Prognostic genome and transcriptome signatures in colorectal cancers.

Colorectal cancer is caused by a sequence of somatic genomic alterations affecting driver genes in core cancer pathways1. Here, to understand the functional and prognostic impact of cancer-causing somatic mutations, we analysed the whole genomes and transcriptomes of 1,063 primary colorectal cancers in a population-based cohort with long-term follow-up. From the 96 mutated driver genes, 9 were not previously implicated in colorectal cancer and 24 had not been linked to any cancer. Two distinct patterns of pathway co-mutations were observed, timing analyses identified nine early and three late driver gene mutations, and several signatures of colorectal-cancer-specific mutational processes were identified. Mutations in WNT, EGFR and TGFß pathway genes, the mitochondrial CYB gene and 3 regulatory elements along with 21 copy-number variations and the COSMIC SBS44 signature correlated with survival. Gene expression classification yielded five prognostic subtypes with distinct molecular features, in part explained by underlying genomic alterations. Microsatellite-instable tumours divided into two classes with different levels of hypoxia and infiltration of immune and stromal cells. To our knowledge, this study constitutes the largest integrated genome and transcriptome analysis of colorectal cancer, and interlinks mutations, gene expression and patient outcomes. The identification of prognostic mutations and expression subtypes can guide future efforts to individualize colorectal cancer therapy.

Noninvasive detection of any-stage cancer using free glycosaminoglycans.

Cancer mortality is exacerbated by late-stage diagnosis. Liquid biopsies based on genomic biomarkers can noninvasively diagnose cancers. However, validation studies have reported ~10% sensitivity to detect stage I cancer in a screening population and specific types, such as brain or genitourinary tumors, remain undetectable. We investigated urine and plasma free glycosaminoglycan profiles (GAGomes) as tumor metabolism biomarkers for multi-cancer early detection (MCED) of 14 cancer types using 2,064 samples from 1,260 cancer or healthy subjects. We observed widespread cancer-specific changes in biofluidic GAGomes recapitulated in an in vivo cancer progression model. We developed three machine learning models based on urine (Nurine = 220 cancer vs. 360 healthy) and plasma (Nplasma = 517 vs. 425) GAGomes that can detect any cancer with an area under the receiver operating characteristic curve of 0.83-0.93 with up to 62% sensitivity to stage I disease at 95% specificity. Undetected patients had a 39 to 50% lower risk of death. GAGomes predicted the putative cancer location with 89% accuracy. In a validation study on a screening-like population requiring ≥ 99% specificity, combined GAGomes predicted any cancer type with poor prognosis within 18 months with 43% sensitivity (21% in stage I; N = 121 and 49 cases). Overall, GAGomes appeared to be powerful MCED metabolic biomarkers, potentially doubling the number of stage I cancers detectable using genomic biomarkers.

A gene-centric approach to biomarker discovery identifies transglutaminase 1 as an epidermal autoantigen.

Autoantigen discovery is a critical challenge for the understanding and diagnosis of autoimmune diseases. While autoantibody markers in current clinical use have been identified through studies focused on individual disorders, we postulated that a reverse approach starting with a putative autoantigen to explore multiple disorders might hold promise. We here targeted the epidermal protein transglutaminase 1 (TGM1) as a member of a protein family prone to autoimmune attack. By screening sera from patients with various acquired skin disorders, we identified seropositive subjects with the blistering mucocutaneous disease paraneoplastic pemphigus. Validation in further subjects confirmed TGM1 autoantibodies as a 55% sensitive and 100% specific marker for paraneoplastic pemphigus. This gene-centric approach leverages the wealth of data available for human genes and may prove generally applicable for biomarker discovery in autoimmune diseases.

Combined expression of HOXA11 and CD10 identifies endometriosis versus normal tissue and tumors.

