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BackgroundPD-1/PD-L1 inhibitors have improved survival for patients with non-small cell lung cancer (NSCLC). We evaluated natural killer cell activity (NKA) and methylated HOXA9 circulating tumor DNA (ctDNA) as prognostic biomarkers in NSCLC patients treated with PD-1/PD-L1 inhibitors.MethodsPlasma was prospectively collected from 71 NSCLC patients before treatment with PD-1/PD-L1 inhibitors and before cycles 2–4. We used the NK Vue® assay to measure the level of interferon gamma (IFNγ) as a surrogate for NKA. Methylated HOXA9 was measured by droplet digital PCR.ResultsA score combining NKA and ctDNA status measured after one treatment cycle had a strong prognostic impact. Group 1 had IFNγ < 250 pg/ml and detectable ctDNA (n = 27), group 2 consisted of patients with either low levels of IFNγ and undetectable ctDNA or high levels of IFNγ and detectable ctDNA (n = 29), group 3 had IFNγ ≥250 pg/ml and undetectable ctDNA (n = 15). Median OS was 221 days (95% CI 121–539 days), 419 days (95% CI 235–650 days), and 1158 days (95% CI 250 days—not reached), respectively (P = 0.002). Group 1 had a poor prognosis with a hazard ratio of 5.560 (95% CI 2.359–13.101, n = 71, P < 0.001) adjusting for PD-L1 status, histology, and performance status.ConclusionsCombining NKA and ctDNA status after one cycle of treatment was prognostic in patients with NSCLC treated with PD-1/PD-L1 inhibitors.

Many studies have focused on the prognostic role of soluble programmed death ligand 1 (sPD-L1) in non-small cell lung cancer (NSCLC), but outcomes are ambiguous and further investigations are needed. We addressed the matter by studying sPD-L1 in baseline samples and in longitudinal samples taken prior to three subsequent cycles of anti-PD-1/anti-PD-L1 treatments. Eighty patients with NSCLC were enrolled. Median sPD-L1 level at baseline was 52 pg/mL [95% confidence interval (CI) 49–57]. In patients treated with pembrolizumab and nivolumab, the concentration of sPD-L1 remained rather stable throughout treatment. In contrast, sPD-L1 rose by 50-fold following the first cycle of atezolizumab therapy. We found the baseline level of sPD-L1 to be related to overall survival (OS) after two years of follow-up in simple Cox analysis (p = 0.006) and multiple Cox Regression, hazard ratio 1.02 (95% CI 1.00–1.03) (p = 0.033). There was no association between sPD-L1 and tissue PD-L1 expression, overall response rate, or progression free survival. In conclusion, sPD-L1 measured in baseline serum samples may be associated with OS in NSCLC patients receiving anti-PD1/anti-PD-L1 treatment. Importantly, the results signify that further research is warranted to explore the clinical utility of sPD-L1 in patients treated with anti-PD-L1.

Background Patients with colorectal metastatic disease have a poor prognosis, limited therapeutic options, and frequent development of resistance. Strategies based on tumor-derived organoids are a powerful tool to assess drug sensitivity at an individual level and to suggest new treatment options or re-challenge. Here, we evaluated the method’s feasibility and clinical outcome as applied to patients with no satisfactory treatment options. Methods In this phase 2, single-center, open-label, non-comparative study (ClinicalTrials.gov, register NCT03251612), we enrolled 90 patients with metastatic colorectal cancer following progression on or after standard therapy. Participants were 18 years or older with an Eastern Cooperative Oncology Group performance status of 0–2, adequate organ function, and metastasis available for biopsy. Biopsies from the metastatic site were cultured using organoids model. Sensitivity testing was performed with a panel of drugs with proven activity in phase II or III trials. At the discretion of the investigator considering toxicity, the drug with the highest relative activity was offered. The primary endpoint was the proportion of patients alive without disease progression at two months per local assessment. Results Biopsies available from 82 to 90 patients were processed for cell culture, of which 44 successfully generated organoids with at least one treatment suggested. The precision cohort of 34 patients started treatment and the primary endpoint, progression-free survival (PFS) at two months was met in 17 patients (50%, 95% CI 32–68), exceeding the pre-defined level (14 of 45; 31%). The median PFS was 67 days (95% CI 51–108), and the median overall survival was 189 days (95% CI 103–277). Conclusions Patient-derived organoids and in-vitro sensitivity testing were feasible in a cohort of metastatic colorectal cancer. The primary endpoint was met, as half of the patients were without progression at two months. Cancer patients may benefit from functional testing using tumor-derived organoids. Trial registration ClinicalTrials.gov, register NCT03251612. Highlights Metastatic colorectal cancer patients ( N  = 90) were enrolled in a phase 2 study. Drug assays were successfully tested in tumor derived organoids of metastatic colorectal cancer patients. Sensitivity drug tests performed in tumor derived organoids pointed out specific treatment for individual patients. A total of 34 patients initiated the treatment according to the drug assay results. Progression-free survival at two months was met in 17 of 34 patients exceeding the pre-defined minimal relevant difference to historical controls from randomized trials.

