| 1. |
- Alvez, Maria Bueno, et al.
(författare)
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Next generation pan-cancer blood proteome profiling using proximity extension assay
- 2023
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.
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| 2. |
- Backman, Max, et al.
(författare)
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Infiltration of NK and plasma cells is associated with a distinct immune subset in non‐small cell lung cancer
- 2021
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Ingår i: Journal of Pathology. - : John Wiley & Sons. - 0022-3417 .- 1096-9896. ; 255:3, s. 243-256
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Tidskriftsartikel (refereegranskat)abstract
- Immune cells of the tumor microenvironment are central but erratic targets for immunotherapy. The aim of this study was to characterize novel patterns of immune cell infiltration in non-small cell lung cancer (NSCLC) in relation to its molecular and clinicopathologic characteristics. Lymphocytes (CD3+, CD4+, CD8+, CD20+, FOXP3+, CD45RO+), macrophages (CD163+), plasma cells (CD138+), NK cells (NKp46+), PD1+, and PD-L1+ were annotated on a tissue microarray including 357 NSCLC cases. Somatic mutations were analyzed by targeted sequencing for 82 genes and a tumor mutational load score was estimated. Transcriptomic immune patterns were established in 197 patients based on RNA sequencing data. The immune cell infiltration was variable and showed only poor association with specific mutations. The previously defined immune phenotypic patterns, desert, inflamed, and immune excluded, comprised 30, 13, and 57% of cases, respectively. Notably, mRNA immune activation and high estimated tumor mutational load were unique only for the inflamed pattern. However, in the unsupervised cluster analysis, including all immune cell markers, these conceptual patterns were only weakly reproduced. Instead, four immune classes were identified: (1) high immune cell infiltration, (2) high immune cell infiltration with abundance of CD20+ B cells, (3) low immune cell infiltration, and (4) a phenotype with an imprint of plasma cells and NK cells. This latter class was linked to better survival despite exhibiting low expression of immune response-related genes (e.g. CXCL9, GZMB, INFG, CTLA4). This compartment-specific immune cell analysis in the context of the molecular and clinical background of NSCLC reveals two previously unrecognized immune classes. A refined immune classification, including traits of the humoral and innate immune response, is important to define the immunogenic potency of NSCLC in the era of immunotherapy. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.
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| 3. |
- Karlsson, Max, et al.
(författare)
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A single-cell type transcriptomics map of human tissues
- 2021
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Ingår i: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 7:31
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Tidskriftsartikel (refereegranskat)abstract
- Advances in molecular profiling have opened up the possibility to map the expression of genes in cells, tissues, and organs in the human body. Here, we combined single-cell transcriptomics analysis with spatial antibody-based protein profiling to create a high-resolution single-cell type map of human tissues. An open access atlas has been launched to allow researchers to explore the expression of human protein-coding genes in 192 individual cell type clusters. An expression specificity classification was performed to determine the number of genes elevated in each cell type, allowing comparisons with bulk transcriptomics data. The analysis highlights distinct expression clusters corresponding to cell types sharing similar functions, both within the same organs and between organs.
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| 4. |
- Kotol, David, et al.
(författare)
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Absolute Quantification of Pan-Cancer Plasma Proteomes Reveals Unique Signature in Multiple Myeloma
- 2023
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 15:19
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Tidskriftsartikel (refereegranskat)abstract
- Mass spectrometry based on data-independent acquisition (DIA) has developed into a powerful quantitative tool with a variety of implications, including precision medicine. Combined with stable isotope recombinant protein standards, this strategy provides confident protein identification and precise quantification on an absolute scale. Here, we describe a comprehensive targeted proteomics approach to profile a pan-cancer cohort consisting of 1800 blood plasma samples representing 15 different cancer types. We successfully performed an absolute quantification of 253 proteins in multiplex. The assay had low intra-assay variability with a coefficient of variation below 20% (CV = 17.2%) for a total of 1013 peptides quantified across almost two thousand injections. This study identified a potential biomarker panel of seven protein targets for the diagnosis of multiple myeloma patients using differential expression analysis and machine learning. The combination of markers, including the complement C1 complex, JCHAIN, and CD5L, resulted in a prediction model with an AUC of 0.96 for the identification of multiple myeloma patients across various cancer patients. All these proteins are known to interact with immunoglobulins.
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| 5. |
- Micke, Patrick, et al.
