ORCID Profile
0000-0003-0139-9757
Current Organisation
University of South Australia
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Publisher: Wiley
Date: 16-08-2019
Abstract: Epithelial ovarian cancer is one of the most fatal gynecological malignancies in adult women. As studies on protein N-glycosylation have extensively reported aberrant patterns in the ovarian cancer tumor microenvironment, obtaining spatial information will uncover tumor-specific N-glycan alterations in ovarian cancer development and progression. matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is employed to investigate N-glycan distribution on formalin-fixed paraffin-embedded ovarian cancer tissue sections from early- and late-stage patients. Tumor-specific N-glycans are identified and structurally characterized by porous graphitized carbon-liquid chromatography-electrospray ionization-tandem mass spectrometry (PGC-LC-ESI-MS/MS), and then assigned to high-resolution images obtained from MALDI-MSI. Spatial distribution of 14 N-glycans is obtained by MALDI-MSI and 42 N-glycans (including structural and compositional isomers) identified and structurally characterized by LC-MS. The spatial distribution of oligomannose, complex neutral, bisecting, and sialylated N-glycan families are localized to the tumor regions of late-stage ovarian cancer patients relative to early-stage patients. Potential N-glycan diagnostic markers that emerge include the oligomannose structure, (Hex)
Publisher: American Chemical Society (ACS)
Date: 09-2020
Publisher: Wiley
Date: 03-0001
Abstract: Cytoskeletal proteins are essential building blocks of cells. More than 100 cytoskeletal and cytoskeleton-associated proteins are known and for some, their function and regulation are understood in great detail. Apart from cell shape and support, they facilitate many processes such as intracellular signaling and transport, and cancer related processes such as proliferation, migration, and invasion. During the last decade, comparative proteomic studies have identified cytoskeletal proteins as in vitro markers for tumor progression and metastasis. Here, these results are summarized and a number of unrelated studies are highlighted, identifying the same cytoskeletal proteins as potential biomarkers. These findings might indicate that the abundance of these potential markers of tumor progression is associated with the biological outcome and are independent of the cancer origin. This correlates well with recently published results from the Cancer Genome Atlas, indicating that cancers show remarkable similarities in their analyzed molecular information, independent of their organ of origin. It is postulated that the quantification of cytoskeletal proteins in healthy tissues, tumors, in adjacent tissues, and in stroma, is a great source of molecular information, which might not only be used to classify tumors, but more importantly to predict patients' outcome or even best treatment choices.
Publisher: Wiley
Date: 09-05-2016
Abstract: Applying MALDI-MS imaging to tissue microarrays (TMAs) provides access to proteomics data from large cohorts of patients in a cost- and time-efficient way, and opens the potential for applying this technology in clinical diagnosis. The complexity of these TMA data-high-dimensional low s le size-provides challenges for the statistical analysis, as classical methods typically require a nonsingular covariance matrix that cannot be satisfied if the dimension is greater than the s le size. We use TMAs to collect data from endometrial primary carcinomas from 43 patients. Each patient has a lymph node metastasis (LNM) status of positive or negative, which we predict on the basis of the MALDI-MS imaging TMA data. We propose a variable selection approach based on canonical correlation analysis that explicitly uses the LNM information. We apply LDA to the selected variables only. Our method misclassifies 2.3-20.9% of patients by leave-one-out cross-validation and strongly outperforms LDA after reduction of the original data with principle component analysis.
Publisher: Wiley
Date: 10-05-2016
Abstract: Metastasis is a crucial step of malignant progression and is the primary cause of death from endometrial cancer. However, clinicians presently face the challenge that conventional surgical-pathological variables, such as tumour size, depth of myometrial invasion, histological grade, lymphovascular space invasion or radiological imaging are unable to predict with accuracy if the primary tumour has metastasized. In the current retrospective study, we have used primary tumour s les of endometrial cancer patients diagnosed with (n = 16) and without (n = 27) lymph node metastasis to identify potential discriminators. Using peptide matrix assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI), we have identified m/z values which can classify 88% of all tumours correctly. The top discriminative m/z values were identified using a combination of in situ sequencing and LC-MS/MS from digested tumour s les. Two of the proteins identified, plectin and α-Actin-2, were used for validation studies using LC-MS/MS data independent analysis (DIA) and immunohistochemistry. In summary, MALDI-MSI has the potential to identify discriminators of metastasis using primary tumour s les.
