Sensitive and Specific Analyses of Colorectal Cancer Recurrence through Multiplex superRCA Mutation Detection in Blood Plasma.

Mutation analysis of circulating tumor DNA (ctDNA) has applications in monitoring of colorectal cancer (CRC) patients for recurrence. Considering the low tumor fraction of ctDNA in cell-free DNA (cfDNA) isolated from blood plasma, the sensitivity of the detection method is important. Here, plasma DNA collected at diagnosis and follow-up from 25 CRC patients was analyzed using a multiplex superRCA mutation detection assay. The assay was also performed on genomic DNA (gDNA) from tumor and normal tissue from 20 of these patients. The lower limit of detection for most sequence variants was in the range of 10-5, while when analyzing cfDNA from plasma with a typical input of 33 ng, the practical detection limit was ~10-4 or 0.01% mutant allele frequency (MAF). In 17 of 19 patients with identified hotspot mutations in tumor gDNA, at least one hotspot mutation could be detected in plasma DNA at the time of diagnosis. The MAF increased at subsequent time points in four of the patients who experienced a clinical relapse. Multiplex superRCA analysis of the remaining six patients did not reveal any hotspot mutations. In conclusion, multiplex superRCA assays proved suitable for monitoring CRC patients by analyzing hotspot mutations in cfDNA, and dynamic changes in MAF were observed in patients with clinical relapse.

Next generation pan-cancer blood proteome profiling using proximity extension assay.

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.

An immune score reflecting pro- and anti-tumoural balance of tumour microenvironment has major prognostic impact and predicts immunotherapy response in solid cancers.

BACKGROUND: Cancer immunity is based on the interaction of a multitude of cells in the spatial context of the tumour tissue. Clinically relevant immune signatures are therefore anticipated to fundamentally improve the accuracy in predicting disease progression. METHODS: Through a multiplex in situ analysis we evaluated 15 immune cell classes in 1481 tumour samples. Single-cell and bulk RNAseq data sets were used for functional analysis and validation of prognostic and predictive associations. FINDINGS: By combining the prognostic information of anti-tumoural CD8+ lymphocytes and tumour supportive CD68+CD163+ macrophages in colorectal cancer we generated a signature of immune activation (SIA). The prognostic impact of SIA was independent of conventional parameters and comparable with the state-of-art immune score. The SIA was also associated with patient survival in oesophageal adenocarcinoma, bladder cancer, lung adenocarcinoma and melanoma, but not in endometrial, ovarian and squamous cell lung carcinoma. We identified CD68+CD163+ macrophages as the major producers of complement C1q, which could serve as a surrogate marker of this macrophage subset. Consequently, the RNA-based version of SIA (ratio of CD8A to C1QA) was predictive for survival in independent RNAseq data sets from these six cancer types. Finally, the CD8A/C1QA mRNA ratio was also predictive for the response to checkpoint inhibitor therapy. INTERPRETATION: Our findings extend current concepts to procure prognostic information from the tumour immune microenvironment and provide an immune activation signature with high clinical potential in common human cancer types. FUNDING: Swedish Cancer Society, Lions Cancer Foundation, Selanders Foundation, P.O. Zetterling Foundation, U-CAN supported by SRA CancerUU, Uppsala University and Region Uppsala.

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.

Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer.

BACKGROUND: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. METHODS: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). RESULTS: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. CONCLUSIONS: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.

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.

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.

The Immune Landscape of Colorectal Cancer.

While the clinical importance of CD8+ and CD3+ cells in colorectal cancer (CRC) is well established, the impact of other immune cell subsets is less well described. We sought to provide a detailed overview of the immune landscape of CRC in the largest study to date in terms of patient numbers and in situ analyzed immune cell types. Tissue microarrays from 536 patients were stained using multiplexed immunofluorescence panels, and fifteen immune cell subclasses, representing adaptive and innate immunity, were analyzed. Overall, therapy-naïve CRC patients clustered into an 'inflamed' and a 'desert' group. Most T cell subsets and M2 macrophages were enriched in the right colon (p-values 0.046-0.004), while pDC cells were in the rectum (p = 0.008). Elderly patients had higher infiltration of M2 macrophages (p = 0.024). CD8+ cells were linked to improved survival in colon cancer stages I-III (q = 0.014), while CD4+ cells had the strongest impact on overall survival in metastatic CRC (q = 0.031). Finally, we demonstrated repopulation of the immune infiltrate in rectal tumors post radiation, following an initial radiation-induced depletion. This study provides a detailed analysis of the in situ immune landscape of CRC paving the way for better diagnostics and providing hints to better target the immune microenvironment.

The prognostic impact of the tumour stroma fraction: A machine learning-based analysis in 16 human solid tumour types.

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. FUNDING: The Swedish Cancer Society, The Lions Cancer Foundation Uppsala, The Swedish Government Grant for Clinical Research, The Mrs Berta Kamprad Foundation, Sweden, Sellanders foundation, P.O.Zetterling Foundation, and The Sjöberg Foundation, Sweden.

