A hybrid DDA/DIA-PASEF based assay library for a deep proteotyping of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and deeper proteome coverage is needed for its molecular characterization. We present comprehensive library of targeted mass spectrometry assays specific for TNBC and demonstrate its applicability. Proteins were extracted from 105 TNBC tissues and digested. Aliquots were pooled, fractionated using hydrophilic chromatography and analyzed by LC-MS/MS in data-dependent acquisition (DDA) parallel accumulation-serial fragmentation (PASEF) mode on timsTOF Pro LC-MS system. 16 individual lysates were analyzed in data-independent acquisition (DIA)-PASEF mode. Hybrid library was generated in Spectronaut software and covers 244,464 precursors, 168,006 peptides and 11,564 protein groups (FDR = 1%). Application of our library for pilot quantitative analysis of 16 tissues increased identification numbers in Spectronaut 18.5 and DIA-NN 1.8.1 software compared to library-free setting, with Spectronaut achieving the best results represented by 190,310 precursors, 140,566 peptides, and 10,463 protein groups. In conclusion, we introduce assay library that offers the deepest coverage of TNBC proteome to date. The TNBC library is available via PRIDE repository (PXD047793).

N-glycan profiling of tissue samples to aid breast cancer subtyping.

Breast cancer is a highly heterogeneous disease. Its intrinsic subtype classification for diagnosis and choice of therapy traditionally relies on the presence of characteristic receptors. Unfortunately, this classification is often not sufficient for precise prediction of disease prognosis and treatment efficacy. The N-glycan profiles of 145 tumors and 10 healthy breast tissues were determined using Matrix-Assisted Laser Desorption-Ionization Time-of-Flight Mass Spectrometry. The tumor samples were classified into Mucinous, Lobular, No-Special-Type, Human Epidermal Growth Factor 2 + , and Triple-Negative Breast Cancer subtypes. Statistical analysis was conducted using the reproducibility-optimized test statistic software package in R, and the Wilcoxon rank sum test with continuity correction. In total, 92 N-glycans were detected and quantified, with 59 consistently observed in over half of the samples. Significant variations in N-glycan signals were found among subtypes. Mucinous tumor samples exhibited the most distinct changes, with 28 significantly altered N-glycan signals. Increased levels of tri- and tetra-antennary N-glycans were notably present in this subtype. Triple-Negative Breast Cancer showed more N-glycans with additional mannose units, a factor associated with cancer progression. Individual N-glycans differentiated Human Epidermal Growth Factor 2 + , No-Special-Type, and Lobular cancers, whereas lower fucosylation and branching levels were found in N-glycans significantly increased in Luminal subtypes (Lobular and No-Special-Type tumors). Clinically normal breast tissues featured a higher abundance of signals corresponding to N-glycans with bisecting moiety. This research confirms that histologically distinct breast cancer subtypes have a quantitatively unique set of N-glycans linked to clinical parameters like tumor size, proliferative rate, lymphovascular invasion, and metastases to lymph nodes. The presented results provide novel information that N-glycan profiling could accurately classify human breast cancer samples, offer stratification of patients, and ongoing disease monitoring.

ΔNp63 is regulated by insulin/IGF-1 signaling in normal basal/progenitor mammary cells and in luminal-type breast cancer cells.

