Proteomic Characterization of Prostate Cancer to Distinguish Nonmetastasizing and Metastasizing Primary Tumors and Lymph Node Metastases

Radiogenomic analysis of ultrasound phenotypic features coupled to proteomes predicts metastatic risk in primary prostate cancer

BACKGROUND

Primary prostate cancer with metastasis has a poor prognosis, so assessing its risk of metastasis is essential.

METHODS

This study combined comprehensive ultrasound features with tissue proteomic analysis to obtain biomarkers and practical diagnostic image features that signify prostate cancer metastasis.

RESULTS

In this study, 17 ultrasound image features of benign prostatic hyperplasia (BPH), primary prostate cancer without metastasis (PPCWOM), and primary prostate cancer with metastasis (PPCWM) were comprehensively analyzed and combined with the corresponding tissue proteome data to perform weighted gene co-expression network analysis (WGCNA), which resulted in two modules highly correlated with the ultrasound phenotype. We screened proteins with temporal expression trends based on the progression of the disease from BPH to PPCWOM and ultimately to PPCWM from two modules and obtained a protein that can promote prostate cancer metastasis. Subsequently, four ultrasound image features significantly associated with the metastatic biomarker HNRNPC (Heterogeneous nuclear ribonucleoprotein C) were identified by analyzing the correlation between the protein and ultrasound image features. The biomarker HNRNPC showed a significant difference in the five-year survival rate of prostate cancer patients (p < 0.0053). On the other hand, we validated the diagnostic efficiency of the four ultrasound image features in clinical data from 112 patients with PPCWOM and 150 patients with PPCWM, obtaining a combined diagnostic AUC of 0.904. In summary, using ultrasound imaging features for predicting whether prostate cancer is metastatic has many applications.

CONCLUSION

The above study reveals noninvasive ultrasound image biomarkers and their underlying biological significance, which provide a basis for early diagnosis, treatment, and prognosis of primary prostate cancer with metastasis.

Proteome alterations in human autopsy tissues in relation to time after death

Protein expression is a primary area of interest for routine histological diagnostics and tissue-based research projects, but the limitations of its post-mortem applicability remain largely unclear. On the other hand, tissue specimens obtained during autopsies can provide unique insight into advanced disease states, especially in cancer research. Therefore, we aimed to identify the maximum post-mortem interval (PMI) which is still suitable for characterizing protein expression patterns, to explore organ-specific differences in protein degradation, and to investigate whether certain proteins follow specific degradation kinetics. Therefore, the proteome of human tissue samples obtained during routine autopsies of deceased patients with accurate PMI (6, 12, 18, 24, 48, 72, 96 h) and without specific diseases that significantly affect tissue preservation, from lungs, kidneys and livers, was analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). For the kidney and liver, significant protein degradation became apparent at 48 h. For the lung, the proteome composition was rather static for up to 48 h and substantial protein degradation was detected only at 72 h suggesting that degradation kinetics appear to be organ specific. More detailed analyses suggested that proteins with similar post-mortem kinetics are not primarily shared in their biological functions. The overrepresentation of protein families with analogous structural motifs in the kidney indicates that structural features may be a common factor in determining similar postmortem stability. Our study demonstrates that a longer post-mortem period may have a significant impact on proteome composition, but sampling within 24 h may be appropriate, as degradation is within acceptable limits even in organs with faster autolysis.

Biomarkers for the Detection and Risk Stratification of Aggressive Prostate Cancer

Current strategies for the clinical management of prostate cancer are inadequate for a precise risk stratification between indolent and aggressive tumors. Recently developed tissue-based molecular biomarkers have refined the risk assessment of the disease. The characterization of tissue biopsy components and subsequent identification of relevant tissue-based molecular alterations have the potential to improve the clinical decision making and patient outcomes. However, tissue biopsies are invasive and spatially restricted due to tumor heterogeneity. Therefore, there is an urgent need for complementary diagnostic and prognostic options. Liquid biopsy approaches are minimally invasive with potential utility for the early detection, risk stratification, and monitoring of tumors. In this review, we focus on tissue and liquid biopsy biomarkers for early diagnosis and risk stratification of prostate cancer, including modifications on the genomic, epigenomic, transcriptomic, and proteomic levels. High-risk molecular alterations combined with orthogonal clinical parameters can improve the identification of aggressive tumors and increase patient survival.

