicity of concurrent CRT and nivolumab plus ipilimumab should be noted.

Genome-wide DNA methylation signature predict clinical benefit of bevacizumab in non-small cell lung cancer.

BACKGROUND: The efficacy of bevacizumab in non-small cell lung cancer (NSCLC) patients is unsatisfactory, and the selection of suitable patients is still challenging. Given the epigenetic modifications can contribute to an aberrant regulation of angiogenesis and microenvironment, we investigated DNA methylation profiles to determine clinical benefit of bevacizumab in NSCLC patients. METHODS: Genome-wide DNA methylation profiling was performed in NSCLC patients treated with chemotherapy in combination with bevacizumab. Patients were divided into better prognosis group (A group) and inferior prognosis group (B group) based on their survival. The difference of methylation patterns and respective functional enrichment analysis were performed between two groups. Prognostic DNA methylation signature for bevacizumab was established with the least absolute shrinkage and selection operator regression analyses. TISIDB database was further used to infer immunological relationship for prognostic related DNA methylation. RESULTS: Twenty patients were included in this study, and significantly distinct methylation patterns were observed between patients with different prognosis. Related genes of different methylation regions were significantly enriched in the biological process of cell projection assembly, neutrophil mediated immunity, and pathway of VEGFA-VEGFR2 signaling pathway, neutrophil degranulation. A 10-gene DNA methylation signature for prognosis prediction was established with the C-index of 0.76. And host genes of signature were found to be related to the abundance of ActCD4, Th1, ActCD8, NKT and neutrophil cells. CONCLUSION: The 10-gene DNA methylation signature could serve as a novel biomarker to predict the clinical benefit of bevacizumab therapy and improve this anti-tumor approach for NSCLC patients.

The soybean plasma membrane-localized cation/H+ exchanger GmCHX20a plays a negative role under salt stress.

Cation/H+ -exchanger (CHX) perform diverse functions in plants, including being a part of the protective mechanisms to cope with salt stress. GmCHX1 has been previously identified as the causal gene in a major salt-tolerance quantitative trait locus (QTL) in soybean, but little is known about another close paralog, GmCHX20a, found in the same QTL. In this study, GmCHX20a was characterized along with GmCHX1. The expression patterns of the two genes and the direction of Na+ flux directed by overexpression of these two transporters are different, suggesting that they are functionally distinct. The ectopic expression of GmCHX20a led to an increase in salt sensitivity and osmotic tolerance, which was consistent with its role in increasing Na+ uptake into the root. Although this seems counter-intuitive, it may in fact be part of the mechanism by which soybean could counter act the effects of osmotic stress, which is commonly manifested in the initial stage of salinity stress. On the other hand, GmCHX1 from salt-tolerant soybean was shown to protect plants via Na+ exclusion under salt stress. Taken together these results suggest that GmCHX20a and GmCHX1 might work complementally through a concerted effort to address both osmotic stress and ionic stress as a result of elevated salinity.

East Asian patients who received immunotherapy-based therapy associated with improved survival benefit in advanced non-small cell lung cancer: An updated meta-analysis.

BACKGROUND: Immune checkpoint inhibitors (ICIs) combined with chemotherapy have been recommended as the standard treatment for advanced NSCLC patients without driver-gene mutations. However, there are different genetic characteristics and biological traits of tumors between non-East Asian (nEA) and East Asian (EA) patients with NSCLC, which may contribute to differences in the efficacy of ICIs in different ethnic populations. Previous findings regarding differences in the efficacy of ICIs among ethnic groups have been inconsistent. Therefore, we performed a meta-analysis by collecting published data to investigate the clinical outcomes of ICIs for EA NSCLC patients compared to nEA patients. METHODS: Overall survival (OS) and progression-free survival (PFS) were used to access the difference in survival outcomes between the two populations. Subgroup analyses were performed based on the line of ICIs, the use of ICIs alone or in combination, and the type of ICIs. RESULTS: A total of 9826 NSCLC patients from 21 randomized controlled trials (RCTs) with 4064 EAs were included, which involved PD-1, PD-L1, and CTLA-4 inhibitors. EA NSCLC patients who received ICIs-based therapy were associated with significantly improved survival benefits in OS (p = 0.02) compared with nEA patients. Subgroup analysis indicated that EA patients receiving first-line ICIs showed significantly superior OS compared with nEA patients (p = 0.007). Chemo-ICIs treatment showed significant advantages in terms of OS (p = 0.002) and PFS (p = 0.02) among EA patients compared to nEA patients. In addition, PD-1 inhibitors were associated with improved OS among both EA patients and nEA patients compared with PD-L1 inhibitors. CONCLUSION: EA NSCLC patients who received ICIs-based therapy were associated with significantly improved survival benefits compared with nEA NSCLC patients. Earlier intervention with ICIs and combination treatment was more recommended for EA NSCLC patients. Moreover, PD-1 inhibitors are associated with prolonged survival among both EA and nEA patients.

