| 1. |
- Karlsson, Anna K, et al.
(författare)
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Mutational and gene fusion analyses of primary large cell and large cell neuroendocrine lung cancer.
- 2015
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Ingår i: Oncotarget. - 1949-2553. ; 6:26, s. 22028-22037
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Tidskriftsartikel (refereegranskat)abstract
- Large cell carcinoma with or without neuroendocrine features (LCNEC and LC, respectively) constitutes 3-9% of non-small cell lung cancer but is poorly characterized at the molecular level. Herein we analyzed 41 LC and 32 LCNEC (including 15 previously reported cases) tumors using massive parallel sequencing for mutations in 26 cancer-related genes and gene fusions in ALK, RET, and ROS1. LC patients were additionally subdivided into three immunohistochemistry groups based on positive expression of TTF-1/Napsin A (adenocarcinoma-like, n = 24; 59%), CK5/P40 (squamous-like, n = 5; 12%), or no marker expression (marker-negative, n = 12; 29%). Most common alterations were TP53 (83%), KRAS (22%), MET (12%) mutations in LCs, and TP53 (88%), STK11 (16%), and PTEN (13%) mutations in LCNECs. In general, LCs showed more oncogene mutations compared to LCNECs. Immunomarker stratification of LC revealed oncogene mutations in 63% of adenocarcinoma-like cases, but only in 17% of marker-negative cases. Moreover, marker-negative LCs were associated with inferior overall survival compared with adenocarcinoma-like tumors (p = 0.007). No ALK, RET or ROS1 fusions were detected in LCs or LCNECs. Together, our molecular analyses support that LC and LCNEC tumors follow different tumorigenic paths and that LC may be stratified into molecular subgroups with potential implications for diagnosis, prognostics, and therapy decisions.
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| 2. |
- Isaksson, Sofi, et al.
(författare)
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CA 19-9 and CA 125 as potential predictors of disease recurrence in resectable lung adenocarcinoma
- 2017
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Ingår i: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 12:10
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Tidskriftsartikel (refereegranskat)abstract
- Objectives Among patients who underwent primary surgery for non-small cell lung cancer (NSCLC), recurrent disease is frequent and cannot be accurately predicted solely from TNM stage and histopathological features. The aim of this study was to examine the association of tumor markers in pre-operative serum with recurrent disease. Material and methods Blood samples were collected prior to lung cancer surgery from 107 patients with stage I-III lung adenocarcinoma surgically treated at Lund University hospital, Lund, Sweden, between 2005 and 2011. The serum tumor markers Carcinoembryonic antigen (CEA), Neuron-specific enolase (NSE), Cancer antigen 125 (CA 125), Human epididymis protein 4 (HE4) and Carbohydrate antigen (CA 19-9) were analyzed retrospectively and clinical follow-up data were collected from patient charts. Forty (37%) patients were diagnosed with recurrent disease. Results Sixty-eight (64%) patients had at least one elevated tumor marker prior to surgery. In analysis of disease-free survival (DFS), CA 125 and/or CA 19-9 were significantly associated with recurrent disease adjusted to stage and adjuvant treatment (hazard ratio 2.8, 95% confidence interval 1.4-5.7, p = 0.006). Conclusion High pre-operative serum CA 19-9 and/or CA 125 might indicate an increased incidence of recurrent disease in resectable lung adenocarcinomas.
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| 3. |
- Isaksson, Sofi, et al.