Proteomics approaches to characterize the immune responses in cancer

Despite the dynamic development of cancer research, annually millions of people die of cancer. The human immune system is the major 'guard' against tumor development. Unfortunately, cancer cells have the ability to evade the immune system and continue to grow. The proper understanding of the intricate immune response in tumorigenesis remains the holy grail of cancer immunology and designing effective immunotherapy. To decode the immune responses in cancer, in recent years, proteomics studies have received considerable attention. Proteomics studies focus on the detection and quantification of proteins, which are the effectors of biological functions, and as such, are proven to reflect the cell state more accurately, in comparison to genomic or transcriptomic studies. In this review, we discuss the proteomics studies applied to characterize the immune responses in cancer and tumor immune microenvironment heterogeneity. Further, we describe emerging single-cell proteomics approaches that have the potential to be applied in cancer immunity studies.

From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer

Cancer arises following alterations at different cellular levels, including genetic and epigenetic modifications, transcription and translation dysregulation, as well as metabolic variations. High-throughput omics technologies that allow one to identify and quantify processes involved in these changes are now available and have been instrumental in generating a wealth of steadily increasing data from patient tumors, liquid biopsies, and from tumor models. Extensive investigation and integration of these data have led to new biological insights into the origin and development of multiple cancer types and helped to unravel the molecular networks underlying this complex pathology. The comprehensive and quantitative analysis of a molecule class in a biological sample is named omics and large-scale omics studies addressing different prostate cancer stages have been performed in recent years. Prostate tumors represent the second leading cancer type and a prevalent cause of cancer death in men worldwide. It is a very heterogenous disease so that evaluating inter- and intra-tumor differences will be essential for a precise insight into disease development and plasticity, but also for the development of personalized therapies. There is ample evidence for the key role of the androgen receptor, a steroid hormone-activated transcription factor, in driving early and late stages of the disease, and this led to the development and approval of drugs addressing diverse targets along this pathway. Early genomic and transcriptomic studies have allowed one to determine the genes involved in prostate cancer and regulated by androgen signaling or other tumor-relevant signaling pathways. More recently, they have been supplemented by epigenomic, cistromic, proteomic and metabolomic analyses, thus, increasing our knowledge on the intricate mechanisms involved, the various levels of regulation and their interplay. The comprehensive investigation of these omics approaches and their integration into multi-omics analyses have led to a much deeper understanding of the molecular pathways involved in prostate cancer progression, and in response and resistance to therapies. This brings the hope that novel vulnerabilities will be identified, that existing therapies will be more beneficial by targeting the patient population likely to respond best, and that bespoke treatments with increased efficacy will be available soon.

On the Road to Accurate Protein Biomarkers in Prostate Cancer Diagnosis and Prognosis: Current Status and Future Advances

Prostate cancer (PC) is a leading cause of morbidity and mortality among men worldwide. Molecular biomarkers work in conjunction with existing clinicopathologic tools to help physicians decide who to biopsy, re-biopsy, treat, or re-treat. The past decade has witnessed the commercialization of multiple PC protein biomarkers with improved performance, remarkable progress in proteomic technologies for global discovery and targeted validation of novel protein biomarkers from clinical specimens, and the emergence of novel, promising PC protein biomarkers. In this review, we summarize these advances and discuss the challenges and potential solutions for identifying and validating clinically useful protein biomarkers in PC diagnosis and prognosis. The identification of multi-protein biomarkers with high sensitivity and specificity, as well as their integration with clinicopathologic parameters, imaging, and other molecular biomarkers, bodes well for optimal personalized management of PC patients.

Proteome biology of primary colorectal carcinoma and corresponding liver metastases

