Mutational variant allele frequency profile as a biomarker of response to immune checkpoint blockade in non-small cell lung Cancer.

INTRODUCTION: Identifying new biomarkers for predicting immune checkpoint inhibitors (ICIs) response in non-small cell lung cancer (NSCLC) is crucial. We aimed to assess the variant allele frequency (VAF)-related profile as a novel biomarker for NSCLC personalized therapy. METHODS: We utilized genomic data of 915 NSCLC patients via cBioPortal and a local cohort of 23 patients for model construction and mutational analysis. Genomic, transcriptomic data from 952 TCGA NSCLC patients, and immunofluorescence (IF) assessment with the local cohort supported mechanism analysis. RESULTS: Utilizing the random forest algorithm, a 15-gene VAF-related model was established, differentiating patients with durable clinical benefit (DCB) from no durable benefit (NDB). The model demonstrated robust performance, with ROC-AUC values of 0.905, 0.737, and 0.711 across training (n = 313), internal validation (n = 133), and external validation (n = 157) cohorts. Stratification by the model into high- and low-score groups correlated significantly with both progression-free survival (PFS) (training: P < 0.0001, internal validation: P < 0.0001, external validation: P = 0.0066) and overall survival (OS) (n = 341) (P < 0.0001). Notably, the stratification system was independent of PD-L1 (P < 0.0001) and TMB (P < 0.0001). High-score patients exhibited an increased DCB ratio and longer PFS across both PD-L1 and TMB subgroups. Additionally, the high-score group appeared influenced by tobacco exposure, with activated DNA damage response pathways. Whereas, immune/inflammation-related pathways were enriched in the low-score group. Tumor immune microenvironment analyses revealed higher proportions of exhausted/effector memory CD8 + T cells in the high-score group. CONCLUSIONS: The mutational VAF profile is a promising biomarker for ICI therapy in NSCLC, with enhanced therapeutic stratification and management as a supplement to PD-L1 or TMB.

Using sustained vowels to identify patients with mild Parkinson's disease in a Chinese dataset.

Introduction: Parkinson's disease (PD) is the second most common neurodegenerative disease and affects millions of people. Accurate diagnosis and subsequent treatment in the early stages can slow down disease progression. However, making an accurate diagnosis of PD at an early stage is challenging. Previous studies have revealed that even for movement disorder specialists, it was difficult to differentiate patients with PD from healthy individuals until the average modified Hoehn-Yahr staging (mH&Y) reached 1.8. Recent researches have shown that dysarthria provides good indicators for computer-assisted diagnosis of patients with PD. However, few studies have focused on diagnosing patients with PD in the early stages, specifically those with mH&Y ≤ 1.5. Method: We used a machine learning algorithm to analyze voice features and developed diagnostic models for differentiating between healthy controls (HCs) and patients with PD, and for differentiating between HCs and patients with mild PD (mH&Y ≤ 1.5). The models were independently validated using separate datasets. Results: Our results demonstrate that, a remarkable diagnostic performance of the model in identifying patients with mild PD (mH&Y ≤ 1.5) and HCs, with area under the ROC curve 0.93 (95% CI: 0.851.00), accuracy 0.85, sensitivity 0.95, and specificity 0.75. Conclusion: The results of our study are helpful for screening PD in the early stages in the community and primary medical institutions where there is a lack of movement disorder specialists and special equipment.

High-Throughput Antigen Microarray Identifies Longitudinal Prognostic Autoantibody for Chemoimmunotherapy in Advanced Non-Small Cell Lung Cancer.

Chemoimmunotherapy has evolved as a standard treatment for advanced non-small cell lung cancer (aNSCLC). However, inevitable drug resistance has limited its efficacy, highlighting the urgent need for biomarkers of chemoimmunotherapy. A three-phase strategy to discover, verify, and validate longitudinal predictive autoantibodies (AAbs) for aNSCLC before and after chemoimmunotherapy was employed. A total of 528 plasma samples from 267 aNSCLC patients before and after anti-PD1 immunotherapy were collected, plus 30 independent formalin-fixed paraffin-embedded samples. Candidate AAbs were firstly selected using a HuProt high-density microarray containing 21,000 proteins in the discovery phase, followed by validation using an aNSCLC-focused microarray. Longitudinal predictive AAbs were chosen for ELISA based on responders versus non-responders comparison and progression-free survival (PFS) survival analysis. Prognostic markers were also validated using immunohistochemistry and publicly available immunotherapy datasets. We identified and validated a panel of two AAbs (MAX and DHX29) as pre-treatment biomarkers and another panel of two AAbs (MAX and TAPBP) as on-treatment predictive markers in aNSCLC patients undergoing chemoimmunotherapy. All three AAbs exhibited a positive correlation with early responses and PFS (p < 0.05). The kinetics of MAX AAb showed an increasing trend in responders (p < 0.05) and a tendency to initially increase and then decrease in non-responders (p < 0.05). Importantly, MAX protein and mRNA levels effectively discriminated PFS (p < 0.05) in aNSCLC patients treated with immunotherapy. Our results present a longitudinal analysis of changes in prognostic AAbs in aNSCLC patients undergoing chemoimmunotherapy.

