Chemotherapy versus chemotherapy plus immune checkpoint inhibitors for the first-line treatment of unresectable thymic carcinoma: A multicenter retrospective study.

Thymic carcinoma (TC) is a rare malignant tumor with a poor prognosis, and there is currently limited data on the use of immunotherapy in patients with unresectable TC. In this study, data of patients with unresectable TC diagnosed from January 2017 were retrospectively collected from multiple centers. Treatment response, progression-free survival (PFS), overall survival (OS), survival-independent prognostic factor, and adverse events (AEs) were further analyzed. As a result, a total of 93 patients with unresectable TC were enrolled, of which 54 received first-line chemotherapy, and 39 received chemotherapy plus immune checkpoint inhibitors (ICIs). The objective response rate was 50% (27/54) in the chemotherapy group and 76.9% (30/39) in the chemotherapy plus ICIs group. The chemotherapy plus ICIs group achieved significant median PFS benefit (8.8 vs. 34.9 months, p < .001) and median OS benefit (41.8 months vs. not reached, p = .025). Multivariate analysis showed that ICIs and local therapy were independent prognostic factors for PFS. In addition, 17 patients developed immune-related AEs (IRAEs), of which 15 (38.5%) had Grade 1 or 2 IRAEs and 2 (5.1%) had Grade 3 IRAEs in the chemotherapy plus ICIs group. In conclusion, the efficacy of chemotherapy plus ICIs is superior to chemotherapy, and the adverse effects are manageable in patients with unresectable TC.

Validation of China Health-Related Outcomes Measures-Cardiovascular Disease.

OBJECTIVES: China Health-Related Outcomes Measures (CHROME) was an initiative aimed at developing a system of preference-based health-related quality of life instruments for China. CHROME-cardiovascular disease (CVD) is a CVD-specific instrument with 14 items developed under this initiative. This study aimed to test the psychometric properties of CHROME-CVD. METHODS: This validation study was conducted using cross-sectional questionnaire survey in China. Eligible patients with CVD were recruited and asked to complete the CHROME-CVD, the EQ-5D-5L, and a CVD-specific nonpreference-based health-related quality of life instrument selected according to the confirmed diagnosis of the patients. Item evaluation, internal consistency, measurement invariance, test-retest reliability, structural validity, and construct validity were tested using classic test theory. Item response theory was used to evaluate item-level performance. RESULTS: A total of 444 patients with CVD (coronary artery disease, n = 276, heart failure, n = 104, angina, n = 33, and atrial fibrillation, n = 16) from 6 provinces in China were enrolled for the validation. Exploratory factor analysis identified 4 factors: chest pain, other symptoms, physical health, and mental and social health. Cronbach's alpha and intraclass correlation coefficient were >0.8. A total of 20 of 26 (76.9%), and 90 of 95 (94.7%) predefined hypotheses were met for convergent and discriminant validities, respectively. No important difference was identified between subgroups of gender and residency. Response options of 10 items were found overlapped based on categorical response curves, which led to modification to 4-level response options. Wording of 3 items were modified by referring wordings of reference instruments. CONCLUSION: The validation of the CHROME-CVD demonstrated generally good psychometric properties. Further validation on the modified CHROME-CVD is needed.

A tunable ultra-broadband and ultra-high sensitivity far-infrared metamaterial absorber based on VO2 and graphene.

We proposed a far-infrared tunable metamaterial absorber using vanadium dioxide (VO2) and graphene as controlling materials. The properties of the absorber are investigated theoretically using the finite-difference time-domain (FDTD) technique. It was found that when the Fermi energy level of graphene is fixed at zero, VO2 is in the insulated state, and the metasurface exhibits far-infrared broadband absorption performance, with absorptance exceeding 90% in the wavelength range of 12.6 µm to 23.2 µm. In addition, by elevating the Fermi energy level of graphene, the absorption bandwidth of the device is expanded continuously. When the VO2 is in the metallic state, the device can flexibly transform into a far-infrared narrowband absorber. The device also has the advantage of being insensitive to changes in polarization and incident angle. The origin of the absorption and the tuning principle of the device were analyzed and verified successfully by using an equivalent circuit model (ECM). Besides, we also studied the refraction index sensing characteristics of the absorber. Surprisingly, the absorber exhibits excellent sensing characteristics, and its sensitivity (S) reaches 14.108 µm per RIU and the figure of merit (FOM) is 6.13 per RIU.