The gold standard for diagnosing endometriosis is by laparoscopic visual demonstration of ectopic endometrial lesions outside the uterus, preferably verified by biopsy and microscopical examination. Molecular markers to facilitate the microscopical diagnosis of endometriosis and for distinguishing endometriosis from other benign and malignant lesions are lacking. Our aim was to test and validate an immunohistochemical antibody panel for improved diagnostic accuracy of endometriosis. Both CD10 and HOXA11 have been implicated in regulation of endometrial homeostasis. Here we have analyzed the expression pattern of these two proteins using immunohistochemistry on human tissues in a tissue microarray format. CD10 and HOXA11 expression in endometriosis lesions were compared to expression patterns in a range of normal tissues and in primary- and metastatic lesions of endometrial-, cervical- and ovarian cancer. HOXA11 and CD10 were expressed in 98% and 91% of endometriosis lesions and the combined double-positive expression profile of both HOXA11 and CD10 was highly sensitive for ectopic endometrial tissue (90%). The specificity and sensitivity for this double-positive signature in endometriosis was significantly different from all investigated tissues, cancers and metastases except normal, eutopic endometrial- and cervical mucosa. The combination of HOXA11 and CD10 expression profiles provides a useful tool to identify ectopic endometrial tissue and for distinguishing endometriosis from various types of gynecological malignancies and metastases.

Metastatic colorectal carcinomas with high SATB2 expression are associated with better prognosis and response to chemotherapy: a population-based Scandinavian study.

Background: Survival and response to therapy in patients with metastatic colorectal cancer (mCRC) are very heterogeneous. There is an unmet need for better markers of prognosis and treatment benefit for mCRC patients. The homeobox 2 gene SATB2 has a highly specific expression in colorectal tissue and is associated with better prognosis in non-metastatic CRC.Material and methods: A population-based cohort of 798 mCRC patients was analysed. From primary tumour material, protein expression was assessed by immunohistochemistry. BRAF and KRAS mutation status was also determined. Associations with clinicopathological data, overall and progression-free survival and response to first-line chemotherapy were analysed.Results: Tumour tissue and clinical data were available from 467 patients. SATB2 was strongly expressed in 58% of cases, significantly more in left-sided, low-grade and wild-type BRAF tumours. Patients with high SATB2 tumours had longer overall survival compared with low SATB2 tumours (median 13 vs 8 months respectively, p < .001). Chemotherapy was given to 282 patients (63%). Patients with high SATB2 tumours had longer OS (median 22 vs 15 months respectively, p = .001) and more often responded to chemotherapy than those with low SATB2 (objective response 43% vs 29%, p = .02; clinical response 83% vs 67%, p = .004). Progression-free survival on first-line irinotecan chemotherapy was longer in high SATB2 cases (median 8 vs 4 months respectively, p = .019). Patients with both low SATB2 expression and mutated BRAF (n = 69) had particularly poor survival compared to the rest (median 8 and 12 months respectively, p = .001). In multivariable analysis, the SATB2 findings were independent of known clinicopathological prognostic markers, including BRAF mutation status.Conclusion: Patients with mCRC expressing high level of SATB2 have better prognosis and response to chemotherapy than those with low SATB2 expression. Patients with both low SATB2 expression and mutated BRAF had particularly poor prognosis and could thus benefit from more aggressive therapies.

Molecular characterization of a large unselected cohort of metastatic colorectal cancers in relation to primary tumor location, rare metastatic sites and prognosis.

Background: We have reported that BRAF V600E mutations and microsatellite instability-high (MSI-H) are more prevalent in a population-based cohort of metastatic colorectal cancer (mCRC) patients than has been reported from clinical trials or hospital-based patient groups. The aim was to explore if other mutations in mCRC differ in prevalence between these cohorts in relation to mismatch repair status and primary tumor location and if presence of bone or brain metastases is associated with any mutations.Material and methods: A population-based cohort of 798 mCRC patients from three regions in Scandinavia was used. Forty-four cancer related genes were investigated in a custom designed Ampliseq hotspot panel. Differences in survival were analyzed using the Kaplan-Meier estimator and the Cox regression analysis.Results: Determination of mutations was possible in 449/501 patients for 40/44 genes. Besides BRAF V600E, seen in 19% of the tumors, none of the other mutations appeared more prevalent than in trial cohorts. BRAF V600E and MSI-H, seen in 8%, were associated with poor prognosis as was right-sided primary tumor location (39%) when compared to left-sided and rectum together; however, in a multivariable regression, only the BRAF mutation retained its statistical significance. No other mutations were associated with poor prognosis. ERBB2 alterations were more common if bone metastases were present at diagnosis (17% vs. 4%, p = .011). No association was found for brain metastases. Fifty-two percent had an alteration that is treatable with an FDA-approved targeted therapy, chiefly by EGFR-inhibitor for RAS wild-type and a check-point inhibitor for MSI-H tumors.Conclusions: Right-sided tumor location, BRAF V600E mutations, but no other investigated mutation, and MSI-H are more commonly seen in an unselected cohort than is reported from clinical patient cohorts, likely because they indicate poor prognosis. Half of the patients have a tumor that is treatable with an already FDA-approved targeted drug for mCRC.