Longitudinal plasma proteomic profiling of EML4-ALK positive lung cancer receiving ALK-TKIs therapy.

BACKGROUND: Anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs) has demonstrated remarkable therapeutic effects in ALK-positive non-small cell lung cancer (NSCLC) patients. Identifying prognostic biomarkers can enhance the clinical efficacy of relapsed or refractory patients. METHODS: We profiled 737 plasma proteins from 159 pre-treatment and on-treatment plasma samples of 63 ALK-positive NSCLC patients using data-independent acquisition-mass spectrometry (DIA-MS). The consensus clustering algorithm was used to identify subtypes with distinct biological features. A plasma-based prognostic model was constructed using the LASSO-Cox method. We performed the Mfuzz analysis to classify the patterns of longitudinal changes in plasma proteins during treatment. 52 baseline plasma samples from another independent ALK-TKI treatment cohort were collected to validate the potential prognostic markers using ELISA. RESULTS: We identified three subtypes of ALK-positive NSCLC with distinct biological features and clinical efficacy. Patients in subgroup 1 exhibited activated humoral immunity and inflammatory responses, increased expression of positive acute-phase response proteins, and the worst prognosis. Then we constructed and verified a prognostic model that predicts the efficacy of ALK-TKI therapy using the expression levels of five plasma proteins (SERPINA4, ATRN, APOA4, TF, and MYOC) at baseline. Next, we explored the longitudinal changes in plasma protein expression during treatment and identified four distinct change patterns (Clusters 1-4). The longitudinal changes of acute-phase proteins during treatment can reflect the treatment status and tumor progression of patients. Finally, we validated the prognostic efficacy of baseline plasma CRP, SAA1, AHSG, SERPINA4, and TF in another independent NSCLC cohort undergoing ALK-TKI treatment. CONCLUSIONS: This study contributes to the search for prognostic and drug-resistance biomarkers in plasma samples for ALK-TKI therapy and provides new insights into the mechanism of drug resistance and the selection of follow-up treatment.

Longitudinal plasma proteomic analysis identifies biomarkers and combinational targets for anti-PD1-resistant cancer patients.

The response rate of anti-PD1 therapy is limited, and the influence of anti-PD1 therapy on cancer patients is unclear. To address these challenges, we conducted a longitudinal analysis of plasma proteomic changes with anti-PD1 therapy in non-small cell lung cancer (NSCLC), alveolar soft part sarcoma (ASPS), and lymphoma patients. We included 339 plasma samples before and after anti-PD1 therapy from 193 patients with NSCLC, ASPS, or lymphoma. The plasma proteins were detected using data-independent acquisition-mass spectrometry and customable antibody microarrays. Differential proteomic characteristics in responders (R) and non-responders (NR) before and after anti-PD1 therapy were elucidated. A total of 1019 proteins were detected using our in-depth proteomics platform and distributed across 10-12 orders of abundance. By comparing the differential plasma proteome expression between R and NR groups, 50, 206, and 268 proteins were identified in NSCLC, ASPS, and lymphoma patients, respectively. Th17, IL-17, and JAK-STAT signal pathways were identified upregulated in NR group, while cellular senescence and transcriptional misregulation pathways were activated in R group. Longitudinal proteomics analysis revealed the IL-17 signaling pathway was downregulated after treatment. Consistently, many proteins were identified as potential combinatorial therapeutic targets (e.g., IL-17A and CD22). Five noninvasive biomarkers (FLT4, SFTPB, GNPTG, F5, and IL-17A) were further validated in an independent lymphoma cohort (n = 39), and another three noninvasive biomarkers (KIT, CCL3, and TNFSF1) were validated in NSCLC cohort (n = 76). Our results provide molecular insights into the anti-PD1 therapy in cancer patients and identify new therapeutic strategies for anti-PD1-resistant patients.

Identification of novel prognostic autoantibodies in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone via a high-throughput antigen microarray.

