Placebo immune-related adverse events (irAEs): A neglected phenomenon in cancer immunotherapy trials.

PURPOSE: This study aims to investigate the underexplored prevalence of placebo-reported immune-related adverse events (irAEs) in immune checkpoint inhibitor (ICI) trials. METHODS: We searched public databases for randomized clinical trials (RCTs) involving ICI versus placebo treatments in patients with malignancies. Study characteristics and irAEs occurrences were extracted for meta-analyses using a random-effects model. MAIN OUTCOMES: Proportions of patients reported to experience any grade and grade 3 to 5 placebo irAEs; the risk ratio (RR) of reporting 'false' irAEs in the experiment arm (defined as 'false-irAE ratio', calculated by dividing the proportion of patients documented with irAEs in the placebo arm by that in the experimental arm). RESULTS: 47 RCTs with 30,119 patients were analyzed. The pooled proportion of patients reported to experience any grade and grade 3 to 5 irAEs among placebo participants was 22.85 % (17.33 %-29.50 %) and 3.40 % (2.35 %-4.63 %), respectively. The pooled proportion of placebo-treated patients who experienced serious irAEs was 0.67 % (0.03 %-1.91 %). Treatment discontinuation and death due to placebo irAEs occurred in 0.69 % (<0.01 %-1.30 %) and 0.12 % (<0.01 %-0.40 %) of patients, respectively. The false-irAE ratio for any grade and grade 3 to 5 irAEs were 0.49 and 0.28. The false-irAE ratio was significantly higher in RCTs with control arms of placebo plus non-immunotherapy than in those with placebo alone (any grade: 0.57 vs. 0.32, P < 0.001; grade 3 to 5: 0.36 vs. 0.12, P = 0.009). CONCLUSION: Our analyses of placebo-treated participants in ICI RCTs document the common occurrence of placebo irAEs. These findings are important for interpreting irAE profiles, avoiding inappropriate therapeutic interventions.

Neoadjuvant-Adjuvant vs Neoadjuvant-Only PD-1 and PD-L1 Inhibitors for Patients With Resectable NSCLC: An Indirect Meta-Analysis.

Importance: Neoadjuvant therapy combining programmed cell death 1 (PD-1) and programmed death ligand 1 (PD-L1) inhibitors with platinum-based chemotherapy has demonstrated significant improvement in pathologic response and survival rates among patients with resectable non-small cell lung cancer (NSCLC). However, it remains controversial whether PD-1 blockade therapy given before and after surgery (neoadjuvant-adjuvant treatment) is associated with better outcomes than when given only before surgery (neoadjuvant-only treatment). Objective: To compare the efficacy and safety associated with neoadjuvant-adjuvant anti-PD-1 and anti-PD-L1 therapy with neoadjuvant-only anti-PD-1 and anti-PD-L1 therapy for patients with resectable NSCLC. Data Sources: A systematic search was conducted across databases including PubMed, Embase, and the Cochrane Library, as well as major oncology conferences, through July 31, 2023. Study Selection: Randomized clinical trials comparing neoadjuvant-adjuvant or neoadjuvant-only PD-1 and PD-L1 inhibitor therapy vs chemotherapy alone for patients with resectable NSCLC were selected. Data Extraction and Synthesis: Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline, 2 authors independently extracted data. Hazard ratios (HRs) and 95% CIs for event-free survival (EFS) and overall survival (OS) were extracted and then pooled through the generic inverse-variance methods. Relative risks (RRs) for treatment-related adverse events (TRAEs) were derived via the Mantel-Haenszel method. Using chemotherapy as a common comparator, indirect comparisons between neoadjuvant-adjuvant immunotherapy and neoadjuvant-only immunotherapy were conducted using frequentist methods. A random or fixed model was used based on intertrial heterogeneity identified through the Cochran Q test. Main Outcomes and Measures: The primary outcome was EFS, with secondary outcomes including OS and TRAEs. Results: The study encompassed 4 trials of neoadjuvant-adjuvant immunotherapy and 1 trial of neoadjuvant-only immunotherapy, involving 2385 patients. Direct meta-analysis revealed significant improvements in EFS for both neoadjuvant-adjuvant and neoadjuvant-only immunotherapy compared with chemotherapy alone. In indirect meta-analysis, the addition of adjuvant immunotherapy to neoadjuvant immunotherapy was not associated with improved EFS (HR, 0.90; 95% CI, 0.63-1.30; P = .59) or OS (HR, 1.18; 95% CI, 0.73-1.90; P = .51) compared with neoadjuvant-only immunotherapy. Moreover, the incidence of any grade of TRAEs significantly increased with the addition of adjuvant immunotherapy (RR, 1.08; 95% CI, 1.00-1.17; P = .04). Conclusions and Relevance: This meta-analysis suggests that adding PD-1 or PD-L1 inhibitors in the adjuvant phase to neoadjuvant treatment with PD-1 or PD-L1 inhibitors and chemotherapy may not improve survival outcomes for patients with resectable NSCLC and may be associated with increased adverse events. Future validation of these findings is warranted through head-to-head randomized clinical trials.