Difunctional terahertz metasurface with switchable polarization conversion and absorption by VO2 and photosensitive silicon.

In this study, a terahertz (THz) switchable multifunctional metasurface is proposed to realize polarization conversion and absorption. When vanadium dioxide (VO2) is in the dielectric state, the structure demonstrates polarization conversion with double broadband transmission. The transmittance of the double broadband is greater than 80% in the frequency ranges of 2.05-2.38 THz and 3.38-3.68 THz, and the polarization conversion rate (PCR) is greater than 90%. Excellent asymmetric transmission (AT) properties are exhibited by polarization conversion. The transmittance of the double broadband can be modulated dynamically by the pump light by controlling the conductivity of the photosensitive silicon (PS). When VO2 is in the metallic state, the metasurface is switched to be a bidirectional THz absorber for TE and TM wave incidence, and the maximum absorptance of the absorber can reach more than 95%. Furthermore, the absorption is insensitive to the angle of incidence, and the absorption frequency and intensity can be dynamically tuned by changing the polarization angle. By changing the conductivity of the PS, the intensity and frequency of the absorption can also be adjusted. Using the metasurface, we achieved a dynamic multiplexing imaging function for linearly polarized waves. The metasurface showed a new vision for multifunctional THz devices and exhibited a wide application prospect in the field of THz imaging.

A switchable and tunable multifunctional terahertz polarization converter based on a graphene metasurface.

We propose a switchable and tunable terahertz metasurface polarization converter based on graphene. The metasurface is composed of a bottom gold film, a lower SiO2 layer, an intermediate N-type graphene layer, an upper SiO2 layer, and a top layer of square graphene resonant rings. By using the CST Microwave Studio, we studied their polarization conversion properties. The results show that the metasurface enables a versatile range of functions, including x-to-y linear polarization conversion within the frequency range of 4.23-7 THz, the transformation of linearly polarized waves into right-hand circularly polarized and left-hand circularly polarized waves. Moreover, at 3.873 THz, the metasurface can exhibit circular dichroism (CD) with a high CD value of 0.7. Based on the effect, a strategy to detect three representative avian influenza viruses was proposed and tested, which implies that the metasurface can be applied in biosensing.

Dynamic monitoring of cerebrospinal fluid circulating tumor DNA to identify unique genetic profiles of brain metastatic tumors and better predict intracranial tumor responses in non-small cell lung cancer patients with brain metastases: a prospective cohort study (GASTO 1028).