Breast cancers are a heterogeneous group of tumors classified according to their histological growth patterns and receptor expression characteristics. Intratumor heterogeneity also exists, with subpopulations of cells with different phenotypes found in individual cancers, including cells with stem or progenitor cell properties. At least two types of breast cancer stem cells (CSCs) exist, the epithelial and the basal/mesenchymal subtypes, although how these phenotypes are controlled is unknown. ΔNp63 is a basal cell marker and regulator of stem/progenitor cell activities in the normal mammary gland and is expressed in the basal-like CSC subpopulation in some estrogen receptor-positive (ER+) and/or human epidermal growth factor receptor 2-positive (HER2+) breast adenocarcinomas. Whilst p63 is known to directly impart CSC properties in luminal breast cancer cells, how p63 is regulated and induced in these cells is unknown. We initially confirmed the existence of a small subpopulation of ΔNp63+ cells in lymph node metastases of ER+ human ductal adenocarcinomas, indicating together with previous reports that ΔNp63+ tumor cells are present in approximately 40% of these metastases. Notably, ΔNp63+ cells show a preferential location at the edge of tumor areas, suggesting possible regulation of ΔNp63 by the tumor microenvironment. Subsequently, we showed that the high levels of ΔNp63 in basal non-transformed MCF-10A mammary epithelial cells rely on insulin in their culture medium, whilst ΔNp63 levels are increased in MCF-7 ER+ luminal-type breast cancer cells treated with insulin or insulin-like growth factor 1 (IGF-1). Mechanistically, small molecule inhibitors and siRNA gene knockdown demonstrated that induction of ΔNp63 by IGF-1 requires PI3K, ERK1/2, and p38 MAPK activation, and acts through FOXO transcriptional inactivation. We also show that metformin inhibits ΔNp63 induction. These data reveal an IGF-mediated mechanism to control basal-type breast CSCs, with therapeutic implications to modify intratumor breast cancer cell heterogeneity and plasticity.

Molecular portraits of colorectal cancer morphological regions.

Heterogeneity of colorectal carcinoma (CRC) represents a major hurdle towards personalized medicine. Efforts based on whole tumor profiling demonstrated that the CRC molecular subtypes were associated with specific tumor morphological patterns representing tumor subregions. We hypothesize that whole-tumor molecular descriptors depend on the morphological heterogeneity with significant impact on current molecular predictors. We investigated intra-tumor heterogeneity by morphology-guided transcriptomics to better understand the links between gene expression and tumor morphology represented by six morphological patterns (morphotypes): complex tubular, desmoplastic, mucinous, papillary, serrated, and solid/trabecular. Whole-transcriptome profiling by microarrays of 202 tumor regions (morphotypes, tumor-adjacent normal tissue, supportive stroma, and matched whole tumors) from 111 stage II-IV CRCs identified morphotype-specific gene expression profiles and molecular programs and differences in their cellular buildup. The proportion of cell types (fibroblasts, epithelial and immune cells) and differentiation of epithelial cells were the main drivers of the observed disparities with activation of EMT and TNF-α signaling in contrast to MYC and E2F targets signaling, defining major gradients of changes at molecular level. Several gene expression-based (including single-cell) classifiers, prognostic and predictive signatures were examined to study their behavior across morphotypes. Most exhibited important morphotype-dependent variability within same tumor sections, with regional predictions often contradicting the whole-tumor classification. The results show that morphotype-based tumor sampling allows the detection of molecular features that would otherwise be distilled in whole tumor profile, while maintaining histopathology context for their interpretation. This represents a practical approach at improving the reproducibility of expression profiling and, by consequence, of gene-based classifiers.

Shedding light on the black box of a neural network used to detect prostate cancer in whole slide images by occlusion-based explainability.

Diagnostic histopathology faces increasing demands due to aging populations and expanding healthcare programs. Semi-automated diagnostic systems employing deep learning methods are one approach to alleviate this pressure. The learning models for histopathology are inherently complex and opaque from the user's perspective. Hence different methods have been developed to interpret their behavior. However, relatively limited attention has been devoted to the connection between interpretation methods and the knowledge of experienced pathologists. The main contribution of this paper is a method for comparing morphological patterns used by expert pathologists to detect cancer with the patterns identified as important for inference of learning models. Given the patch-based nature of processing large-scale histopathological imaging, we have been able to show statistically that the VGG16 model could utilize all the structures that are observable by the pathologist, given the patch size and scan resolution. The results show that the neural network approach to recognizing prostatic cancer is similar to that of a pathologist at medium optical resolution. The saliency maps identified several prevailing histomorphological features characterizing carcinoma, e.g., single-layered epithelium, small lumina, and hyperchromatic nuclei with halo. A convincing finding was the recognition of their mimickers in non-neoplastic tissue. The method can also identify differences, i.e., standard patterns not used by the learning models and new patterns not yet used by pathologists. Saliency maps provide added value for automated digital pathology to analyze and fine-tune deep learning systems and improve trust in computer-based decisions.