Region-by-region analysis of PET, MRI, and histology in en bloc-resected oligodendrogliomas reveals intra-tumoral heterogeneity.

PURPOSE: Oligodendrogliomas are heterogeneous tumors in terms of imaging appearance, and a deeper understanding of the histopathological tumor characteristics in correlation to imaging parameters is needed. We used PET-to-MRI-to-histology co-registration with the aim of studying intra-tumoral 11C-methionine (MET) uptake in relation to tumor perfusion and the protein expression of histological cell markers in corresponding areas. METHODS: Consecutive histological sections of four tumors covering the entire en bloc-removed tumor were immunostained with antibodies against IDH1-mutated protein (tumor cells), Ki67 (proliferating cells), and CD34 (blood vessels). Software was developed for anatomical landmarks-based co-registration of subsequent histological images, which were overlaid on corresponding MET PET scans and MRI perfusion maps. Regions of interest (ROIs) on PET were selected throughout the entire tumor volume, covering hot spot areas, areas adjacent to hot spots, and tumor borders with infiltrating zone. Tumor-to-normal tissue (T/N) ratios of MET uptake and mean relative cerebral blood volume (rCBV) were measured in the ROIs and protein expression of histological cell markers was quantified in corresponding regions. Statistical correlations were calculated between MET uptake, rCBV, and quantified protein expression. RESULTS: A total of 84 ROIs were selected in four oligodendrogliomas. A significant correlation (p < 0.05) between MET uptake and tumor cell density was demonstrated in all tumors separately. In two tumors, MET correlated with the density of proliferating cells and vessel cell density. There were no significant correlations between MET uptake and rCBV, and between rCBV and histological cell markers. CONCLUSIONS: The MET uptake in hot spots, outside hotspots, and in infiltrating tumor edges unanimously reflects tumor cell density. The correlation between MET uptake and vessel density and density of proliferating cells is less stringent in infiltrating tumor edges and is probably more susceptible to artifacts caused by larger blood vessels surrounding the tumor. Although based on a limited number of samples, this study provides histological proof for MET as an indicator of tumor cell density and for the lack of statistically significant correlations between rCBV and histological cell markers in oligodendrogliomas.

Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues.

A large portion of human proteins are referred to as missing proteins, defined as protein-coding genes that lack experimental data on the protein level due to factors such as temporal expression, expression in tissues that are difficult to sample, or they actually do not encode functional proteins. In the present investigation, an integrated omics approach was used for identification and exploration of missing proteins. Transcriptomics data from three different sources-the Human Protein Atlas (HPA), the GTEx consortium, and the FANTOM5 consortium-were used as a starting point to identify genes selectively expressed in specialized tissues. Complementing the analysis with profiling on more specific tissues based on immunohistochemistry allowed for further exploration of cell-type-specific expression patterns. More detailed tissue profiling was performed for >300 genes on complementing tissues. The analysis identified tissue-specific expression of nine proteins previously listed as missing proteins (POU4F1, FRMD1, ARHGEF33, GABRG1, KRTAP2-1, BHLHE22, SPRR4, AVPR1B, and DCLK3), as well as numerous proteins with evidence of existence on the protein level that previously lacked information on spatial resolution and cell-type-specific expression pattern. We here present a comprehensive strategy for identification of missing proteins by combining transcriptomics with antibody-based proteomics. The analyzed proteins provide interesting targets for organ-specific research in health and disease.

Combined ASRGL1 and p53 immunohistochemistry as an independent predictor of survival in endometrioid endometrial carcinoma.