(författare)
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The prognostic impact of the tumour stroma fraction : A machine learning-based analysis in 16 human solid tumour types
- 2021
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 65
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Tidskriftsartikel (refereegranskat)abstract
- Background: The development of a reactive tumour stroma is a hallmark of tumour progression and pronounced tumour stroma is generally considered to be associated with clinical aggressiveness. The variability between tumour types regarding stroma fraction, and its prognosis associations, have not been systematically analysed.Methods: Using an objective machine-learning method we quantified the tumour stroma in 16 solid cancer types from 2732 patients, representing retrospective tissue collections of surgically resected primary tumours. Image analysis performed tissue segmentation into stromal and epithelial compartment based on pan-cytokeratin staining and autofluorescence patterns.Findings: The stroma fraction was highly variable within and across the tumour types, with kidney cancer showing the lowest and pancreato-biliary type periampullary cancer showing the highest stroma proportion (median 19% and 73% respectively). Adjusted Cox regression models revealed both positive (pancreato-biliary type periampullary cancer and oestrogen negative breast cancer, HR(95%CI)=0.56(0.34-0.92) and HR (95%CI)=0.41(0.17-0.98) respectively) and negative (intestinal type periampullary cancer, HR(95%CI)=3.59 (1.49-8.62)) associations of the tumour stroma fraction with survival.Interpretation: Our study provides an objective quantification of the tumour stroma fraction across major types of solid cancer. Findings strongly argue against the commonly promoted view of a general associations between high stroma abundance and poor prognosis. The results also suggest that full exploitation of the prognostic potential of tumour stroma requires analyses that go beyond determination of stroma abundance.
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| 6. |
- Sjöstedt, Evelina, et al.
(författare)
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An atlas of the protein-coding genes in the human, pig, and mouse brain
- 2020
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 367:6482, s. 1090-
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Tidskriftsartikel (refereegranskat)abstract
- The brain, with its diverse physiology and intricate cellular organization, is the most complex organ of the mammalian body. To expand our basic understanding of the neurobiology of the brain and its diseases, we performed a comprehensive molecular dissection of 10 major brain regions and multiple subregions using a variety of transcriptomics methods and antibody-based mapping. This analysis was carried out in the human, pig, and mouse brain to allow the identification of regional expression profiles, as well as to study similarities and differences in expression levels between the three species. The resulting data have been made available in an open-access Brain Atlas resource, part of the Human Protein Atlas, to allow exploration and comparison of the expression of individual protein-coding genes in various parts of the mammalian brain.
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| 7. |
- Wegrzyniak, Olivia, et al.
(författare)
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Imaging of fibrogenesis in the liver by [18F]TZ-Z0959 : an Affibody molecule targeting platelet derived growth factor receptor β
- 2023
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Ingår i: EJNMMI Radiopharmacy and Chemistry. - : Springer Nature. - 2365-421X. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Platelet-derived growth factor receptor beta (PDGFRβ) is a receptor overexpressed on activated hepatic stellate cells (aHSCs). Positron emission tomography (PET) imaging of PDGFRβ could potentially allow the quantification of fibrogenesis in fibrotic livers. This study aims to evaluate a fluorine-18 radiolabeled Affibody molecule ([18F]TZ-Z09591) as a PET tracer for imaging liver fibrogenesis. Results: In vitro specificity studies demonstrated that the trans-Cyclooctenes (TCO) conjugated Z09591 Affibody molecule had a picomolar affinity for human PDGFRβ. Biodistribution performed on healthy rats showed rapid clearance of [18F]TZ-Z09591 through the kidneys and low liver background uptake. Autoradiography (ARG) studies on fibrotic livers from mice or humans correlated with histopathology results. Ex vivo biodistribution and ARG revealed that [18F]TZ-Z09591 binding in the liver was increased in fibrotic livers (p = 0.02) and corresponded to binding in fibrotic scars. Conclusions: Our study highlights [18F]TZ-Z09591 as a specific tracer for fibrogenic cells in the fibrotic liver, thus offering the potential to assess fibrogenesis clearly. Graphical abstract: [Figure not available: see fulltext.]
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| 8. |
- Aasebo, Kristine, et al.
(författare)
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CDX2 : A Prognostic Marker in Metastatic Colorectal Cancer Defining a Better BRAF Mutated and a Worse KRAS Mutated Subgroup
- 2020
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Ingår i: Frontiers in Oncology. - : FRONTIERS MEDIA SA. - 2234-943X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: Survival of metastatic colorectal cancer (mCRC) patients has improved, but mainly for trial patients. New predictive and prognostic biomarkers validated in the general mCRC population are needed. Caudal-type homeobox 2 (CDX2) is an intestine-specific transcription factor with potential prognostic and predictive effect, but the importance in mCRC has not been fully investigated. Methods: Immunohistochemistry analysis of CDX2 was performed in a Scandinavian population-based cohort of mCRC (n = 796). Frequency, clinical and tumor characteristics, response rate, progression-free survival, and overall survival (OS) were estimated. Results: Loss of CDX2 expression was found in 87 (19%) of 452 stained cases, in 53% if BRAF mutated (BRAFmut) and in 9% if KRAS mutated (KRASmut). CDX2 loss was associated with microsatellite instability, BRAFmut, and poor differentiation and inversely associated with KRASmut. Patients with CDX2 loss received less first-line (53 vs. 64%, p = 0.050) and second-line (23 vs. 39%, p = 0.006) chemotherapy and secondary surgery (1 vs. 9%, p = 0.019). Median progression-free survival and OS for patients given first-line combination chemotherapy was 4 and 10 months if CDX2 loss vs. 9 and 24 months if CDX2 expressed (p = 0.001, p < 0.001). Immediate progression on first-line combination chemotherapy was seen in 35% of patients with CDX2 loss vs. 10% if CDX2 expressed (p = 0.003). Median OS in patients with BRAFmut or KRASmut and CDX2 expressed in tumor (both 21 months) was comparable to wild-type patients (27 months). However, if CDX2 loss, median OS was only 8 and 11 months in BRAFmut and KRASmut cases, respectively, and 10 months in double wild-type patients. In multivariate analysis, CDX2 loss (hazard ratio: 1.50, p = 0.027) and BRAFmut (hazard ratio: 1.62, p = 0.012) were independent poor prognostic markers for OS. Conclusion: In a population-based cohort of mCRC patients, CDX2 loss is an independent poor prognostic marker. Expression of CDX2 defines a new subgroup of BRAFmut cases with a much better prognosis. Loss of CDX2 defines a small group of KRASmut cases with a worse prognosis. Patients with CDX2 loss receive less palliative chemotherapy with less benefit and rarely reach secondary surgery.
