Interstitial pneumonitis associated with combined regimen of immunotherapy and conventional therapies-pharmacovigilance database analysis with real-world data validation.

BACKGROUND: Immune checkpoint inhibitor (ICI) therapy combined with conventional therapies is being broadly applied in non-small cell lung cancer (NSCLC) patients. However, the risk of interstitial pneumonitis (IP) following a combined regimen is incompletely characterized. METHODS: A total of 46,127 NSCLC patients were extracted for disproportionality analyses of IP from the Food and Drug Administration's Adverse Event Reporting System (FAERS) database. A total of 1108 NSCLC patients who received ICI treatment at Nanfang Hospital of Southern Medical University were collected and utilized for real-world validation. RESULTS: Of the 46,127 patients with NSCLC, 3830 cases (8.3%; 95% confidence interval [CI], 8.05-8.56) developed IP. Multivariable logistic regression analyses revealed that the adjusted ROR of ICI combined with radiation (RT) was the highest (121.69; 95% CI, 83.60-184.96; P < 0.0001) among all therapies, while that of ICI combined with chemotherapy (CHEMO) or targeted therapy (TARGET) was 0.90 (95% CI, 0.78-1.04; P = 0.160) and 1.49 (95% CI, 0.95-2.23; P = 0.065), respectively, using ICI monotherapy as reference. Furthermore, analyses from our validation cohort of 1108 cases showed that the adjusted odds ratio of ICI combined with RT was the highest (12.25; 95% CI, 3.34-50.22; P < 0.01) among all the therapies, while that of ICI combined with CHEMO or TARGET was 2.32 (95% CI, 0.89-7.92; P = 0.12) and 0.66 (95% CI, 0.03-4.55; P = 0.71), respectively, using ICI monotherapy as reference. CONCLUSIONS: Compared with ICI monotherapy, ICI combined with RT, rather than with CHEMO or TARGET, is associated with a higher risk of IP in NSCLC patients. Hence, patients receiving these treatments should be carefully monitored for IP.

Organ-specific metastatic landscape dissects PD-(L)1 blockade efficacy in advanced non-small cell lung cancer: applicability from clinical trials to real-world practice.

BACKGROUND: Organ-specific metastatic context has not been incorporated into the clinical practice of guiding programmed death-(ligand) 1 [PD-(L)1] blockade, due to a lack of understanding of its predictive versus prognostic value. We aim at delineating and then incorporating both the predictive and prognostic effects of the metastatic-organ landscape to dissect PD-(L)1 blockade efficacy in non-small cell lung cancer (NSCLC). METHODS: A total of 2062 NSCLC patients from a double-arm randomized trial (OAK), two immunotherapy trials (FIR, BIRCH), and a real-world cohort (NFyy) were included. The metastatic organs were stratified into two categories based on their treatment-dependent predictive significance versus treatment-independent prognosis. A metastasis-based scoring system (METscore) was developed and validated for guiding PD-(L)1 blockade in clinical trials and real-world practice. RESULTS: Patients harboring various organ-specific metastases presented significantly different responses to immunotherapy, and those with brain and adrenal gland metastases survived longer than others [overall survival (OS), p = 0.0105; progression-free survival (PFS), p = 0.0167]. In contrast, survival outcomes were similar in chemotherapy-treated patients regardless of metastatic sites (OS, p = 0.3742; PFS, p = 0.8242). Intriguingly, the immunotherapeutic predictive significance of the metastatic-organ landscape was specifically presented in PD-L1-positive populations (PD-L1 > 1%). Among them, a paradoxical coexistence of a favorable predictive effect coupled with an unfavorable prognostic effect was observed in metastases to adrenal glands, brain, and liver (category I organs), whereas metastases to bone, pleura, pleural effusion, and mediastinum yielded consistent unfavorable predictive and prognostic effects (category II organs). METscore was capable of integrating both predictive and prognostic effects of the entire landscape and dissected OS outcome of NSCLC patients received PD-(L)1 blockade (p < 0.0001) but not chemotherapy (p = 0.0805) in the OAK training cohort. Meanwhile, general performance of METscore was first validated in FIR (p = 0.0350) and BIRCH (p < 0.0001), and then in the real-world NFyy cohort (p = 0.0181). Notably, METscore was also applicable to patients received PD-(L)1 blockade as first-line treatment both in the clinical trials (OS, p = 0.0087; PFS, p = 0.0290) and in the real-world practice (OS, p = 0.0182; PFS, p = 0.0045). CONCLUSIONS: Organ-specific metastatic landscape served as a potential predictor of immunotherapy, and METscore might enable noninvasive forecast of PD-(L)1 blockade efficacy using baseline radiologic assessments in advanced NSCLC.

Recent (2000-2015) developments in the analysis of minor unknown natural products based on characteristic fragment information using LC-MS.