BACKGROUND: R-CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) is a standard first-line treatment for diffuse large B-cell lymphoma (DLBCL). However, 20%-40% of patients survive less than 5 years. Novel prognostic biomarkers remain in demand. METHODS: Baseline plasma autoantibodies (AAbs) were assessed in 336 DLBCLs. In the discovery phase (n = 20), a high-density antigen microarray (∼21,000 proteins) was used to expound AAb profiles. In the verification phase (n = 181), with a DLBCL-focused microarray, comparative results based on event-free survival at 24 months (EFS24) and lasso Cox regression models of progression-free survival (PFS) and overall survival (OS) were integrated to identify potential biomarkers. They were further validated by enzyme-linked immunosorbent assay in validation phase 1 (n = 135) and a dynamic cohort (n = 12). In validation phase 2, a two-AAb-based risk score was established. They were further validated in an immunohistochemistry cohort (n = 55) and four independent Gene Expression Omnibus datasets (n = 1598). RESULTS: Four AAbs (CREB1, N4BP1, UBAP2, and DEAF1) were identified that showed associations with EFS24 status (p < .05) and superior PFS and OS (p < .05). A novel risk score model based on CREB1 and N4BP1 AAbs was developed to predict PFS with areas under the curve of 0.72, 0.71, 0.76, and 0.82 at 1, 3, 5, and 7 years, respectively, in DLBCL treated with R-CHOP independent of the International Prognostic Index (IPI) and provided significant additional recurrence risk discrimination (p < .05) for the IPI. CREB1 and N4BP1 proteins and messenger RNAs were also associated with better PFS and OS (p < .05). CONCLUSIONS: This study identified a novel prognostic panel of CREB1, N4BP1, DEAF1, and UBAP2 AAbs that is independent of the IPI in DLBCL.

Immunogenicity assessment of elder hepatocellular carcinoma patients after inactivated whole-virion SARS-CoV-2 vaccination.

BACKGROUND: Research on immunogenicity after 3rd SARS-CoV-2 vaccine in elder hepatocellular carcinoma (HCC) was limited. This study aimed to investigate the efficacy and influencing factors of inactivated SARS-CoV-2 vaccine in elder HCC. RESEARCH DESIGN AND METHODS: We assessed total antibodies, anti-RBD IgG, and neutralizing antibodies (NAb) toward SARS-CoV-2 wild type (WT) as well as BA.4/5 in 304 uninfected HCC, 147 matched healthy control (HC), and 53 SARS-CoV-2 infected HCC, all aged over 60 years. The levels of antibodies were compared in the period 7-90, 91-180, and >180 days after 2nd or 3rd vaccination, respectively. RESULTS: HCC had lower seropositivity than HC after 2nd dose (total antibodies, 64% vs. 92%, P < 0.0001; anti-RBD IgG, 50% vs. 77%, P < 0.0001). But 3rd dose can efficaciously close the gap (total antibodies, 96% vs. 100%, P = 0.1212; anti-RBD IgG: 87% vs. 87%, P > 0.9999). Booster effect of 3rd dose can persist >180 days in HCC (2nd vs. 3rd: total antibodies, 0.60 vs. 3.20, P < 0.0001; anti-RBD IgG, 13.86 vs. 68.85, P < 0.0001; WT NAb, 11.70 vs. 22.47, P < 0.0001). Vaccinated HCC had more evident humoral responses than unvaccinated ones after infection (total antibodies: 3.85 vs. 3.20, P < 0.0001; anti-RBD IgG: 910.92 vs. 68.85, P < 0.0001; WT NAb: 96.09 vs. 22.47, P < 0.0001; BA.4/5 NAb: 86.53 vs. 5.59, P < 0.0001). CONCLUSIONS: Our findings highlight the booster effect and protective role of 3rd dose. Our results could provide a theoretical foundation for informing decisions regarding SARS-CoV-2 vaccination in elder HCC.

Obesity and head and neck cancer risk: a mendelian randomization study.

BACKGROUND: Observational studies have reported controversial results on the association between obesity and head and neck cancer risk. This study aimed to perform a two-sample Mendelian randomization (MR) analysis to assess the causal association between obesity and head and neck cancer risk using publicly available genome-wide association studies (GWAS) summary statistics. METHODS: Single-nucleotide polymorphisms (SNPs) for obesity [body mass index (BMI), waist-to-hip ratio (WHR), whole body fat mass, lean body mass, and trunk fat mass] and head and neck cancer (total head and neck cancer, oral cavity cancer, oropharyngeal cancer, and oral cavity and oropharyngeal cancer) were retrieved from published GWASs and used as genetic instrumental variables. Five methods including inverse-variance-weighted (IVW), weighted-median, MR-Egger, weighted mode, and MR-PRESSO were used to obtain reliable results, and odds ratio with 95% confidence interval (CI) were calculated. Tests for horizontal pleiotropy, heterogeneity, and sensitivity were performed separately. RESULTS: Genetically predicted BMI was negatively associated with the risk of total head and neck cancer, which was significant in the IVW [OR (95%CI), 0.990 (0.984-0.996), P = 0.0005], weighted-median [OR (95%CI), 0.984 (0.975-0.993), P = 0.0009], and MR-PRESSO [OR (95%CI), 0.990 (0.984-0.995), P = 0.0004] analyses, but suggestive significant in the MR-Egger [OR (95%CI), 0.9980 (0.9968-0.9991), P < 0.001] and weighted mode [OR (95%CI), 0.9980 (0.9968-0.9991), P < 0.001] analyses. Similar, genetically predicted BMI adjust for smoking may also be negatively associated with the risk of total head and neck cancer (P < 0.05). Genetically predicted BMI may be negatively related to the risk of oral cavity cancer, oropharyngeal cancer, and oral cavity and oropharyngeal cancer (P < 0.05), but no causal association was observed for BMI adjust for smoking (P > 0.05). In addition, no causal associations were observed for other exposures and outcomes (all P > 0.05). CONCLUSION: This MR analysis supported the causal association of BMI-related obesity with decreased risk of total head and neck cancer. However, the effect estimates from the MR analysis were close to 1, suggesting a slight protective effect of BMI-related obesity on head and neck cancer risk.