BACKGROUND: Due to the blood-brain barrier, plasma is not an ideal source to evaluate the genetic characteristics of central nervous system tumors. Thus, cerebrospinal fluid (CSF) is becoming an alternative biopsy type to evaluate the genetic landscape of intracranial tumors. We aimed to explore the genetic profiles of CSF-derived circulating tumor DNA (ctDNA) to predict intracranial tumor responses and monitor mutational evolution during the treatment of non-small cell lung cancer (NSCLC) patients with brain metastases. METHODS: We conducted a prospective study of 92 newly diagnosed NSCLC patients with brain metastases. Paired CSF and plasma samples were collected at baseline, 8 weeks after treatment initiation, and disease progression. All samples underwent next-generation sequencing of 425 cancer-related genes. RESULTS: At baseline, the positive detection rates of ctDNA in CSF, plasma, and extracranial tumors were 63.7% (58/91), 91.1% (82/90), and 100% (58/58), respectively. A high level of genetic heterogeneity was observed between paired CSF and plasma, while concordance in driver mutations was also observed. A higher number of unique copy number variations was detected in CSF-ctDNA than in plasma. ctDNA positivity of CSF samples at baseline was associated with poor outcomes (HR=2.565, P=0.003). Moreover, patients with ≥ 50% reductions in the concentrations of CSF ctDNA after 8 weeks of treatment had significantly longer intracranial progression-free survivals (PFS) than patients with < 50% reductions in CSF ctDNA concentrations (13.27 months vs 6.13 months, HR=0.308, P=0.017). A ≥ 50% reduction in CSF ctDNA concentrations had better concordance with radiographic intracranial tumor responses than plasma. A ≥ 50% reduction in plasma ctDNA concentrations was also associated with longer extracranial PFS (11.57 months vs 6.20 months, HR=0.406, P=0.033). Based on clonal evolution analyses, the accumulation of subclonal mutations in CSF ctDNA was observed after 8 weeks of treatment. The clonal mutations that remained in more than 80% in CSF after 8 weeks also predicted shorter intracranial PFS (HR=3.785, P=0.039). CONCLUSIONS: CSF ctDNA exhibited unique genetic profiles of brain metastases, and dynamic changes in CSF ctDNA could better predict intracranial tumor responses and track clonal evolution during treatment in NSCLC patients with brain metastases. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03257735.

Direct Synthesis of Amides from Benzonitriles and Benzylic Alcohols via a KOt-Bu-Mediated MPV-type Hydrogen Transfer Process.

Meerwein-Ponndorf-Verley (MPV)-type reduction between benzonitriles and benzylic alcohols under transition-metal-free conditions has been demonstrated for the first time. Using simple KOt-Bu as the base, various benzonitriles can be efficiently reduced by benzylic alcohols via hydrogen transfer reduction, and the resultant phenyl imine can react further with benzylic alcohols to give amides as the final product in which both the alcohols and the nitriles are incorporated. Preliminary mechanistic investigations indicated that the reaction may go through multiple MPV-type hydrogen transfer processes.

Efficacy of adjuvant EGFR inhibitors and impact of clinical factors in resected EGFR-mutated non-small-cell lung cancer: a meta-analysis.

Background: The role of adjuvant EGFR tyrosine kinase inhibitors (TKIs) in resected EGFR-mutated non-small-cell lung cancer (NSCLC) remains unclear. Materials & methods: We evaluated pooled hazard ratio and 95% CI for disease-free survival, overall survival and prespecified subgroups. Results: Seven prospective studies with 1288 patients were included in the meta-analysis. Adjuvant EGFR TKIs significantly improved disease-free survival in EGFR-mutated resected NSCLC (HR: 0.41; 95% CI: 0.24-0.70) and in all subgroups. However, the overall survival benefit was not significant (HR: 0.65; 95% CI: 0.36-1.17). The benefit of adjuvant TKIs may be associated with TKI regimens, treatment duration, pathological stage and EGFR mutation type. Conclusion: Adjuvant EGFR TKIs significantly improved disease-free survival and nonsignificantly improved overall survival in resected EGFR-mutated NSCLC.

For lung cancer patients who undergo radical surgery and whose tumors have EGFR mutation (a specific gene alteration in the tumor tissue), the optimal treatment following surgery is unclear. We summarized the available studies to compare the efficacy of anti-EGFR targeted therapies (EGFR inhibitors) with chemotherapy in patients after surgery. We found patients who received EGFR inhibitors after surgery had longer survival without disease recurrence, and a tendency toward longer overall survival than patients who received chemotherapy or no further therapy. The different treatment regimes, treatment duration, tumor stage and EGFR mutation type may impact the efficacy of EGFR inhibitors in these patients after undergoing surgery.

Visible-light-promoted direct C3-trifluoromethylation and perfluoroalkylation of imidazopyridines.