Evaluation of two treatment concepts of four implants supporting fixed prosthesis in an atrophic maxilla: finite element analysis.

BACKGROUND: Currently, oblique placement of long implants or the use of short implants to circumvent the maxillary sinus area and provide support for fixed prostheses are viable alternatives. The purpose of this study was to compare these two treatment concepts and ascertain which one exhibits superior biomechanical characteristics. METHODS: Two different treatment concept models were constructed. The first one, LT4I, consisting of two mesial vertical implants positioned in lateral incisor regions and two distal tilted implants (45°) situated in second premolar regions of the maxilla. The second model, VS4I, includes two mesial vertical implants in lateral incisor regions and two vertically positioned short implants in second premolar regions. Numerical simulations were conducted under three loading types: firstly, oblique forces upon the molars; secondly, vertical forces upon the molars; thirdly, oblique forces upon the incisors. The maximum principal stress (σmax) and minimum principal stress (σmin) of the bone, as well as von Mises stress of the implants, were calcuated. RESULTS: Under oblique loading on the molar, higher stress values in the bone were observed in LT4I group. Under vertical loading on molar, higher stress values in the bone were also observed in LT4I group. Furthermore, little difference was found between the two groups under oblique loading on the incisor. CONCLUSION: Both treatment concepts can be applicable for edentulous individuals with moderate atrophic maxilla. Compared to tilted implants, short implants can transmit less occlusal force to the supporting tissues.

Tumor response assessment by measuring the single largest lesion per organ in advanced non-small cell lung cancer patients treated with PD-1/PD-L1 inhibitor.

Background: For Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST1.1), measuring up to two target lesions per organ is an arbitrary criterion. Objectives: We sought to compare response assessment using RECIST1.1 and modified RECIST1.1 (mRECIST1.1, measuring the single largest lesion per organ) in advanced non-small cell lung cancer (aNSCLC) patients undergoing anti-PD-1/PD-L1 monotherapy. Methods: Concordance of radiologic response categorization between RECIST1.1 and mRECIST1.1 was compared using the Kappa statistics. C-index was calculated to evaluate prognostic accuracy of radiologic response by the two criteria. The Kaplan-Meier method and Cox regression analysis were conducted for progression-free survival (PFS) and overall survival (OS). Results: Eighty-seven patients who had at least two target lesions in any organ per the RECIST1.1 were eligible for comparison analysis. Tumor response showed excellent concordance when measured using the RECIST1.1 and mRECIST1.1 (Kappa = 0.961). C-index by these two criteria was similar for PFS (0.784 versus 0.785) and OS (0.649 versus 0.652). Responders had significantly longer PFS and OS versus non-responders (p < 0.05), whichever criterion adopted. Radiologic response remained a significant predictor of PFS and OS in multivariate analysis (p < 0.05). Conclusion: The mRECIST1.1 was comparable to RECIST1.1 in response assessment among aNSCLC patients who received single-agent PD-1/PD-L1 inhibitor. The mRECIST1.1, with reduced number of lesions to be measured, may be sufficient and more convenient to assess antitumor activity in clinical practice.

Deciphering transcriptomic determinants of the divergent link between PD-L1 and immunotherapy efficacy.