Privacy risks of whole-slide image sharing in digital pathology.

Access to large volumes of so-called whole-slide images-high-resolution scans of complete pathological slides-has become a cornerstone of the development of novel artificial intelligence methods in pathology for diagnostic use, education/training of pathologists, and research. Nevertheless, a methodology based on risk analysis for evaluating the privacy risks associated with sharing such imaging data and applying the principle "as open as possible and as closed as necessary" is still lacking. In this article, we develop a model for privacy risk analysis for whole-slide images which focuses primarily on identity disclosure attacks, as these are the most important from a regulatory perspective. We introduce a taxonomy of whole-slide images with respect to privacy risks and mathematical model for risk assessment and design . Based on this risk assessment model and the taxonomy, we conduct a series of experiments to demonstrate the risks using real-world imaging data. Finally, we develop guidelines for risk assessment and recommendations for low-risk sharing of whole-slide image data.

Stat3 Tyrosine 705 and Serine 727 Phosphorylation Associate With Clinicopathological Characteristics and Distinct Tumor Cell Phenotypes in Triple-Negative Breast Cancer.

Signal transducer and activator of transcription 3 (Stat3) is responsible for many aspects of normal development and contributes to the development and progression of cancer through regulating epithelial cell identity and cancer stem cells. In breast cancer, Stat3 is associated with triple-negative breast cancers (TNBC) and its function has been related to the activation of p63, itself a marker of basal-like TNBC and a master regulator of stem cell activities. Stat3 activation is controlled by dual phosphorylation at tyrosine 705 (pTyr705) and serine 727 (pSer727), although it is unclear whether these have equivalent effects, and whether they are related or independent events. To address these issues, we investigated Stat3 phosphorylation at the two sites by immunohistochemistry in 173 patients with TNBC. Stat3 phosphorylation was assessed by automated quantitative measurements of digitized scanned images and classified into four categories based on histoscore. The results were analyzed for associations with multiple markers of tumor phenotype, proliferation, BRCA status, and clinicopathological characteristics. We show that the levels of pTyr705- and pSer727-Stat3 were independent in 34% of tumors. High pTyr705-Stat3 levels were associated with the luminal differentiation markers ERß/AR and MUC1, whereas tumors with high levels of pSer727-Stat3 were more likely to be positive for the basal marker CK5/6, but were independent of p63 and were EGFR negative. Combined high pSer727- and low Tyr705-Stat3 phosphorylation associated with basal-like cancer. Although high Stat3 phosphorylation levels were associated with less aggressive tumor characteristics, they did not associate with improved survival, indicating that Stat3 phosphorylation is an unfavorable indicator for tumors with an otherwise good prognosis according to clinicopathological characteristics. These findings also show that pTyr705-Stat3 and pSer727-Stat3 associate with specific breast tumor phenotypes, implying that they exert distinct functional activities in breast cancer.

Automated annotations of epithelial cells and stroma in hematoxylin-eosin-stained whole-slide images using cytokeratin re-staining.

