Safety and Efficacy of Durvalumab With or Without Tremelimumab in Patients With PD-L1-Low/Negative Recurrent or Metastatic HNSCC The Phase 2 CONDOR Randomized Clinical Trial

IMPORTANCE: Dual blockade of programmed death ligand 1(PD-L1) and cytotoxic T-lymphocyte associated protein 4 (CTLA-4) may overcome immune checkpoint inhibition. It is unknown whether dual blockade can potentiate antitumor activity without compromising safety in patients with recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC) and low or no PD-L1 tumor cell expression. OBJECTIVE :To assess safety and objective response rate of durvalumab combined with tremelimumab. DESIGN, SETTING, AND PARTICIPANTS: The CONDOR study was a phase 2, randomized, open-label study of Durvalumab, Tremelimumab, and Durvalumab in Combination With Tremelimumab in Patients With R/M HNSCC. Eligibility criteria included PD-L1-low/negative disease that had progressed after 1 platinum-containing regimen in the R/M setting. Patients were randomized (N = 267) from April 15, 2015, to March 16, 2016, at 127 sites in North America, Europe, and Asia Pacific. INTERVENTIONS: Durvalumab (20 mg/kg every 4 weeks) + tremelimumab (1 mg/kg every 4 weeks) for 4 cycles, followed by durvalumab (10 mg/kg every 2 weeks), or durvalumab (10 mg/kg every 2 weeks) monotherapy, or tremelimumab (10 mg/kg every 4 weeks for 7 doses then every 12 weeks for 2 doses) monotherapy. MAIN OUTCOMES AND MEASURES: Safety and tolerability and efficacy measured by objective response rate. RESULTS: Among the 267 patients (220 men [82.4%]), median age (range) of patients was 61.0 (23-82) years. Grade 3/4 treatment-related adverse events occurred in 21 patients (15.8%) treated with durvalumab + tremelimumab, 8 (12.3%) treated with durvalumab, and 11 (16.9%) treated with tremelimumab. Grade 3/4 immune-mediated adverse events occurred in 8 patients (6.0%) in the combination arm only. Objective response rate (95% CI) was 7.8% (3.78%1339%) in the combination arm (n =129), 9.2% (3.46%-19.02%) for durvalumab monotherapy (n = 65), and 1.6% (0.04%-8.53%) for tremelimumab monotherapy (n = 63); median overall survival (95% CI) for all patients treated was 7.6 (4.9-10.6), 6.0 (4.0-11.3), and 5.5 (3.9-7.0) months, respectively. CONCLUSIONS AND RELEVANCE: In patients with R/M HNSCC and low or no PD-Lt tumor cell expression, all 3 regimens exhibited a manageable toxicity profile. Durvalumab and durvalumab + tremelimumab resulted in clinical benefit, with minimal observed difference between the two. A phase 3 study is under way

LIMPRINT: the UK experience - subjective control of swelling in patients attending specialist lymphedema services

Background and study design: This study was undertaken as part of the UK LIMPRINT international study to determine the number of people with chronic oedema and its impact on health services. Overall 7436 with chronic oedema (CO) were recruited in the main UK study from a range of health settings. Methods and results: Subjective control of arm and leg chronic oedema (CO) was defined for patients attending three Lymphoedema services in the UK. Of the total available in the UK dataset 5165 (69.4%)/ 7436(100%) of participants were included. Reasons for exclusions included the following: lack of information (1669), having both arm and leg swelling (272), lack of description of control (5) and professional inability to decide whether CO was controlled (325). Arm swelling occurred in 953 (18.5%), with leg CO in 4212 (81.5%). Poor control was found in 1430 (27.7%) and good control in 3735 (72.3%). Control of arm swelling was worse in men and control increased overall in those aged over 45 years. In contrast control of CO worsened in those with leg CO with increasing age and multiple co-morbidities. Obesity and cellulitis, particularly an episode in the last year were associated with poor control. Independent risk factors for arm CO were obesity, neurological disease and cellulitis in the last year and for leg CO: obesity, poor mobility, heart disease, presence of a wound, cellulitis in the last year and duration of swelling. Conclusion: Control of CO within specialised centres is complex due to sociodemographic and clinical comorbidities

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Molecular Characterization of Uterine Carcinosarcoma

SummaryWe performed genomic, epigenomic, transcriptomic, and proteomic characterizations of uterine carcinosarcomas (UCSs). Cohort samples had extensive copy-number alterations and highly recurrent somatic mutations. Frequent mutations were found in TP53, PTEN, PIK3CA, PPP2R1A, FBXW7, and KRAS, similar to endometrioid and serous uterine carcinomas. Transcriptome sequencing identified a strong epithelial-to-mesenchymal transition (EMT) gene signature in a subset of cases that was attributable to epigenetic alterations at microRNA promoters. The range of EMT scores in UCS was the largest among all tumor types studied via The Cancer Genome Atlas. UCSs shared proteomic features with gynecologic carcinomas and sarcomas with intermediate EMT features. Multiple somatic mutations and copy-number alterations in genes that are therapeutic targets were identified

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation