The transcription levels and prognostic values of seven proteasome alpha subunits in human cancers

Aberrated PSMA1 expression associated with clinicopathological features and prognosis in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is a globally prevalent cancer with significant mortality rates. OSCC a predominant subtype of head and neck squamous cell carcinoma (HNSCC), poses a substantial health burden. Despite advancements in diagnosis and therapy, OSCC prognosis remains poor. The 26S proteasome, a cellular protein degradation complex, is associated with cancer, including PSMA1, a proteasomal subunit, which is upregulated in various cancers. We analyzed PSMA1 expression using TCGA data, validated it in OSCC samples using real-time PCR, and explored its role through various databases. Tumor and adjacent normal tissues from OSCC patients were examined, and PSMA1 expression was analyzed. Survival analysis assessed the impact of PSMA1 on patient outcomes, while immune infiltration was examined using the TIMER database. GeneMANIA, STRING, and Metascape were utilized for gene interaction and pathway analysis. PSMA1 was significantly upregulated in OSCC and HNSCC. Its overexpression correlated with advanced clinicopathological features and poorer prognosis in HNSCC patients. PSMA1 expression is also related to immune cell infiltration. Gene interaction analysis revealed PSMA1 involvement in proteolysis regulation, suggesting its potential as a therapeutic target. PSMA1 upregulation in HNSCC association with adverse clinicopathological features and prognosis underscores its potential significance. Further research is warranted to elucidate its molecular mechanisms and therapeutic potential in OSCC management.

Changes Induced by P2X7 Receptor Stimulation of Human Glioblastoma Stem Cells in the Proteome of Extracellular Vesicles Isolated from Their Secretome

Extracellular vesicles (EVs) are secreted from many tumors, including glioblastoma multiforme (GBM), the most common and lethal brain tumor in adults, which shows high resistance to current therapies and poor patient prognosis. Given the high relevance of the information provided by cancer cell secretome, we performed a proteomic analysis of microvesicles (MVs) and exosomes (EXOs) released from GBM-derived stem cells (GSCs). The latter, obtained from the brain of GBM patients, expressed P2X7 receptors (P2X7Rs), which positively correlate with GBM growth and invasiveness. P2X7R stimulation of GSCs caused significant changes in the EV content, mostly ex novo inducing or upregulating the expression of proteins related to cytoskeleton reorganization, cell motility/spreading, energy supply, protection against oxidative stress, chromatin remodeling, and transcriptional regulation. Most of the induced/upregulated proteins have already been identified as GBM diagnostic/prognostic factors, while others have only been reported in peripheral tumors. Our findings indicate that P2X7R stimulation enhances the transport and, therefore, possible intercellular exchange of GBM aggressiveness-increasing proteins by GSC-derived EVs. Thus, P2X7Rs could be considered a new druggable target of human GBM, although these data need to be confirmed in larger experimental sets.

Single-cell and transcriptomic analyses reveal the influence of diabetes on ovarian cancer

BACKGROUND

There has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.

METHODS

Multiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.

RESULTS

The immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.

CONCLUSION

This study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.

Isolation of lymph shows dysregulation of STAT3 and CREB pathways in the spleen and liver during leukemia development in a rat model

BACKGROUND AND AIMS

Acute myeloid leukemia (AML) is a heterogeneous malignant condition characterized by massive infiltration of poorly differentiated white blood cells in the blood stream, bone marrow, and extramedullary sites. During leukemic development, hepatosplenomegaly is expected to occur because large blood volumes are continuously filtered through these organs. We asked whether infiltration of leukemic blasts initiated a response that could be detected in the interstitial fluid phase of the spleen and liver.

MATERIAL AND METHODS

We used a rat model known to mimic human AML in growth characteristics and behavior. By cannulating efferent lymphatic vessels from the spleen and liver, we were able to monitor the response of the microenvironment during AML development.

RESULTS AND DISCUSSION

Flow cytometric analysis of lymphocytes showed increased STAT3 and CREB signaling in spleen and depressed signaling in liver, and proteins related to these pathways were identified with a different profile in lymph and plasma in AML compared with control. Additionally, several proteins were differently regulated in the microenvironment of spleen and liver in AML when compared with control.

CONCLUSION

Interstitial fluid, and its surrogate efferent lymph, can be used to provide unique information about responses in AML-infiltered organs and substances released to the general circulation during leukemia development.

PSMA2 knockdown impacts expression of proteins involved in immune and cellular stress responses in human lung cells

Proteasome subunit alpha type-2 (PSMA2) is a critical component of the 20S proteasome, which is the core particle of the 26S proteasome complex and is involved in cellular protein quality control by recognizing and recycling defective proteins. PSMA2 expression dysregulation has been detected in different human diseases and viral infections. No study yet has reported PSMA2 knockdown (KD) effects on the cellular proteome.

METHODS

We used SOMAScan, an aptamer-based multiplexed technique, to measure >1300 human proteins to determine the impact of PSMA2 KD on A549 human lung epithelial cells.

RESULTS

PSMA2 KD resulted in significant dysregulation of 52 cellular proteins involved in different bio-functions, including cellular movement and development, cell death and survival, and cancer. The immune system and signal transduction were the most affected cellular functions. PSMA2 KD caused dysregulation of several signaling pathways involved in immune response, cytokine signaling, organismal growth and development, cellular stress and injury (including autophagy and unfolded protein response), and cancer responses.

CONCLUSIONS

In summary, this study helps us better understand the importance of PSMA2 in different cellular functions, signaling pathways, and human diseases.

Identification of prognostically significant DNA methylation signatures in patients with various breast cancer types

Breast cancer (BC) is the most frequently diagnosed cancer and one of the major causes of female mortality. The development of prognostic models based on multiomics data is the main goal of precision oncology. Aberrant DNA methylation in BC is a diagnostic marker of carcinogenesis. Despite the existing factors of BC prognosis, introduction of methylation markers would make it possible to obtain more accurate prognostic scores. The study was aimed to assess DNA methylation signatures in various BC subtypes for clinical endpoints and patients' clinicopathological characteristics. The data on methylation of CpG dinucleotides (probes) and clinical characteristics of BC samples were obtained from The Cancer Genome Atlas Breast Cancer database. CpG dinucleotides associated with the selected endpoints were chosen by univariate Cox regression method. The LASSO method was used to search for stable probes, while further signature construction and testing of the clinical characteristics independence were performed using multivariate Cox regression. The dignostic and prognostic potential of the signatures was assessed using ROC analysis and Kaplan–Meier curves. It has been shown that the signatures of selected probes have a significant diagnostic (AUC 0.76–1) and prognostic (p < 0.05) potential. This approach has made it possible to identify 47 genes associated with good and poor prognosis, among these five genes have been described earlier. If the genome-wide DNA analysis results are available, the research approach applied can be used to study molecular pathogenesis of BC and other disorders.

Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types

Background

The human proteasome gene family (PSM) consists of 49 genes that play a crucial role in cancer proteostasis. However, little is known about the effect of PSM gene expression and genetic alterations on clinical outcome in different cancer forms.

Methods

Here, we performed a comprehensive pan-cancer analysis of genetic alterations in PSM genes and the subsequent prognostic value of PSM expression using data from The Cancer Genome Atlas (TCGA) containing over 10,000 samples representing up to 33 different cancer types. External validation was performed using a breast cancer cohort and KM plotter with four cancer types.

Results

The PSM genetic alteration frequency was high in certain cancer types (e.g. 67%; esophageal adenocarcinoma), with DNA amplification being most common. Compared with normal tissue, most PSM genes were predominantly overexpressed in cancer. Survival analysis also established a relationship with PSM gene expression and adverse clinical outcome, where PSMA1 and PSMD11 expression were linked to more unfavorable prognosis in ≥ 30% of cancer types for both overall survival (OS) and relapse-free interval (PFI). Interestingly, PSMB5 gene expression was associated with OS (36%) and PFI (27%), and OS for PSMD2 (42%), especially when overexpressed.