OBJECTIVE: In clinical practise, prognostication of endometrial cancer is based on clinicopathological risk factors. The use of immunohistochemistry-based markers as prognostic tools is generally not recommended and a systematic analysis of their utility as a panel is lacking. We evaluated whether an immunohistochemical marker panel could reliably assess endometrioid endometrial cancer (EEC) outcome independent of clinicopathological information. METHODS: A cohort of 306 EEC specimens was profiled using tissue microarray (TMA). Cost- and time-efficient immunohistochemical analysis of well-established tissue biomarkers (ER, PR, HER2, Ki-67, MLH1 and p53) and two new biomarkers (L1CAM and ASRGL1) was carried out. Statistical modelling with embedded variable selection was applied on the staining results to identify minimal prognostic panels with maximal prognostic accuracy without compromising generalizability. RESULTS: A panel including p53 and ASRGL1 immunohistochemistry was identified as the most accurate predictor of relapse-free and disease-specific survival. Within this panel, patients were allocated into high- (5.9%), intermediate- (29.5%) and low- (64.6%) risk groups where high-risk patients had a 30-fold risk (P<0.001) of dying of EEC compared to the low-risk group. CONCLUSIONS: P53 and ASRGL1 immunoprofiling stratifies EEC patients into three risk groups with significantly different outcomes. This simple and easily applicable panel could provide a useful tool in EEC risk stratification and guiding the allocation of treatment modalities.

Asparaginase-like protein 1 is an independent prognostic marker in primary endometrial cancer, and is frequently lost in metastatic lesions.

OBJECTIVE: Loss of Asparaginase-like protein 1 (ASRGL1) has been suggested as a prognostic biomarker in endometrial carcinoma. Our objective was to validate this in a prospectively collected, independent patient cohort, and evaluate ASRGL1 expression in endometrial carcinoma precursor lesion and metastases. METHODS: 782 primary endometrial carcinomas, 90 precursor lesions (complex atypical hyperplasia), and 179 metastases (from 87 patients) were evaluated for ASRGL1 expression by immunohistochemistry in relation to clinical and histopathological data. ASRGL1 mRNA level was investigated in 237 primary tumors and related to survival and ASRGL1 protein expression. RESULTS: Low expression of ASRGL1 protein and ASRGL1 mRNA predicted poor disease specific survival (P<0.001). In multivariate survival analyses ASRGL1 had independent prognostic value both in the whole patient cohort (Hazard ratio (HR): 1.53, 95% confidence interval (CI): 1.04-2.26, P=0.031) and within the endometrioid subgroup (HR: 2.64, CI: 1.47-4.74, P=0.001). Low ASRGL1 expression was less frequent in patients with low grade endometrioid primary tumors compared to high grade endometrioid and non-endometrioid primary tumors, and ASRGL1 was lost in the majority of metastatic lesions. CONCLUSIONS: In a prospective setting ASRGL1 validates as a strong prognostic biomarker in endometrial carcinoma. Loss of ASRGL1 is associated with aggressive disease and poor survival, and is demonstrated for the first time to have independent prognostic value in the entire endometrial carcinoma patient population.

U-CAN: a prospective longitudinal collection of biomaterials and clinical information from adult cancer patients in Sweden.

BACKGROUND: Progress in cancer biomarker discovery is dependent on access to high-quality biological materials and high-resolution clinical data from the same cases. To overcome current limitations, a systematic prospective longitudinal sampling of multidisciplinary clinical data, blood and tissue from cancer patients was therefore initiated in 2010 by Uppsala and Umeå Universities and involving their corresponding University Hospitals, which are referral centers for one third of the Swedish population. MATERIAL AND METHODS: Patients with cancer of selected types who are treated at one of the participating hospitals are eligible for inclusion. The healthcare-integrated sampling scheme encompasses clinical data, questionnaires, blood, fresh frozen and formalin-fixed paraffin-embedded tissue specimens, diagnostic slides and radiology bioimaging data. RESULTS: In this ongoing effort, 12,265 patients with brain tumors, breast cancers, colorectal cancers, gynecological cancers, hematological malignancies, lung cancers, neuroendocrine tumors or prostate cancers have been included until the end of 2016. From the 6914 patients included during the first five years, 98% were sampled for blood at diagnosis, 83% had paraffin-embedded and 58% had fresh frozen tissues collected. For Uppsala County, 55% of all cancer patients were included in the cohort. CONCLUSIONS: Close collaboration between participating hospitals and universities enabled prospective, longitudinal biobanking of blood and tissues and collection of multidisciplinary clinical data from cancer patients in the U-CAN cohort. Here, we summarize the first five years of operations, present U-CAN as a highly valuable cohort that will contribute to enhanced cancer research and describe the procedures to access samples and data.