The diagnosis of solid tumors of epithelial origin (carcinomas) represents a major part of the workload in clinical histopathology. Carcinomas consist of malignant epithelial cells arranged in more or less cohesive clusters of variable size and shape, together with stromal cells, extracellular matrix, and blood vessels. Distinguishing stroma from epithelium is a critical component of artificial intelligence (AI) methods developed to detect and analyze carcinomas. In this paper, we propose a novel automated workflow that enables large-scale guidance of AI methods to identify the epithelial component. The workflow is based on re-staining existing hematoxylin and eosin (H&E) formalin-fixed paraffin-embedded sections by immunohistochemistry for cytokeratins, cytoskeletal components specific to epithelial cells. Compared to existing methods, clinically available H&E sections are reused and no additional material, such as consecutive slides, is needed. We developed a simple and reliable method for automatic alignment to generate masks denoting cytokeratin-rich regions, using cell nuclei positions that are visible in both the original and the re-stained slide. The registration method has been compared to state-of-the-art methods for alignment of consecutive slides and shows that, despite being simpler, it provides similar accuracy and is more robust. We also demonstrate how the automatically generated masks can be used to train modern AI image segmentation based on U-Net, resulting in reliable detection of epithelial regions in previously unseen H&E slides. Through training on real-world material available in clinical laboratories, this approach therefore has widespread applications toward achieving AI-assisted tumor assessment directly from scanned H&E sections. In addition, the re-staining method will facilitate additional automated quantitative studies of tumor cell and stromal cell phenotypes.

Colorectal Tumour Mucosa Microbiome Is Enriched in Oral Pathogens and Defines Three Subtypes That Correlate with Markers of Tumour Progression.

Long-term dysbiosis of the gut microbiome has a significant impact on colorectal cancer (CRC) progression and explains part of the observed heterogeneity of the disease. Even though the shifts in gut microbiome in the normal-adenoma-carcinoma sequence were described, the landscape of the microbiome within CRC and its associations with clinical variables remain under-explored. We performed 16S rRNA gene sequencing of paired tumour tissue, adjacent visually normal mucosa and stool swabs of 178 patients with stage 0-IV CRC to describe the tumour microbiome and its association with clinical variables. We identified new genera associated either with CRC tumour mucosa or CRC in general. The tumour mucosa was dominated by genera belonging to oral pathogens. Based on the tumour microbiome, we stratified CRC patients into three subtypes, significantly associated with prognostic factors such as tumour grade, sidedness and TNM staging, BRAF mutation and MSI status. We found that the CRC microbiome is strongly correlated with the grade, location and stage, but these associations are dependent on the microbial environment. Our study opens new research avenues in the microbiome CRC biomarker detection of disease progression while identifying its limitations, suggesting the need for combining several sampling sites (e.g., stool and tumour swabs).

Kinomics platform using GBM tissue identifies BTK as being associated with higher patient survival.

Better understanding of GBM signalling networks in-vivo would help develop more physiologically relevant ex vivo models to support therapeutic discovery. A "functional proteomics" screen was undertaken to measure the specific activity of a set of protein kinases in a two-step cell-free biochemical assay to define dominant kinase activities to identify potentially novel drug targets that may have been overlooked in studies interrogating GBM-derived cell lines. A dominant kinase activity derived from the tumour tissue, but not patient-derived GBM stem-like cell lines, was Bruton tyrosine kinase (BTK). We demonstrate that BTK is expressed in more than one cell type within GBM tissue; SOX2-positive cells, CD163-positive cells, CD68-positive cells, and an unidentified cell population which is SOX2-negative CD163-negative and/or CD68-negative. The data provide a strategy to better mimic GBM tissue ex vivo by reconstituting more physiologically heterogeneous cell co-culture models including BTK-positive/negative cancer and immune cells. These data also have implications for the design and/or interpretation of emerging clinical trials using BTK inhibitors because BTK expression within GBM tissue was linked to longer patient survival.

TAp63 and ΔNp63 (p40) in prostate adenocarcinomas: ΔNp63 associates with a basal-like cancer stem cell population but not with metastasis.

