Combination of osteopontin and activated leukocyte cell adhesion molecule as potent prognostic discriminators in HER2- and ER-negative breast cancer

Hydrophilic magnetic covalent triazine frameworks for differential N-glycopeptides enrichment in breast cancer plasma membranes

Alterations in plasma membrane glycoproteins (PMGs) have been identified as a hallmark of cancer. The comparison and identification of differential PMGs is significant for finding new markers and understanding pathological processes. However, the research on PMGs is often constrained by the low abundance and the disturbance of abundant endogenous biomolecules during direct analysis. Here, we report a bottom-up strategy to enrich the PMGs of breast cancer cells using hydrophilic magnetic covalent triazine frameworks (CTFs). A total of 972 N-glycopeptides and 1006 N-glycosites belonging to 526 N-glycoproteins were enriched in MCF-10A plasma membrane tryptic digest by magnetic CTFs. And 680 N-glycopeptides and 806 N-glycosites belonging to 443 N-glycoproteins were enriched in SK-BR-3 plasma membrane tryptic digest. Furthermore, comparative analysis was performed based on gene ontology to verify breast cancer biomarkers (SUSD2 and ALCAM) and differential PMGs' function. This strategy which systematically integrates efficient enrichment of differential PMGs and in-depth comparative analysis has great potential for helping illuminate the atlas of breast cancer PMGs and the causes of tumor metastasis.

Activated leukocyte cell adhesion molecule (ALCAM)/CD166 in pancreatic cancer, a pivotal link to clinical outcome and vascular embolism

Activated leukocyte cell adhesion molecule (ALCAM, or CD166) is a cell adhesion molecule and one of potential tumour metastasis 'soil' receptors that via homotypic and heterotypic interactions, mediates cancer cell adhesion. The present study investigated clinical, pathological and prognostic values of ALCAM in patients with pancreatic cancer. Human pancreatic cancer (PANC-1 and Mia PaCa-2) and human vascular endothelial cell lines were used to construct cell models differentially expressing levels of ALCAM. Tumour-endothelial interaction and tumour migration were assessed by a DiI-based method and electric cell-substrate impedance sensing (ECIS) assay. Pancreatic cancer tissues (n=223), collected immediately after surgery, were analysed for levels of the ALCAM transcripts, which were also analysed against clinical, pathological and clinical outcomes of the patients. ALCAM protein was assessed by immunohistochemistry on a tissue array. Our study demonstrate that pancreatic cancer tissues had significantly higher levels of ALCAM transcripts than normal tissues (P<0.00001). There were no significant differences with staging, differentiation and tumour locations. Tumours from patients who died of pancreatic cancer had significantly high levels of ALCAM compared with those who lived (P=0.018), and this finding was further supported by ROC analysis (P=0.016). Multivariant analysis showed that ALCAM is an independent prognosis factor for overall survival (HR=5.485), with both nodal status and TNM staging contributing to the model (HR=2.578 and 3.02, respectively). A surprising finding was the relationship between ALCAM expression and microvessel embolism of tumour cells (P=0.021, with vs without tumour embolism). Levels of ALCAM were found to be a determinant factor to adherence of the pancreatic cancer cells to vascular endothelial cells, as demonstrated by pancreatic cancer cell models genetically engineered to express differential levels of ALCAM. The tumour-endothelial interaction mediated by ALCAM was readily blocked by addition of soluble ALCAM. Our data supports the conclusion that ALCAM expression is aberrant in pancreatic cancer and its raised expression is an independent prognostic factor for the survival of the patients and the microvascular embolism by cancer cells. Our results suggest that ALCAM plays a key role in mediating tumour-endothelial cell interactions and enhancing tumour embolism in pancreatic cancer, and targeting ALCAM represents a potential therapeutic strategy for treating human pancreatic cancer.

The Clinical and Theranostic Values of Activated Leukocyte Cell Adhesion Molecule (ALCAM)/CD166 in Human Solid Cancers

Simple Summary

ALCAM (activated leukocyte cell adhesion molecule) is an important regulator in human cancers, particularly solid tumours. Its expression in cancer tissues has prognostic values depending on cancer types and is also linked to distant metastases. A truncated form, soluble form of ALCAM (sALCAM) in circulation has been suggested to be a prognostic indicator and a potential therapeutic tool. This article summarises recent findings and progress in ALCAM and its involvement in cancer, with a primary focus on its clinical connections and therapeutic values.

Abstract

Activated leukocyte cell adhesion molecule (ALCAM), also known as CD166, is a cell adhesion protein that is found in multiple cell types. ALCAM has multiple and diverse roles in various physiological and pathological conditions, including inflammation and cancer. There has been compelling evidence of ALCAM’s prognostic value in solid cancers, indicating that it is a potential therapeutic target. The present article overviews the recent findings and progress in ALCAM and its involvement in cancer, with a primary focus on its clinical connections in cancer and therapeutic values.

A targeted mass spectrometry immunoassay to quantify osteopontin in fresh-frozen breast tumors and adjacent normal breast tissues

Osteopontin (OPN) is a multifunctional protein that can activate cell-signaling pathways and lead to cancer development and metastasis. Elevated OPN expression was reported in different cancer types, including breast tumors. Here, we present a new immuno-mass spectrometry method for OPN quantification in fresh-frozen malignant and adjacent normal human breast tissues. For quantification we used two proteotypic peptides: OPN-peptide-1 and OPN-peptide-2. Peptide concentrations were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode with stable isotope standards (SIS) and immuno-affinity enrichment for isolation of OPN peptides. Based on the OPN-peptide-1, the average OPN concentration in normal breast tissue was 19.42 μg/g, while the corresponding level in breast tumors was 603.9 μg/g. Based on OPN-peptide-2, the average concentration in normal breast tissue was 19.30 μg/g and in breast tumors 535.0 μg/g. In ER/PR/HER2(-) patients the OPN levels in breast tumors were significantly higher than in corresponding normal breast tissue samples, whereas in the single ER/PR/HER2(+) patient the OPN concentration in tumor samples was lower than in normal breast tissue sample. In conclusion, the current method is considered promising for the quantification of OPN in research and in clinical settings and should be further studied in breast cancer patients. SIGNIFICANCE: A new immuno-mass spectrometry method was successfully developed and applied to determine OPN concentrations in malignant tumor and normal breast tissues from six patients, and the method is promising for OPN quantification in both research and clinical settings.

Key Factors in Breast Cancer Dissemination and Establishment at the Bone: Past, Present and Future Perspectives

Bone metastases associated with breast cancer remain a clinical challenge due to their associated morbidity, limited therapeutic intervention and lack of prognostic markers. With a continually evolving understanding of bone biology and its dynamic microenvironment, many potential new targets have been proposed. In this chapter, we discuss the roles of well-established bone markers and how their targeting, in addition to tumour-targeted therapies, might help in the prevention and treatment of bone metastases. There are a vast number of bone markers, of which one of the best-known families is the bone morphogenetic proteins (BMPs). This chapter focuses on their role in breast cancer-associated bone metastases, associated signalling pathways and the possibilities for potential therapeutic intervention. In addition, this chapter provides an update on the role receptor activator of nuclear factor-κB (RANK), RANK ligand (RANKL) and osteoprotegerin (OPG) play on breast cancer development and their subsequent influence during the homing and establishment of breast cancer-associated bone metastases. Beyond the well-established bone molecules, this chapter also explores the role of other potential factors such as activated leukocyte cell adhesion molecule (ALCAM) and its potential impact on breast cancer cells' affinity for the bone environment, which implies that ALCAM could be a promising therapeutic target.

Syntenin-1 and ezrin proteins link activated leukocyte cell adhesion molecule to the actin cytoskeleton

Activated leukocyte cell adhesion molecule (ALCAM) is a type I transmembrane protein member of the immunoglobulin superfamily of cell adhesion molecules. Involved in important pathophysiological processes such as the immune response, cancer metastasis, and neuronal development, ALCAM undergoes both homotypic interactions with other ALCAM molecules and heterotypic interactions with the surface receptor CD6 expressed at the T cell surface. Despite biochemical and biophysical evidence of a dynamic association between ALCAM and the actin cytoskeleton, no detailed information is available about how this association occurs at the molecular level. Here, we exploit a combination of complementary microscopy techniques, including FRET detected by fluorescence lifetime imaging microscopy and single-cell force spectroscopy, and we demonstrate the existence of a preformed ligand-independent supramolecular complex where ALCAM stably interacts with actin by binding to syntenin-1 and ezrin. Interaction with the ligand CD6 further enhances these multiple interactions. Altogether, our results propose a novel biophysical framework to understand the stabilizing role of the ALCAM supramolecular complex engaged to CD6 during dendritic cell-T cell interactions and provide novel information on the molecular players involved in the formation and signaling of the immunological synapse at the dendritic cell side.