Targeting tumor cells based on Phosphodiesterase 3A expression.

We and others have previously reported a correlation between high phosphodiesterase 3A (PDE3A) expression and selective sensitivity to phosphodiesterase (PDE) inhibitors. This indicates that PDE3A could serve both as a drug target and a biomarker of sensitivity to PDE3 inhibition. In this report, we explored publicly available mRNA gene expression data to identify cell lines with different PDE3A expression. Cell lines with high PDE3A expression showed marked in vitro sensitivity to PDE inhibitors zardaverine and quazinone, when compared with those having low PDE3A expression. Immunofluorescence and immunohistochemical stainings were in agreement with PDE3A mRNA expression, providing suitable alternatives for biomarker analysis of clinical tissue specimens. Moreover, we here demonstrate that tumor cells from patients with ovarian carcinoma show great variability in PDE3A protein expression and that level of PDE3A expression is correlated with sensitivity to PDE inhibition. Finally, we demonstrate that PDE3A is highly expressed in subsets of patient tumor cell samples from different solid cancer diagnoses and expressed at exceptional levels in gastrointestinal stromal tumor (GIST) specimens. Importantly, vulnerability to PDE3 inhibitors has recently been associated with co-expression of PDE3A and Schlafen family member 12 (SLFN12). We here demonstrate that high expression of PDE3A in clinical specimens, at least on the mRNA level, seems to be frequently associated with high SLFN12 expression. In conclusion, PDE3A seems to be both a promising biomarker and drug target for individualized drug treatment of various cancers.

A systematic search strategy identifies cubilin as independent prognostic marker for renal cell carcinoma.

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.

Expression of possible targets for new proteasome inhibitors in diffuse large B-cell lymphoma.

OBJECTIVES: Investigating expression of possible targets for proteasome inhibitors in patients with diffuse large B-cell lymphoma (DLBCL) and correlating the findings to clinical parameters and outcome. METHODS: Tumour material from 92 patients with DLBCL treated with either R-CHOP like (n = 69) or CHOP like (n = 23) regimens were stained for possible targets of proteasome inhibitors. RESULTS: The primary target molecule of bortezomib, proteasome subunit beta, type 5 (PSMB5), was not detected in the tumour cells in any of the cases but showed an abundant expression in cells in the microenvironment. However, the deubiquitinases (DUBs) of the proteasome, the ubiquitin carboxyl-terminal hydrolase L5 (UCHL5) and the ubiquitin specific peptidase 14 (USP14), were detected in the cytoplasm of the tumour cells in 77% and 74% of the cases, respectively. The adhesion regulating molecule 1 (ADRM1) was detected in 98% of the cases. There was no correlation between the expression of any of the studied markers and clinical outcome or GC/non-GC phenotype. CONCLUSIONS: We suggest that UCHL5 and/or USP14 should be further evaluated as new targets for proteasome inhibitors in DLBCL. The lack of expression of PSMB5 on the tumour cells might provide an explanation of the relatively poor results of bortezomib in DLBCL.

Cetuximab sensitivity of head and neck squamous cell carcinoma xenografts is associated with treatment-induced reduction in EGFR, pEGFR, and pSrc.

BACKGROUND: The aims of this study were to validate in vitro drug sensitivity testing of head and neck squamous cell carcinoma (HNSCC) cell lines in an in vivo xenograft model and to identify treatment-induced changes in the epidermal growth factor receptor (EGFR) signaling pathway that could be used as markers for cetuximab treatment response. MATERIALS AND METHODS: The in vitro and in vivo cetuximab sensitivity of two HNSCC cell lines, UT-SCC-14 and UT-SCC-45, was assessed using a crystal violet assay and xenografts in nude mice, respectively. The expression of EGFR, phosphorylated EGFR (pEGFR), phosphorylated Src (pSrc), and Ki-67 was investigated by immunohistochemistry. To verify these results, the in vitro expression of EGFR and pEGFR was analyzed with ELISA in a panel of 10 HNSCC cell lines. RESULTS: A close correlation was found between in vitro and in vivo cetuximab sensitivity data in the two investigated HNSCC cell lines. In treatment sensitive UT-SCC-14 xenografts, there was a decrease in EGFR, pEGFR, and pSrc upon cetuximab treatment. Interestingly, in insensitive UT-SCC-45 xenografts, an increased expression of these three proteins was found. The change in EGFR and pEGFR expression in vivo was confirmed in cetuximab-sensitive and cetuximab-insensitive HNSCC cell lines using ELISA. CONCLUSION: High sensitivity to cetuximab was strongly associated with a treatment-induced reduction in pEGFR both in vivo and in vitro in a panel of HNSCC cell lines, suggesting that EGFR and pEGFR dynamics could be used as a predictive biomarker for cetuximab treatment response.