Colorectal adenocarcinomas (CRC) are one of the most commonly diagnosed tumors worldwide. Colorectal adenocarcinomas primarily metastasize into the liver and (less often) into the peritoneum. Patients suffering from CRC-liver metastasis (CRC-LM) typically present with a dismal overall survival compared to non-metastasized CRC patients. The metastasis process and metastasis-promoting factors in patients with CRC are under intensive debate. However, CRC studies investigating the proteome biology are lacking. Formalin-fixed paraffin-embedded (FFPE) tissue specimens provide a valuable resource for comprehensive proteomic studies of a broad variety of clinical malignancies. The presented pilot study compares the proteome of primary CRC and patient-matched CRC-LM. The applied protocol allows a reproducible and straightforward identification and quantification of over 2,600 proteins within the dissected tumorous tissue. Subsequent unsupervised clustering reveals distinct proteome biologies of the primary CRC and the corresponding CRC-LM. Statistical analysis yields multiple differentially abundant proteins in either primary CRC or their corresponding liver metastases. A more detailed analysis of dysregulated biological processes suggests an active immune response in the liver metastases, including several proteins of the complement system. Proteins with structural roles, e.g. cytoskeleton organization or cell junction assembly appear to be less prominent in liver metastases as compared to primary CRC. Immunohistochemistry corroborates proteomic high expression levels of metabolic proteins in CRC-LM. We further assessed how the in vitro inhibition of two in CRC-LM enriched metabolic proteins affected cell proliferation and chemosensitivity. The presented proteomic investigation in a small clinical cohort promotes a more comprehensive understanding of the distinct proteome biology of primary CRC and their corresponding liver metastases.

Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes

Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.

Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research

Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.

A Systematic Evaluation of Semispecific Peptide Search Parameter Enables Identification of Previously Undescribed N-Terminal Peptides and Conserved Proteolytic Processing in Cancer Cell Lines

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has become the most commonly used technique in explorative proteomic research. A variety of open-source tools for peptide-spectrum matching have become available. Most analyses of explorative MS data are performed using conventional settings, such as fully specific enzymatic constraints. Here we evaluated the impact of the fragment mass tolerance in combination with the enzymatic constraints on the performance of three search engines. Three open-source search engines (Myrimatch, X! Tandem, and MSGF+) were evaluated concerning the suitability in semi- and unspecific searches as well as the importance of accurate fragment mass spectra in non-specific peptide searches. We then performed a semispecific reanalysis of the published NCI-60 deep proteome data applying the most suited parameters. Semi- and unspecific LC-MS/MS data analyses particularly benefit from accurate fragment mass spectra while this effect is less pronounced for conventional, fully specific peptide-spectrum matching. Search speed differed notably between the three search engines for semi- and non-specific peptide-spectrum matching. Semispecific reanalysis of NCI-60 proteome data revealed hundreds of previously undescribed N-terminal peptides, including cases of proteolytic processing or likely alternative translation start sites, some of which were ubiquitously present in all cell lines of the reanalyzed panel. Highly accurate MS2 fragment data in combination with modern open-source search algorithms enable the confident identification of semispecific peptides from large proteomic datasets. The identification of previously undescribed N-terminal peptides in published studies highlights the potential of future reanalysis and data mining in proteomic datasets.

Proteomics of REPLICANT perfusate detects changes in the metastatic lymph node microenvironment

In breast cancer (BC), detecting low volumes of axillary lymph node (ALN) metastasis pre-operatively is difficult and novel biomarkers are needed. We recently showed that patient-derived ALNs can be sustained ex-vivo using normothermic perfusion. We now compare reactive (tumour-free; n = 5) and macrometastatic (containing tumour deposits >2 mm; n = 4) ALNs by combining whole section multiplex immunofluorescence with TMT-labelled LC-MS/MS of the circulating perfusate. Macrometastases contained significantly fewer B cells and T cells (CD4⁺/CD8⁺/regulatory) than reactive nodes (p = 0.02). Similarly, pathway analysis of the perfusate proteome (119/1453 proteins significantly differentially expressed) showed that immune function was diminished in macrometastases in favour of ‘extracellular matrix degradation’; only ‘neutrophil degranulation’ was preserved. Qualitative comparison of the perfusate proteome to that of node-positive pancreatic and prostatic adenocarcinoma also highlighted ‘neutrophil degranulation’ as a contributing factor to nodal metastasis. Thus, metastasis-induced changes in the REPLICANT perfusate proteome are detectable, and could facilitate biomarker discovery.

Identification of Novel Prognosis and Prediction Markers in Advanced Prostate Cancer Tissues Based on Quantitative Proteomics

BACKGROUND/AIM

Prostate cancer (PCa) is the most frequent cancer found in males worldwide, and its mortality rate is increasing every year. However, there are no known molecular markers for advanced or aggressive PCa, and there is an urgent clinical need for biomarkers that can be used for prognosis and prediction of PCa.

MATERIALS AND METHODS

Mass spectrometry-based proteomics was used to identify new biomarkers in tissues obtained from patients with PCa who were diagnosed with T2, T3, or metastatic PCa in regional lymph nodes.