(författare)
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Pre-operative plasma cell-free circulating tumor DNA and serum protein tumor markers as predictors of lung adenocarcinoma recurrence
- 2019
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Ingår i: Acta Oncologica. - 0284-186X. ; 58:8, s. 1079-1086
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Tidskriftsartikel (refereegranskat)abstract
- Background: Lung cancer patients have a risk of recurrence even after curatively intended surgery. Cell-free circulating tumor DNA (ctDNA) and circulating tumor marker measurements are easily accessible through peripheral blood and could potentially identify patients with worse prognosis. The aim of this study was to examine ctDNA in pre-operative plasma and the role of tumor markers in pre-operative serum for their predictive potential on risk of tumor recurrence. Methods: Mutation analysis by 26-gene targeted sequencing was performed on 157 lung adenocarcinomas (ACs) from patients surgically treated at the Lund University Hospital 2005–2014. Of these, 58 tumors from patients in stages I–IIIA (34 stage I, 14 stage II and 10 stage III) with mutation(s) in EGFR, BRAF or KRAS were included. ctDNA from corresponding plasma (median 1.5 ml, range 1–1.6) was analyzed for one tumor-specific mutation in either of these three oncogenes using ultrasensitive IBSAFE droplet digital PCR (ddPCR). The tumor markers cancer antigen 125 (CA 125) and carbohydrate antigen 19-9 (CA 19-9) were analyzed in corresponding serum with electrochemiluminiscence immunoassay. Results: 6/7 patients with ctDNA and 19/51 without detected ctDNA were diagnosed with recurrence (log-rank test p =.001). 8/10 patients with positive serum tumor markers and 17/47 without tumor markers were diagnosed with recurrence (log-rank test, p =.0002). Fifteen patients had positive ctDNA and/or tumor markers, 12 of these had recurrence (log-rank test, p <.0001). Conclusion: A combination of tumor markers and ctDNA single mutation detection in low-volume pre-operative blood samples is a promising prognostic test. Prediction of recurrent disease in surgically treated early stage lung cancer can likely be further improved by using larger volumes of blood.
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| 4. |
- Lindquist, Kajsa Ericson, et al.
(författare)
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Clinical framework for next generation sequencing based analysis of treatment predictive mutations and multiplexed gene fusion detection in non-small cell lung cancer
- 2017
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Ingår i: Oncotarget. - : Impact Journals, LLC. - 1949-2553. ; 8:21, s. 34796-34810
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Tidskriftsartikel (refereegranskat)abstract
- Precision medicine requires accurate multi-gene clinical diagnostics. We describe the implementation of an Illumina TruSight Tumor (TST) clinical NGS diagnostic framework and parallel validation of a NanoString RNA-based ALK, RET, and ROS1 gene fusion assay for combined analysis of treatment predictive alterations in non-small cell lung cancer (NSCLC) in a regional healthcare region of Sweden (Scandinavia). The TST panel was clinically validated in 81 tumors (99% hotspot mutation concordance), after which 533 consecutive NSCLCs were collected during one-year of routine clinical analysis in the healthcare region (~90% advanced stage patients). The NanoString assay was evaluated in 169 of 533 cases. In the 533-sample cohort 79% had 1-2 variants, 12% >2 variants and 9% no detected variants. Ten gene fusions (five ALK, three RET, two ROS1) were detected in 135 successfully analyzed cases (80% analysis success rate). No ALK or ROS1 FISH fusion positive case was missed by the NanoString assay. Stratification of the 533-sample cohort based on actionable alterations in 11 oncogenes revealed that 66% of adenocarcinomas, 13% of squamous carcinoma (SqCC) and 56% of NSCLC not otherwise specified harbored ≥1 alteration. In adenocarcinoma, 10.6% of patients (50.3% if including KRAS) could potentially be eligible for emerging therapeutics, in addition to the 15.3% of patients eligible for standard EGFR or ALK inhibitors. For squamous carcinoma corresponding proportions were 4.4% (11.1% with KRAS) vs 2.2%. In conclusion, multiplexed NGS and gene fusion analyses are feasible in NSCLC for clinical diagnostics, identifying notable proportions of patients potentially eligible for emerging molecular therapeutics.
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| 5. |
- Walkowska, Joanna, et al.