Proteomics Identifies Circulating TIMP-1 as a Prognostic Biomarker for Diffuse Large B-Cell Lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, although disease stratification using in-depth plasma proteomics has not been performed to date. By measuring more than 1000 proteins in the plasma of 147 DLBCL patients using data-independent acquisition mass spectrometry and antibody array, DLBCL patients were classified into four proteomic subtypes (PS-I-IV). Patients with the PS-IV subtype and worst prognosis had increased levels of proteins involved in inflammation, including a high expression of metalloproteinase inhibitor-1 (TIMP-1) that was associated with poor survival across two validation cohorts (n = 180). Notably, the combination of TIMP-1 with the international prognostic index (IPI) identified 64.00% to 88.24% of relapsed and 65.00% to 80.49% of deceased patients in the discovery and two validation cohorts, which represents a 24.00% to 41.67% and 20.00% to 31.70% improvement compared to the IPI score alone, respectively. Taken together, we demonstrate that DLBCL heterogeneity is reflected in the plasma proteome and that TIMP-1, together with the IPI, could improve the prognostic stratification of patients.

Antibody response to SARS-CoV-2 WT and Omicron BA.4/5 of inactivated COVID-19 vaccine in patients with lung cancer after second and booster immunization.

COVID-19 inactivated vaccine-induced humoral responses in patients with lung cancer (LCs) to SARS-CoV-2 wild-type (WT) strain and variants BA.4/5 after the primary 2-dose and booster vaccination remained unknown. We conducted a cross-sectional study in 260 LCs, 140 healthy controls (HC) and additional 40 LCs with serial samples by detecting total antibodies, IgG anti-RBD and neutralizing antibodies (NAb) toward WT and BA.4/5. SARS-CoV-2-specific antibody responses were augmented by the booster dose of inactivated vaccines in LCs, whereas they were lower than that in HCs. Enhanced humoral responses waned over time after triple injection, notably in NAb against WT and BA.4/5. The NAb against BA.4/5 was much lower than WT. Age ≥ 65 was risk factor for immunization of NAb to WT. Undergoing treatment resulted in a lower antibody response than those without and radiotherapy was a also risk factor for seroconversion of NAb to WT. Lower lymphocyte counts contributed to a lower titer of IgG anti-RBD and NAb against BA.4/5 in LCs than HCs. Specifically, total B cells, CD4+T cells and CD8+T counts were correlated with the humoral response. These results should be taken into consideration for the elderly patients under treatment.

High-Throughput Peptide Arrays Identify Potential Diagnostic Autoantibody Signatures in Early-Stage Lung Adenocarcinoma.

BACKGROUND: Early diagnosis is critical to lung adenocarcinoma patients' survival but faces inadequacies in convenient early detection. METHODS: We applied a comprehensive microarray of 130,000 peptides to detect "autoantibody signature" that is autoantibodies binding to mimotopes for early detection of stage 0-I LUAD. Plasma samples were collected from 147 early-stage lung adenocarcinoma (Early-LUAD), 108 benign lung disease (BLD), and 122 normal healthy controls (NHC). Clinical characteristics, low-dose CT (LDCT), and laboratory tests were incorporated into correlation analysis. RESULTS: We identified 143 and 133 autoantibody signatures, distinguishing Early-LUAD from NHC/BLD in the discovery cohort. Autoantibody signatures significantly correlated with age, stage, tumor size, basophil count, and IgM level (P < 0.05). The random forest models based on differential autoantibody signatures displayed AUC of 0.92 and 0.87 to discern Early-LUAD from NHC/BLD in the validation cohort, respectively. Compared with LDCT, combining autoantibody signature and LDCT improved the positive predictive value from 50% to 78.33% (P = 0.049). In addition, autoantibody signatures displayed higher sensitivity of 72.4% to 81.0% compared with the combinational tumor markers (cyfra21.1, NSE, SCC, ProGRP) with a sensitivity of 22.4% (P = 0.000). Proteins matched by differential peptides were enriched in cancer-related PI3K/Akt, MAPK, and Wnt pathways. Overlaps between matched epitopes and autoantibody signatures illustrated the underlying engagement of autoantibodies in immune recognition. CONCLUSIONS: Collectively, autoantibody signatures identified by a high-throughput peptide microarray have the potential to detect Early-LUAD, which could assist LDCT to better diagnose Early-LUAD. IMPACT: Novel sensitive autoantibody signatures can adjuvant LDCT to better diagnose LUAD at very early stage.