Liquid chromatography-Mass Spectrometry (LC-MS) has been widely used in natural product analysis. Global detection and identification of nontargeted components are desirable in natural product research, for example, in quality control of Chinese herbal medicine. Nontargeted components analysis continues to expand to exciting life science application domains such as metabonomics. With this background, the present review summarizes recent developments in the analysis of minor unknown natural products using LC-MS and mainly focuses on the determination of the molecular formulae, selection of precursor ions, and characteristic fragmentation patterns of the known compounds. This review consists of three parts. Firstly, the methods used to determine unique molecular formula of unknown compounds such as accurate mass measurements, MSn spectra, or relative isotopic abundance information, are introduced. Secondly, the methods improving signal-to-noise ratio of MS/MS spectra by manual-MS/MS or workflow targeting-only signals were elucidated; pure precursor ions can be selected by changing the precursor ion isolated window. Lastly, characteristic fragmentation patterns such as Retro-Diels-Alder (RDA), McLafferty rearrangements, "internal residue loss," and so on, occurring in the molecular ions of natural products are summarized. Classical application of characteristic fragmentation patterns in identifying unknown compounds in extracts and relevant fragmentation mechanisms are presented (RDA reactions occurring readily in the molecular ions of flavanones or isoflavanones, McLafferty-type fragmentation reactions of some natural products such as epipolythiodioxopiperazines; fragmentation by "internal residue loss" possibly involving ion-neutral complex intermediates). © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:202-216, 2018.

PARP Inhibition Induces Synthetic Lethality and Adaptive Immunity in LKB1-Mutant Lung Cancer.

Contradictory characteristics of elevated mutational burden and a "cold" tumor microenvironment (TME) coexist in liver kinase B1 (LKB1)-mutant non-small cell lung cancers (NSCLC). The molecular basis underlying this paradox and strategies tailored to these historically difficult to treat cancers are lacking. Here, by mapping the single-cell transcriptomic landscape of genetically engineered mouse models with Kras versus Kras/Lkb1-driven lung tumors, we detected impaired tumor-intrinsic IFNγ signaling in Kras/Lkb1-driven tumors that explains the inert immune context. Mechanistic analysis showed that mutant LKB1 led to deficiency in the DNA damage repair process and abnormally activated PARP1. Hyperactivated PARP1 attenuated the IFNγ pathway by physically interacting with and enhancing the poly(ADP-ribosyl)ation of STAT1, compromising its phosphorylation and activation. Abrogation of the PARP1-driven program triggered synthetic lethality in NSCLC on the basis of the LKB1 mutation-mediated DNA repair defect, while also restoring phosphorylated STAT1 to favor an immunologically "hot" TME. Accordingly, PARP1 inhibition restored the disrupted IFNγ signaling and thus mounted an adaptive immune response to synergize with PD-1 blockade in multiple LKB1-deficient murine tumor models. Overall, this study reveals an unexplored interplay between the DNA repair process and adaptive immune response, providing a molecular basis for dual PARP1 and PD-1 inhibition in treating LKB1-mutant NSCLC. SIGNIFICANCE: Targeting PARP exerts dual effects to overcome LKB1 loss-driven immunotherapy resistance through triggering DNA damage and adaptive immunity, providing a rationale for dual PARP and PD-1 inhibition in treating LKB1-mutant lung cancers.

CDK4/6 inhibition triggers ICAM1-driven immune response and sensitizes LKB1 mutant lung cancer to immunotherapy.

Liver kinase B1 (LKB1) mutation is prevalent and a driver of resistance to immune checkpoint blockade (ICB) therapy for lung adenocarcinoma. Here leveraging single cell RNA sequencing data, we demonstrate that trafficking and adhesion process of activated T cells are defected in genetically engineered Kras-driven mouse model with Lkb1 conditional knockout. LKB1 mutant cancer cells result in marked suppression of intercellular adhesion molecule-1 (ICAM1). Ectopic expression of Icam1 in Lkb1-deficient tumor increases homing and activation of adoptively transferred SIINFEKL-specific CD8+ T cells, reactivates tumor-effector cell interactions and re-sensitises tumors to ICB. Further discovery proves that CDK4/6 inhibitors upregulate ICAM1 transcription by inhibiting phosphorylation of retinoblastoma protein RB in LKB1 deficient cancer cells. Finally, a tailored combination strategy using CDK4/6 inhibitors and anti-PD-1 antibodies promotes ICAM1-triggered immune response in multiple Lkb1-deficient murine models. Our findings renovate that ICAM1 on tumor cells orchestrates anti-tumor immune response, especially for adaptive immunity.

De Novo Mutation in Non-Tyrosine Kinase Domain of ROS1 as a Potential Predictor of Immune Checkpoint Inhibitors in Melanoma.