Like other malignancies, prostate tumors are thought to contain cancer stem-like cells (CSCs) that are responsible for growth, metastasis, and therapy resistance. ΔNp63 (also called p40) is a regulator of normal prostate stem/progenitor cell activities and a marker of normal basal epithelial cells. The levels of ΔNp63 are reduced in prostate adenocarcinomas, although there is also evidence that ΔNp63 is involved in CSC regulation and drives metastasis to the bone. We studied metastatic deposits of prostate cancers with isoform-specific ΔNp63 and TAp63 antibodies. We identified p63-positive cells in only 3 of 42 metastatic prostate tumors (7%), including 2/38 (5.3%) "usual-type" adenocarcinomas. ΔNp63 and TAp63 isoforms were present in the nuclei of a small subpopulation (< 1%) of tumor cells in these metastases. ΔNp63-positive cells showed a basal-like cell phenotype (cytokeratin 8- and androgen receptor-negative, high molecular weight cytokeratin- and cytokeratin 19-positive), distinct from the tumor bulk. TAp63-positive cells were similar but were sometimes cytokeratin 8-positive. A subset of ΔNp63-positive tumor cells were CD44-positive, a marker of "basal" CSCs but were not positive for the "epithelial" CSC marker ALDH1. TAp63 was not associated with either of these CSC markers. None of the tumors containing p63-positive cells showed evidence of bone metastasis, compared with 28% of the p63-negative tumors. These data show that both ΔNp63 and TAp63 are present in only a small proportion of prostate adenocarcinomas and do not associate with metastasis. The data suggest heterogeneity of CSCs in prostate cancer, similar to other cancer types.

N-Glycome changes reflecting resistance to platinum-based chemotherapy in ovarian cancer.

A number of studies have reported aberrant glycosylation in connection with malignancy. Our investigation further expands on this topic through the examination of N-glycans, which could be associated with the resistance of advanced stage, high-grade non-mucinous ovarian cancer to platinum/taxane based chemotherapy. We used tissue samples of 83 ovarian cancer patients, randomly divided into two independent cohorts (basic and validation). Both groups involved either cases with/without postoperative tumor residue or the cases determined either resistant or sensitive to this chemotherapy. In the validation cohort, preoperative serum samples were also available. N-glycans released from tumors and sera were permethylated and analyzed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The MS analysis yielded a consecutive detection of 68 (tissue) and 63 (serum) N-glycan spectral signals. Eight of these were found to be differentially abundant in tissues of both independent cohorts including the cases with a postoperative cancer residue. One of these glycans was detected as differentially abundant in sera of the validation cohort. No statistically significant differences in intensities due to the same N-glycans were found in the cases without postoperative macroscopic residues in either the basic or validation cohort. From the biochemical point of view, the statistically significant N-glycans correspond to the structures carrying bisecting (terminal) GlcNAc residue and tetra-antennary structures with sialic acid and/or fucose residues. Among them, six tissue N-glycans could be considered potential markers connected with a resistance to chemotherapy in ovarian cancer patients. The prediction of primary resistance to standard chemotherapy may identify the group of patients suitable for alternative treatment strategies. SIGNIFICANCE: Drug resistance has become a major impediment to a successful treatment of patients with advanced ovarian cancer. The glycomic measurements related to cancer are becoming increasingly popular in identification of the key molecules as potential diagnostic and prognostic indicators. Our report deals with identification of differences in N-glycosylation of proteins in tissue and serum samples from the individuals showing sensitivity or resistance to platinum/taxane-based chemotherapy. The detection sensitivity to chemotherapy is vitally important for these patients.

SWATH-MS Analysis of FFPE Tissues Identifies Stathmin as a Potential Marker of Endometrial Cancer in Patients Exposed to Tamoxifen.

A specific form of endometrial cancer (EC) can develop in breast cancer patients previously treated with tamoxifen (ET), an antagonist of estrogen receptor (ER) that inhibits proliferation of ER positive breast cancer. ET tumors have a different phenotype than endometrial tumors, which typically develop de novo without previous exposure to tamoxifen (EN). Here we aimed to identify specific protein markers that could serve as specific molecular targets in either phenotype. A set of total 45 formalin-fixed paraffin-embedded (FFPE) endometrial tumor tissues and adjacent myometrium tissue samples were analyzed using LC-MS/MS in SWATH-MS mode. We found that calcyphosin (CAPS) levels were elevated in EN tumors compared to ET tumors. The higher CAPS level in EC tissue invading to myometrium supports its relationship to EC aggressiveness. Further, stathmin (STMN1) levels were found significantly elevated in ET versus EN tumors and significantly associated with patient survival. This finding connects elevated levels of this cell cycle regulating, proliferation-associated protein with tamoxifen exposure. In summary, using SWATH-MS we show that CAPS and STMN1 should be recognized as clinicopathologically different EC markers of which STMN1 is specifically connected with a previous tamoxifen exposition.