Conclusion

These findings indicate that several PSM genes may potentially be prognostic biomarkers and novel therapeutic targets for different cancer forms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10079-4.

IFITM3 promotes malignant progression, cancer stemness and chemoresistance of gastric cancer by targeting MET/AKT/FOXO3/c-MYC axis

Background

Targeting the HGF/MET signaling pathway has been a viable therapeutic strategy for various cancer types due to hyperactivation of HGF/MET axis occurs frequently that leads to detrimental cancer progression and recurrence. Deciphering novel molecule mechanisms underlying complex HGF/MET signaling network is therefore critical to development of effective therapeutics for treating MET-dependent malignancies.

Results

Using isobaric mass tag-based quantitative proteomics approach, we identified IFITM3, an interferon-induced transmembrane protein that was highly expressed in micro-dissected gastric cancer (GC) tumor regions relative to adjacent non-tumor epithelia. Analyses of GC clinical specimens revealed that expression IFITM3 was closely correlated to advanced pathological stages. IFITM3 has been reported as a PIP3 scaffold protein that promotes PI3K signaling. In present study, we unprecedentedly unraveled that IFITM3 associated with MET and AKT to facilitate HGF/MET mediated AKT signaling crosstalk in suppressing FOXO3, consequently leading to c-MYC mediated GC progression. In addition, gene ontology analyses of the clinical GC cohort revealed significant correlation between IFITM3-associated genes and targets of c-MYC, which is a crucial downstream effector of HGF/MET pathway in cancer progression. Moreover, we demonstrated ectopic expression of IFITM3 suppressed FOXO3 expression, consequently led to c-MYC induction to promote tumor growth, cell metastasis, cancer stemness as well as chemoresistance. Conversely, depletion of IFITM3 resulted in suppression of HGF triggered cellular growth and migration via inhibition of AKT/c-MYC signaling in GC.

Conclusions

In summary, our present study unveiled a novel regulatory mechanism for c-MYC-driven oncogenesis underlined by IFITM3-mediated signaling crosstalk between MET associated AKT signaling cascade.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00858-8.

AKT1 Transcriptomic Landscape in Breast Cancer Cells

Overexpression and hyperactivation of the serine/threonine protein kinase B (AKT) pathway is one of the most common cellular events in breast cancer progression. However, the nature of AKT1-specific genome-wide transcriptomic alterations in breast cancer cells and breast cancer remains unknown to this point. Here, we delineate the impact of selective AKT1 knock down using gene-specific siRNAs or inhibiting the AKT activity with a pan-AKT inhibitor VIII on the nature of transcriptomic changes in breast cancer cells using the genome-wide RNA-sequencing analysis. We found that changes in the cellular levels of AKT1 lead to changes in the levels of a set of differentially expressed genes and, in turn, imply resulting AKT1 cellular functions. In addition to an expected positive relationship between the status of AKT1 and co-expressed cellular genes, our study unexpectedly discovered an inherent role of AKT1 in inhibiting the expression of a subset of genes in both unstimulated and growth factor stimulated breast cancer cells. We found that depletion of AKT1 leads to upregulation of a subset of genes—many of which are also found to be downregulated in breast tumors with elevated high AKT1 as well as upregulated in breast tumors with no detectable AKT expression. Representative experimental validation studies in two breast cancer cell lines showed a reasonable concurrence between the expression data from the RNA-sequencing and qRT-PCR or data from ex vivo inhibition of AKT1 activity in cancer patient-derived cells. In brief, findings presented here provide a resource for further understanding of AKT1-dependent modulation of gene expression in breast cancer cells and broaden the scope and significance of AKT1 targets and their functions.

