FEV1Q: a race-neutral approach to assessing lung function.

BACKGROUND: Forced expiratory volume in 1 s quotient (FEV1Q) is a simple approach to spirometry interpretation that compares measured lung function to a lower boundary. This study evaluated how well FEV1Q predicts survival compared with current interpretation methods and whether race impacts FEV1Q. METHODS: White and Black adults with complete spirometry and mortality data from the National Health and Nutrition Examination Survey (NHANES) III and the United Network for Organ Sharing (UNOS) database for lung transplant referrals were included. FEV1Q was calculated as FEV1 divided by 0.4 L for females or 0.5 L for males. Cumulative distributions of FEV1 were compared across races. Cox proportional hazards models tested mortality risk from FEV1Q adjusting for age, sex, height, smoking, income and among UNOS individuals, referral diagnosis. Harrell's C-statistics were compared between absolute FEV1, FEV1Q, FEV1/height2, FEV1 z-scores and FEV1 % predicted. Analyses were stratified by race. RESULTS: Among 7182 individuals from NHANES III and 7149 from UNOS, 1907 (27%) and 991 (14%), respectively, were Black. The lower boundary FEV1 values did not differ between Black and White individuals in either population (FEV1 first percentile difference ≤0.01 L; p>0.05). Decreasing FEV1Q was associated with increasing hazard ratio (HR) for mortality (NHANES III HR 1.33 (95% CI 1.28-1.39) and UNOS HR 1.18 (95% CI 1.12-1.23)). The associations were not confounded nor modified by race. Discriminative power was highest for FEV1Q compared with alternative FEV1 approaches in both Black and White individuals. CONCLUSIONS: FEV1Q is an intuitive and simple race-neutral approach to interpreting FEV1 that predicts survival better than current alternative methods.

Clinical and molecular features of acquired resistance to immunotherapy in non-small cell lung cancer.

Although immunotherapy with PD-(L)1 blockade is routine for lung cancer, little is known about acquired resistance. Among 1,201 patients with non-small cell lung cancer (NSCLC) treated with PD-(L)1 blockade, acquired resistance is common, occurring in >60% of initial responders. Acquired resistance shows differential expression of inflammation and interferon (IFN) signaling. Relapsed tumors can be separated by upregulated or stable expression of IFNγ response genes. Upregulation of IFNγ response genes is associated with putative routes of resistance characterized by signatures of persistent IFN signaling, immune dysfunction, and mutations in antigen presentation genes which can be recapitulated in multiple murine models of acquired resistance to PD-(L)1 blockade after in vitro IFNγ treatment. Acquired resistance to PD-(L)1 blockade in NSCLC is associated with an ongoing, but altered IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance may inform therapeutic strategies to effectively reprogram and reverse acquired resistance.

Cell-of-origin-specific proteomics of extracellular vesicles.

The ability to assign cellular origin to low-abundance secreted factors in extracellular vesicles (EVs) would greatly facilitate the analysis of paracrine-mediated signaling. Here, we report a method, named selective isolation of extracellular vesicles (SIEVE), which uses cell type-specific proteome labeling via stochastic orthogonal recoding of translation (SORT) to install bioorthogonal reactive groups into the proteins derived from the cells targeted for labeling. We establish the native purification of intact EVs from a target cell, via a bioorthogonal tetrazine ligation, leading to copurification of the largely unlabeled EV proteome from the same cell. SIEVE enables capture of EV proteins at levels comparable with those obtained by antibody-based methods, which capture all EVs regardless of cellular origin, and at levels 20× higher than direct capture of SORT-labeled proteins. Using proteomic analysis, we analyze nonlabeled cargo proteins of EVs and show that the enhanced sensitivity of SIEVE allows for unbiased and comprehensive analysis of EV proteins from subpopulations of cells as well as for cell-specific EV proteomics in complex coculture systems. SIEVE can be applied with high efficiency in a diverse range of existing model systems for cell-cell communication and has direct applications for cell-of-origin EV analysis and for protein biomarker discovery.

How to account for Inuit ancestry in lung function prediction.

Rigorous lung function prediction equations for the Inuit are lacking. We used spirometry from 351 Inuit and 29 people of other ancestry obtained during an occupational survey in Greenland to determine how to obtain valid lung function predictions for the Inuit using Global Lung Function Initiative (GLI) equations for Europeans. Standing height for the Inuit was used in the predictions as well as their height modified in line with the known differences in standing to sitting height ratio (SHR) for the Inuit. With recorded height in predicting lung function, mean±SD Inuit z-scores for FVC and FEV1 were significantly higher than predicted (0.81±1.20 and 0.53±1.36, respectively, p<0.0001) which was not true for the non-Inuit participants (-0.01±1.04 and 0.15±1.17, respectively). When using height modified for SHR the mean±SD Inuit z-scores for FVC and FEV1 were no longer significantly different from predicted (0.10±1.10 and -0.12±1.24, respectively). The mean±SD Inuit FEV1/FVC z-scores were not significantly different from the non-Inuit, being respectively -0.45±0.98 and -0.01±1.04. Modified height changed the mean±SD Inuit FEV1/FVC z-scores to -0.39±0.99. Representative lung function predictions from GLI equations can be made for Inuit by using standing height modified for the known differences in SHR between Inuit and those of European ancestry.

