Treatment and outcomes of non-small-cell lung cancer patients with high comorbidity

ANKRD49 promotes the invasion and metastasis of lung adenocarcinoma via a P38/ATF-2 signalling pathway

Lung adenocarcinoma (LUAD) is the most challenging neoplasm to treat in clinical practice. Ankyrin repeat domain 49 protein (ANKRD49) is highly expressed in several carcinomas; however, its pattern of expression and role in LUAD are not known. Tissue microarrays, immunohistochemistry, χ² test, Spearman correlation analysis, Kaplan–Meier, log‐rank test, and Cox's proportional hazard model were used to analyse the clinical cases. The effect of ANKRD49 on the LUAD was investigated using CCK‐8, clonal formation, would healing, transwell assays, and nude mice experiment. Expressions of ANKRD49 and its associated downstream protein molecules were verified by real‐time PCR, Western blot, immunohistochemistry, and/or immunofluorescence analyses. ANKRD49 expression was highly elevated in LUAD. The survival rate and Cox's modelling analysis indicated that there may be an independent prognostic indicator for LUAD patients. We also found that ANKRD49 promoted the invasion and migration in both in in vitro and in vivo assays, through upregulating matrix metalloproteinase (MMP)‐2 and MMP‐9 activities via the P38/ATF‐2 signalling pathway Our findings suggest that ANKRD49 is a latent biomarker for evaluating LUAD prognosis and promotes the metastasis of A549 cells via upregulation of MMP‐2 and MMP‐9 in a P38/ATF‐2 pathway‐dependent manner.

Dosimetric Validation of a System to Treat Moving Tumors Using Scanned Ion Beams That Are Synchronized With Anatomical Motion

Purpose

The purpose of this study was to validate the dosimetric performance of scanned ion beam deliveries with motion-synchronization to heterogenous targets.

Methods

A 4D library of treatment plans, comprised of up to 10 3D sub-plans, was created with robust and conventional 4D optimization methods. Each sub-plan corresponded to one phase of periodic target motion. The plan libraries were delivered to a test phantom, comprising plastic slabs, dosimeters, and heterogenous phantoms. This phantom emulated range changes that occur when treating moving tumors. Similar treatment plans, but without motion synchronization, were also delivered to a test phantom with a stationary target and to a moving target; these were used to assess how the target motion degrades the quality of dose distributions and the extent to which motion synchronization can improve dosimetric quality. The accuracy of calculated dose distributions was verified by comparison with corresponding measurements. Comparisons utilized the gamma index analysis method. Plan quality was assessed based on conformity, dose coverage, overdose, and homogeneity values, each extracted from calculated dose distributions.

Results

High pass rates for the gamma index analysis confirmed that the methods used to calculate and reconstruct dose distributions were sufficiently accurate for the purposes of this study. Calculated and reconstructed dose distributions revealed that the motion-synchronized and static deliveries exhibited similar quality in terms of dose coverage, overdose, and homogeneity for all deliveries considered. Motion-synchronization substantially improved conformity in deliveries with moving targets. Importantly, measurements at multiple locations within the target also confirmed that the motion-synchronized delivery system satisfactorily compensated for changes in beam range caused by the phantom motion. Specifically, the overall planning and delivery approach achieved the desired dose distribution by avoiding range undershoots and overshoots caused by tumor motion.

Conclusions

We validated a dose delivery system that synchronizes the movement of the ion beam to that of a moving target in a test phantom. Measured and calculated dose distributions revealed that this system satisfactorily compensated for target motion in the presence of beam range changes due to target motion. The implication of this finding is that the prototype system is suitable for additional preclinical research studies, such as irregular anatomic motion.

Immunotherapy Utilization Among Patients With Metastatic NSCLC: Impact of Comorbidities

In patients with metastatic non-small cell lung cancer (mNSCLC), the extent to which immunotherapy utilization rate varies by comorbidities is unclear. Using the National Cancer Database from 2015 to 2016, we assessed the association between levels of comorbidity and immunotherapy utilization among mNSCLC patients. Burden of comorbidities was ascertained based on the modified Charlson-Deyo score and categorized as an ordinal variable (0, 1, and ≥2). Immunotherapy utilization was determined based on registry data. Multivariable logistic regressions were used to estimate adjusted odds ratios (aOR) and 95% confidence intervals (CI) for the comorbidity score while adjusting for sociodemographic factors, histopathologic subtype, surgery, chemotherapy, radiotherapy, insurance, facility type, and other cancer history. Subgroup analyses were conducted by age and race/ethnicity. Overall, of the 89,030 patients with mNSCLC, 38.6% (N=34,382) had the comorbidity score of ≥1. Most patients were non-Hispanic white (82.3%, N=73,309) and aged 65 years and above (63.2%, N=56,300), with the mean age of 68.4 years (SD=10.6). Only 7.0% (N=6220) of patients received immunotherapy during 2015-2106. Patients with a comorbidity score of ≥2 had a significantly lower rate of immunotherapy utilization versus those without comorbidities (aOR=0.85; 95% CI, 0.78-0.93; P-trend<0.01). In subgroup analysis by age, association patterns were similar among patients younger than 65 and those aged 65-74 years. There were no significant differences in subgroup analysis by race/ethnicity, although statistical significance was only observed for white patients (comorbidity score ≥2 vs. 0: aOR=0.85; 95% CI, 0.77-0.93; P-trend<0.01). In conclusion, mNSCLC patients with a high burden of comorbidities are less likely to receive immunotherapy.