RESULTS

Among 1,904 proteins identified in the prostate tissues, 344 differentially expressed proteins were defined, of which 124 were up-regulated and 216 were down-regulated. Subsequently, based on the results of partial least squares discriminant analysis and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, we proposed that spermidine synthase (SRM), nucleolar and coiled-body phosphoprotein 1 (NOLC1), and prostacyclin synthase (PTGIS) represent new protein biomarkers for diagnosis of advanced PCa. These proteomics results were verified by immunoblot assays in metastatic PCa cell lines and by indirect enzyme-linked immunosorbent assay in prostate specimens.

CONCLUSION

SRM was significantly increased depending on the cancer stage, confirming the possibility of using SRM as a biomarker for prognosis and prediction of advanced PCa.

Neoplastic-Stromal Cell Cross-talk Regulates Matrisome Expression in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a highly desmoplastic reaction, warranting intense cancer-stroma communication. In this study, we interrogated the contribution of the BET family of chromatin adaptors to the cross-talk between PDAC cells and the tumor stroma. Short-term treatment of orthotopic xenograft tumors with CPI203, a small-molecule inhibitor of BET proteins, resulted in broad changes in the expression of genes encoding components of the extracellular matrix (matrisome) in both cancer and stromal cells. Remarkably, more than half of matrisome genes were expressed by cancer cells. In vitro cocultures of PDAC cells and cancer-associated fibroblasts (CAF) demonstrated that matrisome expression was regulated by BET-dependent cancer-CAF cross-talk. Disrupting this cross-talk in vivo resulted in diminished growth of orthotopic patient-derived xenograft tumors, reduced proliferation of cancer cells, and changes in collagen structure consistent with that of patients who experienced better survival. Examination of matrisome gene expression in publicly available data sets of 573 PDAC tumors identified a 65-gene signature that was able to distinguish long- and short-term PDAC survivors. Importantly, the expression of genes predictive of short-term survival was diminished in the cancer cells of orthotopic xenograft tumors of mice treated with CPI203. Taken together, these results demonstrate that inhibiting the activity BET proteins results in transcriptional and structural differences in the matrisome are associated with better patient survival. IMPLICATIONS: These studies highlight the biological relevance of the matrisome program in PDAC and suggest targeting of epigenetically driven tumor-stroma cross-talk as a potential therapeutic avenue.

Proteomics Analysis of Formalin Fixed Paraffin Embedded Tissues in the Investigation of Prostate Cancer

Prostate cancer (PCa) is one of the leading causes of death in men worldwide. The molecular features, associated with the onset and progression of the disease, are under vigorous investigation. Formalin-fixed paraffin-embedded (FFPE) tissues are valuable resources for large-scale studies; however, their application in proteomics is limited due to protein cross-linking. In this study, the adjustment of a protocol for the proteomic analysis of FFPE tissues was performed which was followed by a pilot application on FFPE PCa clinical samples to investigate whether the optimized protocol can provide biologically relevant data for the investigation of PCa. For the optimization, FFPE mouse tissues were processed using seven protein extraction protocols including combinations of homogenization methods (beads, sonication, boiling) and buffers (SDS based and urea-thiourea based). The proteome extraction efficacy was then evaluated based on protein identifications and reproducibility using SDS electrophoresis and high resolution LC-MS/MS analysis. Comparison between the FFPE and matched fresh frozen (FF) tissues, using an optimized protocol involving protein extraction with an SDS-based buffer following beads homogenization and boiling, showed a substantial overlap in protein identifications with a strong correlation in relative abundances (r_s = 0.819, p < 0.001). Next, FFPE tissues (3 sections, 15 μm each per sample) from 10 patients with PCa corresponding to tumor (GS = 6 or GS ≥ 8) and adjacent benign regions were processed with the optimized protocol. Extracted proteins were analyzed by GeLC-MS/MS followed by statistical and bioinformatics analysis. Proteins significantly deregulated between PCa GS ≥ 8 and PCa GS = 6 represented extracellular matrix organization, gluconeogenesis, and phosphorylation pathways. Proteins deregulated between cancerous and adjacent benign tissues, reflected increased translation, peptide synthesis, and protein metabolism in the former, which is consistent with the literature. In conclusion, the results support the relevance of the proteomic findings in the context of PCa and the reliability of the optimized protocol for proteomics analysis of FFPE material.