The validation of estrogen receptor 1 mRNA expression as a predictor of outcome in patients with metastatic non-small cell lung cancer

The prognostic role of estrogen receptors in lung cancer is not validated. Results from patients with early stage non-small lung cancer patients indicate a prognostic role of estrogen receptor 1 (ESR1) mRNA expression in these patients. Automated RNA extraction from paraffin and RT-quantitative PCR was used for evaluation of tumoral ESR1 and progesterone receptor (PGR) mRNA expression. The test cohort consisted of 31 patients with advanced or metastatic non-small cell lung cancer (NSCLC) patients, treated in a first-line registry trial. For validation, 53 patients from a randomized multicentre first-line study with eligible tumor samples were evaluated. There was no significant correlation of ESR1 expression with clinical characteristics. ESR1 high expression was of significant positive prognostic value in the training set with a median overall survival (OS) of 15.9 versus 6.2 months for high versus low ESR1 expression patients (p = 0.0498, HR 0.39). This could be confirmed in the validation cohort with a median OS of 10.9 versus 5.0 months in ESR1 high versus low patients, respectively (p = 0.0321, HR 0.51). In the multivariate analysis adjusted for histological subtype, gender, age and performance status, ESR1 expression remained an independent prognostic parameter for survival in both cohorts. In contrast to ESR1, PGR expression was not able to separate prognostic groups or to predict outcome significantly (for OS; p = 0.94). Our study shows that ESR1 mRNA as assessed by qPCR represents a reliable method for detecting ESR1 expression in NSCLC and that ESR1 expression is an independent prognostic factor in metastatic NSCLC.

Identification and validation of a multigene predictor of recurrence in primary laryngeal cancer

Purpose

Local recurrence is the major manifestation of treatment failure in patients with operable laryngeal carcinoma. Established clinicopathological factors cannot sufficiently predict patients that are likely to recur after treatment. Additional tools are therefore required to accurately identify patients at high risk for recurrence. This study attempts to identify and independently validate gene expression models, prognostic of disease-free survival (DFS) in operable laryngeal cancer.

Materials and Methods

Using Affymetrix U133A Genechips, we profiled fresh-frozen tumor tissues from 66 patients with laryngeal cancer treated locally with surgery. We applied Cox regression proportional hazards modeling to identify multigene predictors of recurrence. Gene models were then validated in two independent cohorts of 54 and 187 patients (fresh-frozen and formalin-fixed tissue validation sets, respectively).

Results

We focused on genes univariately associated with DFS (p<0.01) in the training set. Among several models comprising different numbers of genes, a 30-probe set model demonstrated optimal performance in both the training (log-rank, p<0.001) and 1^st validation (p = 0.010) sets. Specifically, in the 1^st validation set, median DFS as predicted by the 30-probe set model, was 34 and 80 months for high- and low-risk patients, respectively. Hazard ratio (HR) for recurrence in the high-risk group was 3.87 (95% CI 1.28–11.73, Wald's p = 0.017). Testing the expression of selected genes from the above model in the 2^nd validation set, with qPCR, revealed significant associations of single markers, such as ACE2, FLOT1 and PRKD1, with patient DFS. High PRKD1 remained an unfavorable prognostic marker upon multivariate analysis (HR = 2.00, 95% CI 1.28–3.14, p = 0.002) along with positive nodal status.

Conclusions

We have established and validated gene models that can successfully stratify patients with laryngeal cancer, based on their risk for recurrence. It seems worthy to prospectively validate PRKD1 expression as a laryngeal cancer prognostic marker, for routine clinical applications.

Sample parameters affecting the clinical relevance of RNA biomarkers in translational breast cancer research

In the frame of translational breast cancer research, eligibility criteria for formalin-fixed paraffin-embedded tissue (FFPE) material processing for gene expression studies include tumor cell content (TCC) and sample site (primary vs metastatic tumors). Herein we asked whether the observed differences in gene expression between paired samples with respect to TCC and sample site also have different clinical significance. We assessed ESR1, ERBB2, MAPT, MMP7, and RACGAP1 mRNA expression with real time PCR in paired samples before (NMD) and after macrodissection (MD) from 98 primary tumors (P_MD, P_NMD) and 72 metastatic lymph nodes (LN_MD, LN_NMD), as well as from 93 matched P (mP) and LN (mLN). TCC range was 2.5–75 % in the NMD series and 28–98 % in the MD and in the mP/mLN series. The prognostic effect of these markers, individually or in clusters, remained stable between paired P_MD/NMD. In comparison, cluster classification failed in the LN_NMD group with lower TCC. In the mP/mLN cohort, RACGAP1 mRNA expression was of prognostic significance when tested in mLN samples (p < 0.001). Similarly, luminal B, HER2, and triple negative tumors were of dismal prognosis when classified in the LN component of the same series (mLN, overall survival: p = 0.013, p = 0.034, and p = 0.007, respectively). In conclusion, the clinical relevance of the RNA markers examined may be affected by TCC in metastatic LN samples but not in primary tumors, while it differs between primary tumors and matched metastases. These data will facilitate the design of translational studies involving FFPE sample series.