The treatment of locally advanced rectal cancer (LARC) has evolved during the last decades, but recurrence remains a problem. Circulating tumor DNA (ctDNA) may result in an individualized treatment approach with improved survival and quality of life, but diverging results impede further development. In this systematic review, we addressed the quality of reporting and its impact on the interpretation of ctDNA results. We performed a systematic literature search using subject headings and search terms related to ctDNA and rectal cancer. The Quality of Prognostic Studies (QUIPS) tool was used to assess bias. Nine studies, with substantial heterogeneity, were included in the analysis. Three out of nine articles had moderate or high risk of bias. No association was found between treatment response and ctDNA status at baseline. There was a negative association between ctDNA positivity at baseline, before and after surgery and survival. The ctDNA status may be of importance to the long-term prognosis, but the area of research is new and is short of dedicated studies. There is an obvious need for standardization in ctDNA research, and the issue should be addressed in future research.

IntroductionPatient engagement is continuously being promoted by patients as well as politicians and healthcare professionals. One way of increasing patient engagement is by using shared decision-making (SDM), which is a joint effort of clinicians and patients making decisions together.When planning stereotactic body radiation therapy (SBRT) for a lung tumour located close to the thoracic wall, there are conflicting interests between (1) delivering the highest possible dose to obtain local tumour control and (2) reducing the dose to the thoracic wall to decrease the risk of chest wall pain and rib fractures following treatment. The radiation oncologist often makes the choice of dose without any engagement of the patient. We believe that the patients should be engaged in such a decision.To explore this matter, we have designed a randomised trial, ‘SDM Lung SBRT’, for which we present our study protocol with a special focus on a patient decision aid (PtDA), which is being tested in this trial.Methods and analysisThis study includes patients with a lung tumour located ≤1 cm from the thoracic wall. Patients are randomised to have the primary consultation with or without use of the PtDA. Treatment options are a radiation dose of either 66 Gray (Gy) in three fractions, 45 Gy in three fractions or no treatment. The primary outcome is patient engagement in decision-making measured by the validated observer-rated OPTION-12 score. Secondary outcomes are patient-reported outcomes, quality of life and side effects following treatment.Ethics and disseminationAll patients give informed consent to participate. According to Danish legislation, ethical approval is not required for this study as studies using questionnaires, observations or other non-biological studies are not considered interventions according to the Committee Act. Results from this study will be presented at scientific meetings and published in English peer-reviewed journals.Trial registration numberClinicalTrials.gov (NCT04940936).

The indigenous people of Greenland, the Inuit, have lived for a long time in the extreme conditions of the Arctic, including low annual temperatures, and with a specialized diet rich in protein and fatty acids, particularly omega-3 polyunsaturated fatty acids (PUFAs). A scan of Inuit genomes for signatures of adaptation revealed signals at several loci, with the strongest signal located in a cluster of fatty acid desaturases that determine PUFA levels. The selected alleles are associated with multiple metabolic and anthropometric phenotypes and have large effect sizes for weight and height, with the effect on height replicated in Europeans. By analyzing membrane lipids, we found that the selected alleles modulate fatty acid composition, which may affect the regulation of growth hormones. Thus, the Inuit have genetic and physiological adaptations to a diet rich in PUFAs.

Background Pain catastrophizing contributes to acute and long-term pain after knee arthroplasty (KA), but the association between pain catastrophizing and physical function is not clear. We examined the association between preoperative pain catastrophizing and physical function one year after surgery, as well as differences in physical function, pain and general health in two groups of patients with high and low preoperative pain catastrophizing score. Methods We included 615 patients scheduled for KA between March 2011 and December 2013. Patients completed The Pain Catastrophizing Scale (PCS) prior to surgery. The Oxford Knee Score (OKS), Short Form-36 (SF-36) and the EuroQol-5D (EQ-5D) were completed prior to surgery, and 4 and 12 months after the surgery. Results Of the 615 patients, 442 underwent total knee arthroplasty (TKA) and 173 unicompartmental knee arthroplasty (UKA). Mean age was 67.3 (SD: 9.7) and 53.2% were females. Patients with PCS > 21 had statistically significantly larger improvement in mean OKS for both TKA and UKA than patients with PCS < 11; 3.2 (95% CI: 1.0, 5.4) and 5.4 (95% CI: 2.2, 8.6), respectively. Furthermore, patients with preoperative PCS > 21 had statistically significantly lower OKS, SF-36 and EQ-5D and higher pain score than patients with PCS < 11 both preoperatively and 4 and 12 months postoperatively. Conclusions Patients with high levels of preoperative pain catastrophizing have lower physical function, more pain and poorer general health both before and after KA than patients without elevated pain catastrophizing.