∆Np63/p40 correlates with the location and phenotype of basal/mesenchymal cancer stem-like cells in human ER+ and HER2+ breast cancers.

ΔNp63, also known as p40, regulates stemness of normal mammary gland epithelium and provides stem cell characteristics in basal and HER2-driven murine breast cancer models. Whilst ΔNp63/p40 is a characteristic feature of normal basal cells and basal-type triple-negative breast cancer, some receptor-positive breast cancers express ΔNp63/p40 and its overexpression imparts cancer stem cell-like properties in ER+ cell lines. However, the incidence of ER+ and HER2+ tumours that express ΔNp63/p40 is unclear and the phenotype of ΔNp63/p40+ cells in these tumours remains uncertain. Using immunohistochemistry with p63 isoform-specific antibodies, we identified a ΔNp63/p40+ tumour cell subpopulation in 100 of 173 (58%) non-triple negative breast cancers and the presence of this population associated with improved survival in patients with ER- /HER2+ tumours (p = 0.006). Furthermore, 41% of ER+ /PR+ and/or HER2+ locally metastatic breast cancers expressed ΔNp63/p40, and these cells commonly accounted for <1% of the metastatic tumour cell population that localised to the tumour/stroma interface, exhibited an undifferentiated phenotype and were CD44+ /ALDH- . In vitro studies revealed that MCF7 and T47D (ER+ ) and BT-474 (HER2+ ) breast cancer cell lines similarly contained a small subpopulation of ΔNp63/p40+ cells that increased in mammospheres. In vivo, MCF7 xenografts contained ΔNp63/p40+ cells with a similar phenotype to primary ER+ cancers. Consistent with tumour samples, these cells also showed a distinct location at the tumour/stroma interface, suggesting a role for paracrine factors in the induction or maintenance of ΔNp63/p40. Thus, ΔNp63/p40 is commonly present in a small population of tumour cells with a distinct phenotype and location in ER+ and/or HER2+ human breast cancers.

Role of the Microbiome in the Formation and Development of Colorectal Cancer.

BACKGROUND: The clinical, histopathological, and molecular characteristics of colorectal cancer vary considerably. Factors associated with the heterogeneity of this disease and with understanding the effects of heterogeneity on disease progression and response to therapy are critical for the better stratification of patients and the development of new therapeutic methods. Although studies have focused mainly on tumor molecular profiling, current molecular predictive and prognostic factors are relevant to specific groups of colorectal cancer patients and are mostly used to predict the applicability of targeted biological agents rather than to predict their benefits. Molecular profiling fails to capture aspects important for tumor growth and aggressiveness, including the tumor microenvironment. The gut microbiome, consisting of specific communities of all commensal, symbiotic, and pathogenic microorganisms, has been shown to have a significant impact on the development of many diseases, including Crohns disease, type II diabetes, and obesity. Recent studies have indicated that long-term dysbiosis of the intestinal microflora can influence the development and progression of colorectal cancer, as well as tumor aggressiveness and response to treatment. CONCLUSION: This review article summarizes current knowledge of the gut microbiome in colorectal cancer, including the various mechanisms by which the gut microbiome affects the intestinal wall, thereby contributing to the development and progression of colorectal cancer. This work was supported by Ministry of Health of the Czech Republic (project AZV 16-31966A), project of Ministry of Education, Youth and Sports of the Czech Republic - NPU I - LO1413 a Ministry of Health of the Czech Republic - RVO (MMCI, 00209805). The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers. Submitted: 15. 4. 2019 Accepted: 17. 6. 2019.

Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry.

Accurate classification of breast tumors is vital for patient management decisions and enables more precise cancer treatment. Here, we present a quantitative proteotyping approach based on sequential windowed acquisition of all theoretical fragment ion spectra (SWATH) mass spectrometry and establish key proteins for breast tumor classification. The study is based on 96 tissue samples representing five conventional breast cancer subtypes. SWATH proteotype patterns largely recapitulate these subtypes; however, they also reveal varying heterogeneity within the conventional subtypes, with triple negative tumors being the most heterogeneous. Proteins that contribute most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2 and are associated with estrogen receptor (ER) status, tumor grade status, and HER2 status. Although these three key proteins exhibit high levels of correlation with transcript levels (R > 0.67), general correlation did not exceed R = 0.29, indicating the value of protein-level measurements of disease-regulated genes. Overall, this study highlights how cancer tissue proteotyping can lead to more accurate patient stratification.

Circulating T cell subsets are associated with clinical outcome of anti-VEGF-based 1st-line treatment of metastatic colorectal cancer patients: a prospective study with focus on primary tumor sidedness.

BACKGROUND: In a prospective study with long-term follow-up, we analyzed circulating T cell subsets in patients with metastatic colorectal cancer (mCRC) in the context of primary tumor sidedness, KRAS status, and clinical outcome. Our primary goal was to investigate whether baseline levels of circulating T cell subsets serve as a potential biomarker of clinical outcome of mCRC patients treated with an anti-VEGF-based regimen. METHODS: The study group consisted of 36 patients with colorectal adenocarcinoma who started first-line chemotherapy with bevacizumab for metastatic disease. We quantified T cell subsets including Tregs and CD8+ T cells in the peripheral blood prior to therapy initiation. Clinical outcome was evaluated as progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). RESULTS: 1) mCRC patients with KRAS wt tumors had higher proportions of circulating CD8+ cytotoxic T cells among all T cells but also higher measures of T regulatory (Treg) cells such as absolute count and a higher proportion of Tregs in the CD4+ subset. 2) A low proportion of circulating Tregs among CD4+ cells, and a high CD8:Treg ratio at initiation of VEGF-targeting therapy, were associated with favorable clinical outcome. 3) In a subset of patients with primarily right-sided mCRC, superior PFS and OS were observed when the CD8:Treg ratio was high. CONCLUSIONS: The baseline level of circulating immune cells predicts clinical outcome of 1st-line treatment with the anti-VEGF angio/immunomodulatory agent bevacizumab. Circulating immune biomarkers, namely the CD8:Treg ratio, identified patients in the right-sided mCRC subgroup with favorable outcome following treatment with 1st-line anti-VEGF treatment.

The effects of IFITM1 and IFITM3 gene deletion on IFNγ stimulated protein synthesis.

Interferon-induced transmembrane proteins IFITM1 and IFITM3 (IFITM1/3) play a role in both RNA viral restriction and in human cancer progression. Using immunohistochemical staining of FFPE tissue, we identified subgroups of cervical cancer patients where IFITM1/3 protein expression is inversely related to metastasis. Guide RNA-CAS9 methods were used to develop an isogenic IFITM1/IFITM3 double null cervical cancer model in order to define dominant pathways triggered by presence or absence of IFITM1/3 signalling. A pulse SILAC methodology identified IRF1, HLA-B, and ISG15 as the most dominating IFNγ inducible proteins whose synthesis was attenuated in the IFITM1/IFITM3 double-null cells. Conversely, SWATH-IP mass spectrometry of ectopically expressed SBP-tagged IFITM1 identified ISG15 and HLA-B as dominant co-associated proteins. ISG15ylation was attenuated in IFNγ treated IFITM1/IFITM3 double-null cells. Proximity ligation assays indicated that HLA-B can interact with IFITM1/3 proteins in parental SiHa cells. Cell surface expression of HLA-B was attenuated in IFNγ treated IFITM1/IFITM3 double-null cells. SWATH-MS proteomic screens in cells treated with IFITM1-targeted siRNA cells resulted in the attenuation of an interferon regulated protein subpopulation including MHC Class I molecules as well as IFITM3, STAT1, B2M, and ISG15. These data have implications for the function of IFITM1/3 in mediating IFNγ stimulated protein synthesis including ISG15ylation and MHC Class I production in cancer cells. The data together suggest that pro-metastatic growth associated with IFITM1/3 negative cervical cancers relates to attenuated expression of MHC Class I molecules that would support tumor immune escape.