Programmed cell death ligand 1 (PD-L1) expression remains the most widely used biomarker for predicting response to immune checkpoint inhibitors (ICI), but its predictiveness varies considerably. Identification of factors accounting for the varying PD-L1 performance is urgently needed. Here, using data from three independent trials comprising 1239 patients, we have identified subsets of cancer with distinct PD-L1 predictiveness based on tumor transcriptome. In the Predictiveness-High (PH) group, PD-L1+ tumors show better overall survival, progression-free survival, and objective response rate with ICI than PD-L1- tumors across three trials. However, the Predictiveness-Low (PL) group demonstrates an opposite trend towards better outcomes for PD-L1- tumors. PD-L1+ tumors from the PH group demonstrate the superiority of ICI over chemotherapy, whereas PD-L1+ tumors from the PL group show comparable efficacy between two treatments or exhibit an opposite trend favoring chemotherapy. This observation of context-dependent predictiveness remains strong regardless of immune subtype (Immune-Enriched or Non-Immune), PD-L1 regulation mechanism (adaptative or constitutive), tumor mutation burden, or neoantigen load. This work illuminates avenues for optimizing the use of PD-L1 expression in clinical decision-making and trial design, although this exploratory concept should be further confirmed in large trials.

STK11/LKB1-Deficient Phenotype Rather Than Mutation Diminishes Immunotherapy Efficacy and Represents STING/Type I Interferon/CD8+ T-Cell Dysfunction in NSCLC.

INTRODUCTION: Conflicting findings have been reported regarding the association between STK11/LKB1 mutations and immune checkpoint inhibitor (ICB) efficacy in NSCLC. It has been reported that tumors could exhibit impaired STK11/LKB1 function even without STK11 mutations. We hypothesized that STK11 phenotype rather than mutation may better stratify ICB outcomes. METHODS: Selected functional STK11 events and LKB1 protein data were leveraged to establish a transcriptomics-based classifier of STK11 phenotype (STK11-deficient [-def] or -proficient [-prof]). We analyzed in-house and Genentech/Roche's data of three randomized trials of programmed cell death protein-1 or programmed death-ligand 1 (PD-L1) inhibition in NSCLC (ORIENT-11, n = 171; OAK, n = 699; POPLAR, n = 192) and The Cancer Genome Atlas-NSCLC cohort. RESULTS: Tissue STK11 mutation did not affect ICB outcomes. However, the survival benefit of ICB versus chemotherapy were lost or reversed in STK11-def tumors (hazard ratios for death, 95% confidence interval: OAK [0.97, 0.69-1.35]; POPLAR [1.61, 0.88-2.97]; ORIENT-11 [1.07, 0.50-2.29]), while remaining in STK11-prof tumors (hazard ratios for death, 95% confidence interval: OAK [0.81, 0.66-0.99]; POPLAR [0.66, 0.46-0.95]; ORIENT-11 [0.59, 0.37-0.92]). In tumors differentially classified by phenotype and mutation status, STK11-wild-type/def tumors had significantly worse ICB outcomes than STK11-mutated (STK11-MUT)/prof tumors (p < 0.05). The deleterious impact of STK11 deficiency was independent of STK11/KRAS/KEAP1 status or PD-L1 expression. The STING/interferon-I signaling, which was previously shown to be suppressed in STK11-MUT models, was perturbed in patients with STK11-def tumors rather than those with STK11-MUT tumors. Surprisingly, whereas high CD8+ T-cell infiltration was significantly associated with prolonged survival with ICB in STK11-prof tumors (p < 0.05 for 3 trials), it predicted an opposite trend toward worse ICB outcomes in STK11-def tumors across three trials. This suggested an association between STK11 deficiency and CD8+ T-cell dysfunction, which might not be reversed by programmed cell death protein 1 or PD-L1 blockade. CONCLUSIONS: STK11 phenotype rather than mutation status can accurately identify patients with ICB-refractory NSCLC and reflect immune suppression. It can help refine stratification algorithms for future clinical research and also provide a reliable resource aiding basic and translational studies in identifying therapeutic targets.

Dual Resistive Switching Performance Derived from Ionic Migration in Halide Perovskite Based Memory.

