Distinct Infiltration of T Cell Populations in Bladder Cancer Molecular Subtypes.

Bladder cancer is a heterogenous disease, and molecular subtyping is a promising method to capture this variability. Currently, the immune compartment in relation to subtypes is poorly characterized. Here, we analyzed the immune compartment in bladder tumors and normal bladder urothelium with a focus on T cell subpopulations using flow cytometry and RNA sequencing. The results were investigated in relation to tumor invasiveness (NMIBC/MIBC) and molecular subtypes according to the Lund Taxonomy system. Whereas the NMIBC/MIBC differed in the overall immune infiltration only, the molecular subtypes differed both in terms of immune infiltration and immune compartment compositions. The Basal/Squamous (Ba/Sq) and genomically unstable (GU) tumors displayed increased immune infiltration compared to urothelial-like (Uro) tumors. Additionally, the GU tumors had a higher proportion of regulatory T cells within the immune compartment compared to Uro tumors. Furthermore, sequencing showed higher levels of exhaustion in CD8+ T cells from GU tumors compared to both Uro tumors and the control. Although no such difference was detected at the transcriptomic level in Uro tumors compared to the controls, CD8+ T cells in Uro tumors showed higher expression of several exhaustion markers at the protein level. Taken together, our findings indicate that depending on the molecular subtype, different immunotherapeutic interventions might be warranted.

One-year recovery from breast cancer: Importance of tumor and treatment-related factors, resilience, and sociodemographic factors for health-related quality of life.

Aim: This study investigated the changes in health-related quality of life from diagnosis to 1 year after diagnosis in breast cancer (BC) patients and the influence of clinical, psychological, and sociodemographic variables. An additional aim was to explore the mediating and moderating effects of resilience on changes in health-related quality of life. Methods: A longitudinal population-based study was conducted in southern Sweden. Newly diagnosed BC patients filled in measures of health-related quality of life, resilience, and sociodemographic variables at diagnosis (N = 980) and 1 year post-diagnosis (N = 780). Clinical variables were extracted from the Swedish national breast cancer quality registry. Mixed-model analyses were performed. Results: Most health-related quality of life outcomes declined from diagnosis to 1 year post-diagnosis. Role limitations due to emotional problems remained the same, whereas mental health improved. Lower health-related quality of life outcomes were associated with symptomatic detection and axillary dissection. Patients with a higher TNM stage and histologic grade and estrogen receptor (ER)-negative and human epidermal growth factor 2 (HER2)-positive status, who received chemotherapy, antibody therapy, or bisphosphonate therapy, had a steeper decline in outcomes. Changes in resilience were positively associated with all outcomes but did not mediate or moderate changes in any. Resilience at baseline moderated changes in bodily pain, vitality, and mental health, with higher baseline resilience being associated with a steeper decline, possibly due to floor or ceiling effects. Patients with lower socioeconomic status, educational level, and older age had a lower health-related quality of life. Conclusion: Physical health-related quality of life among breast cancer patients declined 1 year post-diagnosis, whereas mental health-related quality of life improved. Low resilient patients may be especially vulnerable at diagnosis. Biopsychosocial assessment at diagnosis can help identify patients who may require additional support. A multidimensional treatment plan should be started early to help overcome the problems in everyday activities.