Application of two-dimensional difference gel electrophoresis to identify protein changes between center, margin, and adjacent non-tumor tissues obtained from non-small-cell lung cancer with adenocarcinoma or squamous cell carcinoma subtype

Lung cancer is responsible for the most cancer-related mortality worldwide and the mechanism of its development is poorly understood. Proteomics has become a powerful tool offering vital knowledge related to cancer development. Using a two-dimensional difference gel electrophoresis (2D-DIGE) approach, we sought to compare tissue samples from non-small-cell lung cancer (NSCLC) patients taken from the tumor center and tumor margin. Two subtypes of NSCLC, adenocarcinoma (ADC) and squamous cell carcinoma (SCC) were compared. Data are available via ProteomeXchange with identifier PXD032736 and PXD032962 for ADC and SCC, respectively. For ADC proteins, 26 significant canonical pathways were identified, including Rho signaling pathways, a semaphorin neuronal repulsive signaling pathway, and epithelial adherens junction signaling. For SCC proteins, nine significant canonical pathways were identified, including hypoxia-inducible factor-1α signaling, thyroid hormone biosynthesis, and phagosome maturation. Proteins differentiating the tumor center and tumor margin were linked to cancer invasion and progression, including cell migration, adhesion and invasion, cytoskeletal structure, protein folding, anaerobic metabolism, tumor angiogenesis, EMC transition, epithelial adherens junctions, and inflammatory responses. In conclusion, we identified several proteins that are important for the better characterization of tumor development and molecular specificity of both lung cancer subtypes. We also identified proteins that may be important as biomarkers and/or targets for anticancer therapy.

Cytoskeletal Alteration Is an Early Cellular Response in Pulmonary Epithelium Infected with Aspergillus fumigatus Rather than Scedosporium apiospermum

Invasive aspergillosis and scedosporiosis are life-threatening fungal infections with similar clinical manifestations in immunocompromised patients. Contrarily, Scedosporium apiospermum is susceptible to some azole derivative but often resistant to amphotericin B. Histopathological examination alone cannot diagnose these two fungal species. Pathogenesis studies could contribute to explore candidate protein markers for new diagnosis and treatment methods leading to a decrease in mortality. In the present study, proteomics was conducted to identify significantly altered proteins in A549 cells infected with or without Aspergillus fumigatus and S. apiospermum as measured at initial invasion. Protein validation was performed with immunogold labelling alongside immunohistochemical techniques in infected A549 cells and lungs from murine models. Further, cytokine production was measured, using the Bio-Plex-Multiplex immunoassay. The cytoskeletal proteins HSPA9, PA2G4, VAT1, PSMA2, PEX1, PTGES3, KRT1, KRT9, CLIP1 and CLEC20A were mainly changed during A. fumigatus infection, while the immunologically activated proteins WNT7A, GAPDH and ANXA2 were principally altered during S. apiospermum infection. These proteins are involved in fungal internalisation and structural destruction leading to pulmonary disorders. Interleukin (IL)-21, IL-1α, IL-22, IL-2, IL-8, IL-12, IL-17A, interferon-γ and tumour necrosis factor-α were upregulated in both aspergillosis and scedosporiosis, although more predominately in the latter, in accordance with chitin synthase-1 and matrix metalloproteinase levels. Our results demonstrated that during invasion, A. fumigatus primarily altered host cellular integrity, whereas S. apiospermum chiefly induced and extensively modulated host immune responses.

Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer

The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Consequently, we used a holistic bioinformatics approach to study the PSMA genes involved in breast cancer by integrating several well-established high-throughput databases and tools, such as cBioPortal, Oncomine, and the Kaplan–Meier plotter. Additionally, correlations of breast cancer patient survival and PSMA messenger RNA expressions were also studied. The results demonstrated that breast cancer tissues had higher expression levels of PSMA genes compared to normal breast tissues. Furthermore, PSMA2, PSMA3, PSMA4, PSMA6, and PSMA7 showed high expression levels, which were correlated with poor survival of breast cancer patients. In contrast, PSMA5 and PSMA8 had high expression levels, which were associated with good prognoses. We also found that PSMA family genes were positively correlated with the cell cycle, ubiquinone metabolism, oxidative stress, and immune response signaling, including antigen presentation by major histocompatibility class, interferon-gamma, and the cluster of differentiation signaling. Collectively, these findings suggest that PSMA genes have the potential to serve as novel biomarkers and therapeutic targets for breast cancer. Nevertheless, the bioinformatic results from the present study would be strengthened with experimental validation in the future by prospective studies on the underlying biological mechanisms of PSMA genes and breast cancer.