Herein, we report an environmentally stable and friendly halide perovskite based resistive random access memory device with an Ag/PMMA/(PMA)2CuBr4/FTO (PMMA = poly(methyl methacrylate); PMA = C6H5CH2NH3) architecture. The device exhibits the coexistence of two bipolar resistive switching modes, including counterclockwise and clockwise switching characteristics. The devices with both switching modes show stable endurance (>100 cycles) and long retention performance (>104 s). By applying a suitable electrical stimulation, the counterclockwise and clockwise switching behaviors are interconvertible. Furthermore, the Au/PMMA/(PMA)2CuBr4/FTO and Ag/(PMA)2CuBr4/FTO devices were fabricated to verify the origin of dual resistive switching behaviors. The similar dual resistive switching behaviors after electroforming processes of three types of memory devices suggest that the interconvertible dual resistive switching characteristics could be attributed to the ionic migration in the (PMA)2CuBr4 perovskite layer.

[Cuproptosis-related immune gene signature predicts clinical benefits from anti-PD-1/PD-L1 therapy in non-small-cell lung cancer.

Non-small-cell lung cancer (NSCLC) remains the major cause of cancer-related death. Immune checkpoint inhibition has become the cornerstone treatment for NSCLC. Cuproptosis is a newly identified form of cell death relying on mitochondrial respiration that might play a role in shaping tumor immune microenvironment (TIME). The clinical significance of cuproptosis-related genes (CRGs) remains unclear and warrant investigation. The current study extracted RNA sequencing profiles and corresponding clinical information from six aggregated datasets from the Gene Expression Omnibus (GEO) repository as the training set, and from The Cancer Genome Atlas (TCGA) database as the testing set. Cuproptosis-related immune genes (CRIMGs) were obtained through coexpression analysis, univariate Cox regression analysis, and LASSO analysis for overall survival (OS) association analysis. Consensus clustering was employed to divide the subjects into clusters. Stepwise multivariate Cox regression was used to establish the prognostic CRIMG_score from the CRIMGs. A 17-gene prediction signature was established that informed patients' OS both in the training and testing datasets (p < 0.001). The predictive value of the signature in terms of immunotherapeutic responses was assessed in two publicly available NSCLC immunotherapy datasets (POPLAR and OAK studies) and an internal dataset from Sun Yat-sen University Cancer Center (ORIENT-11 study). Patients in the high-risk group displayed worse survival, a characteristic suppressive tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low-risk group. Collectively, the CRIMG_score established herein could serve as a promising indicator of prognosis and immunotherapeutic response in patients with NSCLC.

Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.

BACKGROUND: in current clinical practice, the standard evaluation for axillary lymph node (ALN) status in breast cancer has a low efficiency and is based on an invasive procedure that causes operative-associated complications in many patients. Therefore, we aimed to use machine learning techniques to develop an efficient preoperative magnetic resonance imaging (MRI) radiomics evaluation approach of ALN status and explore the association between radiomics and the tumor microenvironment in patients with early-stage invasive breast cancer. METHODS: in this retrospective multicenter study, three independent cohorts of patients with breast cancer (n = 1,088) were used to develop and validate signatures predictive of ALN status. After applying the machine learning random forest algorithm to select the key preoperative MRI radiomic features, we used ALN and tumor radiomic features to develop the ALN-tumor radiomic signature for ALN status prediction by the support vector machine algorithm in 803 patients with breast cancer from Sun Yat-sen Memorial Hospital and Sun Yat-sen University Cancer Center (training cohort). By combining ALN and tumor radiomic features with corresponding clinicopathologic information, the multiomic signature was constructed in the training cohort. Next, the external validation cohort (n = 179) of patients from Shunde Hospital of Southern Medical University and Tungwah Hospital of Sun Yat-Sen University, and the prospective-retrospective validation cohort (n = 106) of patients treated with neoadjuvant chemotherapy in prospective phase 3 trials [NCT01503905], were included to evaluate the predictive value of the two signatures, and their predictive performance was assessed by the area under operating characteristic curve (AUC). This study was registered with ClinicalTrials.gov, number NCT04003558. FINDINGS: the ALN-tumor radiomic signature for ALN status prediction comprising ALN and tumor radiomic features showed a high prediction quality with AUC of 0·88 in the training cohort, 0·87 in the external validation cohort, and 0·87 in the prospective-retrospective validation cohort. The multiomic signature incorporating tumor and lymph node MRI radiomics, clinical and pathologic characteristics, and molecular subtypes achieved better performance for ALN status prediction with AUCs of 0·90, 0·91, and 0·93 in the training cohort, the external validation cohort, and the prospective-retrospective validation cohort, respectively. Among patients who underwent neoadjuvant chemotherapy in the prospective-retrospective validation cohort, there were significant differences in the key radiomic features before and after neoadjuvant chemotherapy, especially in the gray-level dependence matrix features. Furthermore, there was an association between MRI radiomics and tumor microenvironment features including immune cells, long non-coding RNAs, and types of methylated sites. Interpretation this study presented a multiomic signature that could be preoperatively and conveniently used for identifying patients with ALN metastasis in early-stage invasive breast cancer. The multiomic signature exhibited powerful predictive ability and showed the prospect of extended application to tailor surgical management. Besides, significant changes in key radiomic features after neoadjuvant chemotherapy may be explained by changes in the tumor microenvironment, and the association between MRI radiomic features and tumor microenvironment features may reveal the potential biological underpinning of MRI radiomics. FUNDING: No funding.

