Mass spectrometry-based cancer biomarker discovery

The aim of the projects in this thesis was to identify biomarkers for clear cell renal cell carcinomas (ccRCC) and head and neck/oral squamous cell carcinoma (HNOSCC), using quantitative or qualitative proteomics. Comparative analysis of cancerous and normal tissue homogenates, or secretome analysis of cancer cell cultures using liquid chromatography - mass spectrometry (LC-MS) and immunoassay techniques, allowed the identification of different types of biomarkers: diagnostic or prognostic, biofluid- or tissue-based. Chapter 1 of this thesis provides general information on cancer and cancer biomarker discovery. Chapter 2 gives a brief introduction to the techniques used in this work and theories behind them. Chapters 3 - 5 are papers that resulted from the cancer biomarker discovery research performed here, and Chapter 6 contains the conclusions, the author's comments and the final remarks. The papers on the identification of biomarkers for different diseases, to which the author of this thesis contributed, are listed in the Appendix

Modeling cancer metabolism on a genome scale

Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome‐scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network‐level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field

Teneurins: Role in Cancer and Potential Role as Diagnostic Biomarkers and Targets for Therapy

Teneurins have been identified in vertebrates as four different genes (TENM1-4), coding for membrane proteins that are mainly involved in embryonic and neuronal development. Genetic studies have correlated them with various diseases, including developmental problems, neurological disorders and congenital general anosmia. There is some evidence to suggest their possible involvement in cancer initiation and progression, and drug resistance. Indeed, mutations, chromosomal alterations and the deregulation of teneurins expression have been associated with several tumor types and patient survival. However, the role of teneurins in cancer-related regulatory networks is not fully understood, as both a tumor-suppressor role and pro-tumoral functions have been proposed, depending on tumor histotype. Here, we summarize and discuss the literature data on teneurins expression and their potential role in different tumor types, while highlighting the possibility of using teneurins as novel molecular diagnostic and prognostic biomarkers and as targets for cancer treatments, such as immunotherapy, in some tumors

Comprehensive Molecular Characterization of Papillary Renal-Cell Carcinoma

BACKGROUND Papillary renal-cell carcinoma, which accounts for 15 to 20% of renal-cell carcinomas, is a heterogeneous disease that consists of various types of renal cancer, including tumors with indolent, multifocal presentation and solitary tumors with an aggressive, highly lethal phenotype. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist. METHODS We performed comprehensive molecular characterization of 161 primary papillary renal-cell carcinomas, using whole-exome sequencing, copy-number analysis, messenger RNA and microRNA sequencing, DNA-methylation analysis, and proteomic analysis. RESULTS Type 1 and type 2 papillary renal-cell carcinomas were shown to be different types of renal cancer characterized by specific genetic alterations, with type 2 further classified into three individual subgroups on the basis of molecular differences associated with patient survival. Type 1 tumors were associated with MET alterations, whereas type 2 tumors were characterized by CDKN2A silencing, SETD2 mutations, TFE3 fusions, and increased expression of the NRF2'antioxidant response element (ARE) pathway. A CpG island methylator phenotype (CIMP) was observed in a distinct subgroup of type 2 papillary renal-cell carcinomas that was characterized by poor survival and mutation of the gene encoding fumarate hydratase (FH). CONCLUSIONS Type 1 and type 2 papillary renal-cell carcinomas were shown to be clinically and biologically distinct. Alterations in the MET pathway were associated with type 1, and activation of the NRF2-ARE pathway was associated with type 2; CDKN2A loss and CIMP in type 2 conveyed a poor prognosis. Furthermore, type 2 papillary renalcell carcinoma consisted of at least three subtypes based on molecular and phenotypic features

Role of STAT3 pathway in genitourinary tumors

The STAT3 is often dysregulated in genitourinary tumors. In prostate cancer, STAT3 activation correlates with Gleason score and pathological stage and modulates cancer stem cells and epithelial-mesenchymal transition. In addition, STAT3 promotes the progression from carcinoma in situ to invasive bladder cancer and modulates renal cell carcinoma angiogenesis by increasing the expression of HIF1α and VEGF. STAT3 is also involved in the response to tyrosine kinase inhibitors sunitinib and axitinib, in patients with metastatic renal cell carcinoma, and to second-generation androgen receptor inhibitor enzalutamide in patients with advanced prostate cancer. In this review, we describe the role of STAT3 in genitourinary tumors, thus describing its potential for future therapeutic strategies