PURPOSE: Despite the success of targeted therapy in c-ros oncogene 1 (ROS1)-rearranged cancers, especially non-small cell lung cancer (NSCLC), the clinical significance of ROS1 de novo mutation has not yet been understood. We sought to elucidate the predictive effect of ROS1 mutation for immune checkpoint inhibitor (ICI) therapy in melanoma. METHODS: The Cancer Genome Atlas [TCGA (n = 10967)] and Memorial Sloan Kettering Cancer Center [MSK (n = 10,945)] datasets, as well as two clinical cohorts of melanoma received ICI [CA209-038 (n = 73) and MEL-IPI (n = 110)], were included to explore the prevalence, prognostic effect, and immunotherapeutic predictive effect of ROS1 mutation in melanoma. Overall survival (OS) was defined as the primary outcome. RESULTS: Overall, melanoma accounted for the highest proportion of ROS1 mutation (~20%) which made up the majority (~95%) of the ROS1-alterated cases. Remarkably, ROS1 mutation yielded longer OS from ICI than the wild-type counterpart in the MSK melanoma population [hazard ratio (HR) 0.47, 95% confidence interval (CI) 0.30-0.74], and two external melanoma cohorts (CA209-038: HR 0.42, 95% CI 0.20-0.89; MEL-IPI: HR 0.55, 95% CI 0.34-0.91), without affecting the prognosis of patients. Elevated tumor mutational burden and enrichment of DNA damage repair was observed in ROS1 mutated patients, providing an explanation for the favorable responses to ICI therapy. Precisely, ROS1 mutation in non-protein tyrosine kinase (PTK) domain but not PTK mutation was responsible for the immunotherapy-specific responses of the ROS1 mutated patients in melanoma. CONCLUSIONS: Collectively, ROS1 mutation, specifically the non-PTK mutation, is a potential predictor of ICI therapy in melanoma, which is distinct from the well-established role of ROS1 rearrangement for targeted therapy in NSCLC.

Integrative evaluation of primary and metastatic lesion spectrum to guide anti-PD-L1 therapy of non-small cell lung cancer: results from two randomized studies.

Objectives: Clinical benefits of immune-checkpoint blockade (ICB) versus standard chemotherapy have been established in unselected non-small cell lung cancer (NSCLC). However, the response to ICB therapy among patients is heterogeneous in clinical practice. Materials and Methods: We retrospectively assessed the predicitive effect of the primary and metastatic lesion spectrum (baseline sum of the longest diameters [SLD], number of metastatic sites and specific organ metastases) on the efficacy of atezolizumab over docetaxel in OAK and POPLAR trial cohorts. A decision model, termed DSO (Diameter-Site-Organ), based on the spectrum was developed and validated for guiding ICB. Results: Higher SLD (>38 mm) and more metastatic sites (≥2) were characterized with pronounced overall survival (OS) benefits from atezolizumab versus docetaxel. Specifically, adrenal gland and brain metastases were identified as favorable predictors of atezolizumab treatment. The DSO model was developed in the discovery cohort to integrate the directive effect of the primary and metastatic lesion spectrum. Remarkably, a general pattern of enhanced efficacy of atezolizumab versus docetaxel was observed along with the increase of the DSO score. For patients with DSO score > 0, atezolizumab yielded a significantly prolonged OS than docetaxel, whereas OS was generally similar between two treatments in patients with DSO score ≤ 0. Equivalent findings were also seen in the internal and external validation cohorts. Conclusions: The response to anti-PD-L1 therapy among patients varied with the primary and metastatic lesion spectrum. The DSO-based system might provide promising medication guidance for ICB treatment in NSCLC patients.

Reciprocal regulation of HIF-1α and Uroplakin 1A promotes glycolysis and proliferation in Hepatocellular Carcinoma.

Uroplakin 1A (UPK1A) has recently been found dysregulation in many cancers. However, the functions of UPK1A and its underlying mechanisms in hepatocellular carcinoma (HCC) remain poorly understand. In the present study, we found that UPK1A was highly expressed in HCC tumor tissues compared with adjacent non-tumor tissues. Datasets from the Cancer Genome Atlas project (TCGA) and Gene expression Omnibus confirmed that UPK1A was highly expressed in HCC. High expression of UPK1A predicted poor overall survival (OS) in patients with HCC. Univariate and multivariate analysis showed that UPK1A was a significant and independent prognostic predictor for OS of patients with HCC. Functionally, silencing UPK1A suppressed HCC cell glycolysis and proliferation. Mechanistically, hypoxia-inducible factor 1α (HIF-1α) directly bound to the hypoxia response elements (HRE) of UPK1A promoter region, which led to the up-regulation of UPK1A under hypoxia. Furthermore, downregulation of UPK1A reduced key enzyme of glycolysis via regulating HIF-1α. Taken together, these data indicates the existence of a positive feedback loop between HIF-1α and UPK1A that modulates glycolysis and proliferation under hypoxia in HCC cells.