(författare)
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Immunoprofiles of colorectal cancer from Lynch syndrome
- 2019
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Ingår i: OncoImmunology. - 2162-4011. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Colorectal cancers associated with Lynch syndrome are characterized by defective mismatch repair, microsatellite instability, high mutation rates, and a highly immunogenic environment. These features define a subset of cancer with a favorable prognosis and high likelihood to respond to treatment with anti-programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) drugs. With the aim to define immune-evasive mechanisms and a potential impact hereof in colorectal cancers from Lynch syndrome versus hereditary cases with retained mismatch repair function, we immunohistochemically and transcriptionally profiled 270 tumors. Lynch syndrome-associated tumors showed an overrepresentation of tumor-infiltrating CD3, CD8 and CD68 positive cells, loss of beta-2-microglobulin (B2M) and up-regulation of PD-L1 on tumor cells. The gene expression signature of Lynch syndrome tumors was characterized by upregulation of genes related to antigen processing and presentation, apoptosis, natural killer cell-mediated cytotoxicity, and T cell activation. Tumors with loss of B2M and up-regulation of PD-L1 showed distinctive immunogenic profiles. In summary, our data demonstrate a complex tumor-host interplay where B2M loss and PD-L1 up-regulation influence immunological pathways and clinical outcome in Lynch syndrome tumors. Immunological classification may thus aid in the preselection of colorectal cancers relevant for treatment with anti-PD-1/PD-L1 therapies.
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| 6. |
- Abrantes, João A., et al.
(författare)
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Bayesian Forecasting Utilizing Bleeding Information to Support Dose Individualization of Factor VIII
- 2019
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Ingår i: CPT. - : Wiley. - 2163-8306. ; 8:12, s. 894-903
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Tidskriftsartikel (refereegranskat)abstract
- Bayesian forecasting for dose individualization of prophylactic factor VIII replacement therapy using pharmacokinetic samples is challenged by large interindividual variability in the bleeding risk. A pharmacokinetic‐repeated time‐to‐event model‐based forecasting approach was developed to contrast the ability to predict the future occurrence of bleeds based on individual (i) pharmacokinetic, (ii) bleeding, and (iii) pharmacokinetic, bleeding and covariate information using observed data from the Long‐Term Efficacy Open‐Label Program in Severe Hemophilia A Disease (LEOPOLD) clinical trials (172 severe hemophilia A patients taking prophylactic treatment). The predictive performance assessed by the area under receiver operating characteristic (ROC) curves was 0.67 (95% confidence interval (CI), 0.65–0.69), 0.78 (95% CI, 0.76–0.80), and 0.79 (95% CI, 0.77–0.81) for patients ≥ 12 years when using pharmacokinetics, bleeds, and all data, respectively, suggesting that individual bleed information adds value to the optimization of prophylactic dosing regimens in severe hemophilia A. Further steps to optimize the proposed tool for factor VIII dose adaptation in the clinic are required.
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| 7. |
- Abrantes, João A., et al.
(författare)
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Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data
- 2019
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Ingår i: British Journal of Clinical Pharmacology. - : John Wiley & Sons. - 0306-5251 .- 1365-2125. ; 85:6, s. 1326-1336
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Tidskriftsartikel (refereegranskat)abstract
- AIMS: This study aims to assess approaches to handle interoccasion variability (IOV) in a model-based therapeutic drug monitoring (TDM) context, using a population pharmacokinetic model of coagulation factor VIII as example.METHODS: We assessed five model-based TDM approaches: empirical Bayes estimates (EBEs) from a model including IOV, with individualized doses calculated based on individual parameters either (i) including or (ii) excluding variability related to IOV; and EBEs from a model excluding IOV by (iii) setting IOV to zero, (iv) summing variances of interindividual variability (IIV) and IOV into a single IIV term, or (v) re-estimating the model without IOV. The impact of varying IOV magnitudes (0-50%) and number of occasions/observations was explored. The approaches were compared with conventional weight-based dosing. Predictive performance was assessed with the prediction error (PE) percentiles.RESULTS: When IOV was lower than IIV, the accuracy was good for all approaches (50th percentile of the PE [P50] <7.4%), but the precision varied substantially between IOV magnitudes (P97.5 61-528%). Approach (ii) was the most precise forecasting method across a wide range of scenarios, particularly in case of sparse sampling or high magnitudes of IOV. Weight-based dosing led to less precise predictions than the model-based TDM approaches in most scenarios.CONCLUSIONS: Based on the studied scenarios and theoretical expectations, the best approach to handle IOV in model-based dose individualisation is to include IOV in the generation of the EBEs, but exclude the portion of unexplained variability related to IOV in the individual parameters used to calculate the future dose.
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| 8. |
- Abrantes, João A.