Cloning of the human activated leukocyte cell adhesion molecule promoter and identification of its tissue-independent transcriptional activation by Sp1

Activated leukocyte cell adhesion molecule (ALCAM) belongs to the immunoglobulin cell adhesion molecule super family. ALCAM is implicated in tumor progression, inflammation, and the differentiation of hematopoietic stem cells. Hitherto, the identity of regulatory DNA elements and cognate transcription factors responsible for ALCAM gene expression remained unknown. In this report, the human ALCAM promoter was cloned and its transcriptional mechanisms elucidated. The promoter is TATA-less and contains multiple GC-boxes. A proximal 650-bp promoter fragment conferred tissue-independent activation, whereas two contiguous regions upstream of this region negatively influenced promoter activity in a tissue-specific manner. The positive regulatory promoter region was mapped to a core 50 base pair sequence containing a conical Sp1 element. Mutation analysis revealed that this element alone or in tandem with elements immediately upstream was required for maximal promoter activity. Chromatin analysis revealed that Sp1 binds exclusively to the canonical binding sequence in vivo, but not to DNA sequence immediately upstream. Finally, we showed that over-expression of Sp1 significantly increased the basal promoter activity. Thus, Sp1 activated the ALCAM promoter in most cells. These findings have important ramifications for unraveling the roles of ALCAM in inflammation and tumorigenesis.

Transcriptome data analysis for cell culture processes

In the past decade, DNA microarrays have fundamentally changed the way we study complex biological systems. By measuring the expression levels of thousands of transcripts, the paradigm of studying organisms has shifted from focusing on the local phenomena of a few genes to surveying the whole genome. DNA microarrays are used in a variety of ways, from simple comparisons between two samples to more intricate time-series studies. With the large number of genes being studied, the dimensionality of the problem is inevitably high. The analysis of microarray data thus requires specific approaches. In the case of time-series microarray studies, data analysis is further complicated by the correlation between successive time points in a series.In this review, we survey the methodologies used in the analysis of static and time-series microarray data, covering data pre-processing, identification of differentially expressed genes, profile pattern recognition, pathway analysis, and network reconstruction. When available, examples of their use in mammalian cell cultures are presented.

A seven-gene prognostic model for platinum-treated ovarian carcinomas

BACKGROUND

Prognosis of ovarian carcinoma is poor, heterogeneous, and not accurately predicted by histoclinical features. We analysed gene expression profiles of ovarian carcinomas to identify a multigene expression model associated with survival after platinum-based therapy.

METHODS

Data from 401 ovarian carcinoma samples were analysed. The learning set included 35 cases profiled using whole-genome DNA chips. The validation set included 366 cases from five independent public data sets.

RESULTS

Whole-genome unsupervised analysis could not distinguish poor from good prognosis samples. By supervised analysis, we built a seven-gene optimal prognostic model (OPM) out of 94 genes identified as associated with progression-free survival. Using the OPM, we could classify patients in two groups with different overall survival (OS) not only in the learning set, but also in the validation set. Five-year OS was 57 and 27% for the predicted 'Favourable' and 'Unfavourable' classes, respectively. In multivariate analysis, the OPM outperformed the individual current prognostic factors, both in the learning and the validation sets, and added independent prognostic information.

CONCLUSION

We defined a seven-gene model associated with outcome in 401 ovarian carcinomas. Prospective studies are warranted to confirm its prognostic value, and explore its potential ability for better tailoring systemic therapies in advanced-stage tumours.

Mechanisms of transcriptional regulation and prognostic significance of activated leukocyte cell adhesion molecule in cancer

Background

Activated leukocyte cell adhesion molecule (ALCAM) is implicated in the prognosis of multiple cancers with low level expression associated with metastasis and early death in breast cancer. Despite this significance, mechanisms that regulate ALCAM gene expression and ALCAM's role in adhesion of pre-metastatic circulating tumor cells have not been defined. We studied ALCAM expression in 20 tumor cell lines by real-time PCR, western blot and immunochemistry. Epigenetic alterations of the ALCAM promoter were assessed using methylation-specific PCR and bisulfite sequencing. ALCAM's role in adhesion of tumor cells to the vascular wall was studied in isolated perfused lungs.

Results

A common site for transcription initiation of the ALCAM gene was identified and the ALCAM promoter sequenced. The promoter contains multiple cis-active elements including a functional p65 NF-κB motif, and it harbors an extensive array of CpG residues highly methylated exclusively in ALCAM-negative tumor cells. These CpG residues were modestly demethylated after 5-aza-2-deoxycytidine treatment. Restoration of high-level ALCAM expression using an ALCAM cDNA increased clustering of MDA-MB-435 tumor cells perfused through the pulmonary vasculature of ventilated rat lungs. Anti-ALCAM antibodies reduced the number of intravascular tumor cell clusters.

Conclusion

Our data suggests that loss of ALCAM expression, due in part to DNA methylation of extensive segments of the promoter, significantly impairs the ability of circulating tumor cells to adhere to each other, and may therefore promote metastasis. These findings offer insight into the mechanisms for down-regulation of ALCAM gene expression in tumor cells, and for the positive prognostic value of high-level ALCAM in breast cancer.