Transcriptional profiling demonstrates altered characteristics of CD8+ cytotoxic T-cells and regulatory T-cells in TP53-mutated acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) patients have limited effect from T-cell-based therapies, such as PD-1 and CTLA-4 blockade. However, recent data indicate that AML patients with TP53 mutation have higher immune infiltration and other immunomodulatory therapies could thus potentially be effective. Here, we performed the transcriptional analysis of distinct T-cell subpopulations from TP53-mutated AML to identify gene expression signatures suggestive of altered functional properties. METHODS: CD8+ cytotoxic T lymphocytes (CTLs), conventional helper T cells (Th), and regulatory T cells (Tregs) were sorted from peripheral blood of AML patients with TP53 mutation (n = 5) and healthy donors (n = 3), using FACS, and the different subpopulations were subsequently subjected to RNA-sequencing. Differentially expressed genes were identified and gene set enrichment analysis (GSEA) was performed to outline altered pathways and exhaustion status. Also, expression levels for a set of genes encoding established and emerging immuno-oncological targets were defined. RESULTS: The results showed altered transcriptional profiles for each of the T-cell subpopulations from TP53-mutated AML as compared to control subjects. IFN-α and IFN-γ signaling were stronger in TP53-mutated AML for both CTLs and Tregs. Furthermore, in TP53-mutated AML as compared to healthy controls, Tregs showed gene expression signatures suggestive of metabolic adaptation to their environment, whereas CTLs exhibited features of exhaustion/dysfunction with a stronger expression of TIM3 as well as enrichment of a gene set related to exhaustion. CONCLUSIONS: The results provide insights on mechanisms underlying the inadequate immune response to leukemic cells in TP53-mutated AML and open up for further exploration toward novel treatment regimens for these patients.

Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers.

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.

Identification of a serum biomarker signature associated with metastatic prostate cancer.

PURPOSE: Improved early diagnosis and determination of aggressiveness of prostate cancer (PC) is important to select suitable treatment options and to decrease over-treatment. The conventional marker is total prostate specific antigen (PSA) levels in blood, but lacks specificity and ability to accurately discriminate indolent from aggressive disease. EXPERIMENTAL DESIGN: In this study, we sought to identify a serum biomarker signature associated with metastatic PC. We measured 157 analytes in 363 serum samples from healthy subjects, patients with non-metastatic PC and patients with metastatic PC, using a recombinant antibody microarray. RESULTS: A signature consisting of 69 proteins differentiating metastatic PC patients from healthy controls was identified. CONCLUSIONS AND CLINICAL RELEVANCE: The clinical value of this biomarker signature requires validation in larger independent patient cohorts before providing a new prospect for detection of metastatic PC.

The Value of a New Diagnostic Test for Prostate Cancer: A Cost-Utility Analysis in Early Stage of Development.

BACKGROUND: Standard biopsy for prostate cancer diagnosis is an unpleasant and sometimes painful procedure with a detection rate as low as around 50%. Consequently, an accurate blood-based test would be highly desirable to improve the predictive accuracy. However, the clinical value of a new blood test for diagnosing prostate cancer depends on its sensitivity and specificity, in relation to the selected target population. OBJECTIVE: The aim of this analysis was to investigate the health-economic value of introducing a new and more accurate diagnostic blood-based test to identify men in need of a biopsy to diagnose prostate cancer. METHOD: We developed a Discrete Event Simulation Model with outputs including number of biopsies, cancer diagnosis, treatments and prostate cancer deaths. The analysis was performed from a health care perspective. It used epidemiologic data, treatment patterns, and health care costs from the Swedish region Skåne (population of 1.3 million). A 90% sensitivity and specificity of the new test was assumed. RESULTS: Among 31,250 men, age 50-69 years, 16.4% had a PSA between 3.0 and 9.9 µg/L and 28.9% a PSA of 2.0-9.9 µg/L. Testing men with PSA 3.0-9.9 µg/L, as in current clinical practice, decreased the number of biopsies by 3595, detected 61 more cancers, resulting in and two more fatalities and subsequently a loss of 14 QALYs. Cost offsets could justify a test value of SEK 4996. Testing a larger population, PSA 2.0-9.9 µg/L prevented 6 deaths, added 50 QALYs, and could justify a value of the test of SEK 5165, given a value of health of SEK 500,000 per QALY. CONCLUSION: A new blood-based test for prostate cancer has a significant potential to reduce the number of biopsies needed, resulting in reduced health care costs and improve patient care.

Multiplex profiling of serum proteins in solution using barcoded antibody fragments and next generation sequencing.

The composition of serum proteins is reflecting the current health status and can, with the right tools, be used to detect early signs of disease, such as an emerging cancer. An earlier diagnosis of cancer would greatly increase the chance of an improved outcome for the patients. However, there is still an unmet need for proficient tools to decipher the information in the blood proteome, which calls for further technological development. Here, we present a proof-of-concept study that demonstrates an alternative approach for multiplexed protein profiling of serum samples in solution, using DNA barcoded scFv antibody fragments and next generation sequencing. The outcome shows high accuracy when discriminating samples derived from pancreatic cancer patients and healthy controls and represents a scalable alternative for serum analysis.

Serum Biomarker Signature-Based Liquid Biopsy for Diagnosis of Early-Stage Pancreatic Cancer.

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival of < 10% because of diffuse symptoms leading to late-stage diagnosis. That survival could increase significantly if localized tumors could be detected early. Therefore, we used multiparametric analysis of blood samples to obtain a novel biomarker signature of early-stage PDAC. The signature was derived from a large patient cohort, including patients with well-defined early-stage (I and II) PDAC. This biomarker signature was validated subsequently in an independent patient cohort. PATIENTS AND METHODS: The biomarker signature was derived from a case-control study, using a Scandinavian cohort, consisting of 16 patients with stage I, 132 patients with stage II, 65 patients with stage III, and 230 patients with stage IV PDAC, and 888 controls. This signature was validated subsequently in an independent case-control cohort in the United States with 15 patients with stage I, 75 patients with stage II, 15 patients with stage III, and 38 patients with stage IV PDAC, and 219 controls. An antibody microarray platform was used to identify the serum biomarker signature associated with early-stage PDAC. RESULTS: Using the Scandinavian case-control study, a biomarker signature was created, discriminating samples derived from patients with stage I and II from those from controls with a receiver operating characteristic area under the curve value of 0.96. This signature, consisting of 29 biomarkers, was then validated in an independent case-control study in the United States. The biomarker signature could discriminate patients with stage I and II PDAC from controls in this independent patient cohort with a receiver operating characteristic area under the curve value of 0.96. CONCLUSION: This serum biomarker signature might represent a tenable approach to detecting early-stage, localized PDAC if these findings are supported by a prospective validation study.

A multicenter study investigating the molecular fingerprint of psychological resilience in breast cancer patients: study protocol of the SCAN-B resilience study.

BACKGROUND: Individual patients differ in their psychological response when receiving a cancer diagnosis, in this case breast cancer. Given the same disease burden, some patients master the situation well, while others experience a great deal of stress, depression and lowered quality of life. Patients with high psychological resilience are likely to experience fewer stress reactions and better adapt to and manage the life threat and the demanding treatment that follows the diagnosis. If this phenomenon of mastering difficult situations is reflected also in biomolecular processes is not much studied, nor has its capacity for impacting the cancer prognosis been addressed. This project specifically aims, for the first time, to investigate how a breast cancer patient's psychological resilience is coupled to biomolecular parameters using advanced "omics" and, as a secondary aim, whether it relates to prognosis and quality of life one year after diagnosis. METHOD: The study population consists of newly diagnosed breast cancer patients enrolled in the Sweden Cancerome Analysis Network - Breast (SCAN-B) at four hospitals in Sweden. At the time of cancer diagnosis, the patient fills out the standardized method to measure psychological resilience, the "Connor-Davidson Resilience scale" (CD-RISC), the quality of life measure SF-36, as well as providing social and socioeconomic variables. In addition, one blood sample is collected. At the one-year follow-up, the patient will be subjected to the same assessments, and we also collect information regarding smoking, exercise habits, and BMI, as well as patients' trust in the treatment and their satisfaction with the care and treatment. DISCUSSION: This explorative hypothesis-generating project will pave the way for larger validation studies, potentially leading to a standardized method of measuring psychological resilience as an important parameter in cancer care. Revealing the body-mind interaction, in terms of psychological resilience and quality of life, will herald the development of truly personalized psychosocial care and cancer intervention treatment strategies. TRIAL REGISTRATION: This is a retrospectively registered trial at ClinicalTrials.gov, ID: NCT03430492 on February 6, 2018.

