Citations

Context.— Neoadjuvant systemic therapy refers to the use of systemic agent(s) for malignancy prior to surgical treatment and has recently emerged as an option for most breast cancer patients eligible for adjuvant systemic therapy. Consequently, treated breast carcinomas have become routine specimens in pathology practices. A standard protocol has not yet been universally adopted for the evaluation and reporting of these specimens. The American Joint Committee on Cancer staging system recognizes the challenges in staging breast carcinomas after neoadjuvant treatment and provides important data points but does not currently provide detailed guidance in estimating the residual tumor burden in the breast and lymph nodes. The Residual Cancer Burden system is the only Web-based system that quantifies treatment response as a continuous variable using residual tumor burden in the breast and the lymph nodes. Objective.— To provide clarifications and guidance for evaluation and reporting of postneoadjuvant breast specimens, discuss issues with the current staging and reporting systems, and provide specific suggestions for future modifications to the American Joint Committee on Cancer system and the Residual Cancer Burden calculator. Data Sources.— English-language literature on the subject and the data from the I-SPY 2, a multicenter, adaptive randomization phase 2 neoadjuvant platform trial for early-stage, high-risk breast cancer patients. Conclusions.— This article highlights challenges in the pathologic evaluation and reporting of treated breast carcinomas and provides recommendations and clarifications for pathologists and clinicians. It also provides specific recommendations for staging and discusses future directions.

PURPOSEThe advancement of natural language processing (NLP) has promoted the use of detailed textual data in electronic health records (EHRs) to support cancer research and to facilitate patient care. In this review, we aim to assess EHR for cancer research and patient care by using the Minimal Common Oncology Data Elements (mCODE), which is a community-driven effort to define a minimal set of data elements for cancer research and practice. Specifically, we aim to assess the alignment of NLP-extracted data elements with mCODE and review existing NLP methodologies for extracting said data elements.METHODSPublished literature studies were searched to retrieve cancer-related NLP articles that were written in English and published between January 2010 and September 2020 from main literature databases. After the retrieval, articles with EHRs as the data source were manually identified. A charting form was developed for relevant study analysis and used to categorize data including four main topics: metadata, EHR data and targeted cancer types, NLP methodology, and oncology data elements and standards.RESULTSA total of 123 publications were selected finally and included in our analysis. We found that cancer research and patient care require some data elements beyond mCODE as expected. Transparency and reproductivity are not sufficient in NLP methods, and inconsistency in NLP evaluation exists.CONCLUSIONWe conducted a comprehensive review of cancer NLP for research and patient care using EHRs data. Issues and barriers for wide adoption of cancer NLP were identified and discussed.

Background and Aims: A better understanding of the underlying mechanism of acetaminophen (APAP)‐induced liver injury (AILI) remains an important endeavor to develop therapeutic approaches. Eosinophils have been detected in liver biopsies of patients with APAP overdose. We recently demonstrated a profound protective role of eosinophils against AILI; however, the molecular mechanism had not been elucidated. Approach and Results: In agreement with our previous data from experiments using genetic deletion of eosinophils, we found that depletion of eosinophils in wild‐type (WT) mice by an anti‐IL‐15 antibody resulted in exacerbated AILI. Moreover, adoptive transfer of eosinophils significantly reduced liver injury and mortality rate in WT mice. Mechanistic studies using eosinophil‐specific IL‐4/IL‐13 knockout mice demonstrated that these cytokines, through inhibiting interferon‐γ, mediated the hepatoprotective function of eosinophils. Reverse phase protein array analyses and in vitro experiments using various inhibitors demonstrated that IL‐33 stimulation of eosinophils activated p38 mitogen‐activated protein kinase (MAPK), and in turn, cyclooxygenases (COX), which triggered NF‐κB–mediated IL‐4/IL‐13 production. In vivo adoptive transfer experiments showed that in contrast to naive eosinophils, those pretreated with COX inhibitors failed to attenuate AILI. Conclusions: The current study revealed that eosinophil‐derived IL‐4/IL‐13 accounted for the hepatoprotective effect of eosinophils during AILI. The data demonstrated that the p38 MAPK/COX/NF‐κB signaling cascade played a critical role in inducing IL‐4/IL‐13 production by eosinophils in response to IL‐33.

