The Unfolded Protein Response Mediator PERK Governs Myeloid Cell-Driven Immunosuppression in Tumors through Inhibition of STING Signaling.

The primary mechanisms supporting immunoregulatory polarization of myeloid cells upon infiltration into tumors remain largely unexplored. Elucidation of these signals could enable better strategies to restore protective anti-tumor immunity. Here, we investigated the role of the intrinsic activation of the PKR-like endoplasmic reticulum (ER) kinase (PERK) in the immunoinhibitory actions of tumor-associated myeloid-derived suppressor cells (tumor-MDSCs). PERK signaling increased in tumor-MDSCs, and its deletion transformed MDSCs into myeloid cells that activated CD8+ T cell-mediated immunity against cancer. Tumor-MDSCs lacking PERK exhibited disrupted NRF2-driven antioxidant capacity and impaired mitochondrial respiratory homeostasis. Moreover, reduced NRF2 signaling in PERK-deficient MDSCs elicited cytosolic mitochondrial DNA elevation and, consequently, STING-dependent expression of anti-tumor type I interferon. Reactivation of NRF2 signaling, conditional deletion of STING, or blockade of type I interferon receptor I restored the immunoinhibitory potential of PERK-ablated MDSCs. Our findings demonstrate the pivotal role of PERK in tumor-MDSC functionality and unveil strategies to reprogram immunosuppressive myelopoiesis in tumors to boost cancer immunotherapy.

Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer.

We analyzed large-scale post-translational modification (PTM) data to outline cell signaling pathways affected by tyrosine kinase inhibitors (TKIs) in ten lung cancer cell lines. Tyrosine phosphorylated, lysine ubiquitinated, and lysine acetylated proteins were concomitantly identified using sequential enrichment of post translational modification (SEPTM) proteomics. Machine learning was used to identify PTM clusters that represent functional modules that respond to TKIs. To model lung cancer signaling at the protein level, PTM clusters were used to create a co-cluster correlation network (CCCN) and select protein-protein interactions (PPIs) from a large network of curated PPIs to create a cluster-filtered network (CFN). Next, we constructed a Pathway Crosstalk Network (PCN) by connecting pathways from NCATS BioPlanet whose member proteins have PTMs that co-cluster. Interrogating the CCCN, CFN, and PCN individually and in combination yields insights into the response of lung cancer cells to TKIs. We highlight examples where cell signaling pathways involving EGFR and ALK exhibit crosstalk with BioPlanet pathways: Transmembrane transport of small molecules; and Glycolysis and gluconeogenesis. These data identify known and previously unappreciated connections between receptor tyrosine kinase (RTK) signal transduction and oncogenic metabolic reprogramming in lung cancer. Comparison to a CFN generated from a previous multi-PTM analysis of lung cancer cell lines reveals a common core of PPIs involving heat shock/chaperone proteins, metabolic enzymes, cytoskeletal components, and RNA-binding proteins. Elucidation of points of crosstalk among signaling pathways employing different PTMs reveals new potential drug targets and candidates for synergistic attack through combination drug therapy.

SHP2 inhibition displays efficacy as a monotherapy and in combination with JAK2 inhibition in preclinical models of myeloproliferative neoplasms.

Myeloproliferative neoplasms (MPNs), including polycythemia vera, essential thrombocytosis, and primary myelofibrosis, are clonal hematopoietic neoplasms driven by mutationally activated signaling by the JAK2 tyrosine kinase. Although JAK2 inhibitors can improve MPN patients' quality of life, they do not induce complete remission as disease-driving cells persistently survive therapy. ERK activation has been highlighted as contributing to JAK2 inhibitor persistent cell survival. As ERK is a component of signaling by activated RAS proteins and by JAK2 activation, we sought to inhibit RAS activation to enhance responses to JAK2 inhibition in preclinical MPN models. We found the SHP2 inhibitor RMC-4550 significantly enhanced growth inhibition of MPN cell lines in combination with the JAK2 inhibitor ruxolitinib, effectively preventing ruxolitinib persistent growth, and the growth and viability of established ruxolitinib persistent cells remained sensitive to SHP2 inhibition. Both SHP2 and JAK2 inhibition diminished cellular RAS-GTP levels, and their concomitant inhibition enhanced ERK inactivation and increased apoptosis. Inhibition of SHP2 inhibited the neoplastic growth of MPN patient hematopoietic progenitor cells and exhibited synergy with ruxolitinib. RMC-4550 antagonized MPN phenotypes and increased survival of an MPN mouse model driven by MPL-W515L. The combination of RMC-4550 and ruxolitinib, which was safe and tolerated in healthy mice, further inhibited disease compared to ruxolitinib monotherapy, including extending survival. Given SHP2 inhibitors are undergoing clinical evaluation in patients with solid tumors, our preclinical findings suggest that SHP2 is a candidate therapeutic target with potential for rapid translation to clinical assessment to improve current targeted therapies for MPN patients.