An efficient method for direct trifluoromethylation and perfluoroalkylation at C3 of imidazopyridines through visible light-promoted C-H bond functionalization was developed. Under the irradiation of a blue LED, a series of C3-perfluoroalkyl-substituted imidazopyridines were synthesized from the corresponding imidazopyridines and perfluoroalkyl iodides in moderate to good yields at room temperature. It should be mentioned that this reaction proceeded in the absence of any transition-metal catalyst, oxidant and photocatalyst.

Research on the predictive effect of a combined model of ARIMA and neural networks on human brucellosis in Shanxi Province, China: a time series predictive analysis.

BACKGROUND: Brucellosis is a major public health problem that seriously affects developing countries and could cause significant economic losses to the livestock industry and great harm to human health. Reasonable prediction of the incidence is of great significance in controlling brucellosis and taking preventive measures. METHODS: Our human brucellosis incidence data were extracted from Shanxi Provincial Center for Disease Control and Prevention. We used seasonal-trend decomposition using Loess (STL) and monthplot to analyse the seasonal characteristics of human brucellosis in Shanxi Province from 2007 to 2017. The autoregressive integrated moving average (ARIMA) model, a combined model of ARIMA and the back propagation neural network (ARIMA-BPNN), and a combined model of ARIMA and the Elman recurrent neural network (ARIMA-ERNN) were established separately to make predictions and identify the best model. Additionally, the mean squared error (MAE), mean absolute error (MSE) and mean absolute percentage error (MAPE) were used to evaluate the performance of the model. RESULTS: We observed that the time series of human brucellosis in Shanxi Province increased from 2007 to 2014 but decreased from 2015 to 2017. It had obvious seasonal characteristics, with the peak lasting from March to July every year. The best fitting and prediction effect was the ARIMA-ERNN model. Compared with those of the ARIMA model, the MAE, MSE and MAPE of the ARIMA-ERNN model decreased by 18.65, 31.48 and 64.35%, respectively, in fitting performance; in terms of prediction performance, the MAE, MSE and MAPE decreased by 60.19, 75.30 and 64.35%, respectively. Second, compared with those of ARIMA-BPNN, the MAE, MSE and MAPE of ARIMA-ERNN decreased by 9.60, 15.73 and 11.58%, respectively, in fitting performance; in terms of prediction performance, the MAE, MSE and MAPE decreased by 31.63, 45.79 and 29.59%, respectively. CONCLUSIONS: The time series of human brucellosis in Shanxi Province from 2007 to 2017 showed obvious seasonal characteristics. The fitting and prediction performances of the ARIMA-ERNN model were better than those of the ARIMA-BPNN and ARIMA models. This will provide some theoretical support for the prediction of infectious diseases and will be beneficial to public health decision making.

Application of a novel hybrid algorithm of Bayesian network in the study of hyperlipidemia related factors: a cross-sectional study.

BACKGROUND: This article aims to understand the prevalence of hyperlipidemia and its related factors in Shanxi Province. On the basis of multivariate Logistic regression analysis to find out the influencing factors closely related to hyperlipidemia, the complex network connection between various variables was presented through Bayesian networks(BNs). METHODS: Logistic regression was used to screen for hyperlipidemia-related variables, and then the complex network connection between various variables was presented through BNs. Since some drawbacks stand out in the Max-Min Hill-Climbing (MMHC) hybrid algorithm, extra hybrid algorithms are proposed to construct the BN structure: MMPC-Tabu, Fast.iamb-Tabu and Inter.iamb-Tabu. To assess their performance, we made a comparison between these three hybrid algorithms with the widely used MMHC hybrid algorithm on randomly generated datasets. Afterwards, the optimized BN was determined to explore to study related factors for hyperlipidemia. We also make a comparison between the BN model with logistic regression model. RESULTS: The BN constructed by Inter.iamb-Tabu hybrid algorithm had the best fitting degree to the benchmark networks, and was used to construct the BN model of hyperlipidemia. Multivariate logistic regression analysis suggested that gender, smoking, central obesity, daily average salt intake, daily average oil intake, diabetes mellitus, hypertension and physical activity were associated with hyperlipidemia. BNs model of hyperlipidemia further showed that gender, BMI, and physical activity were directly related to the occurrence of hyperlipidemia, hyperlipidemia was directly related to the occurrence of diabetes mellitus and hypertension; the average daily salt intake, daily average oil consumption, smoking, and central obesity were indirectly related to hyperlipidemia. CONCLUSIONS: The BN of hyperlipidemia constructed by the Inter.iamb-Tabu hybrid algorithm is more reasonable, and allows for the overall linking effect between factors and diseases, revealing the direct and indirect factors associated with hyperlipidemia and correlation between related variables, which can provide a new approach to the study of chronic diseases and their associated factors.