Molecular Profile Study of Extracellular Vesicles for the Identification of Useful Small “Hit” in Cancer Diagnosis

Tumor-secreted extracellular vesicles (EVs) are the main mediators of cell-cell communication, permitting cells to exchange proteins, lipids, and metabolites in varying physiological and pathological conditions. They contain signature tumor-derived molecules that reflect the intracellular status of their cell of origin. Recent studies have shown that tumor cell-derived EVs can aid in cancer metastasis through the modulation of the tumor microenvironment, suppression of the immune system, pre-metastatic niche formation, and subsequent metastasis. EVs can easily be isolated from a variety of biological fluids, and their content makes them useful biomarkers for the diagnosis, prognosis, monitorization of cancer progression, and response to treatment. This review aims to explore the biomarkers of cancer cell-derived EVs obtained from liquid biopsies, in order to understand cancer progression and metastatic evolution for early diagnosis and precision therapy.

Targeted Mass Spectrometry Enables Multiplexed Quantification of Immunomodulatory Proteins in Clinical Biospecimens

Immunotherapies are revolutionizing cancer care, producing durable responses and potentially cures in a subset of patients. However, response rates are low for most tumors, grade 3/4 toxicities are not uncommon, and our current understanding of tumor immunobiology is incomplete. While hundreds of immunomodulatory proteins in the tumor microenvironment shape the anti-tumor response, few of them can be reliably quantified. To address this need, we developed a multiplex panel of targeted proteomic assays targeting 52 peptides representing 46 proteins using peptide immunoaffinity enrichment coupled to multiple reaction monitoring-mass spectrometry. We validated the assays in tissue and plasma matrices, where performance figures of merit showed over 3 orders of dynamic range and median inter-day CVs of 5.2% (tissue) and 21% (plasma). A feasibility study in clinical biospecimens showed detection of 48/52 peptides in frozen tissue and 38/52 peptides in plasma. The assays are publicly available as a resource for the research community.

Sperm Associated Antigens: Vigorous Influencers in Life

Sperm associated antigens (SPAGs) are specific proteins in terms of performance and evolution, that have common expressions in the testes or sperm cells. Moreover, the humoral immune response against some of SPAGs can result in immunological infertilities. On the other hand, recent studies have explored several new properties of SPAGs and shed light on sperm's function, the impact of anti-sperm antibodies (ASA) in immunological infertility, and some tumors related to SPAGs. This article presents an exhaustive review of SPAGs and their roles in the cell cycle, signaling pathways, fertility, sperm-oocyte cross-talk as well as their unfavorable positions as prognostic factors in many types of cancers.

Ubiquitin-proteasome system and the role of its inhibitors in cancer therapy

Despite all the other cells that have the potential to prevent cancer development and metastasis through tumour suppressor proteins, cancer cells can upregulate the ubiquitin–proteasome system (UPS) by which they can degrade tumour suppressor proteins and avoid apoptosis. This system plays an extensive role in cell regulation organized in two steps. Each step has an important role in controlling cancer. This demonstrates the importance of understanding UPS inhibitors and improving these inhibitors to foster a new hope in cancer therapy. UPS inhibitors, as less invasive chemotherapy drugs, are increasingly used to alleviate symptoms of various cancers in malignant states. Despite their success in reducing the development of cancer with the lowest side effects, thus far, an appropriate inhibitor that can effectively inactivate this system with the least drug resistance has not yet been fully investigated. A fundamental understanding of the system is necessary to fully elucidate its role in causing/controlling cancer. In this review, we first comprehensively investigate this system, and then each step containing ubiquitination and protein degradation as well as their inhibitors are discussed. Ultimately, its advantages and disadvantages and some perspectives for improving the efficiency of these inhibitors are discussed.