Deciphering Phenotypes from Protein Biomarkers for Translational Research with PIPER.

Liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) has widespread clinical use for detection of inborn errors of metabolism, therapeutic drug monitoring, and numerous other applications. This technique detects proteolytic peptides as surrogates for protein biomarker expression, mutation, and post-translational modification in individual clinical assays and in cancer research with highly multiplexed quantitation across biological pathways. LC-MRM for protein biomarkers must be translated from multiplexed research-grade panels to clinical use. LC-MRM panels provide the capability to quantify clinical biomarkers and emerging protein markers to establish the context of tumor phenotypes that provide highly relevant supporting information. An application to visualize and communicate targeted proteomics data will empower translational researchers to move protein biomarker panels from discovery to clinical use. Therefore, we have developed a web-based tool for targeted proteomics that provides pathway-level evaluations of key biological drivers (e.g., EGFR signaling), signature scores (representing phenotypes) (e.g., EMT), and the ability to quantify specific drug targets across a sample cohort. This tool represents a framework for integrating summary information, decision algorithms, and risk scores to support Physician-Interpretable Phenotypic Evaluation in R (PIPER) that can be reused or repurposed by other labs to communicate and interpret their own biomarker panels.

Differential Chemoproteomics Reveals MARK2/3 as Cell Migration-Relevant Targets of the ALK Inhibitor Brigatinib.

Metastasis poses a major challenge in cancer management, including EML4-ALK-rearranged non-small cell lung cancer (NSCLC). As cell migration is a critical step during metastasis, we assessed the anti-migratory activities of several clinical ALK inhibitors in NSCLC cells and observed differential anti-migratory capabilities despite similar ALK inhibition, with brigatinib displaying superior anti-migratory effects over other ALK inhibitors. Applying an unbiased in situ mass spectrometry-based chemoproteomics approach, we determined the proteome-wide target profile of brigatinib in EML4-ALK+ NSCLC cells. Dose-dependent and cross-competitive chemoproteomics suggested MARK2 and MARK3 as relevant brigatinib kinase targets. Functional validation showed that combined pharmacological inhibition or genetic modulation of MARK2/3 inhibited cell migration. Consistently, brigatinib treatment induced inhibitory YAP1 phosphorylation downstream of MARK2/3. Collectively, our data suggest that brigatinib exhibits unusual cross-phenotype polypharmacology as, despite similar efficacy for inhibiting EML4-ALK-dependent cell proliferation as other ALK inhibitors, it more effectively prevented migration of NSCLC cells due to co-targeting of MARK2/3.

Phase I Study of JNJ-74699157 in Patients with Advanced Solid Tumors Harboring the KRAS G12C Mutation.

BACKGROUND: Patients with KRAS-mutant cancers have limited treatment options. Here we present a phase I study of JNJ-74699157, an oral, selective, covalent inhibitor of the KRAS G12C isoform, in patients with advanced cancer harboring the KRAS G12C mutation. METHODS: Eligible patients (aged ≥18 years) who had previously received or were ineligible for standard treatment received JNJ-74699157 once daily on a 21-day cycle. Dose escalation was guided by a modified continual reassessment method. RESULTS: Ten patients (100 mg: 9 and 200 mg: 1) were enrolled. Tumor types included non-small cell lung cancer (n = 5), colorectal cancer (n = 4), and carcinoma of unknown primary site (n = 1). The median age was 65 (range: 36-74) years and median treatment duration was 2.91 (range: 0.5-7.5) months. Dose-limiting toxicities of grades 3-4 increased blood creatinine phosphokinase (CPK) were observed in 100 mg and 200 mg dose levels. The most common adverse event was increased blood CPK (6 patients). No significant clinical benefit was observed; the best response was stable disease in 4 patients (40%). CONCLUSION: Based on dose-limiting skeletal muscle toxicities and the lack of efficacy at the 100 mg dose, further enrollment was stopped. The safety profile of JNJ-74699157 was not considered favorable for further clinical development. CLINICALTRIALS.GOV IDENTIFIER: NCT04006301.