CDX2: A Prognostic Marker in Metastatic Colorectal Cancer Defining a Better BRAF Mutated and a Worse KRAS Mutated Subgroup.

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.

Lipogenic signalling modulates prostate cancer cell adhesion and migration via modification of Rho GTPases.

Fatty acid synthase (FASN) is commonly overexpressed in prostate cancer and associated with tumour progression. FASN is responsible for de novo synthesis of the fatty acid palmitate; the building block for protein palmitoylation. Recent work has suggested that alongside its established role in promoting cell proliferation FASN may also promote invasion. We now find depletion of FASN expression increases prostate cancer cell adhesiveness, impairs HGF-mediated cell migration and reduces 3D invasion. These changes in motility suggest that FASN can mediate actin cytoskeletal remodelling; a process known to be downstream of Rho family GTPases. Here, we demonstrate that modulation of FASN expression specifically impacts on the palmitoylation of the atypical GTPase RhoU. Impaired RhoU activity in FASN depleted cells leads to reduced adhesion turnover downstream of paxillin serine phosphorylation, which is rescued by addition of exogenous palmitate. Moreover, canonical Cdc42 expression is dependent on the palmitoylation status of RhoU. Thus we uncover a novel relationship between FASN, RhoU and Cdc42 that directly influences cell migration potential. These results provide compelling evidence that FASN activity directly promotes cell migration and supports FASN as a potential therapeutic target in metastatic prostate cancer.

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.

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.

Consequences of a high incidence of microsatellite instability and BRAF-mutated tumors: A population-based cohort of metastatic colorectal cancer patients.

BACKGROUND: Immunotherapy for patients with microsatellite-instable (MSI-H) tumors or BRAF-inhibitors combination treatment for BRAF-mutated (mutBRAF) tumors in metastatic colorectal cancer (mCRC) is promising, but the frequency of these molecular changes in trial patients are low. Unselected population-based studies of these molecular changes are warranted. METHODS: A population-based cohort of 798 mCRC patients in Scandinavia was studied. Patient and molecular tumor characteristics, overall survival (OS) and progression-free survival (PFS) were estimated. RESULTS: Here, 40/583 (7%) tumor samples were MSI-H and 120/591 (20%) were mutBRAF; 87% of MSI-H tumors were mutBRAF (non-Lynch). Elderly (>75 years) had more often MSI-H (10% vs 6%) and MSI-H/mutBRAF (9% vs 4%) tumors. Response rate (5% vs 44%), PFS (4 vs 8 months), and OS (9 vs 18 months) after first-line chemotherapy was all significantly lower in patients with MSI-H compared to patients with microsatellite stable tumors. MSI-H and mutBRAF were both independent poor prognostic predictors for OS (P = 0.049, P < 0.001) and PFS (P = 0.045, P = 0.005) after first-line chemotherapy. Patients with MSI-H tumors received less second-line chemotherapy (15% vs 37%, P = 0.005). CONCLUSIONS: In unselected mCRC patients, MSI-H and mutBRAF cases were more common than previously reported. Patients with MSI-H tumors had worse survival, less benefit from chemotherapy, and they differed considerably from recent third-line immunotherapy trial patients as they were older and most had mutBRAF tumor (non-Lynch).

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.

Affibody-derived drug conjugates: Potent cytotoxic molecules for treatment of HER2 over-expressing tumors.

Patients with HER2-positive tumors often suffer resistance to therapy, warranting development of novel treatment modalities. Affibody molecules are small affinity proteins which can be engineered to bind to desired targets. They have in recent years been found to allow precise targeting of cancer specific molecular signatures such as the HER2 receptor. In this study, we have investigated the potential of an affibody molecule targeting HER2, ZHER2:2891, conjugated with the cytotoxic maytansine derivate MC-DM1, for targeted cancer therapy. ZHER2:2891 was expressed as a monomer (ZHER2:2891), dimer ((ZHER2:2891)2) and dimer with an albumin binding domain (ABD) for half-life extension ((ZHER2:2891)2-ABD). All proteins had a unique C-terminal cysteine that could be used for efficient and site-specific conjugation with MC-DM1. The resulting affibody drug conjugates were potent cytotoxic molecules for human cells over-expressing HER2, with sub-nanomolar IC50-values similar to trastuzumab emtansine, and did not affect cells with low HER2 expression. A biodistribution study of a radiolabeled version of (ZHER2:2891)2-ABD-MC-DM1, showed that it was taken up by the tumor. The major site of off-target uptake was the kidneys and to some extent the liver. (ZHER2:2891)2-ABD-MC-DM1 was found to have a half-life in circulation of 14 h. The compound was tolerated well by mice at 8.5 mg/kg and was shown to extend survival of mice bearing HER2 over-expressing tumors. The findings in this study show that affibody molecules are a promising class of engineered affinity proteins to specifically deliver small molecular drugs to cancer cells and that such conjugates are potential candidates for clinical evaluation on HER2-overexpressing cancers.

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.