Early implementation of intended exercise improves quality of life in Parkinson's disease patients.

OBJECTIVE: Recent data have shown that regular exercise may ameliorate motor symptoms in Parkinson's disease (PD). This study aims to investigate how intended exercise impacts motor and non-movement symptoms of PD. METHODS: Eighty-eight patients were randomly assigned to an early exercise group (E-EG), late exercise group (L-EG), or a control group (CG) using a randomized delayed-start design. The E-EG carried out a rigorous, formal exercise program for 1 h, twice per week, for 18 months (May 2018-November 2019). The L-EG took part in the exercise program in the final 6-12 months of the study. We assessed outcomes using the Unified Parkinson's Disease Rating Scale (UPDRS), PDQ-39 Questionnaire, Line A test, Line B test, Nine-hole column test, 30 s squat and stand-up test (30 s SST), 10-m walk test (10mW), Balance Evaluation Systems Mini Test (MiniBESTest), FAB, and Time Up and Go Test (TUG). RESULTS: The patients with PD in the E-EG had lower performance in the UPDRS and Line B test compared to those in the L-EG at post-exercise (p < 0.05). Moreover, the patients with PD in the E-EG had much lower performance in the PDQ-39 and 9-Hole Peg test compared to those in the L-EG at post-exercise (p < 0.01). CONCLUSION: Implementation of an exercise regimen improved the movement abilities and quality of life in PD patients, especially in the E-EG. This data supports the idea that intended exercise should be implemented as part of the treatment strategy for PD patients as early as possible.

Cytokines screening identifies MIG (CXCL9) for postoperative recurrence prediction in operated non-small cell lung cancer patients.

BACKGROUND: Exploration of reliable biomarkers most likely to identify non-small cell lung cancer (NSCLC) patients at high risk for recurrence after surgery is needed. METHODS: Quantibody® Human Cytokine Antibody 6000 was used as screening tool to measure serum levels of 280 cytokines in ten healthy individuals and nine samples from three NSCLC patients before operation, after operation and postoperative recurrence. Selected cytokines were validated in two independent sets (89 patients before surgery, 69 patients after surgery and 40 patients with postoperative recurrence for each set) using ELISA method. The association of the selected cytokine with clinicopathologic features was also evaluated. RESULTS: Thirty-six cytokines were declined after surgery and again elevated when recurrence. We selected MIG to be further assessed in 2 validation sets, the mean value of serum MIG levels in 396 NSCLC patients was 253.42 ± 274.48 pg/mL and was significantly higher than the level in 60 healthy controls (47.65 ± 33.23 pg/mL, P < 0.0001). The serum MIG levels were 366.36 ± 324.04 pg/mL pre-operation, 134.04 ± 127.52 pg/mL post-operation and 208.05 ± 239.39 pg/mL in recurrence in NSCLC patients. The serum MIG levels were significant differences among NSCLC patients of pre-operation, post-operation and recurrence and controls (P < 0.0001). Moreover, Serum MIG levels were decreased markedly after operation and notably increased when disease relapsed (P < 0.0005). Serum MIG levels trend to be higher in patients with male gender, older age, smoking habit, poor tumor differentiation, and non-adenocarcinoma histology. CONCLUSIONS: These data indicated that MIG might be an indicator of postoperative recurrence and help to identify NSCLC patient who was easy to relapse after surgery.

Effective Rituximab Treatment in Patients with Neuromyelitis Optica Spectrum Disorders Compared with Azathioprine and Mycophenolate.

