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Adoptive cell therapy using tumor-infiltrating lymphocytes (TILs) has shown activity in melanoma, but has not been previously evaluated in metastatic non-small cell lung cancer. We conducted a single-arm open-label phase 1 trial ( NCT03215810 ) of TILs administered with nivolumab in 20 patients with advanced non-small cell lung cancer following initial progression on nivolumab monotherapy. The primary end point was safety and secondary end points included objective response rate, duration of response and T cell persistence. Autologous TILs were expanded ex vivo from minced tumors cultured with interleukin-2. Patients received cyclophosphamide and fludarabine lymphodepletion, TIL infusion and interleukin-2, followed by maintenance nivolumab. The end point of safety was met according to the prespecified criteria of ≤17% rate of severe toxicity (95% confidence interval, 3–29%). Of 13 evaluable patients, 3 had confirmed responses and 11 had reduction in tumor burden, with a median best change of 35%. Two patients achieved complete responses that were ongoing 1.5 years later. In exploratory analyses, we found T cells recognizing multiple types of cancer mutations were detected after TIL treatment and were enriched in responding patients. Neoantigen-reactive T cell clonotypes increased and persisted in peripheral blood after treatment. Cell therapy with autologous TILs is generally safe and clinically active and may constitute a new treatment strategy in metastatic lung cancer. Adoptive cell therapy with tumor-infiltrating lymphocytes in metastatic lung cancer patients is safe and elicits antitumor activity, including ongoing complete responses, in association with polyclonal T cell responses against tumor antigens.

The human oral cavity is sterile prior to birth, and we have limited knowledge of how complex oral communities are assembled. To examine bacterial acquisition and community assembly over the first year of life, oral samples from a cohort of nine infants and their mothers were collected, and bacterial community composition was studied by 16S rRNA gene sequencing. Exogenous species including skin and environmental bacteria were present initially, but were quickly replaced by a small, shared microbial community of species common to all infants and adults. Subsequent ordered microbial succession and the formation of increasingly complex communities was observed. By one year of age oral microbial community composition converged to a profile that was remarkably similar among children. The introduction of new nutrient sources, but not tooth eruption, was associated with increasing complexity. Infants had fewer species than mothers, mostly accounted for by the lack of certain anaerobes, and showing that the acquisition and assembly of oral microbial communities continues past infancy. When relative abundance was considered, a shared set of species accounted for the majority of the microbial community at all ages, indicating that the dominant structure of the oral microbiome establishes early, and suggesting that it persists throughout life.

Lung cancer screening identifies cancers with heterogeneous behaviors. Some lung cancers will be identified among patients who had prior negative CT screens and upon follow-up scans develop a de novo nodule that was determined to be cancerous. Other lung cancers will be identified among patients who had one or more prior stable positive scans that were not determined to be lung cancer (indeterminate pulmonary nodules), but in follow-up scans was diagnosed with an incidence lung cancer. Using data from the CT arm of the National Lung Screening Trial, this analysis investigated differences in patient characteristics and survival endpoints between prevalence-, interval-, and screen-detected lung cancers, characterized based on sequence of screening results. Lung cancers immediately following a positive baseline (T0), and prior to the T1 screen, formed the prevalence cohort. Interval cancers were diagnosed following a negative screen at any time point prior to the next screening round. Two cohorts of screen-detected lung cancers (SDLC) were identified that had a baseline positive screen that was that was not determined to be lung cancer (i.e., an indeterminate pulmonary nodule), but in follow-up scans was diagnosed with an incidence lung cancer 12 (SDLC1) or 24 (SDLC2) months later. Two other incidence cohorts had screen-detected lung cancers that had baseline negative screen and upon follow-up scans developed a de novo nodule determined to be cancerous at 12 (SDLC3) or 24 (SDLC4) months later. Differences in patient characteristics, progression-free survival (PFS), and overall survival (OS) were assessed. The lung cancer-specific death rate was higher for SDLC3/SDLC4 compared to SDLC1/SDLC2 lung cancers (136.6/1,000 person-years vs. 71.3/1,000 person-years, P < 0.001). Moreover, PFS and OS were significantly lower for SDLC3/SDLC4 compared to SDLC1/SDLC2 (P < 0.004; P < 0.002, respectively). The findings were consistent when stratified by stage and histology. Multivariable Cox proportional models revealed that the SDLC3/SDLC4 case groups were associated with significantly poorer PFS (HR = 1.89; 95% CI 1.31-2.74) and OS (HR = 1.80; 95% CI 1.21-2.67) compared to SDLC1/SDLC2 lung cancers (HR = 1.00). Lung cancer patients who develop a de novo nodule that determined to be cancerous (i.e., at least one negative CT screen prior to cancer diagnosis) had poorer survival outcomes compared to patients who had at least one positive screen prior to cancer diagnosis. As such, the observation that de novo screen-detected are associated with poorer survival could be attributed to faster growing, more aggressive cancers that arose from a lung environment previously lacking focal abnormalities.