Loss of ASRGL1 expression is an independent biomarker for disease-specific survival in endometrioid endometrial carcinoma.

OBJECTIVE: For endometrial carcinoma, prognostic stratification methods do not satisfactorily identify patients with adverse outcome. Currently, histology, tumor grade and stage are used to tailoring surgical treatment and to determine the need for adjuvant treatment. Low-risk patients are not considered to require adjuvant therapy or staging lymphadenectomy. For patients with intermediate or high risk, some guidelines recommend tailoring adjuvant treatment according to additional negative prognostic factors. Our objective was to evaluate the biomarker potential of the ASRGL1 protein in endometrial carcinoma. METHODS: Using The Human Protein Atlas (www.proteinatlas.org), the l-asparaginase (ASRGL1) protein was identified as an endometrial carcinoma biomarker candidate. ASRGL1 expression was immunohistochemically evaluated with an extensively validated antibody on two independent endometrial carcinoma cohorts (n=229 and n=286) arranged as tissue microarrays. Staining results were correlated with clinical features. RESULTS: Reduced expression of ASRGL1, defined as <75% positively stained tumor cells, was significantly associated with poor prognosis and reduced disease-specific survival in endometrioid endometrial adenocarcinoma (EEA). In multivariate analysis the hazard ratios for disease-specific survival were 3.55 (95% CI=1.10-11.43; p=0.003) and 3.23 (95% CI=1.53-6.81; p=0.002) in the two cohorts, respectively. Of the 48 cases with Grade 3 Stage I tumor all disease-related deaths were associated with low ASRGL1 expression. CONCLUSIONS: Loss of ASRGL1 in EEA is a powerful biomarker for poor prognosis and retained ASRGL1 has a positive impact on survival. ASRGL1 immunohistochemistry has potential to become an additional tool for prognostication in cases where tailoring adjuvant treatment according to additional prognostic factors besides grade and stage is recommended.

FGF2 as a potential prognostic biomarker for proneural glioma patients.

BACKGROUND: The survival of high-grade glioma patients is poor and the treatment of these patients can cause severe side effects. This fosters the necessity to identify prognostic biomarkers, in order to optimize treatment and diminish unnecessary suffering of patients. The aim of this study was to identify prognostic biomarkers for high-grade glioma patients. METHODS: Eleven proteins were selected for analysis due to their suggested importance for survival of patients with other types of cancers and due to a high variation in protein levels between glioma patients (according to the Human Protein Atlas, www.proteinatlas.org). Protein expression patterns of these 11 proteins were analyzed by immunohistochemistry in tumor samples from 97 high-grade glioma patients. The prognostic values of the proteins were analyzed with univariate and multivariate Cox regression analyses for the high-grade glioma patients, including subgroup analyses of histological subtypes and immunohistochemically defined molecular subtypes. RESULTS: The proteins with the most significant (univariate and multivariate p<0.05) correlations were analyzed further with cross-validated Kaplan-Meier analyses for the possibility of predicting survival based on the protein expression pattern of the corresponding candidate. Random Forest classification with variable subset selection was used to analyze if a protein signature consisting of any combination of the 11 proteins could predict survival for the high-grade glioma patients and the subgroup with glioblastoma patients. The proteins which correlated most significantly (univariate and multivariate p<0.05) to survival in the Cox regression analyses were Myc for all high-grade gliomas and FGF2, CA9 and CD44 for the subgroup of proneural gliomas, with FGF2 having a strong negative predictive value for survival. No prognostic signature of the proteins could be found. CONCLUSION: FGF2 is a potential prognostic biomarker for proneural glioma patients, and warrants further investigation.

A study of embryonic stem cell-related proteins in human astrocytomas: identification of Nanog as a predictor of survival.