INTRODUCTION: As an autoimmune central nervous system disease characterized by inflammation and demyelination, neuromyelitis optica (NMO) has been extensively investigated. A specific antigenic target, astrocytic water channel aquaporin-4 (AQP4) has already been identified, and it can be recognized explicitly by the autoantibody marker NMO-IgG. Along with the immune attacks, clinical disabilities would gradually accumulate. As there has been no validated and well-recognized therapy for NMO till now, preventing and postponing attack using immunosuppressive therapies is the primary treatment option. METHODS: In the current retrospective study, the effect of immunosuppressive agents was investigated through a long-term follow-up. To assess the long-term effectiveness and safety of rituximab (RTX), azathioprine (AZA), and mycophenolate mofetil (MMF) therapies, all 129 patients with NMO spectrum disorders (NMOSD) who received at least one of these treatments were studied, including 55 seropositive for AQP4-Ab and 74 seronegative for AQP4-Ab. RESULTS: The median post-treatment annualized relapse rate (ARR) was lower than the pre-treatment rates in all AQP4+Ab groups (from 1.0 to 0.7 in RTX, from 0.8 to 0.3 in AZA, and from 0.85 to 0.35 in MMF). Meanwhile, the ARR also decreased in all AQP4-Ab groups (from 0.3 to 0.2 in RTX, from 0.9 to 0.5 in AZA, and from 0.9 to 0.4 in MMF). Disability condition improved in the Expanded Disability Status Scale (EDSS) in all AQP4+Ab groups (from 4.0 to 2.75 in RTX, from 3.5 to 2.5 in AZA, and from 3.0 to 2.0 in MMF) and in all AQP4-Ab groups (from 3.0 to 2.5 in RTX, from 3.0 to 2.5 in AZA, and from 3.5 to 2.0 in MMF). There was no statistically significant difference between the post-treatment and pre-treatment changes of EDSS and ARR in the RTX, AZA, and MMF groups (P > 0.05). However, according to Kaplan-Meier survival analysis, RTX-treated patients were more likely to be relapse-free after long-term follow-up than those who received AZA or MMF therapy. Meanwhile, adverse effects were noted in three out of 23 patients with RTX treatment, five of 32 with AZA treatment, and three of 21 with MMF treatment. No serious adverse events were observed in all treatment groups during the study. CONCLUSIONS: RTX, AZA, and MMF therapies efficiently lowered the relapse frequency and disability in both of the AQP4-Ab seropositive or seronegative patients with NMO. Furthermore, low dosage of RTX is recommended for the patients with NMO owing to its long-term effectiveness and safety.

Anti-PD1/PDL1 IgG subclass distribution in ten cancer types and anti-PD1 IgG4 as biomarker for the long time survival in NSCLC with anti-PD1 therapy.

BACKGROUND: Antibodies targeting programmed cell death-1(PD1) and its ligand (PDL1) have revolutionized cancer therapy. However, little is known about the preexisted anti-PD1/PDL1 autoantibodies (AAbs) distribution in multiple cancer types, nor is their potential biomarker role for anti-PD1 therapy. METHOD: Plasma anti-PD1/PDL1 AAb IgG and subclasses (IgG1-4) were detected by enzyme-linked immune sorbent assay (ELISA) in 190 cancer patients, covering 10 cancer types (lung, breast, esophageal, colorectal, liver, prostatic, cervical, ovarian, gastric cancers and lymphoma), the comprehensive correlation of AAbs with multiple clinical parameters was analyzed. We further tested these AAbs in 76 non-small cell lung cancer (NSCLC) samples receiving anti-PD1 therapy, the association of AAbs level with survival was analyzed and validated in an independent cohort (n = 32). RESULTS: Anti-PD1/PDL1 AAb IgG were globally detected in 10 types of cancer patients. IgG1 and IgG2 were the major subtypes for anti-PD1/PDL1 AAbs. Correlation analysis revealed a distinct landscape between various cancer types. The random forest model indicated that IgG4 subtype was mostly associated with cancer. In discovery cohort of 76 NSCLC patients, high anti-PD1 IgG4 was associated with a reduced overall survival (OS, p = 0.019), not progression-free survival (PFS, p = 0.088). The negative association of anti-PD1 IgG4 with OS was validated in 32 NSCLC patients (p = 0.032). CONCLUSION: This study reports for the first time the distribution of preexisted anti-PD1/PDL1 AAb IgG and subclasses across 10 cancer types. Moreover, the anti-PD1 AAb IgG4 subclass was identified to associate with OS, which may serve as a potential biomarker for anti-PD1 therapeutic survival benefit in NSCLC patients.

Development and validation of a UPLC-MS/MS method to quantitate anti-PD1 monoclonal antibody (Toripalimab), and comparison with electrochemiluminescence immunoassay.