Development and Validation of Nomograms for Predicting Pneumonia in Patients with COVID-19 and Lung Cancer.

Background: COVID-19 has spread worldwide, becoming a global threat to public health and can lead to complications, especially pneumonia, which can be life-threatening. However, in lung cancer patients, the prediction of pneumonia and severe pneumonia has not been studied. We aimed to develop effective models to assess pneumonia after SARS-CoV-2 infection in lung cancer patients to guide COVID-19 management. Methods: We retrospectively recruited 621 lung cancer patients diagnosed with COVID-19 via SARS-CoV-2 RT-PCR analysis in two medical centers and divided into training and validation group, respectively. Univariate and multivariate logistic regression analysis were used to identify independent risk factors of all-grade pneumonia and ≥ grade 2 pneumonia in the training group. Nomograms were established based on independent predictors and verified in the validation group. C-index, ROC curves, calibration curve, and DCA were used to evaluate the nomograms. Subgroup analyses in immunotherapy or thoracic radiotherapy patients were then conducted. Results: Among 621 lung cancer patients infected with SARS-CoV-2, 203 (32.7%) developed pneumonia, and 66 (10.6%) were ≥ grade 2. Multivariate logistic regression analysis showed that diabetes, thoracic radiotherapy, low platelet and low albumin at diagnosis of COVID-19 were significantly associated with all-grade pneumonia. The C-indices of the prediction nomograms in the training group and validation group were 0.702 and 0.673, respectively. Independent predictors of ≥ grade 2 pneumonia were age, KPS, thoracic radiotherapy, platelet and albumin at COVID 19 diagnosis, with C-indices of 0.811 and 0.799 in the training and validation groups. In the thoracic radiotherapy subgroup, 40.8% and 11% patients developed all-grade and ≥grade 2 pneumonia, respectively. The rates in the immunotherapy subgroup were 31.3% and 6.6%, respectively. Conclusion: We developed nomograms predicting the probability of pneumonia in lung cancer patients infected with SARS-CoV-2. The models showed good performance and can be used in the clinical management of COVID-19 in lung cancer patients. Higher-risk patients should be managed with enhanced protective measures and appropriate intervention.

Improving the efficacy of combined radiotherapy and immunotherapy: focusing on the effects of radiosensitivity.

Cancer treatment is gradually entering an era of precision, with multitude studies in gene testing and immunotherapy. Tumor cells can be recognized and eliminated by the immune system through the expression of tumor-associated antigens, but when the cancer escapes or otherwise suppresses immunity, the balance between cancer cell proliferation and immune-induced cancer cell killing may be interrupted, resulting in tumor proliferation and progression. There has been significant attention to combining conventional cancer therapies (i.e., radiotherapy) with immunotherapy as opposed to treatment alone. The combination of radio-immunotherapy has been demonstrated in both basic research and clinical trials to provide more effective anti-tumor responses. However, the absolute benefits of radio-immunotherapy are dependent on individual characteristics and not all patients can benefit from radio-immunotherapy. At present, there are numerous articles about exploring the optimal models for combination radio-immunotherapy, but the factors affecting the efficacy of the combination, especially with regard to radiosensitivity remain inconclusive. Radiosensitivity is a measure of the response of cells, tissues, or individuals to ionizing radiation, and various studies have shown that the radiosensitivity index (RSI) will be a potential biomarker for predicting the efficacy of combination radio-immunotherapy. The purpose of this review is to focus on the factors that influence and predict the radiosensitivity of tumor cells, and to evaluate the impact and predictive significance of radiosensitivity on the efficacy of radio-immunotherapy combination.