Recent studies suggest that the regulatory networks controlling the functions of stem cells during development may be abnormally active in human cancers. An embryonic stem cell (ESC) gene signature was found to correlate with a more undifferentiated phenotype of several human cancer types including gliomas, and associated with poor prognosis in breast cancer. In the present study, we used tissue microarrays of 80 low-grade (WHO Grade II) and 98 high-grade human gliomas (WHO Grades III and IV) to investigate the presence of the ESC-related proteins Nanog, Klf4, Oct4, Sox2 and c-Myc by immunohistochemistry. While similar patterns of co-expressed proteins between low- and high-grade gliomas were present, we found up-regulated protein levels of Nanog, Klf4, Oct4 and Sox2 in high-grade gliomas. Survival analysis by Kaplan-Meier analysis revealed a significant shorter survival in the subgroups of low-grade astrocytomas (n = 42) with high levels of Nanog protein (p = 0.0067) and of Klf4 protein (p = 0.0368), in high-grade astrocytomas (n = 85) with high levels of Nanog (p = 0.0042), Klf4 (p = 0.0447), and c-Myc (p = 0.0078) and in glioblastomas only (n = 71) with high levels of Nanog (p = 0.0422) and of c-Myc (p = 0.0256). In the multivariate model, Nanog was identified as an independent prognostic factor in the subgroups of low-grade astrocytomas (p = 0.0039), high-grade astrocytomas (p = 0.0124) and glioblastomas only (p = 0.0544), together with established clinical variables in these tumors. These findings provide further evidence for the joint regulatory pathways of ESC-related proteins in gliomas and identify Nanog as one of the key players in determining clinical outcome of human astrocytomas.

Subtyping of gliomas of various WHO grades by the application of immunohistochemistry.

AIMS: In 2010, four subtypes (classical, proneural, mesenchymal, and neural) of glioblastoma multiforme (GBM) were defined by molecular genetic analyses. The objective of this study was to assess whether gliomas, independently of the type and grade, could be subdivided into protein-based subtypes. METHODS AND RESULTS: A tissue microarray (TMA) approach was applied to incorporate tissue samples of low-grade and high-grade gliomas into five TMAs. High expression levels of epidermal growth factor receptor (EGFR), CD44, c-MER proto-oncogene tyrosine kinase (MERTK), platelet-derived growth factor receptor α, p53, oligodendrocyte transcription factor 2 (OLIG2) and isocitrate dehydrogenase 1 with the R132H mutation were assessed using immunohistochemistry (IHC). Glioma could be subdivided into four subtypes by IHC. The majority of the low-grade gliomas were of the proneural subtype, i.e. high p53 expression (63% of grade II). The classical subtype, with high EGFR and low p53 expression, was most common in GBMs (39%), followed by the proneural (29%) and mesenchymal (with high CD44 and MERTK expression) (29%) subtypes, a frequency that is in line with previously published data based on molecular genetics. CONCLUSIONS: Assessment of the expression of the five proteins EGFR, CD44, MERTK, p53 and OLIG2 is sufficient for subtyping gliomas, and can be recommended for implementation in clinical practice for both low-grade and high-grade gliomas.

A systematic analysis of commonly used antibodies in cancer diagnostics.

AIMS: Immunohistochemistry plays a pivotal role in cancer differential diagnostics. To identify the primary tumour from a metastasis specimen remains a significant challenge, despite the availability of an increasing number of antibodies. The aim of the present study was to provide evidence-based data on the diagnostic power of antibodies used frequently for clinical differential diagnostics. METHODS AND RESULTS: A tissue microarray cohort comprising 940 tumour samples, of which 502 were metastatic lesions, representing tumours from 18 different organs and four non-localized cancer types, was analysed using immunohistochemistry with 27 well-established antibodies used in clinical differential diagnostics. Few antibodies, e.g. prostate-specific antigen and thyroglobulin, showed a cancer type-related sensitivity and specificity of more than 95%. A majority of the antibodies showed a low degree of sensitivity and specificity for defined cancer types. Combinations of antibodies provided limited added value for differential diagnostics of cancer types. CONCLUSIONS: The results from analysing 27 diagnostic antibodies on consecutive sections of 940 defined tumours provide a unique repository of data that can empower a more optimal use of clinical immunohistochemistry. Our results highlight the benefit of immunohistochemistry and the unmet need for novel markers to improve differential diagnostics of cancer.