Exploratory study on classification of diabetes mellitus through a combined Random Forest Classifier.

BACKGROUND: Diabetes Mellitus (DM) has become the third chronic non-communicable disease that hits patients after tumors, cardiovascular and cerebrovascular diseases, and has become one of the major public health problems in the world. Therefore, it is of great importance to identify individuals at high risk for DM in order to establish prevention strategies for DM. METHODS: Aiming at the problem of high-dimensional feature space and high feature redundancy of medical data, as well as the problem of data imbalance often faced. This study explored different supervised classifiers, combined with SVM-SMOTE and two feature dimensionality reduction methods (Logistic stepwise regression and LAASO) to classify the diabetes survey sample data with unbalanced categories and complex related factors. Analysis and discussion of the classification results of 4 supervised classifiers based on 4 data processing methods. Five indicators including Accuracy, Precision, Recall, F1-Score and AUC are selected as the key indicators to evaluate the performance of the classification model. RESULTS: According to the result, Random Forest Classifier combining SVM-SMOTE resampling technology and LASSO feature screening method (Accuracy = 0.890, Precision = 0.869, Recall = 0.919, F1-Score = 0.893, AUC = 0.948) proved the best way to tell those at high risk of DM. Besides, the combined algorithm helps enhance the classification performance for prediction of high-risk people of DM. Also, age, region, heart rate, hypertension, hyperlipidemia and BMI are the top six most critical characteristic variables affecting diabetes. CONCLUSIONS: The Random Forest Classifier combining with SVM-SMOTE and LASSO feature reduction method perform best in identifying high-risk people of DM from individuals. And the combined method proposed in the study would be a good tool for early screening of DM.

High Accuracy WiFi-Based Human Activity Classification System with Time-Frequency Diagram CNN Method for Different Places.

Older people are very likely to fall, which is a significant threat to the health. However, falls are preventable and are not necessarily an inevitable part of aging. Many different fall detection systems have been developed to help people avoid falling. However, traditional systems based on wearable devices or image recognition-based have many disadvantages, such as user-unfriendly, privacy issues. Recently, WiFi-based fall detection systems try to solve the above problems. However, there is a common problem of reduced accuracy. Since the system is trained at the original signal collecting/training place, however, the application is at a different place. The proposed solution only extracts the features of the changed signal, which is caused by a specific human action. To implement this, we used Channel State Information (CSI) to train Convolutional Neural Networks (CNNs) and further classify the action. We have designed a prototype to test the performance of our proposed method. Our simulation results show an average accuracy of same place and different place is 93.2% and 90.3%, respectively.

Trichinella spiralis muscle larvae excretory/secretory products trigger apoptosis and S-phase arrest of the non-small-cell lung cancer line A549.