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| 9. |
- Abdellah, Tebani, et al.
(författare)
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Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
- 2021
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Ingår i: Acta neuropathologica communications. - : BioMed Central (BMC). - 2051-5960. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Pituitary neuroendocrine tumors (PitNETs) are common, generally benign tumors with complex clinical characteristics related to hormone hypersecretion and/or growing sellar tumor mass. PitNETs can be classified based on the expression pattern of anterior pituitary hormones and three main transcriptions factors (TF), SF1, PIT1 and TPIT that regulate differentiation of adenohypophysial cells. Here, we have extended this classification based on the global transcriptomics landscape using tumor tissue from a well-defined cohort comprising 51 PitNETs of different clinical and histological types. The molecular profiles were compared with current classification schemes based on immunohistochemistry. Our results identified three main clusters of PitNETs that were aligned with the main pituitary TFs expression patterns. Our analyses enabled further identification of specific genes and expression patterns, including both known and unknown genes, that could distinguish the three different classes of PitNETs. We conclude that the current classification of PitNETs based on the expression of SF1, PIT1 and TPIT reflects three distinct subtypes of PitNETs with different underlying biology and partly independent from the expression of corresponding hormones. The transcriptomic analysis reveals several potentially targetable tumor-driving genes with previously unknown role in pituitary tumorigenesis.
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| 10. |
- Backman, Max, 1987-
(författare)
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Spatial immune analyses in clinical cancer tissue
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cancer is a leading cause of premature death and lung cancer is the deadliest cancer type, with non-small cell lung cancer (NSCLC) representing 85% of lung cancer cases. Despite promising development in cancer treatment in recent decades, overall prognosis is poor. The aim of this thesis was to explore novel techniques in protein visualization in clinical cancer tissue to better our understanding of cancer immunity and to discover new biomarkers for improved cancer diagnostics.In Paper I traditional immunohistochemistry (IHC) was compared to the in-situ proximity ligation assay (isPLA). Both techniques were applied to stain 12 proteins in 39 cell lines and 37 tissue types. Two different antibodies were used in the IHC assay and in the isPLA, where binding by both antibodies is required to generate detection signals. The comparison of staining patterns showed that the isPLA presents a valuable alternative to traditional IHC.In Paper II cancer tissue from 357 NSCLC patients was immunophenotyped through IHC annotations of 11 different immune markers. A distinct group of cases with a signature of NK cells and/or plasma cells had favorable prognosis despite significantly lower T-cell activation signatures. This study provides a detailed description of the immune landscape in NSCLC, extending previous concepts, and highlights plasma and NK-cells as potential biomarkers for further validation.In Paper III a multiplex-multispectral pipeline was established to explore three immune marker panels in a NSCLC cohort, spatially quantifying 13 immune cell types. The immune composition of NSCLC was analyzed for the prognostic relevance of immune cell coordination. Cell densities and distances were found to contribute independently to prognosis, indicating that spatial information on local immune cell infiltration is crucial for understanding tumor immunity.In Paper IV an extensive characterization of the immune cell landscape of colon cancer identified a prognostic signature based on the ratio of CD8+ lymphocytes to CD68+CD163+ macrophages. This signature was superior to the state-of-the-art ‘Immunoscore’, and was also associated with longer survival when analyzed in other common cancer types. This presents a promising immunological biomarker that warrants further validation as a prognostic and predictive signature in common cancers.In summary, this thesis presents an in-depth study of immune cell infiltration in several cancer types to better understand cancer immunity. Through novel techniques and spatial metrics, we describe immunophenotypes that might contribute to cancer classification and prognostication. The identified immune phenomena may also present alternative treatment targets to overcome resistance to immunotherapy.
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