NcRNAs-mediated P2RX1 expression correlates with clinical outcomes and immune infiltration in patients with breast invasive carcinoma.

The development of novel treatments for breast invasive carcinoma (BC) has been stagnant. P2RX1, a member of the purinergic receptor family, has been found to have a prognostic impact in several tumors. Therefore, we analyzed the expression pattern of P2RX1 in pan-cancers including BC and its impact on survival and found that the expression level of P2RX1 was lower in BC compared with para-cancerous tissues, and higher P2RX1 expression indicated better prognoses. But real-time quantitative reverse transcription PCR (RT-qPCR) and Western blot detected that the P2RX1 expression in normal mammary epithelial cells was lower than that in tumor cells. Then we comprehensively analyzed the regulatory mechanism and protein-protein interaction network, and found that P2RX1 was significantly positively linked with immune cell infiltration and immune checkpoints.

A novel deep learning prognostic system improves survival predictions for stage III non-small cell lung cancer.

BACKGROUND: Accurate prognostic prediction plays a crucial role in the clinical setting. However, the TNM staging system fails to provide satisfactory individual survival prediction for stage III non-small cell lung cancer (NSCLC). The performance of the deep learning network for survival prediction in stage III NSCLC has not been explored. OBJECTIVES: This study aimed to develop a deep learning-based prognostic system that could achieve better predictive performance than the existing staging system for stage III NSCLC. METHODS: In this study, a deep survival learning model (DSLM) for stage III NSCLC was developed based on the Surveillance, Epidemiology, and End Results (SEER) database and was independently tested with another external cohort from our institute. DSLM was compared with the Cox proportional hazard (CPH) and random survival forest (RSF) models. A new prognostic system for stage III NSCLC was also proposed based on the established deep learning model. RESULTS: The study included 16,613 patients with stage III NSCLC from the SEER database. DSLM showed the best performance in survival prediction, with a C-index of 0.725 in the validation set, followed by RSF (0.688) and CPH (0.683). DSLM also showed C-indices of 0.719 and 0.665 in the internal and real-world external testing datasets, respectively. In addition, the new prognostic system based on DSLM (AUROC = 0.744) showed better performance than the TNM staging system (AUROC = 0.561). CONCLUSION: In this study, a new, integrated deep learning-based prognostic model was developed and evaluated for stage III NSCLC. This novel approach may be valuable in improving patient stratification and potentially provide meaningful prognostic information that contributes to personalized therapy.

Development of a Novel Deep Learning-Based Prediction Model for the Prognosis of Operable Cervical Cancer.

Background: Cervical cancer ranks as the 4th most common female cancer worldwide. Early stage cervical cancer patients can be treated with operation, but clinical staging system is not a good predictor of patients' survival. We aimed to develop a novel prognostic model to predict the prognosis for operable cervical cancer patients with better accuracy than clinical staging system. Methods: A total of 13,952 operable cervical cancer patients were retrospectively enrolled in this study. The whole dataset was randomly split into a training set (n = 9,068, 65%), validation set (n = 2,442, 17.5%), and testing set (n = 2,442, 17.5%). Cox proportional hazard (CPH) model and random survival forest (RSF) model were used as baseline models for the prediction of overall survival (OS). Then, a deep survival learning model (DSLM) was developed for OS prediction. Finally, a novel prognostic model was explored based on this DSLM. Results: The C-indexes for the CPH and RSF model were 0.731 and 0.753, respectively. DSLM, which had four layers that had 50 neurons in each layer, achieved a C-index of 0.782 in the validation set and a C-index of 0.758 in the testing set. The novel prognostic model based on DSLM showed better performances than the conventional clinical staging system (area under receiver operating curves were 0.826 and 0.689, respectively). Personalized survival curves for individual patient using this novel model also showed notably different survival slopes. Conclusions: Our study developed a novel, practical, personalized prognostic model for operable cervical cancer patients. This novel prognostic model may have the potential to provide a more prognostic information to oncologists.

