Proteomics investigation of breast cancer biomarkers in urine and blood for diagnosis and monitoring

Breast cancer (BC) is the most commonly diagnosed cancer among women in the world. Currently, there are no biomarkers available for early diagnosis and monitoring BC progression. Advances in proteomics technology have allowed new insight into cancer biology by allowing us to mine the human proteome. Therefore, the main research objectives for my thesis were to 1) analyse urine and blood, from BC patients and control subjects by proteomics analysis; 2) identify novel proteins which highlight the presence of disease; 3) validate the identified potential biomarkers for diagnosis. After successfully developing a standardised method for urine protein extraction and precipitation using liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, it was applied to additional urine samples from BC patients. The study cohort consisted of urine and blood samples from 20 BC patients, 20 healthy control subjects and 6 benign breast disease patients. Blood was collected in 4 different blood tubes (2 serum/2 plasma). Statistical analysis revealed 59 urinary proteins that were significantly different in BC patients compared to the normal healthy control subjects (p3). Thirty-six urinary proteins were exclusively found in specific BC stages, with 24 increasing and 12 decreasing in abundance. Preliminary validation of 3 potential markers ECM1, MAST4 and filaggrin was performed in BC cell lines by Western blotting (WB). One potential marker MAST4, was further validated in human BC tissues as well as human BC urine samples with immunohistochemistry (IHC) and WB, respectively. From my human serum and plasma proteomic analysis, over 100 differentially abundant proteins were identified and the greatest number were identified from the Gold-top serum tubes in the 3-50kDa mass fractions. Normalization of data against the control samples demonstrated 5 secreted proteins, potential markers Clusterin, Vitronectin, LRG1, IGFBP-3 and S100-6 (secreted proteins), as promising to define early stage BC. Preliminary validation, was performed in BC cell lines and blood samples by WB. Two potential marker CLU, IGFBP-1 were further validated in human BC tissues with IHC. In summary, I have identified several important proteins from urine and blood for BC detection and monitoring BC progression. My findings may have a major impact on the prognosis of BC for the thousands of women who die from the disease each year

Proteomic analysis of urine to identify breast cancer biomarker candidates using a label-free LC-MS/MS approach

Introduction: Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression. Method: We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20). Results: Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively. Conclusions: Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns (biomarkers) identified, have potential for clinical use in the detection of BC. Validation with a larger independent cohort of patients is required in the following study

Multiplexed immunofluorescence identifies high stromal CD68+PD‑L1+ macrophages as a predictor of improved survival in triple negative breast cancer

Triple negative breast cancer (TNBC) comprises 10–15% of all breast cancers and has a poor prognosis with a high risk of recurrence within 5 years. PD-L1 is an important biomarker for patient selection for immunotherapy but its cellular expression and co-localization within the tumour immune microenvironment and associated prognostic value is not well defined. We aimed to characterise the phenotypes of immune cells expressing PD-L1 and determine their association with overall survival (OS) and breast cancer-specific survival (BCSS). Using tissue microarrays from a retrospective cohort of TNBC patients from St George Hospital, Sydney (n = 244), multiplexed immunofluorescence (mIF) was used to assess staining for CD3, CD8, CD20, CD68, PD-1, PD-L1, FOXP3 and pan-cytokeratin on the Vectra Polaris™ platform and analysed using QuPath. Cox multivariate analyses showed high CD68+PD-L1+ stromal cell counts were associated with improved prognosis for OS (HR 0.56, 95% CI 0.33–0.95, p = 0.030) and BCSS (HR 0.47, 95% CI 0.25–0.88, p = 0.018) in the whole cohort and in patients receiving chemotherapy, improving incrementally upon the predictive value of PD-L1+ alone for BCSS. These data suggest that CD68+PD-L1+ status can provide clinically useful prognostic information to identify sub-groups of patients with good or poor prognosis and guide treatment decisions in TNBC

TILs immunophenotype in breast cancer predicts local failure and overall survival : analysis in a large radiotherapy trial with long-term follow-up

Aim: To determine the prognostic significance of the immunophenotype of tumour-infiltrating lymphocytes (TILs) within a cohort of breast cancer patients with long-term follow-up. Methods: Multiplexed immunofluorescence and automated image analysis were used to assess the expression of CD3, CD8, CD20, CD68, Fox P3, PD-1 and PD-L1 in a clinical trial of local excision and radiotherapy randomised to a cavity boost or not (n = 485, median follow-up 16 years). Kaplan–Meier and Cox multivariate analysis (MVA) methodology were used to ascertain relationships with local recurrence (LR), overall survival (OS) and disease-free survival (DFS). NanoString BC360 gene expression panel was applied to a subset of luminal patients to identify pathways associated with LR. Results: LR was predicted by low CD8 in MVA in the whole cohort (HR 2.34, CI 1.4–4.02, p = 0.002) and luminal tumours (HR 2.19, CI 1.23–3.92, p = 0.008) with associations with increased stromal components, decreased Tregs (FoxP3), inflammatory chemokines and SOX2. Poor OS was associated with low CD20 in the whole cohort (HR 1.73, CI 1.2–2.4, p = 0.002) and luminal tumours on MVA and low PD-L1 in triple-negative cancer (HR 3.44, CI 1.5–7, p = 0.003). Conclusions: Immunophenotype adds further prognostic data to help further stratify risk of LR and OS even in TILs low-luminal tumours

Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

Background: High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. Methods: Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. Results: Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. Conclusions: We show that the viable cryopreservation of human cancers provides high-quality single-cells for multiomics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies

Anti-MUC1 Monoclonal Antibody (C595) and Docetaxel Markedly Reduce Tumor Burden and Ascites, and Prolong Survival in an in vivo Ovarian Cancer Model