Long noncoding RNA UPK1A-AS1 indicates poor prognosis of hepatocellular carcinoma and promotes cell proliferation through interaction with EZH2.

BACKGROUND: Dysregulation of long non-coding RNAs (lncRNAs) is responsible for cancer initiation and development, positioning lncRNAs as not only biomarkers but also promising therapeutic targets for cancer treatment. A growing number of lncRNAs have been reported in hepatocellular carcinoma (HCC), but their functional and mechanistic roles remain unclear. METHODS: Gene Set Enrichment Analysis was used to investigate the molecular mechanism of UPK1A antisense RNA 1 (UPK1A-AS1). Cell Counting Kit-8 assays, EdU assays, flow cytometry, western blotting, and xenograft assays were used to confirm the role of UPK1A-AS1 in the proliferation of HCC cells in vitro and in vivo. Bioinformatics analyses and quantitative polymerase chain reaction (qRT-PCR) were performed to explore the interplay between UPK1A-AS1 and enhancer of zeste homologue 2 (EZH2). RNA immunoprecipitation (RIP), RNA pull-down assays, western blotting, and qRT-PCR were conducted to confirm the interaction between UPK1A-AS1 and EZH2. The interaction between UPK1A-AS1 and miR-138-5p was examined by luciferase reporter and RIP assays. Finally, the expression level and prognosis value of UPK1A-AS1 in HCC were analyzed using RNA sequencing data from The Cancer Genome Atlas datasets. RESULTS: We showed that UPK1A-AS1, a newly identified lncRNA, promoted cellular proliferation and tumor growth by accelerating cell cycle progression. Cell cycle-related genes, including CCND1, CDK2, CDK4, CCNB1, and CCNB2, were significantly upregulated in HCC cells overexpressing UPK1A-AS1. Furthermore, overexpression of UPK1A-AS1 could protect HCC cells from cis-platinum toxicity. Mechanistically, UPK1A-AS1 interacted with EZH2 to mediate its nuclear translocation and reinforce its binding to SUZ12, leading to increased H27K3 trimethylation. Targeting EZH2 with specific small interfering RNA impaired the UPK1A-AS1-mediated upregulation of proliferation and cell cycle progression-related genes. Moreover, miR-138-5p was identified as a direct target of UPK1A-AS1. Additionally, UPK1A-AS1 was significantly upregulated in HCC, and the upregulation of UPK1A-AS1 predicted poor prognosis for patients with HCC. CONCLUSIONS: Our study revealed that UPK1A-AS1 promotes HCC development by accelerating cell cycle progression through interaction with EZH2 and sponging of miR-138-5p, suggesting that UPK1A-AS1 possesses substantial potential as a novel biomarker for HCC prognosis and therapy.

Combination of TMB and CNA Stratifies Prognostic and Predictive Responses to Immunotherapy Across Metastatic Cancer.

PURPOSE: Although tumor mutation burden (TMB) has been well known to predict the response to immune checkpoint inhibitors (ICI), lack of randomized clinical trial data has restricted its clinical application. This study aimed to explore the significance and feasibility of biomarker combination based on TMB and copy-number alteration (CNA) for the prognosis of each tumor and prediction for ICI therapy in metastatic pan-cancer milieu. EXPERIMENTAL DESIGN: Non-ICI-treated MSK pan-cancer cohort was used for prognosis analysis. Three independent immunotherapy cohorts, including non-small cell lung cancer (n = 240), skin cutaneous melanoma (n = 174), and mixed cancer (Dana-Farber, n = 98) patients from previous studies, were analyzed for efficacy of ICI therapy. RESULTS: TMB and CNA showed optimized combination for the prognosis of most metastatic cancer types, and patients with TMBlowCNAlow showed better survival. In the predictive analysis, both TMB and CNA were independent predictive factors for ICI therapy. Remarkably, when TMB and CNA were jointly analyzed, those with TMBhighCNAlow showed favorable responses to ICI therapy. Meanwhile, TMBhighCNAlow as a new biomarker showed better prediction for ICI efficacy compared with either TMB-high or CNA-low alone. Furthermore, analysis of the non-ICI-treated MSK pan-cancer cohort supported that the joint stratification of TMB and CNA can be used to categorize tumors into distinct sensitivity to ICI therapy across pan-tumors. CONCLUSIONS: The combination of TMB and CNA can jointly stratify multiple metastatic tumors into groups with different prognosis and heterogeneous clinical responses to ICI treatment. Patients with TMBhighCNAlow cancer can be an optimal subgroup for ICI therapy.