Risk Factors for Short-Term Lung Cancer Survival

Background: Lung cancer is typically diagnosed in an advanced phase of its natural history. Explanatory models based on epidemiological and clinical variables provide an approximation of patient survival less than one year using information extracted from the case history only, whereas models involving therapeutic variables must confirm that any treatment applied is worse than surgery in survival terms. Models for classifying less than one year survival for patients diagnosed with lung cancer which are able to identify risk factors and quantify their effect for prognosis are analyzed. Method: Two stepwise binary logistic regression models, based on a retrospective study of 521 cases of patients diagnosed with lung cancer in the Interventional Pneumology Unit at the Hospital “Virgen de las Nieves”, Granada, Spain. Results: The first model included variables age, history of pulmonary neoplasm, tumor location, dyspnea, dysphonia, and chest pain. The independent risk factors age greater than 70 years, a peripheral location, dyspnea and dysphonia were significant. For the second model, treatments were also significant. Conclusions: Age, history of pulmonary neoplasm, tumor location, dyspnea, dysphonia, and chest pain are predictors for survival in patients diagnosed with lung cancer at the time of diagnosis. The treatment applied is significant for classifying less than one year survival time which confirms that any treatment is markedly inferior to surgery in terms of survival. This allows to consider applications of more or less aggressive treatments, anticipation of palliative cares or comfort measures, inclusion in clinical trials, etc.

miR‑654‑3p suppresses cell viability and promotes apoptosis by targeting RASAL2 in non‑small‑cell lung cancer

Non-small-cell lung cancer (NSCLC) accounts for 80% of lung cancer cases, and is the leading cause of cancer-associated mortality worldwide. The present study aimed to investigate the roles of microRNA (miR)-654-3p in NSCLC. The expression levels of miR-654-3p and its target ras protein activator like 2 (RASAL2) mRNA were determined by reverse transcription-quantitative polymerase chain reaction; protein expression was analyzed by western blotting. Plasmids expressing miR-654-3p mimics were constructed and transfected into A549 cells. In addition, the viability and apoptotic rate of cells were analyzed by an MTT assay and flow cytometry, respectively. A luciferase reporter assay was performed to verify whether RASAL2 is a target of miR-654-3p. Downregulated miR-654-3p and upregulated RASAL2 expression were observed in tumor tissues and cells. Cell viability was suppressed and the apoptotic rate was increased in the miR-654-3p mimics-transfected cells compared with the control. Luciferase activity was decreased in the RASAL2-3′ untranslated region-wild type group treated with miR-654-3p mimics. Furthermore, the present study revealed that overexpression of miR-654-3p could suppress the viability and induce the apoptosis of cells by targeting RASAL2 in NSCLC. The present findings may contribute to developments in the treatment of NSCLC.

The impact of symptoms and comorbidity on health utility scores and health-related quality of life in small cell lung cancer using real world data

PURPOSE

Small cell lung cancer (SCLC) is a highly fatal disease associated with significant morbidity, with a need for real-world symptom and health utility score (HUS) data. HUS can be measured using an EQ-5D-5L questionnaire, however most captured data is available in non-SCLC (NSCLC) only. As new treatment regimens become available in SCLC it becomes important to understand factors which influence health-related quality of life and health utility.

METHODS

A prospective observational cohort study (2012-2017) of ambulatory histologically confirmed SCLC evaluated patient-reported EQ-5D-5L-derived HUS, toxicity and symptoms. A set of NSCLC patients was used to compare differential factors affecting HUS. Clinical and demographic factors were evaluated for differential interactions between lung cancer types. Comorbidity scores were documented for each patient.

RESULTS

In 75 SCLC and 150 NSCLC patients, those with SCLC had lower mean HUS ((SCLC vs NSCLC: mean 0.69 vs 0.79); (p < 0.001)) when clinically stable and with progressive disease: ((SCLC mean HUS = 0.60 vs NSCLC mean HUS = 0.77), (p = 0.04)). SCLC patients also had higher comorbidity scores ((1.11 vs 0.73); (p < 0.015)). In multivariable analyses, increased symptom severity and comorbidity scores decreased HUS in both SCLC and NSCLC (p < 0.001); however, only comorbidity scores differentially affected HUS (p < 0.0001), with a greater reduction of HUS adjusted per unit of comorbidity in SCLC.

CONCLUSION

Patients with advanced SCLC had significantly lower HUS than NSCLC. Both patient cohorts are impacted by symptoms and comorbidity, however, comorbidity had a greater negative effect in SCLC patients.