GMSimpute: a generalized two-step Lasso approach to impute missing values in label-free mass spectrum analysis.

MOTIVATION: Missingness in label-free mass spectrometry is inherent to the technology. A computational approach to recover missing values in metabolomics and proteomics datasets is important. Most existing methods are designed under a particular assumption, either missing at random or under the detection limit. If the missing pattern deviates from the assumption, it may lead to biased results. Hence, we investigate the missing patterns in free mass spectrometry data and develop an omnibus approach GMSimpute, to allow effective imputation accommodating different missing patterns. RESULTS: Three proteomics datasets and one metabolomics dataset indicate missing values could be a mixture of abundance-dependent and abundance-independent missingness. We assess the performance of GMSimpute using simulated data (with a wide range of 80 missing patterns) and metabolomics data from the Cancer Genome Atlas breast cancer and clear cell renal cell carcinoma studies. Using Pearson correlation and normalized root mean square errors between the true and imputed abundance, we compare its performance to K-nearest neighbors' type approaches, Random Forest, GSimp, a model-based method implemented in DanteR and minimum values. The results indicate GMSimpute provides higher accuracy in imputation and exhibits stable performance across different missing patterns. In addition, GMSimpute is able to identify the features in downstream differential expression analysis with high accuracy when applied to the Cancer Genome Atlas datasets. AVAILABILITY AND IMPLEMENTATION: GMSimpute is on CRAN: https://cran.r-project.org/web/packages/GMSimpute/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cell signaling heterogeneity is modulated by both cell-intrinsic and -extrinsic mechanisms: An integrated approach to understanding targeted therapy.

During the last decade, our understanding of cancer cell signaling networks has significantly improved, leading to the development of various targeted therapies that have elicited profound but, unfortunately, short-lived responses. This is, in part, due to the fact that these targeted therapies ignore context and average out heterogeneity. Here, we present a mathematical framework that addresses the impact of signaling heterogeneity on targeted therapy outcomes. We employ a simplified oncogenic rat sarcoma (RAS)-driven mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase-protein kinase B (PI3K-AKT) signaling pathway in lung cancer as an experimental model system and develop a network model of the pathway. We measure how inhibition of the pathway modulates protein phosphorylation as well as cell viability under different microenvironmental conditions. Training the model on this data using Monte Carlo simulation results in a suite of in silico cells whose relative protein activities and cell viability match experimental observation. The calibrated model predicts distributional responses to kinase inhibitors and suggests drug resistance mechanisms that can be exploited in drug combination strategies. The suggested combination strategies are validated using in vitro experimental data. The validated in silico cells are further interrogated through an unsupervised clustering analysis and then integrated into a mathematical model of tumor growth in a homogeneous and resource-limited microenvironment. We assess posttreatment heterogeneity and predict vast differences across treatments with similar efficacy, further emphasizing that heterogeneity should modulate treatment strategies. The signaling model is also integrated into a hybrid cellular automata (HCA) model of tumor growth in a spatially heterogeneous microenvironment. As a proof of concept, we simulate tumor responses to targeted therapies in a spatially segregated tissue structure containing tumor and stroma (derived from patient tissue) and predict complex cell signaling responses that suggest a novel combination treatment strategy.

Synthesis and structural characterization of a monocarboxylic inhibitor for GRB2 SH2 domain.

