Identification of novel candidate circulating biomarkers for malignant soft tissue sarcomas: Correlation with metastatic progression

The human factor H protein family - an update

Complement is an ancient and complex network of the immune system and, as such, it plays vital physiological roles, but it is also involved in numerous pathological processes. The proper regulation of the complement system is important to allow its sufficient and targeted activity without deleterious side-effects. Factor H is a major complement regulator, and together with its splice variant factor H-like protein 1 and the five human factor H-related (FHR) proteins, they have been linked to various diseases. The role of factor H in inhibiting complement activation is well studied, but the function of the FHRs is less characterized. Current evidence supports the main role of the FHRs as enhancers of complement activation and opsonization, i.e., counter-balancing the inhibitory effect of factor H. FHRs emerge as soluble pattern recognition molecules and positive regulators of the complement system. In addition, factor H and some of the FHR proteins were shown to modulate the activity of immune cells, a non-canonical function outside the complement cascade. Recent efforts have intensified to study factor H and the FHRs and develop new tools for the distinction, quantification and functional characterization of members of this protein family. Here, we provide an update and overview on the versatile roles of factor H family proteins, what we know about their biological functions in healthy conditions and in diseases.

Clinical biomarkers in soft tissue sarcoma A comprehensive review of current soft tissue sarcoma biomarkers

Soft tissue sarcomas (STS) are a heterogeneous group of tumors that arise from mesenchymal tissue. Investigation at the molecular level has been challenging due to the rarity of STS and the number of histologic subtypes. However, recent research has provided new insight into potential genomic, proteomic, and immunological biomarkers of STS. The identification of biomarkers can improve diagnosis, prognosis, and prediction of recurrence and treatment response. This review provides an understanding of biomarkers, discussing the current status of biomarker research in STS.

Techniques, perspectives, and challenges of bioactive peptide generation: A comprehensive systematic review

Due to the digestible refractory and absorbable structures of bioactive peptides (BPs), they could induce notable biological impacts on the living organism. In this regard, the current study was devoted to providing an overview regarding the available methods for BPs generation by the aid of a systematic review conducted on the published articles up to April 2019. In this context, the PubMed and Scopus databases were screened to retrieve the related publications. According to the results, although the characterization of BPs mainly has been performed using enzymatic and microbial in-vitro methods, they cannot be considered as suitable techniques for further stimulation of digestion in the gastrointestinal tract. Therefore, new approaches for both in-vivo and in-silico methods for BPs identification should be developed to overcome the obstacles that belonged to the current methods. The purpose of this review was to compile the recent analytical methods applied for studying various aspects of food-derived biopeptides, and emphasizing generation at in vitro, in vivo, and in silico.

Shotgun proteomics coupled to nanoparticle-based biomarker enrichment reveals a novel panel of extracellular matrix proteins as candidate serum protein biomarkers for early-stage breast cancer detection

Background

The lack of specificity and high degree of false positive and false negative rates when using mammographic screening for detecting early-stage breast cancer is a critical issue. Blood-based molecular assays that could be used in adjunct with mammography for increased specificity and sensitivity could have profound clinical impact. Our objective was to discover and independently verify a panel of candidate blood-based biomarkers that could identify the earliest stages of breast cancer and complement current mammographic screening approaches.

Methods

We used affinity hydrogel nanoparticles coupled with LC-MS/MS analysis to enrich and analyze low-abundance proteins in serum samples from 20 patients with invasive ductal carcinoma (IDC) breast cancer and 20 female control individuals with positive mammograms and benign pathology at biopsy. We compared these results to those obtained from five cohorts of individuals diagnosed with cancer in organs other than breast (ovarian, lung, prostate, and colon cancer, as well as melanoma) to establish IDC-specific protein signatures. Twenty-four IDC candidate biomarkers were then verified by multiple reaction monitoring (LC-MRM) in an independent validation cohort of 60 serum samples specifically including earliest-stage breast cancer and benign controls (19 early-stage (T1a) IDC and 41 controls).

Results

In our discovery set, 56 proteins were increased in the serum samples from IDC patients, and 32 of these proteins were specific to IDC. Verification of a subset of these proteins in an independent cohort of early-stage T1a breast cancer yielded a panel of 4 proteins, ITGA2B (integrin subunit alpha IIb), FLNA (Filamin A), RAP1A (Ras-associated protein-1A), and TLN-1 (Talin-1), which classified breast cancer patients with 100% sensitivity and 85% specificity (AUC of 0.93).

Conclusions

Using a nanoparticle-based protein enrichment technology, we identified and verified a highly specific and sensitive protein signature indicative of early-stage breast cancer with no false positives when assessing benign and inflammatory controls. These markers have been previously reported in cell-ECM interaction and tumor microenvironment biology. Further studies with larger cohorts are needed to evaluate whether this biomarker panel improves the positive predictive value of mammography for breast cancer detection.

Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma

Objective

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer in adults. The 5-year survival rate of patients with advanced ccRCC is less than 30%. Lack of potential biomarkers for treatment and prognosis is a limitation for early diagnosis and treatment of ccRCC.

Methods

We collected microarray profiles of 39 ccRCC and matched normal samples to identify differential expression genes (DEGs). Then, a weighted gene co-expression network analysis (WGCNA) was constructed to identify gene modules associated with the metastasis in ccRCC. The Cancer Genome Atlas (TCGA) database and the Human Protein Atlas (HPA, https://www.proteinatlas.org/) database were used for verification set. Finally, we used biological experiments to preliminary investigate the impact of LTF on the tumor biological behavior of ccRCC, including proliferation, migration, invasion, and apoptosis.