ERS/ATS technical standard on interpretive strategies for routine lung function tests.

BACKGROUND: Appropriate interpretation of pulmonary function tests (PFTs) involves the classification of observed values as within/outside the normal range based on a reference population of healthy individuals, integrating knowledge of physiological determinants of test results into functional classifications and integrating patterns with other clinical data to estimate prognosis. In 2005, the American Thoracic Society (ATS) and European Respiratory Society (ERS) jointly adopted technical standards for the interpretation of PFTs. We aimed to update the 2005 recommendations and incorporate evidence from recent literature to establish new standards for PFT interpretation. METHODS: This technical standards document was developed by an international joint Task Force, appointed by the ERS/ATS with multidisciplinary expertise in conducting and interpreting PFTs and developing international standards. A comprehensive literature review was conducted and published evidence was reviewed. RESULTS: Recommendations for the choice of reference equations and limits of normal of the healthy population to identify individuals with unusually low or high results are discussed. Interpretation strategies for bronchodilator responsiveness testing, limits of natural changes over time and severity are also updated. Interpretation of measurements made by spirometry, lung volumes and gas transfer are described as they relate to underlying pathophysiology with updated classification protocols of common impairments. CONCLUSIONS: Interpretation of PFTs must be complemented with clinical expertise and consideration of the inherent biological variability of the test and the uncertainty of the test result to ensure appropriate interpretation of an individual's lung function measurements.

Ovarian tumors orchestrate distinct cellular compositions.

The determinants of T cell infiltration in tumors remain largely unknown. In a recent issue of Cancer Cell, Hornburg et al. use single-cell RNA sequencing to characterize the cellular compartments of the ovarian cancer microenvironment and shed light on how tumor, immune, and stromal cells interact and shape T cell infiltration.

Impact of the spirometric definition on comorbidities in chronic obstructive pulmonary disease.

BACKGROUND: Little is known about how the spirometric definition of airway obstruction affects the association between COPD and comorbidities and whether these associations might be due to genetic predisposition. AIM: 1) To examine the impact of the spirometric definition on the associations between COPD and its comorbidities and 2) To examine whether these associations can be explained by shared genetic or environmental factors. METHODS: 11,458 twins, aged 40-80 years, from the Danish Twin Registry were recruited who completed a questionnaire on medical history, life style factors and had a clinical examination. COPD was defined by respiratory symptoms (RS) plus airway obstruction according to either GOLD (FR-COPD) or ERS/ATS guidelines (LLN-COPD). Self-reported physician diagnoses were used to identify comorbidities. RESULTS: The mean age of participants was 58.4 years ±SD 9.7, mean BMI was 26.6 kg/m2 ± SD 4.4, 52% were female and the prevalence of LLN2.5-COPD and FR-COPD was 2.5% and 6.3%, respectively. Among eight major comorbidities, multivariate logistic regression showed COPD was only associated with heart failure, whereas RS alone were associated with 6 out of 8 comorbidities after Bonferroni-correction. There was an increased risk of heart failure, ischemic heart disease, depression and pulmonary embolism in twin individuals with RS compared with the co-twin without RS. CONCLUSIONS: COPD was only associated with an increased risk of heart failure. Discordant COPD-individuals (FR-COPD+/LLN5-COPD-) were at increased risk of heart failure. Sub-analyses showed that RS, but not airway obstruction were associated with an increased risk of comorbidities.

Copy number aberrations drive kinase rewiring, leading to genetic vulnerabilities in cancer.

Somatic DNA copy number variations (CNVs) are prevalent in cancer and can drive cancer progression, albeit with often uncharacterized roles in altering cell signaling states. Here, we integrate genomic and proteomic data for 5,598 tumor samples to identify CNVs leading to aberrant signal transduction. The resulting associations recapitulate known kinase-substrate relationships, and further network analysis prioritizes likely causal genes. Of the 303 significant associations we identify from the pan-tumor analysis, 43% are replicated in cancer cell lines, including 44 robust gene-phosphosite associations identified across multiple tumor types. Several predicted regulators of hippo signaling are experimentally validated. Using RNAi, CRISPR, and drug screening data, we find evidence of kinase addiction in cancer cell lines, identifying inhibitors for targeting of kinase-dependent cell lines. We propose copy number status of genes as a useful predictor of differential impact of kinase inhibition, a strategy that may be of use in the future for anticancer therapies.