Tomm34 is commonly expressed in epithelial ovarian cancer and associates with tumour type and high FIGO stage.

BACKGROUND: Increased activity of the chaperones Hsp70 and Hsp90 is a common feature of solid tumours. Translocase of the outer mitochondrial membrane 34 (Tomm34) is a cochaperone of both Hsp70 and Hsp90 that was found to be overexpressed in colorectal, hepatocellular, lung and breast carcinomas. The expression profile of Tomm34 in ovarian cancer has not been investigated. Therefore, the aim of the current study was to investigate the expression pattern of Tomm34 in ovarian carcinomas and analyse its correlation with clinico-pathological parameters. RESULTS: Epithelial ovarian cancers (140) were histologically classified based on their morphology and graded into two types comprising 5 histologic subgroups. Type I carcinomas comprise low grade serous (LGSC), clear cell (CCOC) and endometrioid (ENOC), type II comprises high grade serous carcinomas (HGSC) and solid, pseudoendometrioid, transitional carcinomas (SET). Tomm34 was more highly expressed in type II than type I carcinomas (p < 0.0001). Comparing tumours based on the mutation in the TP53 gene revealed similar results, where mutant tumours exhibited significantly higher levels of Tomm34 (p < 0.0001). The decreased levels of Tomm34 in type I carcinomas were particularly evident in clear cell and mucinous carcinomas. The expression of Tomm34 was also positively correlated with FIGO stage (r = 0.23; p = 0.007). Tomm34 levels also indicated poor prognosis for patients with mutant p53. CONCLUSIONS: Our data indicate that Tomm34 is commonly expressed at high levels in epithelial ovarian cancers, except for the clear cell and mucinous subtypes. The expression of Tomm34 corresponds with the dualistic model of ovarian cancer pathogenesis where high grade, type II tumours exhibit higher expression of Tomm34 in contrast to type I tumours. These data are also comparable to the previous findings that Tomm34 is a marker of progression and poor prognosis in human cancer.

Microgradient separation technique for purification and fractionation of permethylated N-glycans before mass spectrometric analyses.

Analysis of N-glycans released enzymatically from patients' sera or other clinical samples may provide diagnostically and prognostically important information on human disease. Permethylation of these biomolecules simultaneously increases their hydrophobicity and substantially improves their detection parameters in the following mass spectrometric analyses. The overall procedure, from the glycan cleavage to the final mass spectrometric determinations, includes several steps involving extraction, derivatization, and purification. During these steps, certain polymeric contaminants that may have been coincidentally introduced could hamper the final measurements. To understand and counter these interferences and further fractionate or preconcentrate these glycans, we introduce here an effective microgradient chromatographic technique that employs a small reversed-phase microcolumn connected to a gas-tight microsyringe delivering a mobile-phase gradient. After loading the glycan fraction onto the microcolumn, three elution steps are recommended: (1) remove polar contaminants; (2) recover permethylated glycans for either liquid chromatography with electrospray ionization mass spectrometry or matrix-assisted laser desorption/ionization mass spectrometry; and (3) remove larger polymeric contaminants and regenerate the precolumn. We further demonstrate that the trapped second fraction can be beneficially preconcentrated and further separated to achieve matrix-assisted laser desorption/ionization mass spectrometric detection of the derivatized N-glycans up to 6300 Da. The enhanced detection capabilities for tetra-antennary N-glycans are of increasing interest in disease biomarker discovery.