Results

A total of 15 genetic modules were identified, and the light-green module is considered the most relevant to tumor metastasis. (P = 0.02, R² = −0.4). Protein–protein interaction (PPI) network was performed to identify the hub nodes in the light-green module. Finally, combining the results of PPI, WGCNA and DEGs, lactotransferrin (LTF) gene was regarded as “real” hub genes for cancer metastasis risk. LTF was subsequently validated using the TCGA database. Immunohistochemistry confirmed that the expression of LTF in ccRCC tumor tissue was significantly lower than that in normal tissue based on the HPA database. Intriguingly, patients with low expression of LTF had lower survival rates (HR = 0.66, 95% CI: 0.49–0.89, P = 0.0067), the expression level of the sample was negatively correlated with tumor stage (P = 0.0385), and patients with low expression of LTF gene were more likely to have distant metastasis (P = 0.038). Overexpression of LTF inhibited the proliferation, migration, invasion and promoted apoptosis of human ccRCC cells in vitro.

Conclusion

LTF might be a novel prognostic biomarker for ccRCC.

Differential gene expression identifies KRT7 and MUC1 as potential metastasis-specific targets in sarcoma

BACKGROUND

Despite numerous discoveries regarding the molecular genesis and progression of primary cancers, the biology of metastasis remains poorly understood. Compared to very large numbers of circulating tumor cells that are now known to accompany nearly all cancers, a relatively limited number of lesions actually develop in most patients with metastases. We hypothesized that phenotypic changes driven by differential gene expression in a finite subpopulation of tumor cells render those cells capable of metastasis and sought to identify key pathways through analysis of gene expression in primary and metastatic lesions from the same patients.

METHODS

We compared whole-genome expression in 4 matched samples of primary and metastatic sarcoma, then evaluated candidate genes with differential expression via quantitative PCR in 30 additional matched sets, tumor tissue immunostaining, siRNA loss-of-function in a sarcoma cell migration assay, and clinical correlation with overall and disease-free survival after metastasectomy.

RESULTS

Comparison of microarray signals identified differential expression of cell adhesion genes, including upregulation of KRT7 and MUC1 in metastases; KRT7 and MUC1 upregulation was confirmed in 22 (73%) and 20 (67%) matched sets of metastatic/primary tumors, respectively. Silencing of KRT7 and MUC1 via targeted siRNAs suppressed sarcoma cell migration in vitro, and a significant correlation (two-sided) was observed between both KRT7 and MUC1 expression in metastases and overall patient survival.

CONCLUSION

KRT7 and MUC1 may play a significant role in enabling sarcoma metastasis, and they may therefore be important prognostic biomarkers as well as potential targets for therapeutic prevention of metastasis.

Proteomic analysis of cerebrospinal fluid from children with central nervous system tumors identifies candidate proteins relating to tumor metastatic spread

Central nervous system (CNS) tumors are the most common solid tumors in childhood. Since the sensitivity of combined cerebrospinal fluid (CSF) cytology and radiological neuroimaging in detecting meningeal metastases remains relatively low, we sought to characterize the CSF proteome of patients with CSF tumors to identify biomarkers predictive of metastatic spread. CSF samples from 27 children with brain tumors and 13 controls (extra-CNS non-Hodgkin lymphoma) were processed using core-shell hydrogel nanoparticles, and analyzed with reverse-phase liquid chromatography/electrospray tandem mass spectrometry (LC-MS/MS). Candidate proteins were identified with Fisher's exact test and/or a univariate logistic regression model. Reverse phase protein array (RPPA), Western blot (WB), and ELISA were used in the training set and in an independent set of CFS samples (60 cases, 14 controls) to validate our discovery findings. Among the 558 non-redundant proteins identified by LC-MS/MS, 147 were missing from the CSF database at http://www.biosino.org. Fourteen of the 26 final top-candidate proteins were chosen for validation with WB, RPPA and ELISA methods. Six proteins (type 1 collagen, insulin-like growth factor binding protein 4, procollagen C-endopeptidase enhancer 1, glial cell-line derived neurotrophic factor receptor α2, inter-alpha-trypsin inhibitor heavy chain 4, neural proliferation and differentiation control protein-1) revealed the ability to discriminate metastatic cases from controls. Combining a unique dataset of CSFs from pediatric CNS tumors with a novel enabling nanotechnology led us to identify CSF proteins potentially related to metastatic status.

Shared liver-like transcriptional characteristics in liver metastases and corresponding primary colorectal tumors

Background & Aims: Primary tumors of colorectal carcinoma (CRC) with liver metastasis might gain some liver-specific characteristics to adapt the liver micro-environment. This study aims to reveal potential liver-like transcriptional characteristics associated with the liver metastasis in primary colorectal carcinoma.

Methods: Among the genes up-regulated in normal liver tissues versus normal colorectal tissues, we identified “liver-specific” genes whose expression levels ranked among the bottom 10% (“unexpressed”) of all measured genes in both normal colorectal tissues and primary colorectal tumors without metastasis. These liver-specific genes were investigated for their expressions in both the primary tumors and the corresponding liver metastases of seven primary CRC patients with liver metastasis using microdissected samples.

Results: Among the 3958 genes detected to be up-regulated in normal liver tissues versus normal colorectal tissues, we identified 12 liver-specific genes and found two of them, ANGPTL3 and CFHR5, were unexpressed in microdissected primary colorectal tumors without metastasis but expressed in both microdissected liver metastases and corresponding primary colorectal tumors (Fisher's exact test, P < 0.05). Genes co-expressed with ANGPTL3 and CFHR5 were significantly enriched in metabolism pathways characterizing liver tissues, including “starch and sucrose metabolism” and “drug metabolism-cytochrome P450”.

Conclusions: For primary CRC with liver metastasis, both the liver metastases and corresponding primary colorectal tumors may express some liver-specific genes which may help the tumor cells adapt the liver micro-environment.