Since the late 1990s, therapy for metastatic colorectal cancer (mCRC) has changed considerably, and the combination of doublet or triplet chemotherapy and a targeted agent are now routinely used. The targeting of angiogenesis, the development of new blood vessels, represents a key element in the overall treatment strategy. Since the approval in 2004 of the first anti-angiogenetic drug, multiple agents have been approved and others are currently under investigation. We present an overview of the recent literature on approved systemic treatment of mCRC, with a focus on anti-angiogenic drugs, and current treatment approaches, and elaborate on the future role of angiogenesis in colorectal cancer as seen from a clinical perspective. The treatment of mCRC, in general, has changed from “one strategy fits all” to a more personalized approach. This is, however, not entirely the case for anti-angiogenetic treatments, partly due to a lack of validated biomarkers. The anti-angiogenetic standard treatment at the present primarily includes monoclonal antibodies. The therapeutic field of angiogenesis, however, has received increased interest after the introduction of newer combinations. These approaches will likely change the current treatment strategy, once again, to the overall benefit of patients.

MicroRNAs (miRNAs) play a critical role in many biological processes and are aberrantly expressed in human cancers. Particular miRNAs function either as tumor suppressors or oncogenes and appear to have diagnostic and prognostic significance. Although numerous miRNAs are dys-regulated in colorectal cancer (CRC) only a small fraction has been characterized functionally. Using high-throughput functional screening and miRNA profiling of clinical samples the present study aims at identifying miRNAs important for the control of cellular growth and/or apoptosis in CRC. The high-throughput functional screening was carried out in six CRC cell lines transfected with a pre-miR library including 319 synthetic human pre-miRs. Phenotypic alterations were evaluated by immunostaining of cleaved cPARP (apoptosis) or MKI67 (proliferation). Additionally, TaqMan Human MicroRNA Array Set v2.0 was used to profile the expression of 667 miRNAs in 14 normal colon mucosa and 46 microsatellite stable stage II CRC patients. Among the miRNAs that induced growth arrest and apoptosis in the CRC cell lines, and at same time were dys-regulated in the clinical samples, miR-375 was selected for further analysis. Independent in vitro analysis of transient and stable transfected CRC cell lines confirmed that miR-375 reduces cell viability through the induction of apoptotic death. We identified YAP1 as a direct miR-375 target in CRC and show that HELLS and NOLC1 are down-stream targets. Knock-down of YAP1 mimicked the phenotype induced by miR-375 over-expression indicating that miR-375 most likely exerts its pro-apoptotic role through YAP1 and its anti-apoptotic down-stream targets BIRC5 and BCL2L1. Finally, in vivo analysis of mouse xenograft tumors showed that miR-375 expression significantly reduced tumor growth. We conclude that the high-throughput screening successfully identified miRNAs that induce apoptosis and/or inhibit proliferation in CRC cells. Finally, combining the functional screening with profiling of CRC tissue samples we identified clinically relevant miRNAs and miRNA targets in CRC.

Background Smoking is a critical risk factor responsible for over eight million annual deaths worldwide. It is essential to obtain information on smoking habits to advance research and implement preventive measures such as screening of high-risk individuals. In most countries, including Denmark, smoking habits are not systematically recorded and at best documented within unstructured free-text segments of electronic health records (EHRs). This would require researchers and clinicians to manually navigate through extensive amounts of unstructured data, which is one of the main reasons that smoking habits are rarely integrated into larger studies. Our aim is to develop machine learning models to classify patients’ smoking status from their EHRs. Methods This study proposes an efficient natural language processing (NLP) pipeline capable of classifying patients’ smoking status and providing explanations for the decisions. The proposed NLP pipeline comprises four distinct components, which are; (1) considering preprocessing techniques to address abbreviations, punctuation, and other textual irregularities, (2) four cutting-edge feature extraction techniques, i.e. Embedding, BERT, Word2Vec, and Count Vectorizer, employed to extract the optimal features, (3) utilization of a Stacking-based Ensemble (SE) model and a Convolutional Long Short-Term Memory Neural Network (CNN-LSTM) for the identification of smoking status, and (4) application of a local interpretable model-agnostic explanation to explain the decisions rendered by the detection models. The EHRs of 23,132 patients with suspected lung cancer were collected from the Region of Southern Denmark during the period 1/1/2009-31/12/2018. A medical professional annotated the data into ‘Smoker’ and ‘Non-Smoker’ with further classifications as ‘Active-Smoker’, ‘Former-Smoker’, and ‘Never-Smoker’. Subsequently, the annotated dataset was used for the development of binary and multiclass classification models. An extensive comparison was conducted of the detection performance across various model architectures. Results The results of experimental validation confirm the consistency among the models. However, for binary classification, BERT method with CNN-LSTM architecture outperformed other models by achieving precision, recall, and F1-scores between 97% and 99% for both Never-Smokers and Active-Smokers. In multiclass classification, the Embedding technique with CNN-LSTM architecture yielded the most favorable results in class-specific evaluations, with equal performance measures of 97% for Never-Smoker and measures in the range of 86 to 89% for Active-Smoker and 91–92% for Never-Smoker. Conclusion Our proposed NLP pipeline achieved a high level of classification performance. In addition, we presented the explanation of the decision made by the best performing detection model. Future work will expand the model’s capabilities to analyze longer notes and a broader range of categories to maximize its utility in further research and screening applications.