Abstract Background: Pancreatitis is an inflammatory disease of the pancreas that causes significant morbidity and mortality and is one of the major risk factors for pancreatic cancer. Protein phosphatase 4 (PP4) has been reported to be overexpressed in breast, lung and pancreatic cancers. PP4 plays an important role in the regulation of centrosome maturation, DNA repair, NF-κB, and c-jun-NH2-kinase (JNK) signaling pathways. However, the expression and functions of PP4 in pancreatitis have not been studied. Methods: To examine the functions of PP4 in cerulein-induced acute pancreatitis (AP), we crossed PP4flox/+ mice with pancreatic acinar cell specific cre, CreERT, which was driven by a full length pancreatic acinar specific elastase I promoter. PP4flox/flox, CreERT mice and control mice were treated with 8 hourly intraperitoneal injections of cerulein (50 µg/kg/h). The pancreata were harvested at different time points for histopathological examination and molecular analysis. Results: PP4 expression was increased at both protein and mRNA levels in mouse pancreas with AP. Compared to CreERT mice, PP4flox/flox, CreERT mice demonstrated significantly less edema, less inflammation, less necrosis or loss of pancreatic acinar cells in pancreas after cerulein treatment. The serum amylase and lipase levels were lower in cerulein-treated PP4flox/flox, CreERT mice compared with controls. The pancreata of PP4flox/flox, CreERT mice exhibited decreased STAT3 Tyr705 phosphorylation and decreased NF-κB activation cerulein-treated PP4flox/flox, CreERT mice than control mice. Conclusion: Our findings demonstrated that PP4 plays an important role in cerulein-induced AP through STAT3 and NF-κB signaling pathways. Inhibition of PP4 may help to reduce the pancreatic injuries and to prevent the development of chronic pancreatitis, which increases the risk of pancreatic cancer. Citation Format: Hua Wang, Reza Abbasgholizadeh, Rohan Moniruzzaman, Baoan Ji, Anirban Maitra, Huamin Wang. Protein phosphatase 4 deficiency protects mice against cerulein-induced acute pancreatitis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB568.

PURPOSE Antitumor activity in preclinical models and a phase I study of patients with dedifferentiated liposarcoma (DD-LPS) was observed with selinexor. We evaluated the clinical benefit of selinexor in patients with previously treated DD-LPS whose sarcoma progressed on approved agents. METHODS SEAL was a phase II-III, multicenter, randomized, double-blind, placebo-controlled study. Patients age 12 years or older with advanced DD-LPS who had received two-five lines of therapy were randomly assigned (2:1) to selinexor (60 mg) or placebo twice weekly in 6-week cycles (crossover permitted). The primary end point was progression-free survival (PFS). Patients who received at least one dose of study treatment were included for safety analysis (ClinicalTrials.gov identifier: NCT02606461 ). RESULTS Two hundred eighty-five patients were enrolled (selinexor, n = 188; placebo, n = 97). PFS was significantly longer with selinexor versus placebo: hazard ratio (HR) 0.70 (95% CI, 0.52 to 0.95; one-sided P = .011; medians 2.8 v 2.1 months), as was time to next treatment: HR 0.50 (95% CI, 0.37 to 0.66; one-sided P < .0001; medians 5.8 v 3.2 months). With crossover, no difference was observed in overall survival. The most common treatment-emergent adverse events of any grade versus grade 3 or 4 with selinexor were nausea (151 [80.7%] v 11 [5.9]), decreased appetite (113 [60.4%] v 14 [7.5%]), and fatigue (96 [51.3%] v 12 [6.4%]). Four (2.1%) and three (3.1%) patients died in the selinexor and placebo arms, respectively. Exploratory RNA sequencing analysis identified that the absence of CALB1 expression was associated with longer PFS with selinexor compared with placebo (median 6.9 v 2.2 months; HR, 0.19; P = .001). CONCLUSION Patients with advanced, refractory DD-LPS showed improved PFS and time to next treatment with selinexor compared with placebo. Supportive care and dose reductions mitigated side effects of selinexor. Prospective validation of CALB1 expression as a predictive biomarker for selinexor in DD-LPS is warranted.