Development and Validation of a Preoperative Magnetic Resonance Imaging Radiomics-Based Signature to Predict Axillary Lymph Node Metastasis and Disease-Free Survival in Patients With Early-Stage Breast Cancer.

Importance: Axillary lymph node metastasis (ALNM) status, typically estimated using an invasive procedure with a high false-negative rate, strongly affects the prognosis of recurrence in breast cancer. However, preoperative noninvasive tools to accurately predict ALNM status and disease-free survival (DFS) are lacking. Objective: To develop and validate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomic signatures for preoperative identification of ALNM and to assess individual DFS in patients with early-stage breast cancer. Design, Setting, and Participants: This retrospective prognostic study included patients with histologically confirmed early-stage breast cancer diagnosed at 4 hospitals in China from July 3, 2007, to September 21, 2019, randomly divided (7:3) into development and vaidation cohorts. All patients underwent preoperative MRI scans, were treated with surgery and sentinel lymph node biopsy or ALN dissection, and were pathologically examined to determine the ALNM status. Data analysis was conducted from February 15, 2019, to March 20, 2020. Exposure: Clinical and DCE-MRI radiomic signatures. Main Outcomes and Measures: The primary end points were ALNM and DFS. Results: This study included 1214 women (median [IQR] age, 47 [42-55] years), split into development (849 [69.9%]) and validation (365 [30.1%]) cohorts. The radiomic signature identified ALNM in the development and validation cohorts with areas under the curve (AUCs) of 0.88 and 0.85, respectively, and the clinical-radiomic nomogram accurately predicted ALNM in the development and validation cohorts (AUC, 0.92 and 0.90, respectively) based on a least absolute shrinkage and selection operator (LASSO)-logistic regression model. The radiomic signature predicted 3-year DFS in the development and validation cohorts (AUC, 0.81 and 0.73, respectively), and the clinical-radiomic nomogram could discriminate high-risk from low-risk patients in the development cohort (hazard ratio [HR], 0.04; 95% CI, 0.01-0.11; P < .001) and the validation cohort (HR, 0.04; 95% CI, 0.004-0.32; P < .001) based on a random forest-Cox regression model. The clinical-radiomic nomogram was associated with 3-year DFS in the development and validation cohorts (AUC, 0.89 and 0.90, respectively). The decision curve analysis demonstrated that the clinical-radiomic nomogram displayed better clinical predictive usefulness than the clinical or radiomic signature alone. Conclusions and Relevance: This study described the application of MRI-based machine learning in patients with breast cancer, presenting novel individualized clinical decision nomograms that could be used to predict ALNM status and DFS. The clinical-radiomic nomograms were useful in clinical decision-making associated with personalized selection of surgical interventions and therapeutic regimens for patients with early-stage breast cancer.

Clinical evidence for association of neoadjuvant chemotherapy or chemoradiotherapy with efficacy and safety in patients with resectable esophageal carcinoma (NewEC study).