Three models that predict the efficacy of immunotherapy in Chinese patients with advanced non-small cell lung cancer.

BACKGROUND: Many tools have been developed to predict the efficacy of immunotherapy, such as lung immune prognostic index (LIPI), EPSILoN [Eastern Cooperative Oncology Group performance status (ECOG PS), smoking, liver metastases, lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR)], and modified lung immune predictive index (mLIPI) scores. The aim of this study was to determine the ability of three predictive scores to predict the outcomes in Chinese advanced non-small cell lung cancer (aNSCLC) patients treated with immune checkpoint inhibitors (ICIs). METHODS: We retrospectively analyzed 429 patients with aNSCLC treated with ICIs at our institution. The predictive ability of these models was evaluated using area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis. Calibration was assessed using the Hosmer-Lemeshow test (H-L test) and Spearman's correlation coefficient. Progression-free survival (PFS) and overall survival (OS) curves were generated using the Kaplan-Meier method. RESULTS: The AUC values of LIPI, mLIPI, and EPSILoN scores predicting PFS at 6 months were 0.642 [95% confidence interval (CI):0.590-0.694], 0.720 (95% CI: 0.675-0.762), and 0.633 (95% CI: 0.585-0.679), respectively (p < 0.001 for all models). The AUC values of LIPI, mLIPI, and EPSILON scores predicting objective response rate (ORR) were 0.606 (95% CI: 0.546-0.665), 0.683 (95% CI: 0.637-0.727), and 0.666 (95% CI: 0.620-0.711), respectively (p < 0.001 for all models). The C-indexes of LIPI, mLIPI, and EPSILoN scores for PFS were 0.627 (95% CI 0.611-6.643), 0.677 (95% CI 0.652-0.682), and 0.631 (95% CI 0.617-0.645), respectively. CONCLUSIONS: As mLIPI scores had the highest accuracy when used to predict the outcomes in Chinese aNSCLC patients, this tool could be used to guide clinical immunotherapy decision-making.

Integrating Clinical Data and Attentional CT Imaging Features for Esophageal Fistula Prediction in Esophageal Cancer.

BACKGROUND AND PURPOSE: This study aims to develop a risk model to predict esophageal fistula in esophageal cancer (EC) patients by learning from both clinical data and computerized tomography (CT) radiomic features. MATERIALS AND METHODS: In this retrospective study, computerized tomography (CT) images and clinical data of 186 esophageal fistula patients and 372 controls (1:2 matched by the diagnosis time of EC, sex, marriage, and race) were collected. All patients had esophageal cancer and did not receive esophageal surgery. 70% patients were assigned into training set randomly and 30% into validation set. We firstly use a novel attentional convolutional neural network for radiographic descriptor extraction from nine views of planes of contextual CT, segmented tumor and neighboring structures. Then clinical factors including general, diagnostic, pathologic, therapeutic and hematological parameters are fed into neural network for high-level latent representation. The radiographic descriptors and latent clinical factor representations are finally associated by a fully connected layer for patient level risk prediction using SoftMax classifier. RESULTS: 512 deep radiographic features and 32 clinical features were extracted. The integrative deep learning model achieved C-index of 0.901, sensitivity of 0.835, and specificity of 0.918 on validation set with superior performance than non-integrative model using CT imaging alone (C-index = 0.857) or clinical data alone (C-index = 0.780). CONCLUSION: The integration of radiomic descriptors from CT and clinical data significantly improved the esophageal fistula prediction. We suggest that this model has the potential to support individualized stratification and treatment planning for EC patients.

Alterations of Gut Microbiome and Metabolite Profiling in Mice Infected by Schistosoma japonicum.