A monocarboxylic inhibitor was designed and synthesized to disrupt the protein-protein interaction (PPI) between GRB2 and phosphotyrosine-containing proteins. Biochemical characterizations show compound 7 binds with the Src homology 2 (SH2) domain of GRB2 and is more potent than EGFR1068 phosphopeptide 14-mer. X-ray crystallographic studies demonstrate compound 7 occupies the GRB2 binding site for phosphotyrosine-containing sequences and reveal key structural features for GRB2-inhibitor binding. This compound with a -1 formal charge offers a new direction for structural optimization to generate cell-permeable inhibitors for this key protein target of the aberrant Ras-MAPK signaling cascade.

Lowering Sample Requirements to Study Tyrosine Kinase Signaling Using Phosphoproteomics with the TMT Calibrator Approach.

Analysis of tyrosine kinase signaling is critical for the development of targeted cancer therapy. Currently, immunoprecipitation of phosphotyrosine (pY) peptides prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS) is used to profile tyrosine kinase substrates. A typical protocol requests 10 mg of total protein from ≈108 cells or 50-100 mg of tissue. Large sample requirements can be cost prohibitive or not feasible for certain experiments. Sample multiplexing using chemical labeling reduces the protein amount required for each sample, and newer approaches use a material-rich reference channel as a calibrator to trigger detection and quantification for smaller samples. Here, it is demonstrated that the tandem mass tag (TMT) calibrator approach reduces the sample input for pY profiling tenfold (to ≈1 mg total protein per sample from 107 cells grown in one plate), while maintaining the depth of pY proteome sampling and the biological content of the experiment. Data are available through PRIDE (PXD019764 for label-free and PXD018952 for TMT). This strategy opens more opportunities for pY profiling of large sample cohorts and samples with limited protein quantity such as immune cells, xenograft models, and human tumors.

Preventing smoking relapse in patients with cancer: A randomized controlled trial.

BACKGROUND: Abstaining from smoking after a cancer diagnosis is critical to mitigating the risk of multiple adverse health outcomes. Although many patients with cancer attempt to quit smoking, the majority relapse. The current randomized controlled trial evaluated the efficacy of adapting an evidence-based smoking relapse prevention (SRP) intervention for patients with cancer. METHODS: The trial enrolled 412 patients newly diagnosed with cancer who had recently quit smoking. Participants were randomized to usual care (UC) or SRP. Participants in the UC group received the institution's standard of care for treating tobacco use. Participants in the SRP group in addition received a targeted educational DVD plus a validated self-help intervention for preventing smoking relapse. The primary outcome was smoking abstinence at 2 months, 6 months, and 12 months. RESULTS: Abstinence rates for participants in the SRP and UC groups were 75% versus 71% at 2 months and 69% versus 64% at 6 months (Ps > .20). At 12 months, abstinence rates among survivors were 68% for those in the SRP group and 63% for those in the UC group (P = .38). Post hoc analyses revealed that across 2 months and 6 months, patients who were married/partnered were more likely to be abstinent after SRP than UC (P = .03). CONCLUSIONS: A smoking relapse prevention intervention did not reduce relapse rates overall, but did appear to have benefited those participants who had the social support of a partner. Future work is needed to extend this effect to the larger population of patients.

Fully Automated Protein Proximity Assay in Formalin-Fixed, Paraffin-Embedded Tissue Using Caged Haptens.

The ability to interrogate for the presence and distribution of protein-protein complexes (PPCs) is of high importance for the advancement of diagnostic capabilities such as determining therapeutic effects in the context of pharmaceutical development. Herein, we report a novel assay for detecting and visualizing PPCs on formalin-fixed, paraffin-embedded material using a caged hapten. To this end, we synthetically modified a nitropyrazole hapten with an alkaline phosphatase (AP)-responsive self-immolative caging group. The AP-labile caging group abrogates antibody binding; however, upon exposure to AP, the native hapten is regenerated. These caged haptens were applied in a proximity assay format by the use of a first antibody labeled with caged haptens that can be uncaged by AP conjugated to the second antibody. Only when the two epitopes of interest are in close proximity to one another will the AP interact with the caged hapten and uncage it. The native hapten, which represents the population of PPCs, was then visualized by an anti-hapten antibody conjugated to horseradish peroxidase, followed by diaminobenzidine detection. We provide proof of concept for the detection of protein proximity pairs (ß-catenin-E-cadherin and EGFR-GRB2), and confirm assay specificity through technical controls involving reagent omission experiments, and biologically by treatment with small-molecule kinase inhibitors that interrupt kinase-adaptor complexes.