Trichinella spiralis (T. spiralis) muscle larvae (ML) excretory/secretory products (ESPs) are antitumor substances extracted from the culture medium of T. spiralis ML. The ESPs inhibit tumor growth and induce tumor cell apoptosis. To explore the effects of these products on the non-small-cell lung cancer (NSCLC) line A549, logarithmically growing A549 cells were co-cultured with different concentrations of T. spiralis ML ESPs for 24, 36 and 48 h. Our results showed that T. spiralis ML ESPs significantly inhibited A549 cells proliferation, which was dose-and time-dependent. To evaluate the inhibition by T. spiralis ML ESPs of the growth of A549 cells, we assayed their apoptosis and cell-cycle distribution by flow cytometry (FCM). To determine whether ESPs induced apoptosis of A549 cells via the mitochondrial pathway, we evaluated the levels of mitochondrion-related factors by Western blotting. The FCM indicated a clear trend toward apoptosis of A549 cells co-cultured with ESPs for 24 h. The cells were blocked in S-phase. Western blotting revealed that the expression levels of the genes encoding Bax, caspase-3, and caspase-9 increased (compared to a control group), and the Bcl-2 gene expression level decreased. Our results suggest that T. spiralis ML ESPs induce apoptosis of the NSCLC line A549 via the mitochondrial pathway; the cells become arrested in S-phase. This may explain the antineoplastic activity of T. spiralis ML ESPs.

α-Tetralonyl Glucosides from the Green Walnut Husks of Juglans mandshurica and Their Antiproliferative Effects.

Two new α-tetralonyl glucosides, (4S)-4,5,8-trihydroxy-α-tetralone-5-O-ß-D-glucopyranosyl(1 → 6)-ß-D-glucopyranoside (1: ) and (4S)-4,8-dihydroxy-α-tetralone-4-O-ß-D-glucopyranosyl(1 → 6)-ß-D-glucopyranoside (2: ), together with eight known compounds (3:  - 10: ) were isolated from the green walnut husks of Juglans mandshurica. The structural characterization of all compounds was performed by spectroscopic analyses, including 1D and 2D NMR and HR-ESI-MS experiments. The isolated compounds were assayed for their cytotoxicity against two human cancer cell lines, A549 and HeLa. Four compounds (7:  - 10: ) exhibited inhibitory effects against two human cancer cell lines with GI50 values between 1.3 and 5.8 µM.

Four new minor brominated indole related alkaloids with antibacterial activities from Laurencia similis.

Four new minor brominated indole related alkaloids (one indoles, 1, one 1,3-dihydro-indole-2-one, 2, one carbazole, 3, and one 2-carbonylamino-benzoate, 4) were isolated and identified from Laurencia similis by extensive chromatographic and spectrometric methods. Among them, 1 and 2 were the first example of naturally occurring indole with 3-benzyl group and 1,3-dihydro-indole-2-one with 2-isopropylidene group, respectively, whereas 3 and 4 were the first carbazole alkaloids and 2-carbonylamino-benzoate, respectively, isolated from the genus Laurencia. Moreover, 1 showed the most potent antibacterial activity against seven bacterial strains with MIC values ranging from 2 to 8µg/mL.

A Comparative Full-Length Transcriptome Analysis Using Oxford Nanopore Technologies (ONT) in Four Tissues of Bovine Origin.

The transcriptome complexity and splicing patterns in male and female cattle are ambiguous, presenting a substantial obstacle to genomic selection programs that seek to improve productivity, disease resistance, and reproduction in cattle. A comparative transcriptomic analysis using Oxford Nanopore Technologies (ONT) was conducted in bovine testes (TESTs), ovaries (OVAs), muscles (MUSCs), and livers (LIVs). An average of 5,144,769 full-length reads were obtained from each sample. The TESTs were found to have the greatest number of alternative polyadenylation (APA) events involved in processes such as sperm flagellum development and fertilization in male reproduction. In total, 438 differentially expressed transcripts (DETs) were identified in the LIVs in a comparison of females vs. males, and 214 DETs were identified in the MUSCs between females and males. Additionally, 14,735, 36,347, and 33,885 DETs were detected in MUSC vs. LIV, MUSC vs. TEST, and OVA vs. TEST comparisons, respectively, revealing the complexity of the TEST. Gene Set Enrichment Analysis (GSEA) showed that these DETs were mainly involved in the "spermatogenesis", "flagellated sperm motility", "spermatid development", "reproduction", "reproductive process", and "microtubule-based movement" KEGG pathways. Additional studies are necessary to further characterize the transcriptome in different cell types, developmental stages, and physiological conditions in bovines and ascertain the functions of the novel transcripts.