Schistosoma japonicum (S. japonicum) is one of the etiological agents of schistosomiasis, a widespread zoonotic parasitic disease. However, the mechanism of the balanced co-existence between the host immune system and S. japonicum as well as their complex interaction remains unclear. In this study, 16S rRNA gene sequencing, combined with metagenomic sequencing approach as well as ultraperformance liquid chromatography-mass spectrometry metabolic profiling, was applied to demonstrate changes in the gut microbiome community structure during schistosomiasis progression, the functional interactions between the gut bacteria and S. japonicum infection in BALB/c mice, and the dynamic metabolite changes of the host. The results showed that both gut microbiome and the metabolites were significantly altered at different time points after the infection. Decrease in richness and diversity as well as differed composition of the gut microbiota was observed in the infected status when compared with the uninfected status. At the phylum level, the gut microbial communities in all samples were dominated by Firmicutes, Bacteroidetes, Proteobacteria, and Deferribacteres, while at the genus level, Lactobacillus, Lachnospiraceae NK4A136 group, Bacteroides, Staphylococcus, and Alloprevotella were the most abundant. After exposure, Roseburia, and Ruminococcaceae UCG-014 decreased, while Staphylococcus, Alistipes, and Parabacteroides increased, which could raise the risk of infections. Furthermore, LEfSe demonstrated several bacterial taxa that could discriminate between each time point of S. japonicum infection. Besides that, metagenomic analysis illuminated that the AMP-activated protein kinase (AMPK) signaling pathway and the chemokine signaling pathway were significantly perturbed after the infection. Phosphatidylcholine and colfosceril palmitate in serum as well as xanthurenic acid, naphthalenesulfonic acid, and pimelylcarnitine in urine might be metabolic biomarkers due to their promising diagnostic potential at the early stage of the infection. Alterations of glycerophospholipid and purine metabolism were also discovered in the infection. The present study might provide further understanding of the mechanisms during schistosome infection in aspects of gut microbiome and metabolites, and facilitate the discovery of new targets for early diagnosis and prognostic purposes. Further validations of potential biomarkers in human populations are necessary, and the exploration of interactions among S. japonicum, gut microbiome, and metabolites is to be deepened in the future.

Flow Cytometric Detection of Newly-formed Breast Cancer Stem Cell-like Cells After Apoptosis Reversal.

Cancer recurrence has long been studied by oncologists while the underlying mechanisms remain unclear. Recently, we and others found that a phenomenon named apoptosis reversal leads to increased tumorigenicity in various cell models under different stimuli. Previous studies have been focused on tracking this process in vitro and in vivo; however, the isolation of real reversed cells has yet to be achieved, which limits our understanding on the consequences of apoptosis reversal. Here, we take advantage of a Caspase-3/7 Green Detection dye to label cells with activated caspases after apoptotic induction. Cells with positive signals are further sorted out by fluorescence-activated cell sorting (FACS) for recovery. Morphological examination under confocal microscopy helps confirm the apoptotic status before FACS. An increase in tumorigenicity can often be attributed to the elevation in the percentage of cancer stem cell (CSC)-like cells. Also, given the heterogeneity of breast cancer, identifying the origin of these CSC-like cells would be critical to cancer treatment. Thus, we prepare breast non-stem cancer cells before triggering apoptosis, isolating caspase-activated cells and performing the apoptosis reversal procedure. Flow cytometry analysis reveals that breast CSC-like cells re-appear in the reversed group, indicating breast CSC-like cells are transited from breast non-stem cancer cells during apoptosis reversal. In summary, this protocol includes the isolation of apoptotic breast cancer cells and detection of changes in CSC percentage in reversed cells by flow cytometry.

Development and validation of a risk prediction model for radiotherapy-related esophageal fistula in esophageal cancer.

OBJECTIVES: We aimed to identify the risk factors and provide a nomogram for the prediction of radiotherapy-related esophageal fistula in patients with esophageal cancer (EC) using a case-control study. PATIENTS AND METHODS: Patients with esophageal fistula who received radiotherapy or chemoradiotherapy between 2003 and 2017 were retrospectively collected in two institutions. In the training cohort (TC), clinical, pathologic, and serum data of 136 patients (cases) who developed esophageal fistula during or after radiotherapy were enrolled and compared with 272 controls (1:2 matched with the diagnosis time of EC, sex, marriage, and race). After the univariable and multivariable logistic regression analyses, the independent risk factors were identified and incorporated into a nomogram. Then the nomogram for the risk prediction was externally validated in the validation cohort (VC; 47 cases and 94 controls) using bootstrap resampling. RESULTS: Multivariable analyses demonstrated that ECOG PS, BMI, T4, N2/3 and re-radiotherapy were independent factors for esophageal fistula. Then a nomogram was constructed with the C-index of 0.805 (95% CI, 0.762-0.848) for predicting the risk of developing esophageal fistula in EC patients receiving radiotherapy. Importantly, the C-index maintained 0.764 (95% CI, 0.683-0.845) after the external validation. CONCLUSIONS: We created and externally validated the first risk nomogram of esophageal fistula associated with radiotherapy. This will aid individual risk stratification of patients with EC developing esophageal fistula.