Comorbidity and early death in Danish stage I lung cancer patients - an individualised approach

Background: Comorbidity is an important prognostic marker and a treatment indicator for lung cancer patients. Register-based studies often describe the burden of comorbidity by the Charlson comorbidity index (CCI) based on hospital discharge data. We assessed the association between somatic and psychiatric comorbidity and death within one year in early lung cancer and, furthermore, the burden of comorbidity according to treatment type.Material and methods: We conducted a population-based matched case-control study of stage I lung cancer identifying all treated patients who died (all-cause) within one year after diagnosis (early death group, cases). On the basis of data from the Danish Lung Cancer Registry these patients were then matched with two controls who survived more than one year (survivors). Through a review of the medical records, we validated inclusion criteria and collected data on somatic and psychiatric comorbidity. We assessed the association between comorbidity and early death with multivariate conditional logistic regression.Results: We included 221 cases and 410 controls. The mean CCI score in the early death group was 2.3 vs. 1.3 in the survivor group (p < .001). Still, 22% vs. 30% had a CCI score of zero (p = .04) with an average number of comorbidities among these patients of 1.63 vs. 1.06 respectively (p = .006). Among women, 23% in the early death group had depression vs. 13% in the survivor group, corresponding to an unadjusted odds ratio (OR) of 2.0 (CI 95% 1.0-3.7). However, in an adjusted analysis (incl. somatic comorbidities) the OR was 1.7 (CI 95% 0.8-3.5). Patients undergoing oncological therapy were older and tended to have more somatic comorbidities than the surgically treated patients.Conclusion: Comorbidity remains a significant prognostic marker even for stage I lung cancer patients with a CCI score of zero. The suggested association between early death and depression among women needs to be studied further.

NSCLC patient "migration" for treatment: A retrospective analysis of patient characteristics, travel patterns, and survival differences

PURPOSE

Every year a significant population exists of those diagnosed with nonsmall cell lung cancer (NSCLC) who do not receive initial treatment upon diagnosis and then "migrate" to additional hospital before ultimately getting treatment. Migration to different hospitals may play a role in the decision to treat or not-to-treat, and we aimed to evaluate the potential factors that lead to treatment.

METHODS

A retrospective review of 6212 patients with NSCLC from 29 Kentucky hospital registries from 2012 to 2014 was performed. Variables collected included hospital accreditation status, age at diagnosis, stage, overall survival (OS), and insurance status. Hospital records were matched to Kentucky Cancer Registry records to determine the number of hospitals visited for treatment.

RESULTS

Most patients were treated at their initial hospital (73%). Of the remaining patients, 36% migrated to a different hospital where most received treatment (93%). Migrating to another hospital was associated with Stage I-III disease, younger age (66.4 vs 72.2 years), and longer OS (561 vs 157 days). Notably, migration was also associated with private insurance status and missing treatment modalities at the initial hospital. Treatment after migrating was associated with Stage I-II disease, younger age (65.8 vs 72.8 years), and longer OS (595 vs 153 days). After adjusting for confounders, treated migrating patients lived longer than initially treated patients (591 vs 505 days), especially among those with stage III (563 vs 495 days) and IV (379 vs 300 days) disease.

CONCLUSION

This analysis demonstrates a survival benefit for initially untreated patients with advanced disease who migrate to another hospital for treatment. Migration was associated with having private insurance, thus making it noteworthy of the relationship between NSCLC survival benefit and insurance status.

Down-regulation of microRNA-144-3p and its clinical value in non-small cell lung cancer: a comprehensive analysis based on microarray, miRNA-sequencing, and quantitative real-time PCR data

BACKGROUND

Previous studies have shown that miR-144-3p might be a potential biomarker in non-small cell lung cancer (NSCLC). Nevertheless, the comprehensive mechanism behind the effects of miR-144-3p on the origin, differentiation, and apoptosis of NSCLC, as well as the relationship between miR-144-3p and clinical parameters, has been rarely reported.

METHODS

We investigated the correlations between miR-144-3p expression and clinical characteristics through data collected from Gene Expression Omnibus (GEO) microarrays, the relevant literature, The Cancer Genome Atlas (TCGA), and real-time quantitative real-time PCR (RT-qPCR) analyses to determine the clinical role of miR-144-3p in NSCLC. Furthermore, we investigated the biological function of miR-144-3p by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Protein-protein interaction (PPI) network was created to identify the hub genes.

RESULTS

From the comprehensive meta-analysis, the combined SMD of miR-144-3p was - 0.95 with 95% CI of (- 1.37, - 0.52), indicating that less miR-144-3p was expressed in the NSCLC tissue than in the normal tissue. MiR-144-3p expression was significantly correlated with stage, lymph node metastasis and vascular invasion (all P <  0.05). As for the bioinformatics analyses, a total of 37 genes were chosen as the potential targets of miR-144-3p in NSCLC. These promising target genes were highly enriched in various key pathways such as the protein digestion and absorption and the thyroid hormone signaling pathways. Additionally, PPI revealed five genes-C12orf5, CEP55, E2F8, STIL, and TOP2A-as hub genes with the threshold value of 6.

CONCLUSIONS

The current study validated that miR-144-3p was lowly expressed in NSCLC. More importantly, miR-144-3p might function as a latent tumor biomarker in the prognosis prediction for NSCLC. The results of bioinformatics analyses may present a new method for investigating the pathogenesis of NSCLC.