Toripalimab, a humanized IgG4 monoclonal antibody (mAb) against programmed death receptor-1, is being extensively studied to treat various malignancies. At present, there is no complete methodology reported for quantifying toripalimab, except for an electrochemiluminescence immunoassay (ECLIA) mentioned in several clinical studies. Therefore, a sensitive and robust ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was developed to accurately detect toripalimab levels, compared with the ECLIA. Plasma samples were pretreated by a five-step process, encompassing denaturation, reduction, alkylation, enzymatic hydrolysis and quenching. And a unique, sensitive and stable enzymatic peptide (ASGYTFTDYEMHWVR) selected as surrogate of toripalimab was eluted and monitored by UPLC-MS/MS system with the linear range of 5.0375-201.5 µg/mL. After fully validated, the UPLC-MS/MS method was applied to determine 77 plasma samples from 29 patients in a phase I clinical trial, and compared with ECLIA based on 56 samples. Wilcoxon paired samples test showed toripalimab levels by UPLC-MS/MS were significantly higher than that by ECLIA (p < 0.001), though a strong correlation was observed (r = 0.96). Moreover, Passing-Bablok regression analysis exhibited constant and proportional biases: UPLC-MS/MS = 2.25 + 1.21 * ECLIA. This discrepancy could be mainly attributed to different forms determined: total mAb for UPLC-MS/MS and free mAb for ECLIA, respectively. As a result, this UPLC-MS/MS method may be complementary to ECLIA to monitor different forms of toripalimab. Beyond that, it can be easily modified to simultaneously quantitate multiple-analyte with a small volume of plasma.

Low CCL19 expression is associated with adverse clinical outcomes for follicular lymphoma patients treated with chemoimmunotherapy.

BACKGROUND: This study aimed to recognize the hub genes associated with prognosis in follicular lymphoma (FL) treated with first-line rituximab combined with chemotherapy. METHOD: RNA sequencing data of dataset GSE65135 (n = 24) were included in differentially expressed genes (DEGs) analysis. Weighted gene co-expression network analysis (WGCNA) was applied for exploring the coexpression network and identifying hub genes. Validation of hub genes expression and prognosis were applied in dataset GSE119214 (n = 137) and independent patient cohort from Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (n = 32), respectively, by analyzing RNAseq expression data and serum protein concentration quantified by ELISA. The Gene Set Enrichment Analysis (GSEA), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analysis were performed. CIBERSORT was applied for tumor-infiltrating immune cells (TIICs) subset analysis. RESULTS: A total of 3260 DEGs were obtained, with 1861 genes upregulated and 1399 genes downregulated. Using WGCNA, eight hub genes, PLA2G2D, MMP9, PTGDS, CCL19, NFIB, YAP1, RGL1, and TIMP3 were identified. Kaplan-Meier analysis and multivariate COX regression analysis indicated that CCL19 independently associated with overall survival (OS) for FL patients treated with rituximab and chemotherapy (HR = 0.47, 95% CI [0.25-0.86], p = 0.014). Higher serum CCL19 concentration was associated with longer progression-free survival (PFS, p = 0.014) and OS (p = 0.039). TIICs subset analysis showed that CCL19 expression had a positive correlation with monocytes and macrophages M1, and a negative correlation with naïve B cells and plasma cells. CONCLUSION: CCL19 expression was associated with survival outcomes and might be a potential prognostic biomarker for FL treated with first-line chemoimmunotherapy.

Recombinant human thrombopoietin prior to mobilization chemotherapy facilitates platelet recovery in autologous transplantation in patients with lymphoma: Results of a prospective randomized study.

BACKGROUND: Chemotherapy plus granulocyte colony-stimulating factor (GCSF) regimen is one of the available approaches to mobilize peripheral blood progenitor cells (PBPCs). It causes thrombocytopenia and delays leukapheresis. This study aimed to evaluate the role of recombinant human thrombopoietin (rhTPO) before mobilization chemotherapy in facilitating leukapheresis in patients with lymphoma. METHODS: In this randomized open-label phase 2 trial, patients were randomly assigned in a 1:2 ratio to receive mobilization with rhTPO plus GCSF in combination with chemotherapy (the rhTPO plus GCSF arm) or GCSF alone in combination with chemotherapy (the GCSF alone arm). The recovery of neutrophils and platelets and the amount of platelet transfusion were monitored. RESULTS: Thirty patients were enrolled in this study between March 2016 and August 2018. Patients in the rhTPO plus GCSF arm (n = 10) had similar platelet nadir after mobilization chemotherapy (P=0.878) and similar amount of platelet transfusion (median 0 vs. 1 unit, P=0.735) when compared with the GCSF alone arm (n = 20). On the day of leukapheresis, the median platelet count was 86 × 109/L (range 18-219) among patients who received rhTPO and 73 × 109/L (range 42-197) among those who received GCSF alone (P=0.982). After the use of rhTPO, the incidence of platelet count <75 × 109/L on the day of leukapheresis did not decrease significantly (30.0% vs. 50.0%, P=0.297). Platelet recovery after PBPC transfusion was more rapid in the rhTPO plus GCSF arm (median 8.0 days [95% confidence interval 2.9-13.1] to platelets ≥50 × 109/L vs. 11.0 days [95% confidence interval 8.6-13.4], P=0.011). The estimated total cost of the mobilization and reconstitution phases per patient was similar between the two treatmtent groups (P=0.362 and P=0.067, respectively). CONCLUSIONS: Our findings indicate that there was no significant clinical benefit of rhTPO use in facilitating mobilization of progenitor cells, but it may promote platelet recovery in the reconstitution phase after high-dose therapy. TRIAL REGISTRATION: This trial has been registered in Clinicaltrials.gov as NCT03014102.