Delineating the pattern of treatment for elderly locally advanced NSCLC and predicting outcomes by a validated model: A SEER based analysis.

INTRODUCTION: Locally advanced nonsmall-cell lung cancer (LA-NSCLC) represented a highly heterogeneous group, with more than half of the patients aged ≥65 years at the time of diagnosis. However, the optimal treatment for elderly LA-NSCLC patients was still not defined. METHODS: A total of 33530 elderly patients (≥65 years) diagnosed with LA-NSCLC from 2004 to 2014 were identified from Surveillance, Epidemiology, and End Results (SEER) database. RESULTS: Locally advanced nonsmall-cell lung cancer patients aged 65-74 years were more frequently treated with chemoradiotherapy (CRT) (40%), while patients aged ≥75 years received more best supportive care (BSC) (36%). For age group of 65-74 years, patients who had surgery with or without (neo)adjuvant therapy had a median survival of 28 months, CRT 15 months, radiotherapy (RT) alone 6 months, chemotherapy alone 11 months, and BSC 3 months; while for patients aged ≥ 75 years, the median OS was 20, 13, 7, 9, and 2, respectively. Besides, independent clinicopathological factors were integrated into nomograms for OS and CSS prediction, C-indexes achieved 0.692 and 0.698, respectively. Importantly, the discrimination of nomogram was superior to that of the American Joint Committee on Cancer TNM classification (0.742 vs 0.572 for training set and 0.731 vs 0.565 for validation set). CONCLUSION: For elderly patients with LA-NSCLC, the curative-intent treatment (surgery or CRT) conferred better survival compared to chemotherapy alone, RT alone and BSC. The proposed nomograms based on independent clinicopathological variables may be practical and helpful for precise evaluation of patient prognosis, and guiding the individualized treatment for elderly LA-NSCLC.

The Kinetic Changes of Systemic Inflammatory Factors during Bevacizumab Treatment and Its Prognostic Role in Advanced Non-small Cell Lung Cancer Patients.

Background: Bevacizumab combined with chemotherapy is still one of the standard options for treatment of advanced non-small cell lung cancer (NSCLC) patients without driver mutations. Serum inflammatory factors, representing the systemic immune status, are shown to have complicated relationships with tumor angiogenesis, and proved to be associated with survival of advanced NSCLC patients. However, the information from the baseline factors is relatively limited, which cannot reflect the dynamic changes of systemic immune status during bevacizumab treatment. We, thus, attempted to evaluate longitudinal kinetics of systemic inflammatory factors during treatment of bevacizumab and to explore their predictive role in treatment response and patient outcomes in advanced NSCLC. Method: Systemic inflammatory factors (neutrophil/lymphocyte (NLR), platelet/lymphocyte (PLR), neutrophil×platelet/lymphocyte (SII) and lymphocyte/monocyte (LMR)) and clinical variables were collected and analyzed from 161 advanced NSCLC patients treated with bevacizumab. Mixed effect regression models were first performed for longitudinal analysis of the changes of serum inflammatory factors during bevacizumab treatment. Then, univariate and multivariate Cox models were used for overall survival (OS) and progression free survival (PFS) analyses to determine the independent prognostic factors. Results: In the first 6 cycles of bevacizumab treatment, patients with complete response/partial response (CR/PR) had a -0.11, -0.066, -0.15, and 0.073 change every 2 cycles in transformed NLR (95%CI: -0.19--0.03, p=0.008), PLR (95%CI: -0.12--0.013, p=0.015), SII (95%CI: -0.23--0.05, p<0.001) and LMR (95%CI: 0.049-0.14, p=0.036), respectively, compared to patients with progressive disease (PD). With respect to analysis of the longitudinal changes before progression, patients experienced a significant increase in transformed NLR (Coef=0.09, 95%CI: 0.019-0.17, p=0.014), PLR (Coef=0.05, 95%CI: 0.002-0.10, p=0.04), and SII (Coef=0.091, 95%CI: 0.015-0.17, p=0.019), but a decrease in transformed LMR (Coef=-0.08, 95%CI: -0.14-0.018, p=0.012). On multivariate Cox model analyses, decrease of LMR (HR=0.62, 95% CI: 0.4-0.96, p=0.033) was shown to be the independent risk factor for PFS; and low level of baseline LMR (HR=0.4, 95% CI: 0.17-0.94, p=0.036), increase of NLR (HR=2.36, 95%CI: 1.25-4.44, p=0.008), and decrease of LMR (HR=0.42, 95%CI: 0.18-0.97, p=0.041) were the independent risk factors for death. Conclusion: The activation of systemic immune status evaluated by the kinetic changes of serum inflammatory factors was associated with good response to bevacizumab; however, the suppressive status may indicate the resistance to bevacizumab. Dynamic changes of systemic inflammatory factors also had prognostic value in predicting outcomes of advanced NSCLC patients treated with bevacizumab.