Recent studies have discovered several unique tumor response subgroups outside of response classification by Response Evaluation Criteria for Solid Tumors (RECIST), such as mixed response and oligometastasis. These subtypes have a distinctive property, lesion heterogeneity defined as diversity of tumor growth profiles in RECIST target lesions. Furthermore, many cancer clinical trials have been activated to evaluate various treatment options for heterogeneity-related subgroups (e.g., 29 trials so far listed in clinicaltrials.gov for cancer patients with oligometastasis). Some of the trials have shown survival benefit by tailored treatment strategies. This evidence presents the unmet need to incorporate lesion heterogeneity to improve RECIST response classification. An approach for Lesion Heterogeneity Classification (LeHeC) was developed using a contemporary statistical approach to assess target lesion variation, characterize patient treatment response, and translate informative evidence to improving treatment strategy. A mixed effect linear model was used to determine lesion heterogeneity. Further analysis was conducted to classify various types of lesion variation and incorporate with RECIST to enhance response classification. A study cohort of 110 target lesions from 36 lung cancer patients was used for evaluation. Due to small sample size issue, the result was exploratory in nature. By analyzing RECIST target lesion data, the LeHeC approach detected a high prevalence (n = 21; 58%) of lesion heterogeneity. Subgroup classification revealed several informative distinct subsets in a descending order of lesion heterogeneity: mix of progression and regression (n = 7), mix of progression and stability (n = 9), mix of regression and stability (n = 5), and non-heterogeneity (n = 15). Evaluation for association of lesion heterogeneity and RECIST best response classification showed lesion heterogeneity commonly occurred in each response group (stable disease: 16/27; 59%; partial response: 3/5; 60%; progression disease: 2/4; 50%). Survival analysis showed a differential trend of overall survival between heterogeneity and non-heterogeneity in RECIST response groups. This is the first study to evaluate lesion heterogeneity, an underappreciated metric, for RECIST application in oncology clinical trials. Results indicated lesion heterogeneity is not an uncommon event. The LeHeC approach could enhance RECIST response classification by utilizing granular lesion level discovery of heterogeneity.

Background NLR, PLR, and LMR have been associated with pancreatic ductal adenocarcinoma (PDAC) survival. Prognostic value and optimal cutpoints were evaluated to identify underlying significance in surgical PDAC patients. Methods NLR, PLR, and LMR preoperative values were available for 277 PDAC patients who underwent resection between 2007 and 2015. OS, RFS, and survival probability estimates were calculated by univariate, multivariable, and Kaplan-Meier analyses. Continuous and dichotomized ratio analysis determined best-fit cutpoints and assessed ratio components to determine primary drivers. Results Elevated NLR and PLR and decreased LMR represented 14%, 50%, and 50% of the cohort, respectively. OS ( P  = .002) and RFS ( P  = .003) were significantly decreased in resected PDAC patients with NLR ≥5 compared to those with NLR < 5. Optimal prognostic OS and RFS cutpoints for NLR, PLR, and LMR were 4.8, 192.6, and 1.7, respectively. Lymphocytes alone were the primary prognostic driver of NLR, demonstrating identical survival to NLR. Conclusions NLR is a significant predictor of OS and RFS, with lymphocytes alone as its primary driver; we identified optimal cutpoints that may direct future investigation of their prognostic value. This study contributes to the growing evidence of immune system influence on outcomes in early-stage pancreatic cancer.

Are patient-reported outcome measures (PROMs) effective at improving patient-reported health outcomes and processes of care for patients and health care professionals?

Purpose of Review Heart failure (HF) is a growing public health concern that impairs the quality of life and is associated with significant mortality. As the prevalence of heart failure increases, multidisciplinary care is essential to provide comprehensive care to individuals. Recent Findings The challenges of implementing an effective multidisciplinary care team can be daunting. Effective multidisciplinary care begins at the initial diagnosis of heart failure. The transition of care from the inpatient to the outpatient setting is critically important. The use of home visits, case management, and multidisciplinary clinics has been shown to decrease mortality and heart failure hospitalizations, and major society guidelines endorse multidisciplinary care for heart failure patients. Summary Expanding heart failure care beyond cardiology entails incorporating primary care, advanced practice providers, and other disciplines. Patient education and self-management are fundamental to multidisciplinary care, as is a holistic approach to effectively address comorbid conditions. Ongoing challenges include navigating social disparities within heart failure care and limiting the economic burden of the disease.