The Interface of Pancreatic Cancer With Diabetes, Obesity, and Inflammation: Research Gaps and Opportunities: Summary of a National Institute of Diabetes and Digestive and Kidney Diseases Workshop.

A workshop on "The Interface of Pancreatic Cancer with Diabetes, Obesity, and Inflammation: Research Gaps and Opportunities" was held by the National Institute of Diabetes and Digestive and Kidney Diseases on October 12, 2017. The purpose of the workshop was to explore the relationship and possible mechanisms of the increased risk of pancreatic ductal adenocarcinoma (PDAC) related to diabetes, the role of altered intracellular energy metabolism in PDAC, the mechanisms and biomarkers of diabetes caused by PDAC, the mechanisms of the increased risk of PDAC associated with obesity, and the role of inflammatory events and mediators as contributing causes of the development of PDAC. Workshop faculty reviewed the state of the current knowledge in these areas and made recommendations for future research efforts. Further knowledge is needed to elucidate the basic mechanisms contributing to the role of hyperinsulinemia, hyperglycemia, adipokines, and acute and chronic inflammatory events on the development of PDAC.

Tumor tissue protein signatures reflect histological grade of breast cancer.

Histological grade is one of the most commonly used prognostic factors for patients diagnosed with breast cancer. However, conventional grading has proven technically challenging, and up to 60% of the tumors are classified as histological grade 2, which represents a heterogeneous cohort less informative for clinical decision making. In an attempt to study and extend the molecular puzzle of histologically graded breast cancer, we have in this pilot project searched for additional protein biomarkers in a new space of the proteome. To this end, we have for the first time performed protein expression profiling of breast cancer tumor tissue, using recombinant antibody microarrays, targeting mainly immunoregulatory proteins. Thus, we have explored the immune system as a disease-specific sensor (clinical immunoproteomics). Uniquely, the results showed that several biologically relevant proteins reflecting histological grade could be delineated. In more detail, the tentative biomarker panels could be used to i) build a candidate model classifying grade 1 vs. grade 3 tumors, ii) demonstrate the molecular heterogeneity among grade 2 tumors, and iii) potentially re-classify several of the grade 2 tumors to more like grade 1 or grade 3 tumors. This could, in the long-term run, lead to improved prognosis, by which the patients could benefit from improved tailored care.

Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

Plasma protein profiling in a stage defined pancreatic cancer cohort - Implications for early diagnosis.

Pancreatic ductal adenocarcinoma (PDAC) is a disease where detection preceding clinical symptoms significantly increases the life expectancy of patients. In this study, a recombinant antibody microarray platform was used to analyze 213 Chinese plasma samples from PDAC patients and normal control (NC) individuals. The cohort was stratified according to disease stage, i.e. resectable disease (stage I/II), locally advanced (stage III) and metastatic disease (stage IV). Support vector machine analysis showed that all PDAC stages could be discriminated from controls and that the accuracy increased with disease progression, from stage I to IV. Patients with stage I/II PDAC could be discriminated from NC with high accuracy based on a plasma protein signature, indicating a possibility for early diagnosis and increased detection rate of surgically resectable tumors.

Advancing the global proteome survey platform by using an oriented single chain antibody fragment immobilization approach.