Apoptosis Reversal Promotes Cancer Stem Cell-Like Cell Formation.

It has long been a puzzle in cancer treatment that despite the initial appearance of apoptosis, the process could be reversed in some cancer cells and often results in more aggressive tumors and metastasis. The mechanism for this recurrence is yet unknown. Here we report that human mammary carcinoma cells induced to undergo apoptosis could recover with increased tumorigenicity in vitro and in vivo, and induced lymph node metastasis. Specifically, the reversed cells underwent epithelial-to-mesenchymal transitions in the primary tumors in situ, and mesenchymal-to-epithelial transitions in the metastatic cells. Flow cytometry confirmed an elevated percentage of cells carrying cancer stem cells (CSCs) markers (CD44+/CD24-) in the reversed breast cancer cell population, with hypomethylated CD44 promoters and hypermethylated CD24 promoters. More importantly, CSCs were generated anew from non-stem cancer cells after apoptosis reversal possibly through epigenetic modifications. The results from this study can open doors to discovering more effective cancer treatments by suppressing apoptosis reversal.

Local ablative therapy with or without chemotherapy for non-small-cell lung cancer patients with postoperative oligometastases.

BACKGROUND: The optimal treatment strategy for patients with non-small-cell lung cancer (NSCLC) with postoperative oligometastases is poorly defined. This two-institution analysis sought to retrospectively compare the efficacy and toxicity of local ablative treatment plus chemotherapy vs local treatment alone in patients with NSCLC who developed oligometastases after surgery. PATIENTS AND METHODS: Among patients who underwent surgery for stage I-III NSCLC, 163 patients with oligometastases were enrolled between 2005 and 2016 in this study. All patients had ≤5 metachronous metastases with a disease-free interval (DFI) of ≥6 months after surgery. Patients with a second primary cancer, local recurrence, or driver mutations were excluded. Overall survival (OS), progression-free survival (PFS), objective response rate (ORR), failure patterns, and treatment-related toxicities were compared between groups receiving local ablative treatment plus chemotherapy and local treatment alone. RESULTS: A total of 105 patients who underwent local ablative therapy combined with chemotherapy and 58 patients who received local ablative therapy alone were included in this study. The median follow-up was 19 (range, 1.5-107) months. The combination therapy group had a higher ORR than the local therapy alone group (66.7% vs 46.5%, P=0.012), while the median PFS was 10 vs 7 months (P=0.006) and the median OS was 19 vs 18.5 months (P=0.498), respectively. By multivariate analysis, combination therapy and DFI ≥24 months were associated with superior PFS. Age was the only independent prognostic factor for OS (P<0.001). The incidences of grade ≥3 adverse events were higher in the combination treatment group. CONCLUSION: Local ablative therapy plus chemotherapy conferred higher ORR and prolonged PFS but did not improve OS in NSCLC patients with postoperative oligometastases. Further prospective and randomized trials are urgently needed to validate these findings.