Characterization of HMGB1/2 Interactome in Prostate Cancer by Yeast Two Hybrid Approach: Potential Pathobiological Implications

High mobility group box B (HMGB) proteins are pivotal in the development of cancer. Although the proteomics of prostate cancer (PCa) cells has been reported, the involvement of HMGB proteins and their interactome in PCa is an unexplored field of considerable interest. We describe herein the results of the first HMGB1/HMGB2 interactome approach to PCa. Libraries constructed from the PCa cell line, PC-3, and from patients’ PCa primary tumor have been screened by the yeast 2-hybrid approach (Y2H) using HMGB1 and HMGB2 baits. Functional significance of this PCa HMGB interactome has been validated through expression and prognosis data available on public databases. Copy number alterations (CNA) affecting these newly described HMGB interactome components are more frequent in the most aggressive forms of PCa: those of neuroendocrine origin or castration-resistant PCa. Concordantly, adenocarcinoma PCa samples showing CNA in these genes are also associated with the worse prognosis. These findings open the way to their potential use as discriminatory biomarkers between high and low risk patients. Gene expression of a selected set of these interactome components has been analyzed by qPCR after HMGB1 and HMGB2 silencing. The data show that HMGB1 and HMGB2 control the expression of several of their interactome partners, which might contribute to the orchestrated action of these proteins in PCa

Quantitative proteomic analysis of prostate tissue specimens identifies deregulated protein complexes in primary prostate cancer

Background

Prostate cancer (PCa) is the most frequently diagnosed non-skin cancer and a leading cause of mortality among males in developed countries. However, our understanding of the global changes of protein complexes within PCa tissue specimens remains very limited, although it has been well recognized that protein complexes carry out essentially all major processes in living organisms and that their deregulation drives the pathogenesis and progression of various diseases.

Methods

By coupling tandem mass tagging-synchronous precursor selection-mass spectrometry/mass spectrometry/mass spectrometry with differential expression and co-regulation analyses, the present study compared the differences between protein complexes in normal prostate, low-grade PCa, and high-grade PCa tissue specimens.

Results

Globally, a large downregulated putative protein–protein interaction (PPI) network was detected in both low-grade and high-grade PCa, yet a large upregulated putative PPI network was only detected in high-grade but not low-grade PCa, compared with normal controls. To identify specific protein complexes that are deregulated in PCa, quantified proteins were mapped to protein complexes in CORUM (v3.0), a high-quality collection of 4274 experimentally verified mammalian protein complexes. Differential expression and gene ontology (GO) enrichment analyses suggested that 13 integrin complexes involved in cell adhesion were significantly downregulated in both low- and high-grade PCa compared with normal prostate, and that four Prothymosin alpha (ProTα) complexes were significantly upregulated in high-grade PCa compared with normal prostate. Moreover, differential co-regulation and GO enrichment analyses indicated that the assembly levels of six protein complexes involved in RNA splicing were significantly increased in low-grade PCa, and those of four subcomplexes of mitochondrial complex I were significantly increased in high-grade PCa, compared with normal prostate.

Conclusions

In summary, to the best of our knowledge, the study represents the first large-scale and quantitative, albeit indirect, comparison of individual protein complexes in human PCa tissue specimens. It may serve as a useful resource for better understanding the deregulation of protein complexes in primary PCa.

Electronic supplementary material

The online version of this article (10.1186/s12014-019-9236-2) contains supplementary material, which is available to authorized users.