Functional Proteomics and Deep Network Interrogation Reveal a Complex Mechanism of Action of Midostaurin in Lung Cancer Cells.

Lung cancer is associated with high prevalence and mortality, and despite significant successes with targeted drugs in genomically defined subsets of lung cancer and immunotherapy, the majority of patients currently does not benefit from these therapies. Through a targeted drug screen, we found the recently approved multi-kinase inhibitor midostaurin to have potent activity in several lung cancer cells independent of its intended target, PKC, or a specific genomic marker. To determine the underlying mechanism of action we applied a layered functional proteomics approach and a new data integration method. Using chemical proteomics, we identified multiple midostaurin kinase targets in these cells. Network-based integration of these targets with quantitative tyrosine and global phosphoproteomics data using protein-protein interactions from the STRING database suggested multiple targets are relevant for the mode of action of midostaurin. Subsequent functional validation using RNA interference and selective small molecule probes showed that simultaneous inhibition of TBK1, PDPK1 and AURKA was required to elicit midostaurin's cellular effects. Immunoblot analysis of downstream signaling nodes showed that combined inhibition of these targets altered PI3K/AKT and cell cycle signaling pathways that in part converged on PLK1. Furthermore, rational combination of midostaurin with the potent PLK1 inhibitor BI2536 elicited strong synergy. Our results demonstrate that combination of complementary functional proteomics approaches and subsequent network-based data integration can reveal novel insight into the complex mode of action of multi-kinase inhibitors, actionable targets for drug discovery and cancer vulnerabilities. Finally, we illustrate how this knowledge can be used for the rational design of synergistic drug combinations with high potential for clinical translation.

Phase 1 trial of dasatinib combined with afatinib for epidermal growth factor receptor- (EGFR-) mutated lung cancer with acquired tyrosine kinase inhibitor (TKI) resistance.

BACKGROUND: Bypass activation of Src family kinases can confer resistance to EGFR tyrosine kinase inhibitors (TKIs) based on preclinical models. We prospectively assessed the safety and clinical activity of dasatinib and afatinib in combination for patients with resistant EGFR-mutant lung cancer. METHODS: An open-label, dose-escalation phase 1/2 trial (NCT01999985) with 2-stage expansion was conducted with 25 lung cancer patients. Dose expansion required activating EGFR mutations and progression following prior EGFR TKI. RESULTS: Patients were 72% Caucasian and received median of 2 prior lines of therapy. Maximum-tolerated dose was 30 mg afatinib with 100 mg dasatinib. New or increased pleural effusions were observed in 56% of patients. No radiologic responses were observed, although several EGFR-mutant TKI-resistant patients (26%) had prolonged stable disease over 6 months. The combination reduced the EGFR mutation and T790M variant allele frequency in cell-free DNA (p < .05). Nonetheless, the threshold for futility was met, based on 6-month progression-free survival. For EGFR TKI-resistant patients, median progression-free survival was 3.7 months (95% confidence interval (CI), 2.3-5.0) and overall survival was 14.7 months (95% CI, 8.5-20.9). CONCLUSIONS: The combination had a manageable toxicity profile and in vivo T790M modulation, but no objective clinical responses were observed.

Randomized-controlled phase II trial of salvage chemotherapy after immunization with a TP53-transfected dendritic cell-based vaccine (Ad.p53-DC) in patients with recurrent small cell lung cancer.