SjCa8, a calcium-binding protein from Schistosoma japonicum, inhibits cell migration and suppresses nitric oxide release of RAW264.7 macrophages.

BACKGROUND: Schistosomiasis is considered second only to malaria as the most devastating parasitic disease in tropical countries. Schistosome cercariae invade the host by penetrating the skin and migrate though the lungs and portal circulation to their final destination in the hepatic portal system and eventually the mesenteric veins. Previous studies have shown that the cytotoxic pathways that target schistosomulum in the lung-stage involve nitric oxide (NO) produced by macrophages. By contrast, skin-stage schistosomulas can evade clearance, indicating that they might be freed from macrophage NO-mediated cytotoxicity to achieve immune evasion; however, the critical molecules and mechanisms involved remain unknown. METHODS: Recombinant SjCa8 (rSjCa8), an 8-kDa calcium-binding protein that is stage-specifically expressed in cercaria and early skin-stage schistosomulas of Schistosoma japonicum, was incubated with mouse RAW264.7 macrophages. Effects on macrophage proliferation were determined using Cell Counting Kit-8. Next, transwell assay was carried out to further investigate the role of rSjCa8 in macrophage migration. The effects of rSjCa8 on macrophage apoptosis were evaluated using confocal microscopy and flow cytometry. Additional impacts of rSjCa8 on NO release by lipopolysaccharide (LPS)-stimulated macrophages as well as the underlying mechanisms were explored using fluorescent probe, nitric oxide signaling pathway microarray, quantitative real-time PCR, mutagenesis, and neutralizing antibody approaches. RESULTS: rSjCa8 exhibited a striking inhibitory effect on macrophage migration, but did not markedly increase cell proliferation or apoptosis. Additionally, rSjCa8 potently inhibited NO release by LPS-stimulated macrophages in a dose- and time-dependent manner, and the inhibitory mechanism was closely associated with intracellular Ca(2+) levels, the up-regulation of catalase expression, and the down-regulation of the expression of 47 genes, including Myc, Gadd45a, Txnip, Fas, Sod2, Nos2, and Hmgb1. Vaccination with rSjCa8 increased NO concentration in the challenging skin area of infected mice and reduced the number of migrated schistosomula after skin penetration by cercariae. CONCLUSIONS: Our findings indicate that SjCa8 might be a novel molecule that plays a critical role in immune evasion by S. japonicum cercaria during the process of skin penetration. The inhibitory impacts of rSjCa8 on macrophage migration and [Ca(2+)]i-dependent NO release suggest it might represent a novel vaccine candidate and chemotherapeutic target for the prevention and treatment of schistosomiasis.

Effects of UV irradiation and UV/chlorine co-exposure on natural organic matter in water.

The effects of co-exposure to ultraviolet (UV) irradiation (with either low- or medium-pressure UV lamps) and free chlorine (chloramine) at practical relevant conditions on changes in natural organic matter (NOM) properties were investigated using four waters. The changes were characterized using the specific disinfection by-product formation potential (SDBPFP), specific total organic halogen formation potential (STOXFP), differential UV absorbance (∆UVA), and size-exclusion chromatography (SEC). The results for exposure to UV irradiation alone and for samples with no exposure were also obtained. The SDBPFPs in all UV-irradiated NOM waters observed were higher than those of non-irradiated samples. UV irradiation led to increases in STOXFPs as a result of chlorination, but no changes, or only small decreases, from chloramination. UV irradiation alone led to positive ∆UVA spectra of the four NOM waters; co-exposure to UV and chlorine gave larger negative ∆UVA spectra than those obtained by chlorine exposure alone. No obvious changes in SEC results were observed for samples only irradiated with UV light; co-exposure gave no detectable changes in the abundances of small fractions for exposure to chlorine only. Both UV photooxidation and photocatalytic oxidation appear to affect the reactivity of the NOM toward subsequent chlorination, and the magnitude of the changes is generally greater for medium-pressure lamps than for low-pressure lamps. These results suggest that applying UV disinfection technology to a particular source may not always be disinfection by-product-problem-free, and the interactions between UV light, chlorine, and NOM may need to be considered.