Publisher: Elsevier BV
Date: 03-2020
Publisher: Springer Science and Business Media LLC
Date: 21-11-2020
Publisher: MDPI AG
Date: 06-04-2023
Abstract: Eighty percent of ovarian cancer patients initially respond to chemotherapy, but the majority eventually experience a relapse and die from the disease with acquired chemoresistance. In addition, 20% of patients do not respond to treatment at all, as their disease is intrinsically chemotherapy resistant. Data-independent acquisition nano-flow liquid chromatography–mass spectrometry (DIA LC-MS) identified the three protein markers: gelsolin (GSN), calmodulin (CALM1), and thioredoxin (TXN), to be elevated in high-grade serous ovarian cancer (HGSOC) tissues from patients that responded to chemotherapy compared to those who did not the differential expression of the three protein markers was confirmed by immunohistochemistry. Analysis of the online GENT2 database showed that mRNA levels of GSN, CALM1, and TXN were decreased in HGSOC compared to fallopian tube epithelium. Elevated levels of GSN and TXN mRNA expression correlated with increased overall and progression-free survival, respectively, in a Kaplan–Meier analysis of a large online repository of HGSOC patient data. Importantly, differential expression of the three protein markers was further confirmed when comparing parental OVCAR-5 cells to carboplatin-resistant OVCAR-5 cells using DIA LC-MS analysis. Our findings suggest that GSN, CALM1, and TXN may be useful biomarkers for predicting chemotherapy response and understanding the mechanisms of chemotherapy resistance. Proteomic data are available via ProteomeXchange with identifier PXD033785.
Publisher: MDPI AG
Date: 10-07-2022
DOI: 10.3390/MPS5040057
Abstract: The molecular analysis of small or rare patient tissue s les is challenging and often limited by available technologies and resources, such as reliable antibodies against a protein of interest. Although targeted approaches provide some insight, here, we describe the workflow of two complementary mass spectrometry approaches, which provide a more comprehensive and non-biased analysis of the molecular features of the tissue of interest. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) generates spatial intensity maps of molecular features, which can be easily correlated with histology. Additionally, liquid chromatography tandem mass spectrometry (LC-MS/MS) can identify and quantify proteins of interest from a consecutive section of the same tissue. Here, we present data from concurrent precancerous lesions from the endometrium and fallopian tube of a single patient. Using this complementary approach, we monitored the abundance of hundreds of proteins within the precancerous and neighboring healthy regions. The method described here represents a useful tool to maximize the number of molecular data acquired from small s le sizes or even from a single case. Our initial data are indicative of a migratory phenotype in these lesions and warrant further research into their malignant capabilities.
Publisher: Wiley
Date: 15-10-2019
Abstract: Malignant ascites is a fluid, which builds up in the abdomen and contains cancer cells in the form of single cells or multicellular clusters called spheroids. Malignant ascites has been observed in patients suffering from ovarian, cervical, gastric, colorectal, pancreatic, endometrial, or primary liver cancer. The spheroids are believed to play a major role in chemo resistance and metastasis of the cancer. To ease the discomfort of patients, malignant ascites (MA) is often drained from the abdomen using a procedure called paracentesis. MA retrieved via this minimal invasive procedure is a great source for cancer spheroids, which can be used for testing chemotherapeutic drugs and drug combinations. Herein, the existing workflow is adapted to make concurrent monitoring of drug accumulation, drug response, and drug metabolites feasible using primary spheroids or spheroids grown without a scaffolding matrix. To achieve this, those spheroids are embedded in matrigel, before fixing them with formalin. This makes it possible to process, store, and ship s les at room temperature. This new approach might be used to choose the best targeted therapy for each patient and thereby facilitate personalized medicine.
Publisher: Public Library of Science (PLoS)
Date: 22-11-2019
Publisher: Wiley
Date: 27-11-2020
DOI: 10.1002/JMS.4689
Publisher: Wiley
Date: 15-12-2016
Abstract: This review discusses the current status of proteomics technology in endometrial cancer diagnosis, treatment and prognosis. The first part of this review focuses on recently identified biomarkers for endometrial cancer, their importance in clinical use as well as the proteomic methods used in their discovery. The second part highlights some of the emerging mass spectrometry based proteomic technologies that promise to contribute to a better understanding of endometrial cancer by comparing the abundance of hundreds or thousands of proteins simultaneously.
Publisher: MDPI AG
Date: 20-04-2023
DOI: 10.3390/CIMB45040235
Abstract: Nearly 90% of cervical cancers are linked to human papillomavirus (HPV). Uncovering the protein signatures in each histological phase of cervical oncogenesis provides a path to biomarker discovery. The proteomes extracted from formalin-fixed paraffin-embedded tissues of the normal cervix, HPV16/18-associated squamous intraepithelial lesion (SIL), and squamous cell carcinoma (SCC) were compared using liquid chromatography-mass spectrometry (LC-MS). A total of 3597 proteins were identified, with 589, 550, and 1570 proteins unique to the normal cervix, SIL, and SCC groups, respectively, while 332 proteins overlapped between the three groups. In the transition from normal cervix to SIL, all 39 differentially expressed proteins were downregulated, while all 51 proteins discovered were upregulated in SIL to SCC. The binding process was the top molecular function, while chromatin silencing in the SIL vs. normal group, and nucleosome assembly in SCC vs. SIL groups was the top biological process. The PI3 kinase pathway appears crucial in initiating neoplastic transformation, while viral carcinogenesis and necroptosis are important for cell proliferation, migration, and metastasis in cervical cancer development. Annexin A2 and cornulin were selected for validation based on LC-MS results. The former was downregulated in the SIL vs. normal cervix and upregulated in the progression from SIL to SCC. In contrast, cornulin exhibited the highest expression in the normal cervix and lowest in SCC. Although other proteins, such as histones, collagen, and vimentin, were differentially expressed, their ubiquitous expression in most cells precluded further analysis. Immunohistochemical analysis of tissue microarrays found no significant difference in Annexin A2 expression between the groups. Conversely, cornulin exhibited the strongest expression in the normal cervix and lowest in SCC, supporting its role as a tumor suppressor and potential biomarker for disease progression.