Small cell lung cancer TP53 mutations lead to expression of tumor antigens that elicits specific cytotoxic T-cell immune responses. In this phase II study, dendritic cells transfected with wild-type TP53 (vaccine) were administered to patients with extensive-stage small cell lung cancer after chemotherapy. Patients were randomized 1:1:1 to arm A (observation), arm B (vaccine alone), or arm C (vaccine plus all-trans-retinoic acid). Vaccine was administered every 2 weeks (3 times), and all patients were to receive paclitaxel at progression. Our primary endpoint was overall response rate (ORR) to paclitaxel. The study was not designed to detect overall response rate differences between arms. Of 69 patients enrolled (performance status 0/1, median age 62 years), 55 were treated in stage 1 (18 in arm A, 20 in arm B, and 17 in arm C) and 14 in stage 2 (arm C only), per 2-stage Simon Minimax design. The vaccine was safe, with mostly grade 1/2 toxicities, although 1 arm-B patient experienced grade 3 fatigue and 8 arm-C patients experienced grade 3 toxicities. Positive immune responses were obtained in 20% of arm B (95% confidence interval [CI], 5.3-48.6) and 43.3% of arm C (95% CI 23.9-65.1). The ORRs to the second-line chemotherapy (including paclitaxel) were 15.4% (95% CI 2.7-46.3), 16.7% (95% CI 2.9-49.1), and 23.8% (95% CI 9.1-47.5) for arms A, B, and C, with no survival differences between arms. Although our vaccine failed to improve ORRs to the second-line chemotherapy, its safety profile and therapeutic immune potential remain. Combinations with the other immunotherapeutic agents are reasonable options.

Polypharmacology-based ceritinib repurposing using integrated functional proteomics.

Targeted drugs are effective when they directly inhibit strong disease drivers, but only a small fraction of diseases feature defined actionable drivers. Alternatively, network-based approaches can uncover new therapeutic opportunities. Applying an integrated phenotypic screening, chemical and phosphoproteomics strategy, here we describe the anaplastic lymphoma kinase (ALK) inhibitor ceritinib as having activity across several ALK-negative lung cancer cell lines and identify new targets and network-wide signaling effects. Combining pharmacological inhibitors and RNA interference revealed a polypharmacology mechanism involving the noncanonical targets IGF1R, FAK1, RSK1 and RSK2. Mutating the downstream signaling hub YB1 protected cells from ceritinib. Consistent with YB1 signaling being known to cause taxol resistance, combination of ceritinib with paclitaxel displayed strong synergy, particularly in cells expressing high FAK autophosphorylation, which we show to be prevalent in lung cancer. Together, we present a systems chemical biology platform for elucidating multikinase inhibitor polypharmacology mechanisms, subsequent design of synergistic drug combinations, and identification of mechanistic biomarker candidates.

Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer.

Recent developments in instrumentation and bioinformatics have led to new quantitative mass spectrometry platforms including LC-MS/MS with data-independent acquisition (DIA) and targeted analysis using parallel reaction monitoring mass spectrometry (LC-PRM), which provide alternatives to well-established methods, such as LC-MS/MS with data-dependent acquisition (DDA) and targeted analysis using multiple reaction monitoring mass spectrometry (LC-MRM). These tools have been used to identify signaling perturbations in lung cancers and other malignancies, supporting the development of effective kinase inhibitors and, more recently, providing insights into therapeutic resistance mechanisms and drug repurposing opportunities. However, detection of kinases in biological matrices can be challenging; therefore, activity-based protein profiling enrichment of ATP-utilizing proteins was selected as a test case for exploring the limits of detection of low-abundance analytes in complex biological samples. To examine the impact of different MS acquisition platforms, quantification of kinase ATP uptake following kinase inhibitor treatment was analyzed by four different methods: LC-MS/MS with DDA and DIA, LC-MRM, and LC-PRM. For discovery data sets, DIA increased the number of identified kinases by 21% and reduced missingness when compared with DDA. In this context, MRM and PRM were most effective at identifying global kinome responses to inhibitor treatment, highlighting the value of a priori target identification and manual evaluation of quantitative proteomics data sets. We compare results for a selected set of desthiobiotinylated peptides from PRM, MRM, and DIA and identify considerations for selecting a quantification method and postprocessing steps that should be used for each data acquisition strategy.

Genome-wide interaction study of smoking behavior and non-small cell lung cancer risk in Caucasian population.