Roles of neutrophil gelatinase-associated lipocalin (NGAL) in human cancer

Cancer remains one of the major cause of death in the Western world. Although, it has been demonstrated that new therapies can improve the outcome of cancer patients, still many patients relapse after treatment. Therefore, there is a need to identify novel factors involved in cancer development and/or progression. Recently, neutrophil gelatinase-associated lipocalin (NGAL) has been suggested as a key player in different cancer types. Its oncogenic effect may be related to the complex NGAL/MMP-9. In the present study, NGAL was analyzed at both transcript and protein levels in different cancer types by analysing 38 public available microarray datasets and the Human Protein Atlas tool. NGAL transcripts were significantly higher in the majority of solid tumors compared to the relative normal tissues for every dataset analyzed. Furthermore, concordance of NGAL at both mRNA and protein levels was observed for 6 cancer types including bladder, colorectal, liver, lung, ovarian, and pancreatic. All metastatic tumors showed a decrease of NGAL expression when compared to matched primary lesions. According to these results, NGAL is a candidate marker for tumor growth in a fraction of solid tumors. Further investigations are required to elucidate the function of NGAL in tumor development and metastatic processes

Soluble Isoforms of Vascular Endothelial Growth Factor Are Predictors of Response to Sunitinib in Metastatic Renal Cell Carcinomas

Angiogenesis is the target of several agents in the treatment of malignancies, including renal cell carcinoma (RCC). There is a real need for surrogate biomarkers that can predict selection of patients who may benefit from antiangiogenic therapies, prediction of disease outcome and which may improve the knowledge regarding mechanism of action of these treatments. Tyrosine kinase inhibitors (TKI) have proven efficacy in metastatic RCC (mRCC). However, the molecular mechanisms underlying the clinical response to these drugs remain unclear.The present study aimed to identify molecular biomarkers associated with the response to sunitinib, a Tyrosine kinase inhibitor. To evaluate this relationship, primary tumors from 23 metastatic RCC patients treated by sunitinib were analyzed for a panel of 16 biomarkers involved in tumor pathways targeted by sunitinib, using real-time quantitative reverse-transcriptase PCR. Nine of the 23 patients (39%) responded to sunitinib. Among transcripts analyzed, only the levels of vascular endothelial growth factor (VEGF) soluble isoforms (VEGF(121) and VEGF(165)) were associated with the response to sunitinib (P = 0.04 for both). Furthermore, the ratio of VEGF soluble isoforms (VEGF(121)/VEGF(165)) was significantly associated with prognosis (P = 0.02).This preliminary study provides a promising tool that might help in the management of metastatic RCC, and could be extended to other tumors treated by TKI

A 17-Gene Expression Signature for Early Identification of Poor Prognosis in Clear Cell Renal Cell Carcinoma

: The Identification of reliable Biomarkers able to predict the outcome after nephrectomy of patients with clear cell renal cell carcinoma (ccRCC) is an unmet need. The gene expression analysis in tumor tissues represents a promising tool for better stratification of ccRCC subtypes and patients' evaluation. Methods: In our study we retrospectively analyzed using Next-Generation expression analysis (NanoString), the expression of a gene panel in tumor tissue from 46 consecutive patients treated with nephrectomy for non-metastatic ccRCC at two Italian Oncological Centres. Significant differences in expression levels of selected genes was sought. Additionally, we performed a univariate and a multivariate analysis on overall survival according to Cox regression model. Results: A 17-gene expression signature of patients with a recurrence-free survival (RFS) < 1 year (unfavorable genomic signature (UGS)) and of patients with a RFS > 5 years (favorable genomic signature (FGS)) was identified and resulted in being significantly correlated with overall survival of the patients included in this analysis (HR 51.37, p < 0.0001). Conclusions: The identified Genomic Signatures may serve as potential biomarkers for prognosis prediction of non-metastatic RCC and could drive both follow-up and treatment personalization in RCC management

Identification of predictors of patient survival with TSPAN8 as a mediator of tumor aggressiveness in clear cell renal cell carcinoma

With the help of a patient-derived clear cell renal cell carcinoma (ccRCC) model system previously established in our laboratory, which recapitulates the heterogeneity of the originating tumor, we were able to study ccRCC on a functional level. In five rounds and in four biological replicates of an in vivo selection, we transplanted lung metastases of orthotopically transplanted tumor cells into the renal capsules of NOD scid gamma (NSG) mice. The tumor was enriched for cells with increased growth and higher metastatic potential compared to the initial heterogeneous population. Comparative gene expression analysis revealed candidate genes associated with enhanced malignant growth and metastasis. Least absolute shrinkage and selection operator (LASSO) regression identified a gene signature that can robustly predict cancer specific patient survival. The prognostic power of our signature was additionally verified in independent patient cohorts suggesting that this approach leverages efficient stratification of patients into distinctive risk groups. Intra- and intertumor heterogeneity remains a clinical challenge as estimated survival rates could vary substantially when comparing different tumor regions. Tetraspanin-8 (TSPAN8) was identified as one of the hallmark genes in the generated ccRCC signature and is known to alter cellular signaling. Therefore, we hypothesized that TSPAN8 contributes to tumor aggressiveness and thus to growth and metastasis of ccRCC. In fact, in knockdown and overexpression xenografts experiments, we could confirm an essential role for tumor aggressiveness in vivo suggesting that TSPAN8 is an attractive target for treatment of clear cell renal cell carcinoma