BACKGROUND: The efficacy and safety of neoadjuvant treatment over surgery alone and that of neoadjuvant chemoradiotherapy (NCRT) over neoadjuvant chemotherapy (NCT) in resectable esophageal carcinoma remains inconclusive. This study (NewEC) used global data to comprehensively evaluate these comparisons and to provide a preferable strategy for patient subsets. METHODS: This study included a meta-analysis of randomized controlled trials (RCTs) identified from inception to May 2019 from PubMed, EMBASE, the Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, and congresses and a registry-based cohort study with patients from Massachusetts General Hospital (Massachusetts, USA) and Guangdong Provincial People's Hospital (Guangzhou, China) recruited from November 2000 and June 2017, to cross-validate the comparisons among NCRT versus NCT versus surgery. The GRADE approach was used to assessed quality of evidence in meta-analysis. Neural network machine learning propensity score-matched analysis was used to account for confounding by patient-level characteristics in the cohort study. The primary endpoint was overall survival (OS). The study was registered with PROSPERO CRD42017072242 and ClinicalTrials.gov NCT04027543. FINDINGS: Of 22,070 studies assessed, there were 38 (n = 6,993 patients) eligible RCTs. Additionally, 423 out of 467 screened patients were included in the cohort study. The results from trials showed that NCT had a better OS than surgery alone (hazard ratio [HR] 0·88, 95% confidence interval [CI] 0·79-0·98; high quality) and was only favorable for adenocarcinoma (HR 0·83, 95% CI 0·72-0·96; moderate quality). High-quality evidence showed a significantly better OS for NCRT than surgery alone (HR 0·74, 95% CI 0·66-0·82) for both adenocarcinoma (HR 0·73, 95% CI 0·62-0·86) and squamous cell carcinoma (SCC) (HR 0·73, 95% CI 0·65-0·83). The OS benefit of NCRT over NCT was seen in the pairwise (HR 0·78, 95% CI 0·62-0·99; high quality) and network (HR 0·82, 95% CI 0·72-0·93; high quality) meta-analyses, with similar results before (HR 0·60, 95% CI 0·40-0·91) and after (HR 0·44, 95% CI 0·25-0·77) matching in the cohort study, leading to a significantly increased 5-year OS rate in both adenocarcinoma and SCC before and after matching. The increased benefits from NCT or NCRT were not associated with the risk of 30-day or in-hospital mortality. INTERPRETATION: NewEC Study provided high-quality evidence supporting the survival benefits of NCRT or NCT over surgery alone, with NCRT presenting the greatest benefit for resectable esophageal carcinoma. FUNDING: National Science and Technology Major Project, the National Natural Science Foundation of China, the Natural Science Foundation of Guangdong Province, the Guangzhou Science and Technology Major Program, the Medical artificial intelligence project of Sun Yat-Sen Memorial Hospital, the Guangdong Science and Technology Department, the Guangdong Province Medical Scientific Research Foundation, and Guangdong Provincial People's Hospital Intermural Program.

Association of Long Noncoding RNA Biomarkers With Clinical Immune Subtype and Prediction of Immunotherapy Response in Patients With Cancer.

Importance: Long noncoding RNAs (lncRNAs) are involved in innate and adaptive immunity in cancer by mediating the functional state of immunologic cells, pathways, and genes. However, whether lncRNAs are associated with immune molecular classification and clinical outcomes of cancer immunotherapy is largely unknown. Objectives: To explore lncRNA-based immune subtypes associated with survival and response to cancer immunotherapy and to present a novel lncRNA score for immunotherapy prediction using computational algorithms. Design, Setting, and Participants: In this cohort study, an individual patient analysis based on a phase 2, single-arm clinical trial and multicohort was performed from June 25 through September 30, 2019. Data are from the phase 2 IMvigor210 trial and from The Cancer Genome Atlas (TCGA). The study analyzed lncRNA and genomic data of 348 patients with bladder cancer from the IMvigor210 trial and 71 patients with melanoma from TCGA who were treated with immunotherapy. In addition, a pancancer multicohort that included 2951 patients was obtained from TCGA. Main Outcomes and Measures: The primary end point was overall survival (OS). Results: Among 348 patients from the IMvigor210 trial (272 [78.2%] male) and 71 patients with melanoma from TCGA (mean [SD] age, 58.3 [13.4] years; 37 [52.1%] female), 4 distinct classes with statistically significant differences in OS (median months, not reached vs 9.6 vs 8.1 vs 6.7 months; P = .002) were identified. The greatest OS benefit was obtained in the immune-active class, as characterized by the immune-functional lncRNA signature and high CTL infiltration. Patients with low vs high lncRNA scores had statistically significantly longer OS (hazard ratio, 0.32; 95% CI, 0.24-0.42; P < .001) in the IMvigor210 trial and across various cancer types. The lncRNA score was associated with immunotherapeutic OS benefit in the IMvigor210 trial cohort (area under the curve [AUC], 0.79 at 12 months and 0.77 at 20 months) and in TCGA melanoma cohort (AUC, 0.87 at 24 months), superior tumor alteration burden, programmed cell death ligand 1 (PD-L1) expression, and cytotoxic T-lymphocyte (CTL) infiltration. Addition of the lncRNA score to the combination of tumor alteration burden, PD-L1 expression, and CTL infiltration to build a novel multiomics algorithm correlated more strongly with OS in the IMvigor210 trial cohort (AUC, 0.81 at 12 months and 0.80 at 20 months). Conclusions and Relevance: This study identifies novel lncRNA-based immune classes in cancer immunotherapy and recommends immunotherapy for patients in the immune-active class. In addition, the study recommends that the lncRNA score should be integrated into multiomic panels for precision immunotherapy.