Increasing the understanding of a proteome and how its protein composition is affected by for example different diseases, such as cancer, has the potential to improve strategies for early diagnosis and therapeutics. The Global Proteome Survey or GPS is a method that combines mass spectrometry and affinity enrichment with the use of antibodies. The technology enables profiling of complex proteomes in a species independent manner. The sensitivity of GPS, and other methods relying on affinity enrichment, is largely affected by the activity of the exploited affinity reagent. We here present an improvement of the GPS platform by utilizing an antibody immobilization approach which ensures a controlled immobilization process of the antibody to the magnetic bead support. More specifically, we make use of an antibody format that enables site-directed biotinylation and use this in combination with streptavidin coated magnetic beads. The performance of the expanded GPS platform was evaluated by profiling yeast proteome samples. We demonstrate that the oriented antibody immobilization strategy increases the ability of the GPS platform and results in larger fraction of functional antibodies. Additionally, we show that this new antibody format enabled in-solution capture, i.e. immobilization of the antibodies after sample incubation. A workflow has been established that permit the use of an oriented immobilization strategy for the GPS platform.

A Multicenter Trial Defining a Serum Protein Signature Associated with Pancreatic Ductal Adenocarcinoma.

Background. Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with rapid tumor progression and poor prognosis. This study was motivated by the lack of sensitive and specific PDAC biomarkers and aimed to identify a diagnostic, serum protein signature for PDAC. Methods. To mimic a real life test situation, a multicenter trial comprising a serum sample cohort, including 338 patients with either PDAC or other pancreatic diseases (OPD) and controls with nonpancreatic conditions (NPC), was analyzed on 293-plex recombinant antibody microarrays targeting immunoregulatory and cancer-associated antigens. Results. Serum samples collected from different hospitals were analyzed and showed that (i) sampling from five different hospitals could not be identified as a preanalytical variable and (ii) a multiplexed biomarker signature could be identified, utilizing up to 10 serum markers that could discriminate PDAC from controls, with sensitivities and specificities in the 91-100% range. The first protein profiles associated with the location of the primary tumor in the pancreas could also be identified. Conclusions. The results demonstrate that robust enough serum signatures could be identified in a multicenter trial, potentially contributing to the development of a multiplexed biomarker immunoassay for improved PDAC diagnosis.

Identification of plasma protein profiles associated with risk groups of prostate cancer patients.

PURPOSE: Early detection of prostate cancer (PC) using prostate-specific antigen (PSA) in blood reduces PC-death among unscreened men. However, due to modest specificity of PSA at commonly used cut-offs, there are urgent needs for additional biomarkers contributing enhanced risk classification among men with modestly elevated PSA. EXPERIMENTAL DESIGN: Recombinant antibody microarrays were applied for protein expression profiling of 80 plasma samples from routine PSA-measurements, a priori divided into four risk groups, based on levels of total and %free PSA. RESULTS: The results demonstrated that plasma protein profiles could be identified that pin-pointed PC (a malignant biomarker signature) and most importantly that showed moderate to high correlation with biochemically defined PC risk groups. Notably, the data also implied that the risk group with midrange PSA and low %free PSA, a priori known to be heterogeneous, could be further stratified into two subgroups, more resembling the lowest and highest risk groups, respectively. CONCLUSIONS AND CLINICAL RELEVANCE: In this pilot study, we have shown that plasma protein biomarker signatures, associated with risk groups of PC, could be identified from crude plasma samples using affinity proteomics. This approach could in the longer perspective provide novel opportunities for improved risk classification of PC patients.

Identification of B-cell lymphoma subsets by plasma protein profiling using recombinant antibody microarrays.

B-cell lymphoma (BCL) heterogeneity represents a key issue, often making the classification and clinical management of these patients challenging. In this pilot study, we outlined the first resolved view of BCL disease heterogeneity on the protein level by deciphering disease-associated plasma biomarkers, specific for chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and mantle cell lymphoma, using recombinant antibody microarrays targeting mainly immunoregulatory proteins. The results showed the BCLs to be heterogeneous, and revealed potential novel subgroups of each BCL. In the case of diffuse large B-cell lymphoma, we also indicated a link between the novel subgroups and survival.

Protein expression profiling of formalin-fixed paraffin-embedded tissue using recombinant antibody microarrays.