ADAM9 contributes to vascular invasion in pancreatic ductal adenocarcinoma

A disintegrin and a metalloprotease (ADAM)‐9 is a metzincin cell‐surface protease with strongly elevated expression in solid tumors, including pancreatic ductal adenocarcinoma (PDAC). In this study, we performed immunohistochemistry (IHC) of a tissue microarray (TMA) to examine the expression of ADAM9 in a cohort of >100 clinically annotated PDAC cases. We report that ADAM9 is prominently expressed by PDAC tumor cells, and increased ADAM9 expression levels correlate with poor tumor grading (P = 0.027) and the presence of vasculature invasion (P = 0.017). We employed gene expression silencing to generate a loss‐of‐function system for ADAM9 in two established PDAC cell lines. In vitro analysis showed that loss of ADAM9 does not impede cellular proliferation and invasiveness in basement membrane. However, ADAM9 plays a crucial role in mediating cell migration and adhesion to extracellular matrix substrates such as fibronectin, tenascin, and vitronectin. This effect appears to depend on its catalytic activity. In addition, ADAM9 facilitates anchorage‐independent growth. In AsPC1 cells, but not in MiaPaCa‐2 cells, we noted a pronounced yet heterogeneous impact of ADAM9 on the abundance of various integrins, a process that we characterized as post‐translational regulation. Sprout formation of human umbilical vein endothelial cells (HUVECs) is promoted by ADAM9, as examined by transfer of cancer cell conditioned medium; this finding further supports a pro‐angiogenic role of ADAM9 expressed by PDAC cancer cells. Immunoblotting analysis of cancer cell conditioned medium highlighted that ADAM9 regulates the levels of angiogenic factors, including shed heparin‐binding EGF‐like growth factor (HB‐EGF). Finally, we carried out orthotopic seeding of either wild‐type AsPC‐1 cells or AsPC‐1 cells with silenced ADAM9 expression into murine pancreas. In this in vivo setting, ADAM9 was also found to foster angiogenesis without an impact on tumor cell proliferation. In summary, our results characterize ADAM9 as an important regulator in PDAC tumor biology with a strong pro‐angiogenic impact.

Proteome Profiling of Primary Pancreatic Ductal Adenocarcinomas Undergoing Additive Chemoradiation Link ALDH1A1 to Early Local Recurrence and Chemoradiation Resistance

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis with frequent post-surgical local recurrence. The combination of adjuvant chemotherapy with radiotherapy is under consideration to achieve a prolonged progression-free survival (PFS). To date, few studies have determined the proteome profiles associated with response to adjuvant chemoradiation. We herein analyzed the proteomes of primary PDAC tumors subjected to additive chemoradiation after surgical resection and achieving short PFS (median 6 months) versus prolonged PFS (median 28 months). Proteomic analysis revealed the overexpression of Aldehyde Dehydrogenase 1 Family Member A1 (ALDH1A1) and Monoamine Oxidase A (MAOA) in the short PFS cohort, which were corroborated by immunohistochemistry. In vitro, specific inhibition of ALDH1A1 by A37 in combination with gemcitabine, radiation, and chemoradiation lowered cell viability and augmented cell death in MiaPaCa-2 and Panc 05.04 cells. ALDH1A1 silencing in both cell lines dampened cell proliferation, cell metabolism, and colony formation. In MiaPaCa-2 cells, ALDH1A1 silencing sensitized cells towards treatment with gemcitabine, radiation or chemoradiation. In Panc 05.04, increased cell death was observed upon gemcitabine treatment only. These findings are in line with previous studies that have suggested a role of ALDH1A1 chemoradiation resistance, e.g., in esophageal cancer. In summary, we present one of the first proteome studies to investigate the responsiveness of PDAC to chemoradiation and provide further evidence for a role of ALDH1A1 in therapy resistance.

Proteomic distinction of renal oncocytomas and chromophobe renal cell carcinomas

BACKGROUND

Renal oncocytomas (ROs) are benign epithelial tumors of the kidney whereas chromophobe renal cell carcinoma (chRCCs) are malignant renal tumors. The latter constitute 5-7% of renal neoplasias. ROs and chRCCs show pronounced molecular and histological similarities, which renders their differentiation demanding. We aimed for the differential proteome profiling of ROs and early-stage chRCCs in order to better understand distinguishing protein patterns.

METHODS

We employed formalin-fixed, paraffin-embedded samples (six RO cases, six chRCC cases) together with isotopic triplex dimethylation and a pooled reference standard to enable cohort-wide quantitative comparison. For lysosomal-associated membrane protein 1 (LAMP1) and integrin alpha-V (ITGAV) we performed corroborative immunohistochemistry (IHC) in an extended cohort of 42 RO cases and 31 chRCC cases.

RESULTS

At 1% false discovery rate, we identified > 3900 proteins, of which > 2400 proteins were consistently quantified in at least four RO and four chRCC cases. The proteomic expression profiling discriminated ROs and chRCCs and highlighted established features such as accumulation of mitochondrial proteins in ROs together with emphasizing the accumulation of endo-lysosomal proteins in chRCCs. In line with the proteomic data, IHC showed enrichment of LAMP1 in chRCC and of ITGAV in RO.

CONCLUSION

We present one of the first differential proteome profiling studies on ROs and chRCCs and highlight differential abundance of LAMP1 and ITGAV in these renal tumors.