Abstract Background: The etiology of colorectal cancer is not fully understood. Methods: Using genetic variants and metabolomics data including 217 metabolites from the Framingham Heart Study (n = 1,357), we built genetic prediction models for circulating metabolites. Models with prediction R2 &gt; 0.01 (Nmetabolite = 58) were applied to predict levels of metabolites in two large consortia with a combined sample size of approximately 46,300 cases and 59,200 controls of European and approximately 21,700 cases and 47,400 controls of East Asian (EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with colorectal cancer risk in logistic regressions within each racial group, after which the results were combined by meta-analysis. Results: Of the 58 metabolites tested, 24 metabolites were significantly associated with colorectal cancer risk [Benjamini–Hochberg FDR (BH-FDR) &lt; 0.05] in the European population (ORs ranged from 0.91 to 1.06; P values ranged from 0.02 to 6.4 × 10−8). Twenty one of the 24 associations were replicated in the EA population (ORs ranged from 0.26 to 1.69, BH-FDR &lt; 0.05). In addition, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with colorectal cancer risk in the EA population only (OREA: 1.94, 95% CI, 1.60−2.36, P = 2.6 × 10−11; OREUR: 1.01, 95% CI, 0.99−1.04, P = 0.3). Nineteen of the 25 metabolites were glycerophospholipids and triacylglycerols (TAG). Eighteen associations exhibited significant heterogeneity between the two racial groups (PEUR-EA-Het &lt; 0.005), which were more strongly associated in the EA population. This integrative study suggested a potential role of lipids, especially certain glycerophospholipids and TAGs, in the etiology of colorectal cancer. Conclusions: This study identified potential novel risk biomarkers for colorectal cancer by integrating genetics and circulating metabolomics data. Impact: The identified metabolites could be developed into new tools for risk assessment of colorectal cancer in both European and EA populations.

Abstract Purpose: Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers. Experimental Design: We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double expressors. Results: We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable effects within ST2 and LymphGen-unclassified cases. FN1 and PD-1–high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases. Conclusions: Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets.

AbstractElevated blood levels of C‐reactive protein (CRP) have been linked to colorectal cancer (CRC) survival. We evaluated genetic variants associated with CRP levels and their interactions with sex and lifestyle factors in association with CRC‐specific mortality. Our study included 16 142 CRC cases from the International Survival Analysis in Colorectal Cancer Consortium. We identified 618 common single nucleotide polymorphisms (SNPs) associated with CRP levels from the NHGRI‐EBI GWAS Catalog. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between SNPs and CRC‐specific mortality adjusting for age, sex, genotyping platform/study and principal components. We investigated their interactions with sex and lifestyle factors using likelihood ratio tests. Of 5472 (33.9%) deaths accrued over up to 10 years of follow‐up, 3547 (64.8%) were due to CRC. No variants were associated with CRC‐specific mortality after multiple comparison correction. We observed strong evidence of interaction between variant rs1933736 at FRK gene and sex in relation to CRC‐specific mortality (corrected Pinteraction = .0004); women had higher CRC‐specific mortality associated with the minor allele (HR = 1.11, 95% CI = 1.04‐1.19) whereas an inverse association was observed for men (HR = 0.88, 95% CI = 0.82‐0.94). There was no evidence of interactions between CRP‐associated SNPs and alcohol, obesity or smoking. Our study observed a significant interaction between sex and a CRP‐associated variant in relation to CRC‐specific mortality. Future replication of this association and functional annotation of the variant are needed.

