| 1. |
- Björn, Niclas, et al.
(författare)
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Genes and variants in hematopoiesis-related pathways are associated with gemcitabine/carboplatin-induced thrombocytopenia
- 2020
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Ingår i: The Pharmacogenomics Journal. - : Nature Publishing Group. - 1470-269X .- 1473-1150. ; 20:2, s. 179-191
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Tidskriftsartikel (refereegranskat)abstract
- Chemotherapy-induced myelosuppression, including thrombocytopenia, is a recurrent problem during cancer treatments that may require dose alterations or cessations that could affect the antitumor effect of the treatment. To identify genetic markers associated with treatment-induced thrombocytopenia, we whole-exome sequenced 215 non-small cell lung cancer patients homogeneously treated with gemcitabine/carboplatin. The decrease in platelets (defined as nadir/baseline) was used to assess treatment-induced thrombocytopenia. Association between germline genetic variants and thrombocytopenia was analyzed at single-nucleotide variant (SNV) (based on the optimal false discovery rate, the severity of predicted consequence, and effect), gene, and pathway levels. These analyses identified 130 SNVs/INDELs and 25 genes associated with thrombocytopenia (P-value < 0.002). Twenty-three SNVs were validated in an independent genome-wide association study (GWAS). The top associations include rs34491125 in JMJD1C (P-value = 9.07 × 10−5), the validated variants rs10491684 in DOCK8 (P-value = 1.95 × 10−4), rs6118 in SERPINA5 (P-value = 5.83 × 10−4), and rs5877 in SERPINC1 (P-value = 1.07 × 10−3), and the genes CAPZA2 (P-value = 4.03 × 10−4) and SERPINC1 (P-value = 1.55 × 10−3). The SNVs in the top-scoring pathway “Factors involved in megakaryocyte development and platelet production” (P-value = 3.34 × 10−4) were used to construct weighted genetic risk score (wGRS) and logistic regression models that predict thrombocytopenia. The wGRS predict which patients are at high or low toxicity risk levels, for CTCAE (odds ratio (OR) = 22.35, P-value = 1.55 × 10−8), and decrease (OR = 66.82, P-value = 5.92 × 10−9). The logistic regression models predict CTCAE grades 3–4 (receiver operator characteristics (ROC) area under the curve (AUC) = 0.79), and large decrease (ROC AUC = 0.86). We identified and validated genetic variations within hematopoiesis-related pathways that provide a solid foundation for future studies using genetic markers for predicting chemotherapy-induced thrombocytopenia and personalizing treatments.
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| 2. |
- Björn, Niclas, et al.
(författare)
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The association of four genetic variants with myelosuppression in gemcitabine-treated Japanese is not evident in gemcitabine/carboplatin-treated Swedes
- 2022
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Ingår i: Basic & Clinical Pharmacology & Toxicology. - : John Wiley & Sons. - 1742-7835 .- 1742-7843. ; 130:4, s. 513-521
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Tidskriftsartikel (refereegranskat)abstract
- Gemcitabine/carboplatin-induced myelosuppressive adverse drug reactions (ADRs) are clinical problems leading to patient suffering and dose alterations. There is a need for personalised medicine to improve treatment effects and patients' well-being. We tested four genetic variants, rs11141915, rs1901440, rs12046844 and rs11719165, previously suggested as potential biomarkers for gemcitabine-induced leukopenia/neutropenia in Japanese patients, in 213 Swedish gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients. DNA was genotyped using TaqMan probes and real-time PCR. The relationships between the risk alleles and low toxicity (non-ADR: Common Terminology Criteria for Adverse Events [CTCAE] grades 0) or high toxicity (ADR: CTCAE grades 3-4) of platelets, leukocytes and neutrophils were evaluated using Fisher's exact test. The risk alleles did not correlate with myelosuppression, and the strongest borderline significance (not withstanding adjustment for multiple testing) was for rs1901440 (neutropenia, p = 0.043) and rs11719165 (leukopenia, p = 0.049) where the risk alleles trended towards lower toxicity, contrasting with previous study findings. Risk alleles and higher risk scores were more common among our patients. We conclude that the genetic variants do not apply to Swedish patients treated with gemcitabine/carboplatin. However, they can still be important in other populations and cohorts, especially in a gemcitabine monotherapy setting, where the causal genetic variation might influence myelosuppressive ADRs.
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| 3. |
- Björn, Niclas, 1990-, et al.