Overexpression of PSMA7 predicts poor prognosis in patients with gastric cancer

Gastric cancer (GC) is the fourth most common tumor and the second most common cause of cancer-associated mortality worldwide. Current tumor biomarkers for GC, such as serum carcinoembryonic antigen and carbohydrate antigen 19-9, are not ideal due to their limited role as prognostic indicators for GC. Proteasome subunit α7 (PSMA7) is a multifunctional protein, which has been revealed to be involved in the development and progression of various types of malignancy. However, little is known about the role of PSMA7 in GC. In the present study, PSMA7 was identified to be overexpressed at the mRNA and protein levels in GC tissues, compared with in non-tumor tissues, using reverse transcription-quantitative PCR and immunohistochemistry. Furthermore, PSMA7 expression is associated with tumor invasion, lymph node metastasis, distant metastasis, and Tumor-Node-Metastasis stage. Univariate and multivariate Cox regression analysis identified that PSMA7 expression is an independent prognostic factor for poor survival. Kaplan-Meier survival curves revealed that high PSMA7 expression is associated with a poor prognosis in patients with GC. Overall, the results of the present study suggested that PSMA7 may be a promising biomarker for the prognosis of GC, and may represent a new diagnostic marker and molecular therapeutic target for GC.

Proteasome 26S Subunit, non-ATPase 3 (PSMD3) Regulates Breast Cancer by Stabilizing HER2 from Degradation

It is well-known that human epidermal growth factor receptor 2 (HER2) is critical for breast cancer (BC) development and progression. Several studies have revealed the role of the ubiquitin/proteasome system (UPS) in cancer. In this study, we investigated the expression level of Proteasome 26S subunit, non-ATPase 3 (PSMD3) in BC using BC cell lines, human BC tissue samples, Oncomine, and TCGA databases and studied the PSMD3-HER2 protein interaction. PSMD3 was upregulated in BC, particularly in the HER2+ subtype. PSMD3 immunostaining was detected in the cytoplasm and nucleus of BC tumor tissues. Strong interaction between PSMD3 and HER2 at the protein level was observed. Knockdown of PSMD3 significantly impaired the stability of HER2, inhibited BC cell proliferation and colony formation, and induced cell apoptosis. Ubiquitination process was strongly enhanced after knockdown of PSMD3 in association with decreased HER2 level. Accumulation and Localization of LAMP-1 in the cell membrane with decreased HER2 immunostaining was observed after knockdown of PSMD3. High expression level of PSMD3 was associated with HER2 expression (p < 0.001), tumor size (p < 0.001), and clinical stage (p = 0.036). High expression level of PSMD3 predicted a short overall survival (OS), particularly for HER2+. Overall, we provide a novel function for PSMD3 in stabilizing HER2 from degradation in HER2+ BC, which suggests that PSMD3 is a novel target for HER2+ BC.

Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data

Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-depth histopathology analysis, clinical data and genomics profiles. This broad view of protein expression allowed to identify novel candidate protein markers that improved prediction of survival in melanoma patients. Some of the prognostic proteins have not been reported in the context of melanoma before, and few of them exhibit unexpected relationship to survival, which likely reflects the limitations of current knowledge on melanoma and shows the potential of proteomics in clinical cancer research.

Novel TG-FGFR1 and TRIM33-NTRK1 transcript fusions in papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is most common among all thyroid cancers. Multiple genomic alterations occur in PTC, and gene rearrangements are one of them. Here we screened 14 tumors for novel fusion transcripts by RNA‐Seq. Two samples harboring RET/PTC1 and RET/PTC3 rearrangements were positive controls whereas the remaining ones were negative regarding the common PTC alterations. We used Sanger sequencing to validate potential fusions. We detected 2 novel potentially oncogenic transcript fusions: TG‐FGFR1 and TRIM33‐NTRK1. We detected 4 novel fusion transcripts of unknown significance accompanying the TRIM33‐NTRK1 fusion: ZSWIM5‐TP53BP2, TAF4B‐WDR1, ABI2‐MTA3, and ARID1B‐PSMA1. Apart from confirming the presence of RET/PTC1 and RET/PTC3 in positive control samples, we also detected known oncogenic fusion transcripts in remaining samples: TFG‐NTRK1, ETV6‐NTRK3, MKRN1‐BRAF, EML4‐ALK, and novel isoform of CCDC6‐RET.