Proteomics, the large-scale analysis of proteins, is a rapidly evolving field with an increasing number of key clinical applications, such as diagnosis, prognosis, and classification. In order to generate complete protein expression profiles, or protein atlases, any crude sample format must be addressable in a rapid, multiplex, and sensitive manner. A common and clinically central sample format, formalin-fixed, paraffin-embedded (FFPE) tissue material, holds great potential as a source for disease-associated biomarker signatures. However, despite major efforts, extraction and subsequent profiling of proteins from FFPE tissue has proven to be challenging. In this proof-of-concept study, we have demonstrated for the first time that proteins could be extracted, labeled, and subsequently profiled in a multiplex, sensitive, and reproducible manner using recombinant scFv antibody microarrays. Thus, we have added FFPE samples to the list of sample formats available for high-throughput analysis by affinity proteomics, paving the way for the next generation of biomarker-driven discovery projects.

Grading breast cancer tissues using molecular portraits.

Tumor progression and prognosis in breast cancer patients are difficult to assess using current clinical and laboratory parameters, where a pathological grading is indicative of tumor aggressiveness. This grading is based on assessments of nuclear grade, tubule formation, and mitotic rate. We report here the first protein signatures associated with histological grades of breast cancer, determined using a novel affinity proteomics approach. We profiled 52 breast cancer tissue samples by combining nine antibodies and label-free LC-MS/MS, which generated detailed quantified proteomic maps representing 1,388 proteins. The results showed that we could define in-depth molecular portraits of histologically graded breast cancer tumors. Consequently, a 49-plex candidate tissue protein signature was defined that discriminated between histological grades 1, 2, and 3 of breast cancer tumors with high accuracy. Highly biologically relevant proteins were identified, and the differentially expressed proteins indicated further support for the current hypothesis regarding remodeling of the tumor microenvironment during tumor progression. The protein signature was corroborated using meta-analysis of transcriptional profiling data from an independent patient cohort. In addition, the potential for using the markers to estimate the likelihood of long-term metastasis-free survival was also indicated. Taken together, these molecular portraits could pave the way for improved classification and prognostication of breast cancer.

Nuclear T-STAR protein expression correlates with HER2 status, hormone receptor negativity and prolonged recurrence free survival in primary breast cancer and decreased cancer cell growth in vitro.

T-STAR (testis-signal transduction and activation of RNA) is an RNA binding protein, containing an SH3-binding domain and thus potentially playing a role in integration of cell signaling and RNA metabolism. The specific function of T-STAR is unknown and its implication in cancer is poorly characterized. Expression of T-STAR has been reported in human testis, muscle and brain tissues, and is associated with a growth-inhibitory role in immortalized fibroblasts. The aim of this paper was to investigate the functional role of T-STAR through (i) survival analysis of patients with primary invasive breast cancer and (ii) experimental evaluation of the effect of T-STAR on breast cancer cell growth. T-STAR protein expression was analysed by immunohistochemistry (IHC) in tissue microarrays with tumors from 289 patients with primary invasive breast cancer, and correlations to clinicopathological characteristics, recurrence-free and overall survival (RFS and OS) and established tumor markers such as HER2 and ER status were evaluated. In addition, the function of T-STAR was investigated using siRNA-mediated knock-down and overexpression of the gene in six breast cancer cell lines. Of the tumors analysed, 86% showed nuclear T-STAR expression, which was significantly associated with an improved RFS and strongly associated with positive HER2 status and negative hormone receptor status. Furthermore, experimental data showed that overexpression of T-STAR decreased cellular growth while knock-down increased it, as shown both by thymidine incorporation and metabolic activity. In summary, we demonstrate that T-STAR protein expression correlates with an improved RFS in primary breast cancer. This is supported by functional data, indicating that T-STAR regulation is of importance both for breast cancer biology and clinical outcome but future studies are needed to determine a potential role in patient stratification.