Non-small cell lung cancer is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between single nucleotide polymorphisms (SNPs) and smoking status (never- versus ever-smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13336 non-small cell lung cancer cases. Candidate SNPs with P-value <0.001 were further analyzed using a standard case-control interaction analysis including 13970 controls. The significant SNPs with P-value <3.5 × 10-5 (correcting for multiple tests) from the case-control analysis in the discovery stage were further validated using an independent replication dataset comprising 5377 controls and 3054 non-small cell lung cancer cases. We further stratified the analysis by histological subtypes. Two novel SNPs, rs6441286 and rs17723637, were identified for overall lung cancer risk. The interaction odds ratio and meta-analysis P-value for these two SNPs were 1.24 with 6.96 × 10-7 and 1.37 with 3.49 × 10-7, respectively. In addition, interaction of smoking with rs4751674 was identified in squamous cell lung carcinoma with an odds ratio of 0.58 and P-value of 8.12 × 10-7. This study is by far the largest genome-wide SNP-smoking interaction analysis reported for lung cancer. The three identified novel SNPs provide potential candidate biomarkers for lung cancer risk screening and intervention. The results from our study reinforce that gene-smoking interactions play important roles in the etiology of lung cancer and account for part of the missing heritability of this disease.

A phase I/randomized phase II study of GM.CD40L vaccine in combination with CCL21 in patients with advanced lung adenocarcinoma.

The GM.CD40L vaccine, which recruits and activates dendritic cells, migrates to lymph nodes, activating T cells and leading to systemic tumor cell killing. When combined with the CCL21 chemokine, which recruits T cells and enhances T-cell responses, additive effects have been demonstrated in non-small cell lung cancer mouse models. Here, we compared GM.CD40L versus GM.CD40L plus CCL21 (GM.CD40L.CCL21) in lung adenocarcinoma patients with ≥ 1 line of treatment. In this phase I/II randomized trial (NCT01433172), patients received intradermal vaccines every 14 days (3 doses) and then monthly (3 doses). A two-stage minimax design was used. During phase I, no dose-limiting toxicities were shown in three patients who received GM.CD40L.CCL21. During phase II, of evaluable patients, 5/33 patients (15.2%) randomized for GM.DCD40L (p = .023) and 3/32 patients (9.4%) randomized for GM.DCD40L.CCL21 (p = .20) showed 6-month progression-free survival. Median overall survival was 9.3 versus 9.5 months with GM.DCD40L versus GM.DCD40L.CCL21 (95% CI 0.70-2.25; p = .44). For GM.CD40L versus GM.CD40L.CCL21, the most common treatment-related adverse events (TRAEs) were grade 1/2 injection site reaction (51.4% versus 61.1%) and grade 1/2 fatigue (35.1% versus 47.2%). Grade 1 immune-mediated TRAEs were isolated to skin. No patients showed evidence of pseudo-progression or immune-related TRAEs of grade 1 or greater of pneumonitis, endocrinopathy, or colitis, and none discontinued treatment due to toxicity. Although we found no significant associations between vaccine immunogenicity and outcomes, in limited biopsies, one patient treated with GMCD40L.CCL21 displayed abundant tumor-infiltrating lymphocytes. This possible effectiveness warrants further investigation of GM.CD40L in combination approaches.

CAR-T cells and combination therapies: What's next in the immunotherapy revolution?

Cancer immunotherapies are dramatically reshaping the clinical management of oncologic patients. For many of these therapies, the guidelines for administration, monitoring, and management of associated toxicities are still being established. This is especially relevant for adoptively transferred, genetically-modified T cells, which have unique pharmacokinetic properties, due to their ability to replicate and persist long-term, following a single administration. Furthermore, in the case of CAR-T cells, the use of synthetic immune receptors may impact signaling pathways involved in T cell function and survival in unexpected ways. We, herein, comment on the most salient aspects of CAR-T cell design and clinical experience in the treatment of solid tumors. In addition, we discuss different possible scenarios for combinations of CAR-T cells and other treatment modalities, with a special emphasis on kinase inhibitors, elaborating on the strategies to maximize synergism. Finally, we discuss some of the technologies that are available to explore the molecular events governing the success of these therapies. The young fields of synthetic and systems biology are likely to be major players in the advancement of CAR-T cell therapies, providing the tools and the knowledge to engineer patients' T lymphocytes into intelligent cancer-fighting micromachines.