Abstract Background and Rationale: Axi-cel is a standard-of-care treatment for relapsed or refractory LBCL after 2 or more lines of systemic therapy. Some patients who would have been ineligible for ZUMA-1 criteria due to comorbidities have been treated with axi-cel in the real-world setting. We interrogated a large registry of patients treated with standard-of-care axi-cel for a definitive report on the impact of age or certain comorbidities on safety and efficacy outcomes after axi-cel infusion. Methods: From October 2017 to August 2020, 1500 patients were enrolled in the postapproval safety observational study of axi-cel treated at 79 centers. Patients eligible for the protocol and followed up for at least 6 months with complete data entry by the time of analyses were included. One patient rescinded consent and 1 was deemed ineligible. Patients previously treated with immune effector cell therapy (n=31), with incomplete follow-up reporting (n=92), or alive but last contacted &lt;180 days postinfusion (n=32) were excluded from analysis. Main efficacy outcomes included complete and objective response rates (CR and ORR), duration of response (DOR), progression-free and overall survival (PFS and OS). Safety endpoints of interest included cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Outcomes were assessed and compared by age and preselected coexisting disease or organ impairment within 3 months prior to the infusion included in the hematopoietic cell transplantation comorbidity index. Multivariate logistic and Cox regression models were used to assess the impact of age or coexistent organ dysfunction on outcomes via odds ratio (OR) or hazard ratio (HR) and their 95% CIs. Results A total of 1343 patients were included in the analysis with a median 25.1 months (range, 10.3-42.7 months) for potential follow-up, defined from infusion to data cutoff date, and a median 11.8 months (range, 0.1-38.8 months) for actual follow-up time, defined from infusion to date of death or last contact. Of these, 38% were 65 years or older (median 62 years), 4% had a performance score ≥2, 13% had cardiac comorbidities, 16% had a prior cancer, 9% were obese, 2% had moderate to severe hepatic comorbidities, and 2% had renal comorbidities. Transformed lymphoma, double or triple-hit by fluorescence in situ hybridization, prior autologous transplant and refractory disease were present in 28%, 15%, 27% and 66%, respectively. Bridging therapy was administered in 21% of patients. Overall, ORR was 74%, (CR 56%), and probabilities of DOR, PFS, and OS at 18 months were 61% (95% CI, 57-65%), 42% (95% CI, 39-45%) and 52% (95% CI, 49-55%), respectively. Overall rates of CRS and ICANS were 83% and 55%, respectively. ORR was 78% (CR 62%, median OS 17.5 [95% CI, 16.0-not evaluated (NE)] months) for patients ≥65 years, ORR 57% (CR 29%; median OS 4.3 [95% CI, 2.5-8.3] months) for patients with hepatic dysfunction, ORR 70% (CR 43%; median OS 8.9 [95% CI, 3.8-NE] months) for patients with renal dysfunction; and ORR 47% (CR 20%, median OS 4 [95% CI, 2.6-6.9] months) for patients with Eastern Cooperative Oncology Group (ECOG) 2 or 3. Multivariate analyses indicated that advanced age (≥65 years vs &lt;65 years; OR 1.38; 95% CI, 1.05-1.83), moderate to severe pulmonary disease (yes vs no; OR 0.74; 95% CI, 0.55-0.98), and ECOG (2-3 vs 0-1; OR 0.31, 95% CI, 0.18-0.53) impacted ORR (Table). Age ≥65 years did not have an impact on survival (HR 1.05, 95% CI, 0.88-1.26), although it was associated with CRS (OR 1.42, 95% CI, 1.03-1.96) and ICANS (OR 1.78, 95% CI, 1.39-2.28). Coexistent cardiac disease (HR 1.44, 95% CI, 1.12-1.83), renal disease (HR 2.13, 95% CI, 1.32-3.46) and hepatic dysfunction (HR 2.65, 95% CI, 1.69-4.14) had an impact on OS, but not on response, CRS, and ICANS. ECOG significantly impacted all efficacy outcomes. None of the other comorbidities tested significantly impacted outcomes. Conclusion: Advanced age (≥65 years) was not associated with worse efficacy outcomes after axi-cel, despite higher rates of CRS and ICANS, which require closer monitoring. Performance status rather than age should be accounted for in patient selection and treatment decisions with axi-cel. Most coexistent organ dysfunctions have no clinically significant impact on axi-cel objective response and safety outcomes. Figure 1 Figure 1. Disclosures Locke: Moffitt Cancer Center: Patents & Royalties: field of cellular immunotherapy; Allogene Therapeutics: Consultancy, Other: Scientific Advisory Role, Research Funding; Amgen: Consultancy, Other: Scientific Advisory Role; Bluebird Bio: Consultancy, Other: Scientific Advisory Role; EcoR1: Consultancy; Emerging Therapy Solutions: Consultancy; Gerson Lehrman Group: Consultancy; Iovance Biotherapeutics: Consultancy, Other: Scientific Advisory Role; Takeda: Consultancy, Other; Novartis: Consultancy, Other, Research Funding; Wugen: Consultancy, Other; GammaDelta Therapeutics: Consultancy, Other: Scientific Advisory Role; Umoja: Consultancy, Other; Cellular Biomedicine Group: Consultancy, Other: Scientific Advisory Role; Calibr: Consultancy, Other: Scientific Advisory Role; Cowen: Consultancy; BMS/Celgene: Consultancy, Other: Scientific Advisory Role; Legend Biotech: Consultancy, Other; Kite, a Gilead Company: Consultancy, Other: Scientific Advisory Role, Research Funding; Janssen: Consultancy, Other: Scientific Advisory Role. Jacobson: Axis: Speakers Bureau; Nkarta: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Other: Travel support, Research Funding; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Other: Travel support; Novartis Pharmaceuticals Corporation: Consultancy, Honoraria, Other: Travel support; Precision Biosciences: Consultancy, Honoraria, Other: Travel support; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel support; Lonza: Consultancy, Honoraria, Other: Travel support; Humanigen: Consultancy, Honoraria, Other: Travel support; Clinical Care Options: Speakers Bureau. Ma: Kite, a Gilead Company: Current Employment. Dong: Kite, a Gilead Company: Current Employment. Hu: Kite, a Gilead Company: Research Funding; Novartis: Research Funding; Celgene: Research Funding. Siddiqi: BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Oncternal: Research Funding; Janssen: Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; BeiGene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics LLC, an AbbVie Company: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; TG Therapeutics: Research Funding. Ahmed: Seagen: Research Funding; Tessa Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Xencor: Research Funding. Ghobadi: Atara: Consultancy; Wugen: Consultancy; Amgen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Celgene: Consultancy. Miklos: Pharmacyclics: Patents & Royalties; Kite, a Gilead Company, Amgen, Atara, Wugen, Celgene, Novartis, Juno-Celgene-Bristol Myers Squibb, Allogene, Precision Bioscience, Adicet, Pharmacyclics, Janssen, Takeda, Adaptive Biotechnologies and Miltenyi Biotechnologies: Consultancy; Pharmacyclics, Amgen, Kite, a Gilead Company, Novartis, Roche, Genentech, Becton Dickinson, Isoplexis, Miltenyi, Juno-Celgene-Bristol Myers Squibb, Allogene, Precision Biosciences, Adicet, Adaptive Biotechnologies: Research Funding; Adaptive Biotechnologies, Novartis, Juno/Celgene-BMS, Kite, a Gilead Company, Pharmacyclics-AbbVie, Janssen, Pharmacyclics, AlloGene, Precision Bioscience, Miltenyi Biotech, Adicet, Takeda: Membership on an entity's Board of Directors or advisory committees. Lin: Kite, a Gilead Company: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Legend: Consultancy; Vineti: Consultancy; Sorrento: Consultancy; Gamida Cell: Consultancy; Janssen: Consultancy, Research Funding; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Novartis: Consultancy; Merck: Research Funding; Takeda: Research Funding. Perales: Bristol-Myers Squibb: Honoraria; Takeda: Honoraria; Nektar Therapeutics: Honoraria, Other; Miltenyi Biotec: Honoraria, Other; MorphoSys: Honoraria; NexImmune: Honoraria; Sellas Life Sciences: Honoraria; Cidara: Honoraria; Merck: Honoraria; Omeros: Honoraria; Servier: Honoraria; Celgene: Honoraria; Novartis: Honoraria, Other; Kite/Gilead: Honoraria, Other; Incyte: Honoraria, Other; Medigene: Honoraria; Karyopharm: Honoraria; Equilium: Honoraria. Lunning: Daiichi-Sankyo: Consultancy; TG Therapeutics: Consultancy; Kite, a Gilead Company: Consultancy; ADC Therapeutics: Consultancy; Spectrum: Consultancy; Beigene: Consultancy; Celgene, a Bristol Myers Squibb Co.: Consultancy; Legend: Consultancy; AbbVie: Consultancy; AstraZeneca: Consultancy; Morphosys: Consultancy; Verastem: Consultancy; Novartis: Consultancy; Myeloid Therapeutics: Consultancy; Janssen: Consultancy; Acrotech: Consultancy; Kyowa Kirin: Consultancy; Karyopharm: Consultancy. Hill: Gentenech: Consultancy, Honoraria, Research Funding; Incyte/Morphysis: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel Support, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria; Celgene (BMS): Consultancy, Honoraria, Research Funding. Nikiforow: Kite/Gilead: Other: ad HOC Advisory Boards; Novartis: Other: ad Hoc Advisory Boards; Iovance: Other: ad Hoc Advisory Boards; Glaxo Smith Kline (GSK): Other: ad Hoc Advisory Boards. Xu: Gilead Sciences: Other: stock or other ownership ; Kite, A Gilead Company: Current Employment. Pasquini: Bristol Myers Squibb: Consultancy, Research Funding; Novartis: Research Funding; Kite Pharma: Research Funding; GlaxoSmithKline: Research Funding.