(författare)
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Whole-genome sequencing and gene network modules predict gemcitabine/carboplatin-induced myelosuppression in non-small cell lung cancer patients
- 2020
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Ingår i: npj Systems Biology and Applications. - : Nature Publishing Group. - 2056-7189. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Gemcitabine/carboplatin chemotherapy commonly induces myelosuppression, including neutropenia, leukopenia, and thrombocytopenia. Predicting patients at risk of these adverse drug reactions (ADRs) and adjusting treatments accordingly is a long-term goal of personalized medicine. This study used whole-genome sequencing (WGS) of blood samples from 96 gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients and gene network modules for predicting myelosuppression. Association of genetic variants in PLINK found 4594, 5019, and 5066 autosomal SNVs/INDELs with p ≤ 1 × 10−3 for neutropenia, leukopenia, and thrombocytopenia, respectively. Based on the SNVs/INDELs we identified the toxicity module, consisting of 215 unique overlapping genes inferred from MCODE-generated gene network modules of 350, 345, and 313 genes, respectively. These module genes showed enrichment for differentially expressed genes in rat bone marrow, human bone marrow, and human cell lines exposed to carboplatin and gemcitabine (p < 0.05). Then using 80% of the patients as training data, random LASSO reduced the number of SNVs/INDELs in the toxicity module into a feasible prediction model consisting of 62 SNVs/INDELs that accurately predict both the training and the test (remaining 20%) data with high (CTCAE 3–4) and low (CTCAE 0–1) maximal myelosuppressive toxicity completely, with the receiver-operating characteristic (ROC) area under the curve (AUC) of 100%. The present study shows how WGS, gene network modules, and random LASSO can be used to develop a feasible and tested model for predicting myelosuppressive toxicity. Although the proposed model predicts myelosuppression in this study, further evaluation in other studies is required to determine its reproducibility, usability, and clinical effect.
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| 4. |
- Liljedahl, Helena, et al.
(författare)
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A gene expression-based single sample predictor of lung adenocarcinoma molecular subtype and prognosis
- 2021
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 148:1, s. 238-251
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Tidskriftsartikel (refereegranskat)abstract
- Disease recurrence in surgically treated lung adenocarcinoma (AC) remains high. New approaches for risk stratification beyond tumor stage are needed. Gene expression-based AC subtypes such as the Cancer Genome Atlas Network (TCGA) terminal-respiratory unit (TRU), proximal-inflammatory (PI) and proximal-proliferative (PP) subtypes have been associated with prognosis, but show methodological limitations for robust clinical use. We aimed to derive a platform independent single sample predictor (SSP) for molecular subtype assignment and risk stratification that could function in a clinical setting. Two-class (TRU/nonTRU=SSP2) and three-class (TRU/PP/PI=SSP3) SSPs using the AIMS algorithm were trained in 1655 ACs (n = 9659 genes) from public repositories vs TCGA centroid subtypes. Validation and survival analysis were performed in 977 patients using overall survival (OS) and distant metastasis-free survival (DMFS) as endpoints. In the validation cohort, SSP2 and SSP3 showed accuracies of 0.85 and 0.81, respectively. SSPs captured relevant biology previously associated with the TCGA subtypes and were associated with prognosis. In survival analysis, OS and DMFS for cases discordantly classified between TCGA and SSP2 favored the SSP2 classification. In resected Stage I patients, SSP2 identified TRU-cases with better OS (hazard ratio [HR] = 0.30; 95% confidence interval [CI] = 0.18-0.49) and DMFS (TRU HR = 0.52; 95% CI = 0.33-0.83) independent of age, Stage IA/IB and gender. SSP2 was transformed into a NanoString nCounter assay and tested in 44 Stage I patients using RNA from formalin-fixed tissue, providing prognostic stratification (relapse-free interval, HR = 3.2; 95% CI = 1.2-8.8). In conclusion, gene expression-based SSPs can provide molecular subtype and independent prognostic information in early-stage lung ACs. SSPs may overcome critical limitations in the applicability of gene signatures in lung cancer.
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| 5. |
- Marzano, Luca, 1995-, et al.