Autoantibody profiling identifies predictive biomarkers of response to anti-PD1 therapy in cancer patients.

Background: Programmed cell death protein 1 (PD1) inhibitors have revolutionized cancer therapy, yet many patients fail to respond. Thus, the identification of accurate predictive biomarkers of therapy response will improve the clinical benefit of anti-PD1 therapy. Method: We assessed the baseline serological autoantibody (AAb) profile against ~2300 proteins in 10 samples and ~4600 proteins in 35 samples with alveolar soft part sarcoma (ASPS), non-small-cell lung cancer (NSCLC) and lymphoma using Nucleic Acid Programmable Protein Arrays (NAPPA). 23 selected potential AAb biomarkers were verified using simple, affordable and rapid enzyme linked immune sorbent assay (ELISA) technology with baseline plasma samples from 12 ASPS, 16 NSCLC and 46 lymphoma patients. SIX2 and EIF4E2 AAbs were further validated in independent cohorts of 17 NSCLC and 43 lymphoma patients, respectively, using ELISA. The IgG subtypes in response to therapy were also investigated. Results: Distinct AAb profiles between ASPS, NSCLC and lymphoma were observed. In ASPS, the production of P53 and PD1 AAbs were significantly increased in non-responders (p=0.037). In NSCLC, the SIX2 AAb was predictive of response with area under the curve (AUC) of 0.87, 0.85 and 0.90 at 3 months, 4.5 months, 6 months evaluation time points, respectively. In the validation cohort, the SIX2 AAb was consistently up-regulated in non-responders (p=0.024). For lymphoma, the EIF4E2 AAb correlated with a favorable response with AUCs of 0.68, 0.70, and 0.70 at 3 months, 4.5 months, and 6 months, respectively. In the validation cohort, the AUCs were 0.74, 0.75 and 0.66 at 3 months, 4.5 months, and 6 months, respectively. The PD1 and PD-L1 IgG2 AAbs were highly produced in ~20% of lymphoma responders. Furthermore, bioinformatics analysis revealed antigen functions of these AAb biomarkers. Conclusion: This study provides the first evidence that AAb biomarkers selected using high-throughput protein microarrays can predict anti-PD1 therapeutic response and guide anti-PD1 therapy.

Safety and clinical efficacy of toripalimab, a PD-1 mAb, in patients with advanced or recurrent malignancies in a phase I study.

PURPOSE: This is a first-in-human phase I study investigating the safety and efficacy of toripalimab, a humanized monoclonal antibody against the programmed cell death-1 (PD-1) receptor, in Chinese patients with advanced or recurrent malignant tumor refractory to standard treatment. PATIENTS AND METHODS: During dose escalation, patients received a single-dose intravenous infusion of toripalimab for 56 days followed by multidose infusions every two weeks. The planned dosing groups were 1, 3 and 10 mg/kg. During dose expansion, patients received toripalimab every two weeks. Clinical response was evaluated by investigators every 6 weeks. RESULTS: Thirty-three patients were enrolled, including 12 patients with alveolar soft part sarcoma (ASPS), seven with non-small-cell lung cancer and 11 with lymphoma. Patients were heavily pretreated with a median of 3 prior lines of systemic treatments. Toripalimab was well tolerated without dose-limiting toxicity. All patients experienced treatment-related adverse events. Grade 3 and above treatment-related adverse events occurred in six (18.2%) patients. Among 22 solid tumors, the objective response rate (ORR) was 22.7% per RECIST v1.1. The ORR was 90.9% in 11 lymphoma patients per IWG 2007. The median duration of response was 21.5 months. The median progression-free survival was 5.7 months for solid tumors and 8.3 months for lymphomas. The median OS was not reached for all patients and the lymphoma subgroups. The median OS was 34.7 months for patients with ASPS. CONCLUSION: Toripalimab was well tolerated up to 10 mg/kg Q2W without dose-limiting toxicity and showed promising and durable antitumour activities in patients with ASPS and lymphoma, who were heavily pretreated. CLINICAL TRIAL INFORMATION: ClinicalTrials.gov Identifier: NCT02836834.