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- Bergman, Julia, et al.
(författare)
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The human adrenal gland proteome defined by transcriptomics and antibody-based profiling.
- 2017
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Ingår i: Endocrinology. - : Endocrine Society. - 0013-7227 .- 1945-7170. ; 158:2, s. 239-251
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Tidskriftsartikel (refereegranskat)abstract
- The adrenal gland is a composite endocrine organ with vital functions that include the synthesis and release of glucocorticoids and catecholamines. To define the molecular landscape that underlies the specific functions of the adrenal gland, we combined a genome-wide transcriptomics approach using messenger RNA sequencing of human tissues with immunohistochemistry-based protein profiling on tissue microarrays. Approximately two-thirds of all putative protein coding genes were expressed in the adrenal gland, and the analysis identified 253 genes with an elevated pattern of expression in the adrenal gland, with only 37 genes showing a markedly greater expression level (more than fivefold) in the adrenal gland compared with 31 other normal human tissue types analyzed. The analyses allowed for an assessment of the relative expression levels for well-known proteins involved in adrenal gland function but also identified previously poorly characterized proteins in the adrenal cortex, such as the FERM (4.1 protein, ezrin, radixin, moesin) domain containing 5 and the nephroblastoma overexpressed (NOV) protein homolog. We have provided a global analysis of the adrenal gland transcriptome and proteome, with a comprehensive list of genes with elevated expression in the adrenal gland and spatial information with examples of protein expression patterns for corresponding proteins. These genes and proteins constitute important starting points for an improved understanding of the normal function and pathophysiology of the adrenal glands.
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| 2. |
- Brunnström, Hans, et al.
(författare)
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PD-L1 immunohistochemistry in clinical diagnostics of lung cancer : inter-pathologist variability is higher than assay variability
- 2017
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Ingår i: Modern Pathology. - : NATURE PUBLISHING GROUP. - 0893-3952 .- 1530-0285. ; 30:10, s. 1411-1421
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Tidskriftsartikel (refereegranskat)abstract
- Assessment of programmed cell death ligand 1 (PD-L1) immunohistochemical staining is used for decision on treatment with programmed cell death 1 and PD-L1 checkpoint inhibitors in lung adenocarcinomas and squamous cell carcinomas. This study aimed to compare the staining properties of tumor cells between the antibody clones 28-8, 22C3, SP142, and SP263 and investigate interrater variation between pathologists to see if these stainings can be safely evaluated in the clinical setting. Using consecutive sections from a tissue microarray with tumor tissue from 55 resected lung cancer cases, staining with five PD-L1 assays (28-8 from two different vendors, 22C3, SP142, and SP263) was performed. Seven pathologists individually evaluated the percentage of positive tumor cells, scoring each sample applying cutoff levels used in clinical studies: < 1% positive tumor cells (score 0), 1-4% (score 1), 5-9% (score 2), 10-24% (score 3), 25-49% (score 4), and > 50% positive tumor cells (score 5). Pairwise analysis of antibody clones showed weighted kappa values in the range of 0.45-0.91 with the highest values for comparisons with 22C3 and 28-8 and the lowest involving SP142. Excluding SP142 resulted in kappa 0.75-0.91. Weighted kappa for interobserver variation between pathologists was 0.71-0.96. Up to 20% of the cases were differently classified as positive or negative by any pathologist compared with consensus score using >= 1% positive tumor cells as cutoff. A significantly better agreement between pathologists was seen using >= 50% as cutoff (0-5% of cases). In conclusion, the concordance between the PD-L1 antibodies 22C3, 28-8 and SP263 is relatively good when evaluating lung cancers and suggests that any one of these assays may be sufficient as basis for decision on treatment with nivolumab, pembrolizumab, and durvalumab. The scoring of the pathologist presents an intrinsic source of error that should be considered especially at low PD-L1 scores.
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| 3. |
- Gremel, Gabriela, et al.
(författare)
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A systematic search strategy identifies cubilin as independent prognostic marker for renal cell carcinoma
- 2017
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Ingår i: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Background: There is an unmet clinical need for better prognostic and diagnostic tools for renal cell carcinoma (RCC). Methods: Human Protein Atlas data resources, including the transcriptomes and proteomes of normal and malignant human tissues, were searched for RCC-specific proteins and cubilin (CUBN) identified as a candidate. Patient tissue representing various cancer types was constructed into a tissue microarray (n = 940) and immunohistochemistry used to investigate the specificity of CUBN expression in RCC as compared to other cancers. Two independent RCC cohorts (n = 181; n = 114) were analyzed to further establish the sensitivity of CUBN as RCC-specific marker and to explore if the fraction of RCCs lacking CUBN expression could predict differences in patient survival. Results: CUBN was identified as highly RCC-specific protein with 58% of all primary RCCs staining positive for CUBN using immunohistochemistry. In venous tumor thrombi and metastatic lesions, the frequency of CUBN expression was increasingly lost. Clear cell RCC (ccRCC) patients with CUBN positive tumors had a significantly better prognosis compared to patients with CUBN negative tumors, independent of T-stage, Fuhrman grade and nodal status (HR 0.382, CI 0.203-0.719, P = 0.003). Conclusions: CUBN expression is highly specific to RCC and loss of the protein is significantly and independently associated with poor prognosis. CUBN expression in ccRCC provides a promising positive prognostic indicator for patients with ccRCC. The high specificity of CUBN expression in RCC also suggests a role as a new diagnostic marker in clinical cancer differential diagnostics to confirm or rule out RCC.
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| 4. |
- Grinberg, Marianna, et al.
(författare)
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Reaching the limits of prognostication in non-small cell lung cancer : an optimized biomarker panel fails to outperform clinical parameters.
- 2017
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Ingår i: Modern Pathology. - : Elsevier BV. - 0893-3952 .- 1530-0285. ; 30:7, s. 964-977
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Tidskriftsartikel (refereegranskat)abstract
- Numerous protein biomarkers have been analyzed to improve prognostication in non-small cell lung cancer, but have not yet demonstrated sufficient value to be introduced into clinical practice. Here, we aimed to develop and validate a prognostic model for surgically resected non-small cell lung cancer. A biomarker panel was selected based on (1) prognostic association in published literature, (2) prognostic association in gene expression data sets, (3) availability of reliable antibodies, and (4) representation of diverse biological processes. The five selected proteins (MKI67, EZH2, SLC2A1, CADM1, and NKX2-1 alias TTF1) were analyzed by immunohistochemistry on tissue microarrays including tissue from 326 non-small cell lung cancer patients. One score was obtained for each tumor and each protein. The scores were combined, with or without the inclusion of clinical parameters, and the best prognostic model was defined according to the corresponding concordance index (C-index). The best-performing model was subsequently validated in an independent cohort consisting of tissue from 345 non-small cell lung cancer patients. The model based only on protein expression did not perform better compared to clinicopathological parameters, whereas combining protein expression with clinicopathological data resulted in a slightly better prognostic performance (C-index: all non-small cell lung cancer 0.63 vs 0.64; adenocarcinoma: 0.66 vs 0.70, squamous cell carcinoma: 0.57 vs 0.56). However, this modest effect did not translate into a significantly improved accuracy of survival prediction. The combination of a prognostic biomarker panel with clinicopathological parameters did not improve survival prediction in non-small cell lung cancer, questioning the potential of immunohistochemistry-based assessment of protein biomarkers for prognostication in clinical practice.Modern Pathology advance online publication, 10 March 2017; doi:10.1038/modpathol.2017.14.
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