Comparison of different functional prediction scores using a gene-based permutation model for identifying cancer driver genes

Background

Identifying cancer driver genes (CDG) is a crucial step in cancer genomic toward the advancement of precision medicine. However, driver gene discovery is a very challenging task because we are not only dealing with huge amount of data; but we are also faced with the complexity of the disease including the heterogeneity of background somatic mutation rate in each cancer patient. It is generally accepted that CDG harbor variants conferring growth advantage in the malignant cell and they are positively selected, which are critical to cancer development; whereas, non-driver genes harbor random mutations with no functional consequence on cancer. Based on this fact, function prediction based approaches for identifying CDG have been proposed to interrogate the distribution of functional predictions among mutations in cancer genomes (eLS 1–16, 2016). Assuming most of the observed mutations are passenger mutations and given the quantitative predictions for the functional impact of the mutations, genes enriched of functional or deleterious mutations are more likely to be drivers. The promises of these methods have been continually refined and can therefore be applied to increase accuracy in detecting new candidate CDGs. However, current function prediction based approaches only focus on coding mutations and lack a systematic way to pick the best mutation deleteriousness prediction algorithms for usage.

Results

In this study, we propose a new function prediction based approach to discover CDGs through a gene-based permutation approach. Our method not only covers both coding and non-coding regions of the genes; but it also accounts for the heterogeneous mutational context in cohort of cancer patients. The permutation model was implemented independently using seven popular deleteriousness prediction scores covering splicing regions (SPIDEX), coding regions (MetaLR, and VEST3) and pan-genome (CADD, DANN, Fathmm-MKL coding and Fathmm-MKL noncoding). We applied this new approach to somatic single nucleotide variants (SNVs) from whole-genome sequences of 119 breast and 24 lung cancer patients and compared the seven deleteriousness prediction scores for their performance in this study.

Conclusion

The new function prediction based approach not only predicted known cancer genes listed in the Cancer Gene Census (CGC), but also new candidate CDGs that are worth further investigation. The results showed the advantage of utilizing pan-genome deleteriousness prediction scores in function prediction based methods. Although VEST3 score, a deleteriousness prediction score for missense mutations, has the best performance in breast cancer, it was topped by CADD and Fathmm-MKL coding, two pan-genome deleteriousness prediction scores, in lung cancer.

Electronic supplementary material

The online version of this article (10.1186/s12920-018-0452-9) contains supplementary material, which is available to authorized users.

A risk score staging system based on the expression of seven genes predicts the outcome of bladder cancer

Bladder cancer (BLCA) is among the most malignant types of cancer. At present, the prognostic tools available for this disease are insufficient. In the present study, the transcriptome of 1,049 BLCA samples from four datasets from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) were analyzed. By utilizing the RNA-seq data provided by TCGA, a risk score staging system model was built to predict the outcome of patients with BLCA using random forest variable hunting and Cox multivariate regression. A total of 7 genes, including zinc finger protein 230, Bcl2-like 14, AHNAK, transmembrane protein 109, apolipoprotein L2, advanced glycation end-product specific receptor and amine oxidase, copper containing 2 were identified as predicting the survival time of patients with BLCA. The patients with a low risk score had a significantly higher survival rate than those with a high-risk score both in the training and validation datasets. Association analyses between risk score and other clinical information were additionally performed; it was demonstrated that the risk score was significantly associated with pathological stage. A nomogram was plotted to compare risk score and other clinical information. The risk score spanned the greatest range of points, indicating the relative accuracy of risk score. In summary, the risk staging model based on the expression of 7 genes is robust and performs more effectively than other clinical information in predicting a prognosis.