(författare)
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Pharmacometric Approaches to Improve Dose Individualization Methods in Hemophilia A
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Hemophilia A is a bleeding disorder caused by the lack of functional coagulation factor VIII (FVIII). The overall aim of this thesis was to improve dose individualization of FVIII replacement therapy in hemophilia A using pharmacometric approaches.A population pharmacokinetic (PK) model of FVIII activity following the administration of moroctocog alfa was developed based on data from a large heterogeneous cohort of moderate to severe hemophilia A patients. Body weight, age, neutralizing anti-FVIII inhibitors, race, and analytical assay were found to be significant predictors of FVIII activity PK. In addition, large inter-individual variability (IIV) and inter-occasion variability (IOV) was identified highlighting the need for dose individualization.High magnitudes of IOV are known to impair model-based therapeutic drug monitoring. Using a population PK model of FVIII activity, several approaches to handle IOV in Bayesian forecasting of individual PK parameters were assessed across a wide range of features. Considering IOV in Bayesian forecasting, but ignoring IOV in dose calculation, led to the most precise individualized doses, in particular, when sparse data was used.The dose-exposure-response relationship of FVIII replacement therapy remains unclear. A parametric repeated time-to-categorical event (RTTCE) model was developed to characterize the relationship between the dose of octocog alfa, plasma FVIII activity, bleeding frequency and severity, and covariates, using data from clinical trials. The bleeding hazard was found to decrease throughout time and to be affected by plasma FVIII activity and number of previous bleeds. Unexplained IIV in the bleeding hazard was found to be large.Bayesian forecasting based on the RTTCE model was used to predict the future occurrence of bleeds, and to contrast the predicted outcome using individual i) PK, ii) bleeding, and iii) PK, bleeding and covariate information, from data collected in clinical trials. The results support that individual bleed information can inform the optimization of prophylactic dosing regimens in severe hemophilia A patients.In summary, the pharmacometric approaches presented provide a valuable quantitative framework to improve dose individualization in hemophilia A. Furthermore, enhanced dosing has the potential to reduce bleeding frequency and to lower the high costs associated to treatment.
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| 9. |
- Acharya, Chayan, et al.
(författare)
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A diagnostic tool for population models using non-compartmental analysis : The ncappc package for R
- 2016
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 127, s. 83-93
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: Non-compartmental analysis (NCA) calculates pharmacokinetic (PK) metrics related to the systemic exposure to a drug following administration, e.g. area under the concentration time curve and peak concentration. We developed a new package in R, called ncappc, to perform (i) a NCA and (ii) simulation-based posterior predictive checks (ppc) for a population PK (PopPK) model using NCA metrics. Methods: The nca feature of ncappc package estimates the NCA metrics by NCA. The ppc feature of ncappc estimates the NCA metrics from multiple sets of simulated concentration time data and compares them with those estimated from the observed data. The diagnostic analysis is performed at the population as well as the individual level. The distribution of the simulated population means of each NCA metric is compared with the corresponding observed population mean. The individual level comparison is performed based on the deviation of the mean of any NCA metric based on simulations for an individual from the corresponding NCA metric obtained from the observed data. The ncappc package also reports the normalized prediction distribution error (NPDE) of the simulated NCA metrics for each individual and their distribution within a population. Results: The ncappc produces two default outputs depending on the type of analysis performed, i.e., NCA and PopPK diagnosis. The PopPK diagnosis feature of ncappc produces 8 sets of graphical outputs to assess the ability of a population model to simulate the concentration time profile of a drug and thereby evaluate model adequacy. In addition, tabular outputs are generated showing the values of the NCA metrics estimated from the observed and the simulated data, along with the deviation, NPDE, regression parameters used to estimate the elimination rate constant and the related population statistics. Conclusions: The ncappc package is a versatile and flexible tool-set written in R that successfully estimates NCA metrics from concentration time data and produces a comprehensive set of graphical and tabular output to summarize the diagnostic results including the model specific outliers. The output is easy to interpret and to use in evaluation of a population PK model. ncappc is freely available on CRAN (http://crantoprojectorg/web/packages/ncappc/index.html/) and GitHub (https://github.comicacha0227/ncappc/).
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| 10. |
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