Reduction in T LCO and survival in a clinical population.

BACKGROUND: How best to express the level of transfer factor of the lung for carbon monoxide (T LCO) has not been properly explored. METHODS: We used the most recent clinical data from 13 829 patients (54% male; 10% non-European ancestry; median age 60.5 years, range 20-97 years; median survival 3.5 years, range 0-20 years) to determine how best to express T LCO function in terms of its relationship to survival. RESULTS: The proportion of subjects of non-European ancestry with Global Lung Function Initiative (GLI) T LCO z-scores above predicted was reduced, but was significantly increased between -1.5 and -3.5, suggesting the need for ethnicity-appropriate equations. Applying GLI forced vital capacity (FVC) ethnicity methodology to GLI T LCO z-scores removed this ethnic bias and was used for all subsequent analysis. T LCO z-scores using the GLI equations were compared with Miller's USA equations with median T LCO z-scores being -1.43 and -1.50 for GLI and Miller equations, respectively (interquartile range -2.8 to -0.3 and -2.4 to -0.7, respectively). GLI T LCO z-scores gave the best Cox regression model for predicting survival. A previously proposed six-tier grading system for level of lung function did not show much separation in survival risk in the less-severe grades. A new four-tier grading based on z-scores of -1.645, -3 and -5 showed better separation of risk with hazard ratio for all-cause mortality of 2.0, 3.4 and 6.6 with increasing severity. CONCLUSION: Applying GLI FVC ethnicity methodology to GLI T LCO predictions to remove ethnic bias together with a new four-tier z-score grading best relates T LCO function to survival.

Promises and challenges of adoptive T-cell therapies for solid tumours.

Cancer is a leading cause of death worldwide and, despite new targeted therapies and immunotherapies, many patients with advanced-stage- or high-risk cancers still die, owing to metastatic disease. Adoptive T-cell therapy, involving the autologous or allogeneic transplant of tumour-infiltrating lymphocytes or genetically modified T cells expressing novel T-cell receptors or chimeric antigen receptors, has shown promise in the treatment of cancer patients, leading to durable responses and, in some cases, cure. Technological advances in genomics, computational biology, immunology and cell manufacturing have brought the aspiration of individualised therapies for cancer patients closer to reality. This new era of cell-based individualised therapeutics challenges the traditional standards of therapeutic interventions and provides opportunities for a paradigm shift in our approach to cancer therapy. Invited speakers at a 2020 symposium discussed three areas-cancer genomics, cancer immunology and cell-therapy manufacturing-that are essential to the effective translation of T-cell therapies in the treatment of solid malignancies. Key advances have been made in understanding genetic intratumour heterogeneity, and strategies to accurately identify neoantigens, overcome T-cell exhaustion and circumvent tumour immunosuppression after cell-therapy infusion are being developed. Advances are being made in cell-manufacturing approaches that have the potential to establish cell-therapies as credible therapeutic options. T-cell therapies face many challenges but hold great promise for improving clinical outcomes for patients with solid tumours.

Integrated Multi-Tumor Radio-Genomic Marker of Outcomes in Patients with High Serous Ovarian Carcinoma.

Purpose: Develop an integrated intra-site and inter-site radiomics-clinical-genomic marker of high grade serous ovarian cancer (HGSOC) outcomes and explore the biological basis of radiomics with respect to molecular signaling pathways and the tumor microenvironment (TME). Method: Seventy-five stage III-IV HGSOC patients from internal (N = 40) and external factors via the Cancer Imaging Archive (TCGA) (N = 35) with pre-operative contrast enhanced CT, attempted primary cytoreduction, at least two disease sites, and molecular analysis performed within TCGA were retrospectively analyzed. An intra-site and inter-site radiomics (cluDiss) measure was combined with clinical-genomic variables (iRCG) and compared against conventional (volume and number of sites) and average radiomics (N = 75) for prognosticating progression-free survival (PFS) and platinum resistance. Correlation with molecular signaling and TME derived using a single sample gene set enrichment that was measured. Results: The iRCG model had the best platinum resistance classification accuracy (AUROC of 0.78 [95% CI 0.77 to 0.80]). CluDiss was associated with PFS (HR 1.03 [95% CI: 1.01 to 1.05], p = 0.002), negatively correlated with Wnt signaling, and positively to immune TME. Conclusions: CluDiss and the iRCG prognosticated HGSOC outcomes better than conventional and average radiomic measures and could better stratify patient outcomes if validated on larger multi-center trials.