(författare)
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A novel analytical framework for risk stratification of real‐world data using machine learning: A small cell lung cancer study
- 2022
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Ingår i: Clinical and Translational Science. - : Wiley. - 1752-8054 .- 1752-8062. ; 15:10, s. 2437-2447
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Tidskriftsartikel (refereegranskat)abstract
- In recent studies, small cell lung cancer (SCLC) treatment guidelines based on Veterans’ Administration Lung Study Group limited/extensive disease staging and resulted in broad and inseparable prognostic subgroups. Evidence suggests that the eight versions of tumor, node, and metastasis (TNM) staging can play an important role to address this issue. The aim of the present study was to improve the detection of prognostic subgroups from a real-word data (RWD) cohort of patients and analyze their patterns using a development pipeline with thoracic oncologists and machine learning methods. The method detected subgroups of patients informing unsupervised learning (partition around medoids) including the impact of covariates on prognosis (Cox regression and random survival forest). An analysis was carried out using patients with SCLC (n = 636) with stage IIIA–IVB according to TNM classification. The analysis yielded k = 7 compacted and well-separated clusters of patients. Performance status (Eastern Cooperative Oncology Group-Performance Status), lactate dehydrogenase, spreading of metastasis, cancer stage, and CRP were the baselines that characterized the subgroups. The selected clustering method outperformed standard clustering techniques, which were not capable of detecting meaningful subgroups. From the analysis of cluster treatment decisions, we showed the potential of future RWD applications to understand disease, develop individualized therapies, and improve healthcare decision making.
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| 6. |
- Marzano, Luca, 1995-, et al.
(författare)
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Application of Process Mining for Modelling Small Cell Lung Cancer Prognosis
- 2023
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Ingår i: Studies in Health Technology and Informatics. - : IOS Press. - 0926-9630 .- 1879-8365. ; 302, s. 18-22
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Tidskriftsartikel (refereegranskat)abstract
- Process mining is a relatively new method that connects data science and process modelling. In the past years a series of applications with health care production data have been presented in process discovery, conformance check and system enhancement. In this paper we apply process mining on clinical oncological data with the purpose of studying survival outcomes and chemotherapy treatment decision in a real-world cohort of small cell lung cancer patients treated at Karolinska University Hospital (Stockholm, Sweden). The results highlighted the potential role of process mining in oncology to study prognosis and survival outcomes with longitudinal models directly extracted from clinical data derived from healthcare.
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| 7. |
- Montero, Angeles M., et al.
(författare)
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Clinicopathological significance of the expression of PD-L1 in Non-Small Cell Lung Cancer
- 2021
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Ingår i: Annals of Diagnostic Pathology. - : Elsevier BV. - 1092-9134 .- 1532-8198. ; 51, s. 151701-
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: PD1/PD-L1 pathway targeting therapies are nowadays an established treatment option for patients with NSCLC. We assessed whether PD-L1 expression in NSCLC tumor cells was associated with specific clinical features or overall survival using four different clones. Methods and results: A retrospective study included formalin-fixed paraffin embedded (FFPE) surgical tumors from 482 patients. PD-L1 status was assessed with immunohistochemistry in tumor cells on tissue microarrays using clones 28-8, 22C3, SP263 and SP142. Associations with OS were assessed by Kaplan-Meier and multivariate Cox's regression analysis. Patients' median age: 68 years (39–86); histology: adenocarcinoma (AdCa) 61%, squamous-cell carcinoma (SqCC) 33%, and large cell carcinoma (LCC) 6%; p-stage: IA (46%), IB (30%), IIA (10%), IIB (11,4%), IIIA (1,2%), IIIB – IV (0,4%). PD-L1 positivity (≥1%) in NSCLC for clones 28-8, 22C3, SP263, SP142 was 41.5%, 34.2%, 42.7%, 10.4%, respectively (Pearson Chi-square p < 0.0001). PD-L1 expression was correlated with histology, tumor size and grading. Statistically significant association between PD-L1 expression and OS in NSCLC and Non-AdCa was observed with clone SP142 (log-rank p = 0.045 and p = 0.05, respectively). Statistically significant association between PD-L1 expression and OS in LCC was observed with clones 22C3 (log-rank p = 0.009) and SP263 (log-rank p = 0.050). Conclusions: Overexpression of the PD-L1 clone SP142 was associated with poor overall survival in NSCLC and Non-AdCa. Clones 22C3 and SP263 were associated with poor prognosis in LCC. PD-L1 status might serve as a prognostic marker in NSCLC.
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| 8. |
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| 9. |
- Stiller, Christiane, et al.