Association of survival and genomic mutation signature with immunotherapy in patients with hepatocellular carcinoma.

BACKGROUND: Current guidelines lack recommendations for the use of immunotherapy and immune-related biomarkers for hepatocellular carcinoma (HCC). We aim to provide reliable evidence of the association of survival with HCC immunotherapy and to demonstrate that genomic mutation signature could be an effective biomarker to predict immunotherapy efficacy of HCC patients. METHODS: We conducted a meta-analysis of 17 randomized trials with 2055 patients and an individual patient-level analysis of 31 patients. Trial data were identified in PubMed, EMBASE and Cochrane Central library, and individual patient data were obtained from the cBioPortal database. Overall survival (OS) and progression-free survival (PFS) were assessed with the hazard ratio (HR) and 95% CI. This study is registered with PROSPERO, number CRD42018083991. RESULTS: The meta-analysis showed that compared to conventional therapy, immunotherapy resulted in prolonged OS (HR =0.65, P<0.0001, high quality) and PFS (HR =0.81, P<0.0001, high quality); the benefits were observed for cellular immunotherapy, tumor vaccine, and cytokine immunotherapy. Findings were robust to subgroup and trial sequential analyses. In the individual patient-level analysis of patients treated with immune checkpoint inhibitor, mutations in TERT, CTNNB1, BRD4, or MLL, and co-mutations in TP53 and TERT or BRD4 were associated with significantly worse survival. These oncogenes were used to develop a novel integrated mutation risk score, which exhibited better utility in predicting survival than the tumor mutation burden (TMB). Patients with low- versus high- mutation risk score had longer OS (HR =0.18, P=0.02) and PFS (HR =0.33, P=0.018). A nomogram comprising the mutation risk score and essential clinical factors further improved the predictive accuracy (AUC =0.840 for both 1- and 2-year OS). CONCLUSIONS: Immunotherapy showed longer OS and PFS than conventional therapy among HCC patients, especially patients with a low mutation risk score. The nomogram based on genomic and clinical characteristics is effective in predicting survival of HCC patients undergoing immune checkpoint inhibitor.

Association of Survival and Immune-Related Biomarkers With Immunotherapy in Patients With Non-Small Cell Lung Cancer: A Meta-analysis and Individual Patient-Level Analysis.