Expression signature of ten genes predicts the survival of patients with estrogen receptor positive-breast cancer that were treated with tamoxifen

Although tamoxifen is the most frequently used drug for the treatment of estrogen receptor positive (ER⁺)-breast cancer (BRCA), its efficacy varies between patients. In the present study, Cox multivariate regression of the relative mRNA expression levels in two microarray-based datasets (GSE17005 and GSE26971) was employed to develop a risk score model to evaluate the outcome of patients with BRCA in the GSE17005 dataset. A total of ten genes were used to develop the prediction model for the survival of tamoxifen-treated patients with breast cancer. The survival time of patients in the low risk score group was significantly longer compared with patients in the high risk score group. This observation was validated in three other datasets (GSE26971, GSE22219 and GSE56884). The prognostic effect of the clinicopathological indicators and the risk score were tested with the 5-year event receiving operating characteristic curve, and the risk score had an improved prognostic value in patients with ER⁺-BRCA with an area under the curve value of 0.733 compared with the factors of age, tumor stage, tumor grade, chemotherapy, lymph invasion and tumor size. The risk score was significantly associated with the tumor-node-metastasis stage and grade, but was independent of age, sex, lymph invasion and tumor size. In summary, the risk model for breast cancer using the expression signature of ten genes may be an important indicator for predicting the survival of patients with ER⁺-breast cancer and treated with tamoxifen.

Proteomic analysis of affinity-purified extracellular proteasomes reveals exclusively 20S complexes

Proteasome-mediated proteolysis is important for many basic cellular processes. In addition to their functions in the cell, proteasomes have been found in physiological fluids of both healthy and diseased humans including cancer patients. Higher levels of these proteasomes are associated with higher cancer burden and stage. The etiology and functions of these proteasomes, referred to as circulating, plasmatic, or extracellular proteasomes (ex-PSs), are unclear. Here we show that human cancer cell lines, as well as human endometrium-derived mesenchymal stem cells (hMESCs), release proteasome complexes into culture medium (CM). To define ex-PS composition, we have affinity purified them from CM conditioned by human leukemia cell line K562. Using matrix-assisted laser desorption/ionization (MALDI) Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry (MS), we have identified core 20S proteasome subunits and a set of 15 proteasome-interacting proteins (PIPs), all previously described as exosome cargo proteins. Three of them, PPIase A, aldolase A, and transferrin, have never been reported as PIPs. The study provides compelling arguments that ex-PSs do not contain 19S or PA200 regulatory particles and are represented exclusively by the 20S complex.

Risk score based on three mRNA expression predicts the survival of bladder cancer

Bladder cancer (BLCA) is one of the most malignant cancers worldwide, and its prognosis varies. 1214 BLCA samples in five different datasets and 2 platforms were enrolled in this study. By utilizing the gene expression in The Cancer Genome Atlas (TCGA) dataset, and another two datasets, in GSE13507 and GSE31684, we constructed a risk score staging system with Cox multivariate regression to evaluate predict the outcome of BLCA patients. Three genes consist of RCOR1, ST3GAL5, and COL10A1 were used to predict the survival of BLCA patients. The patients with low risk score have a better survival rate than those with high risk score, significantly. The survival profiles of another two datasets (GSE13507 and GSE31684), which were used for candidate gene selection, were similar as the training dataset (TCGA). Furthermore, survival prediction effect of risk score staging system in another 2 independent datasets, GSE40875 and E-TABM-4321, were also validated. Compared with other clinical observations, and the risk score performs better in evaluating the survival of BLCA patients. Moreover, the correlation between radiation were also evaluated, and we found that patients have a poor survival in high risk group, regardless of radiation. Gene Set Enrichment Analysis was also implemented to find the difference between high-risk and low-risk groups on biological pathways, and focal adhesion and JAK signaling pathway were significantly enriched. In summary, we developed a risk staging model for BLCA patients with three gene expression. The model is independent from and performs better than other clinical information.