MUC1 is associated with cellular transformation and tumorigenicity and is considered as an important tumor-associated antigen (TAA) for cancer therapy. We previously reported that anti-MUC1 monoclonal antibody C595 (MAb C595) plus docetaxel (DTX) increased efficacy of DTX alone and caused cultured human epithelial ovarian cancer (EOC) cells to undergo apoptosis. To further study the mechanisms of this combination-mediated apoptosis, we investigated the effectiveness of this combination therapy in vivo in an intraperitoneal (i.p.) EOC mouse model. OVCAR-3 cells were implanted intraperitoneally in female athymic nude mice and allowed to grow tumor and ascites. Mice were then treated with single MAb C595, DTX, combination test (MAb C595 and DTX), combination control (negative MAb IgG3 and DTX) or vehicle control i.p for 3 weeks. Treated mice were killed 4 weeks post-treatment. Ascites volume, tumor weight, CA125 levels from ascites and survival of animals were assessed. The expression of MUC1, CD31, Ki-67, TUNEL and apoptotic proteins in tumor xenografts was evaluated by immunohistochemistry. MAb C595 alone inhibited i.p. tumor growth and ascites production in a dose-dependent manner but did not obviously prevent tumor development. However, combination test significantly reduced ascites volume, tumor growth and metastases, CA125 levels in ascites and improved survival of treated mice compared with single agent-treated mice, combination control or vehicle control-treated mice (P<0.05). The data was in a good agreement with that from cultured cells in vitro. The mechanisms behind the observed effects could be through targeting MUC1 antigens, inhibition of tumor angiogenesis, and induction of apoptosis. Our results suggest that this combination approach can effectively reduce tumor burden and ascites, prolong survival of animals through induction of tumor apoptosis and necrosis, and may provide a potential therapy for advanced metastatic EOC

Tumour stroma ratio assessment using digital image analysis predicts survival in triple negative and luminal breast cancer

We aimed to determine the clinical significance of tumour stroma ratio (TSR) in luminal and triple negative breast cancer (TNBC) using digital image analysis and machine learning algorithms. Automated image analysis using QuPath software was applied to a cohort of 647 breast cancer patients (403 luminal and 244 TNBC) using digital H&E images of tissue microarrays (TMAs). Kaplan–Meier and Cox proportional hazards were used to ascertain relationships with overall survival (OS) and breast cancer specific survival (BCSS). For TNBC, low TSR (high stroma) was associated with poor prognosis for both OS (HR 1.9, CI 1.1–3.3, p = 0.021) and BCSS (HR 2.6, HR 1.3–5.4, p = 0.007) in multivariate models, independent of age, size, grade, sTILs, lymph nodal status and chemotherapy. However, for luminal tumours, low TSR (high stroma) was associated with a favourable prognosis in MVA for OS (HR 0.6, CI 0.4–0.8, p = 0.001) but not for BCSS. TSR is a prognostic factor of most significance in TNBC, but also in luminal breast cancer, and can be reliably assessed using quantitative image analysis of TMAs. Further investigation into the contribution of tumour subtype stromal phenotype may further refine these findings

Epithelial cell adhesion molecule (EpCAM) is involved in prostate cancer chemotherapy/radiotherapy response in vivo

BACKGROUND: Development of chemo-/radioresistance is a major challenge for the current prostate cancer (CaP) therapy. We have previously demonstrated that epithelial cell adhesion molecule (EpCAM) is associated with CaP growth and therapeutic resistance in vitro, however, the role of EpCAM in CaP in vivo is not fully elucidated. Here, we aimed to investigate how expression of EpCAM is involved in CaP growth and chemo-/radiotherapy response in NOD/SCID mouse models in vivo and to validate its role as a therapeutic target for CaP therapy. METHODS: EpCAM was knocked down in PC-3 CaP cell line using short hairpin RNA (shRNA). The effect of EpCAM-knockdown (KD) on tumour growth, chemo-/radiotherapy response and animal survival was evaluated on subcutaneous (s.c) and orthotopic mouse models. RESULTS: We found that KD of EpCAM significantly inhibited tumour growth, increased xenograft sensitivity to chemotherapy/radiotherapy, and prolonged the survival of tumour-bearing mice. In addition, we demonstrated that KD of EpCAM is associated with downregulation of the PI3K/Akt/mTOR pathway. CONCLUSIONS: In conclusion, our data confirms that CaP growth and chemo-/radioresistance in vivo is associated with over-expression of EpCAM, which serves both a functional biomarker and promising therapeutic target

Proteomics for breast cancer urine biomarkers

Although the survival of breast cancer (BC) patients has increased over the last two decades due to improved screening programs and postoperative adjuvant systemic therapies, many patients die from metastatic relapse. Current biomarkers used in the clinic are not useful for the early detection of BC, or monitoring its progression, and have limited value in predicting response to treatment. The development of proteomic techniques has sparked new searches for novel protein markers for many diseases including BC. Proteomic techniques allow for a high-throughput analysis of samples with the visualization and quantification of thousands of potential protein and peptide markers. Human urine is one of the most interesting and useful biofluids for routine testing and provides an excellent resource for the discovery of novel biomarkers, with the advantage over tissue biopsy samples due to the ease and less invasive nature of collection. In this review, we summarize the results from studies where urine was used as a source for BC biomarker research and discuss urine sample preparation, its advantage, challenges, and limitation. We focus on the gel-based proteomic approaches as well as the recent development of quantitative techniques in BC urine biomarker detection. Finally, the future use of modern proteomic techniques in BC biomarker identification will be discussed