Importance: The beneficial role of immunotherapy and the clinical relevance of current biomarkers in non-small cell lung cancer (NSCLC) remain inconclusive; thus, appropriate strategies and reliable predictors need further definition. Objectives: To evaluate the association of clinical outcomes with immune checkpoint inhibitors, tumor vaccines, and cellular immunotherapy in patients with advanced NSCLC and to explore appropriate strategies, candidates, and predictors. Data Sources: The PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases were searched from inception to June 2018, using relevant search keywords and Medical Subject Headings (MeSH) terms, including tumor vaccine, cellular immunotherapy, immune checkpoint inhibitor, cytotoxic T-lymphocyte-associated protein 4, programmed death-ligand 1, programmed death receptor 1, and non-small cell lung carcinoma. Systematic reviews, meta-analyses, references, and conference proceedings were manually searched. Study Selection: English-language randomized clinical trials with available data that measured overall survival (OS), progression-free survival (PFS), or objective response rate comparing immune checkpoint inhibitors, tumor vaccines, or cellular immunotherapy with conventional therapy for patients with advanced or metastatic NSCLC were included. Thirty-one immunotherapy randomized clinical trials were included, and multicohort data included next-generation sequencing data from patients with advanced NCSLC. Data Extraction and Synthesis: Hazard ratios and 95% CIs were pooled to estimate the survival increases in OS and PFS. Dichotomous data, such as object response rate data, were analyzed using the risk ratio. Mantel-Haenszel random-effects model was used. I2 was used to assess the heterogeneity between trials; an I2 value exceeding 50% indicated the existence of substantial heterogeneity. Analyses took place from February 1, 2018, to August 31, 2018. Main Outcomes and Measures: Primary outcomes were OS and PFS. Results: In total, 14 395 patients (9500 [66.0%] men) were included in the meta-analysis, and 1833 patients (mean [SD], 65.2 [9.9] years; 1063 [58.0%] men) were included in the individual patient-level study. Compared with conventional therapy, immunotherapy was associated with significantly longer OS (hazard ratio, 0.76; 95% CI, 0.71-0.82; P < .001) and PFS (hazard ratio, 0.76; 95% CI, 0.70-0.83; P < .001). The best checkpoint blockade strategy was first-line pembrolizumab with platinum-based chemotherapy. The combined predictive utility of programmed cell death ligand 1 (PD-L1) expression and tumor mutation burden (TMB) was associated with predictive prognosis (whole-exome sequencing: 1-year PFS area under the receiver operating characteristic curve [AUC], 0.829; 3-year PFS AUC, 0.839; targeted next-generation sequencing: 1-year PFS AUC, 0.826; 3-year PFS AUC, 0.948). Moreover, the addition of CD8+ T-cell tumor-infiltrating lymphocytes was associated with improved prognosis predictions for OS (3-year OS AUC, 0.659; 5-year OS AUC, 0.665). RYR1 or MGAM mutations were significantly associated with concomitantly increased durable clinical benefits (RYR1: durable clinical benefit [DCB], 12 of 51 patients [24%]; no durable benefit [NDB], 2 of 55 patients [4%]; P < .001; MGAM: DCB, 12 of 51 patients [24%]; NDB, 0 patients; P < .001), a higher TMB (RYRI: high TMB, 12 of 53 patients [23%]; low TMB, 2 of 53 patients [38%]; P < .001; MGAM: high TMB, 9 of 53 patients [17%]; low TMB, 0 patients; P < .001), and higher PD-L1 expression (RYRI: high PD-L1 expression, 8 of 30 patients [27%]; low PD-L1 expression, 6 of 85 [7.1%]; P < .001; MGAM: high PD-L1 expression, 6 of 30 patients [20%]; low PD-L1 expression, 5 of 85 patients [6%]; P < .001). Conclusions and Relevance: Immunotherapies showed promising clinical outcomes for patients with NSCLC. Pembrolizumab with platinum-based chemotherapy was found to be the most appropriate first-line immune checkpoint inhibitor regimen for advanced NSCLC, and the combined use of PD-L1 expression and TMB was found to be a promising biomarker to evaluate patients' survival and response to precision immunotherapy. The further combination of CD8+ T-cell tumor-infiltrating lymphocytes, PD-L1 expression, and TMB was associated with reliable prognosis. The predictive value of that combination needs to be prospectively validated in large-scale studies.

Genome-Wide Screening and Characterization of the Dof Gene Family in Physic Nut (Jatropha curcas L.).

Physic nut (Jatropha curcas L.) is a species of flowering plant with great potential for biofuel production and as an emerging model organism for functional genomic analysis, particularly in the Euphorbiaceae family. DNA binding with one finger (Dof) transcription factors play critical roles in numerous biological processes in plants. Nevertheless, the knowledge about members, and the evolutionary and functional characteristics of the Dof gene family in physic nut is insufficient. Therefore, we performed a genome-wide screening and characterization of the Dof gene family within the physic nut draft genome. In total, 24 JcDof genes (encoding 33 JcDof proteins) were identified. All the JcDof genes were divided into three major groups based on phylogenetic inference, which was further validated by the subsequent gene structure and motif analysis. Genome comparison revealed that segmental duplication may have played crucial roles in the expansion of the JcDof gene family, and gene expansion was mainly subjected to positive selection. The expression profile demonstrated the broad involvement of JcDof genes in response to various abiotic stresses, hormonal treatments and functional divergence. This study provides valuable information for better understanding the evolution of JcDof genes, and lays a foundation for future functional exploration of JcDof genes.