How genomic and transcriptomic alterations affect the functional proteome in lung cancer is not fully understood. Here, we integrate DNA copy number, somatic mutations, RNA-sequencing, and expression proteomics in a cohort of 108 squamous cell lung cancer (SCC) patients. We identify three proteomic subtypes, two of which (Inflamed, Redox) comprise 87% of tumors. The Inflamed subtype is enriched with neutrophils, B-cells, and monocytes and expresses more PD-1 . Redox tumours are enriched for oxidation-reduction and glutathione pathways and harbor more NFE2L2/KEAP1 alterations and copy gain in the 3q2 locus. Proteomic subtypes are not associated with patient survival. However, B-cell-rich tertiary lymph node structures, more common in Inflamed, are associated with better survival. We identify metabolic vulnerabilities ( TP63 , PSAT1 , and TFRC ) in Redox. Our work provides a powerful resource for lung SCC biology and suggests therapeutic opportunities based on redox metabolism and immune cell infiltrates. Squamous cell lung cancer has dismal prognosis due to the dearth of effective treatments. Here, the authors perform an integrated proteogenomic analysis of the disease, revealing three proteomics-based subtypes and suggesting potential therapeutic opportunities.

We analyzed the association between social vulnerability index (SVI) and healthcare access among patients with atherosclerotic cardiovascular disease (ASCVD). Using cross-sectional data from the Behavioral Risk Factor Surveillance System 2016 to 2019, we identified measures related to healthcare access in individuals with ASCVD, which included healthcare coverage, presence of primary care clinician, duration since last routine checkup, delay in access to healthcare, inability to see doctor because of cost, and cost-related medication nonadherence. We analyzed the association of state-level SVI (higher SVI denotes higher social vulnerability) and healthcare access using multivariable-adjusted logistic regression models. The study population comprised 203,347 individuals aged 18 years or older who reported a history of ASCVD. In a multivariable-adjusted analysis, prevalence odds ratios (95% confidence interval) for participants residing in states in the third tertile of SVI compared with those in the first tertile (used as reference) were as follows: absence of healthcare coverage = 1.03 (0.85 to 1.24), absence of primary care clinician = 1.33 (1.12 to 1.58), >1 year since last routine checkup = 1.09 (0.96 to 1.23), delay in access to healthcare = 1.39 (1.18, 1.63), inability to see a doctor because of cost = 1.21 (1.06 to 1.40), and cost-related medication nonadherence = 1.10 (0.83 to 1.47). In conclusion, SVI is associated with healthcare access in those with pre-existing ASCVD. Due to the ability of SVI to simultaneously and holistically capture many of the factors of social determinants of health, SVI can be a useful measure for identifying high-risk populations.

Genome-wide association studies (GWAS) have identified hundreds of genetic signals associated with autoimmune disease. The majority of these signals are located in non-coding regions and likely impact cis -regulatory elements (cRE). Because cRE function is dynamic across cell types and states, profiling the epigenetic status of cRE across physiological processes is necessary to characterize the molecular mechanisms by which autoimmune variants contribute to disease risk. We localized risk variants from 15 autoimmune GWAS to cRE active during TCR-CD28 co-stimulation of naïve human CD4+ T cells. To characterize how dynamic changes in gene expression correlate with cRE activity, we measured transcript levels, chromatin accessibility, and promoter–cRE contacts across three phases of naive CD4+ T cell activation using RNA-seq, ATAC-seq, and HiC. We identified ~1200 protein-coding genes physically connected to accessible disease-associated variants at 423 GWAS signals, at least one-third of which are dynamically regulated by activation. From these maps, we functionally validated a novel stretch of evolutionarily conserved intergenic enhancers whose activity is required for activation-induced IL2 gene expression in human and mouse, and is influenced by autoimmune-associated genetic variation. The set of genes implicated by this approach are enriched for genes controlling CD4+ T cell function and genes involved in human inborn errors of immunity, and we pharmacologically validated eight implicated genes as novel regulators of T cell activation. These studies directly show how autoimmune variants and the genes they regulate influence processes involved in CD4+ T cell proliferation and activation.