Prognostic Nutritional Index Predicts Efficacy and Immune-Related Adverse Events of First-Line Chemoimmunotherapy in Patients with Extensive-Stage Small-Cell Lung Cancer.

Background: Currently, there is a lack of well-established markers to predict the efficacy of chemoimmunotherapy in small-cell lung cancer (SCLC). Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), advanced lung cancer inflammation index (ALI) and prognostic nutritional index (PNI) are associated with prognosis in several tumors, whereas their predictive role in SCLC remains unclear. Methods: A retrospective study was conducted at Sun Yat-sen University Cancer Center, involving extensive-stage SCLC (ES-SCLC) patients who received first-line chemoimmunotherapy between January 2020 and December 2021. Peripheral blood biomarkers were extracted from medical records and their correlation with prognosis and immune-related adverse events (IRAEs) was analyzed. Results: A total of 114 patients were included. Patients with a low PLR, high ALI and high PNI had prolonged progression-free survival (PFS) compared to those with a high PLR, low ALI and low PNI. Patients with a low NLR, low PLR, high ALI and high PNI had prolonged overall survival (OS) compared to those with a high NLR, high PLR, low ALI and low PNI. Cox regression model showed that PNI was an independent risk factor for both PFS and OS. ROC curve showed that PNI outperforms NLR, PLR and ALI in predicting both PFS and OS. The PNI-based nomogram demonstrated strong predictive capability for both PFS and OS. In addition, there was a significant correlation between PNI and IRAEs. Conclusion: A high baseline PNI might be associated with improved prognosis and the occurrence of IRAEs in ES-SCLC patients treated with first-line chemoimmunotherapy.

Cerebrospinal fluid immunological cytokines predict intracranial tumor response to immunotherapy in non-small cell lung cancer patients with brain metastases.

Background: Immunotherapy has shown intracranial efficacy in non-small cell lung cancer (NSCLC) patients with brain metastases. However, predictive biomarkers for intracranial response to immunotherapy are lacking. This post-hoc analysis aimed to explore the potential of immunological cytokines in cerebrospinal fluid (CSF) to predict intracranial tumor response to immunotherapy in patients with brain metastases. Methods: Treatment-naive NSCLC patients with brain metastases who received camrelizumab plus chemotherapy were enrolled. Paired plasma and CSF samples were prospectively collected at baseline and the first treatment assessment. All samples were analyzed for 92 immuno-oncology cytokines using Olink's panels. Results: A total of 28 patients were included in this analysis. At baseline, most immunological cytokines were significantly lower in CSF than in plasma, whereas a subset comprising CD83, PTN, TNFRSF21, TWEAK, ICOSLG, DCN, IL-8, and MCP-1, was increased in CSF. Baseline CSF levels of LAMP3 were significantly higher in patients with intracranial tumor response, while the levels of CXCL10, IL-12, CXCL11, IL-18, TIE2, HGF, and PDCD1 were significantly lower. Furthermore, the CXCL10, CXCL11, TIE2, PDCD1, IL-18, HGF, and LAMP3 in CSF were also significantly associated with intracranial progression-free survival for immunotherapy. The identified cytokines in CSF were decreased at the first treatment evaluation in patients with intracranial tumor response. The logistic CSF immuno-cytokine model yielded an AUC of 0.91, as compared to PD-L1 expression (AUC of 0.72). Conclusions: Immunological cytokines in CSF could predict intracranial tumor response to immunotherapy in NSCLC patients with brain metastases, and the findings warrant validation in a larger prospective cohort study. Trial registration: ClinicalTrials.gov identifier: NCT04211090.