(författare)
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Detection of Tumor-Associated Membrane Receptors on Extracellular Vesicles from Non-Small Cell Lung Cancer Patients via Immuno-PCR
- 2021
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 13:4
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Tidskriftsartikel (refereegranskat)abstract
- Simple Summary Lung cancer is often detected at late stages when metastases are present and the genomic make-ups of the tumors are heterogeneous. Analyses of genomic alterations in non-small-cell lung cancer (NSCLC) have revealed mutated tumor-associated membrane receptors and fusion proteins, which can be targeted via tyrosine kinase inhibitors (TKIs). TKIs initially often have a good effect, but a fraction of the tumor lesions may develop resistance through additional mutations in the targeted kinases or by increased expression/function of other membrane receptors. Detection of TKI-bypassing mechanisms is difficult in tissue biopsies as these analyze only a subpart of tumors or lesions. Liquid biopsies based on tumor-secreted small extracellular vesicles (sEVs) into body fluids can assess tumor heterogeneity. We present an immuno-PCR method for the detection of the epidermal growth factor receptor (EGFR), the human epidermal growth factor receptor 2 (HER2), and the insulin-like growth factor 1 receptor (IGF-1R) on sEVs. Initial investigations of sEVs from EGFR-mutant NSCLC tumor cells or pleural effusion (PE) fluid from patients with NSCLC or benign diseases showed different protein profiles for individual sEV samples. Further development of the immuno-PCR could complement DNA/mRNA-based assays detecting kinase mutations to allow longitudinal treatment monitoring of diverse TKI-bypassing mechanisms. Precision cancer medicine for non-small-cell lung cancer (NSCLC) has increased patient survival. Nevertheless, targeted agents towards tumor-associated membrane receptors only result in partial remission for a limited time, calling for approaches which allow longitudinal treatment monitoring. Rebiopsy of tumors in the lung is challenging, and metastatic lesions may have heterogeneous signaling. One way ahead is to use liquid biopsies such as circulating tumor DNA or small extracellular vesicles (sEVs) secreted by the tumor into blood or other body fluids. Herein, an immuno-PCR-based detection of the tumor-associated membrane receptors EGFR, HER2, and IGF-1R on CD9-positive sEVs from NSCLC cells and pleural effusion fluid (PE) of NSCLC patients is developed utilizing DNA conjugates of antibody mimetics and affibodies, as detection agents. Results on sEVs purified from culture media of NSCLC cells treated with anti-EGFR siRNA, showed that the reduction of EGFR expression can be detected via immuno-PCR. Protein profiling of sEVs from NSCLC patient PE samples revealed the capacity to monitor EGFR, HER2, and IGF-1R with the immuno-PCR method. We detected a significantly higher EGFR level in sEVs derived from a PE sample of a patient with an EGFR-driven NSCLC adenocarcinoma than in sEVs from PE samples of non-EGFR driven adenocarcinoma patients or in samples from patients with benign lung disease. In summary, we have developed a diagnostic method for sEVs in liquid biopsies of cancer patients which may be used for longitudinal treatment monitoring to detect emerging bypassing resistance mechanisms in a noninvasive way.
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| 10. |
- Svedberg, Anna, 1988-, et al.
(författare)
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Genetic association of gemcitabine/carboplatin-induced leukopenia and neutropenia in non-small cell lung cancer patients using whole-exome sequencing.
- 2020
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Ingår i: Lung Cancer. - : Elsevier. - 0169-5002 .- 1872-8332. ; 147, s. 106-114
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVES: Gemcitabine/carboplatin treatment is known to cause severe adverse drug reactions which can lead to the need for reduction or cessation of chemotherapy. It would be beneficial to identify patients at risk of severe hematological toxicity in advance before treatment start. This study aims to identify genetic markers for gemcitabine/carboplatin-induced leukopenia and neutropenia in non-small cell lung cancer patients.MATERIAL AND METHODS: Whole-exome sequencing was performed on 215 patients. Association analysis was performed on single-nucleotide variants (SNVs) and genes, and the validation was based on an independent genome-wide association study (GWAS). Based on the association and validation analyses the genetic variants were then selected for and used in weighted genetic risk score (wGRS) prediction models for leukopenia and neutropenia.RESULTS: Association analysis identified 50 and 111 SNVs, and 12 and 20 genes, for leukopenia and neutropenia, respectively. Of these SNVS 20 and 19 were partially validated for leukopenia and neutropenia, respectively. The genes SVIL (p = 2.48E-06) and EFCAB2 (p = 4.63E-06) were significantly associated with leukopenia contain the partially validated SNVs rs3740003, rs10160013, rs1547169, rs10927386 and rs10927387. The wGRS prediction models showed significantly different risk scores for high and low toxicity patients.CONCLUSION: We have identified and partially validated genetic biomarkers in SNVs and genes correlated to gemcitabine/carboplatin-induced leukopenia and neutropenia and created wGRS models for predicting the risk of chemotherapy-induced hematological toxicity. These results provide a strong foundation for further studies of chemotherapy-induced toxicity.
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