Publisher: Elsevier BV
Date: 07-2017
DOI: 10.1016/J.BBAPAP.2016.10.010
Abstract: The prediction of lymph node metastasis using clinic-pathological data and molecular information from endometrial cancers lacks accuracy and is therefore currently not routinely used in patient management. Consequently, although only a small percentage of patients with endometrial cancers suffer from metastasis, the majority undergo radical surgery including removal of pelvic lymph nodes. Upon analysis of publically available data and published research, we compiled a list of 60 proteins having the potential to display differential abundance between primary endometrial cancers with versus those without lymph node metastasis. Using data dependent acquisition LC-ESI-MS/MS we were able to detect 23 of these proteins in endometrial cancers, and using data independent LC-ESI-MS/MS the differential abundance of five of those proteins was observed. The localization of the differentially expressed proteins, was visualized using peptide MALDI MSI in whole tissue sections as well as tissue microarrays of 43 patients. The proteins identified were further validated by immunohistochemistry. Our data indicate that annexin A2 protein level is upregulated, whereas annexin A1 and α actinin 4 expression are downregulated in tumours with lymph node metastasis compared to those without lymphatic spread. Moreover, our analysis confirmed the potential of these markers, to be included in a statistical model for prediction of lymph node metastasis. The predictive model using highly ranked m/z values identified by MALDI MSI showed significantly higher predictive accuracy than the model using immunohistochemistry data. In summary, using publicly available data and complementary proteomics approaches, we were able to improve the prediction model for lymph node metastasis in EC.
Publisher: MDPI AG
Date: 08-07-2016
DOI: 10.3390/IJMS17071088
Publisher: Wiley
Date: 09-02-2018
Abstract: Multicellular tumor spheroids (MCTS) are a powerful biological in vitro model, which closely mimics the 3D structure of primary avascularized tumors. Mass spectrometry (MS) has established itself as a powerful analytical tool, not only to better understand and describe the complex structure of MCTS, but also to monitor their response to cancer therapeutics. The first part of this review focuses on traditional mass spectrometry approaches with an emphasis on elucidating the molecular characteristics of these structures. Then the mass spectrometry imaging (MSI) approaches used to obtain spatially defined information from MCTS is described. Finally the analysis of primary spheroids, such as those present in ovarian cancer, and the great potential that mass spectrometry analysis of these structures has for improved understanding of cancer progression and for personalized in vitro therapeutic testing is discussed.
Publisher: American Chemical Society (ACS)
Date: 29-10-2019
DOI: 10.1021/ACS.ANALCHEM.9B03091
Abstract: The strength of MALDI-MSI is to analyze and visualize spatial intensities of molecular features from an intact tissue. The distribution of the intensities can then be visualized within a single tissue section or compared in between sections, acquired consecutively. This method can be reliably used to reveal physiological structures and has the potential to identify molecular details, which correlate with biological outcomes. MALDI-MSI implementation in clinical laboratories requires the ability to ensure method quality and validation to meet diagnostic expectations. To be able to get consistent qualitative and quantitative results, standardized s le preparation and data acquisition are of highest priority. We have previously shown that the deposition of internal standards onto the tissue section during s le preparation can be used to improve the mass accuracy of monitored
Publisher: MDPI AG
Date: 27-10-2021
Abstract: Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) can determine the spatial distribution of analytes such as protein distributions in a tissue section according to their mass-to-charge ratio. Here, we explored the clinical potential of machine learning (ML) applied to MALDI MSI data for cancer diagnostic classification using tissue microarrays (TMAs) on 302 colorectal (CRC) and 257 endometrial cancer (EC)) patients. ML based on deep neural networks discriminated colorectal tumour from normal tissue with an overall accuracy of 98% in balanced cross-validation (98.2% sensitivity and 98.6% specificity). Moreover, our machine learning approach predicted the presence of lymph node metastasis (LNM) for primary tumours of EC with an accuracy of 80% (90% sensitivity and 69% specificity). Our results demonstrate the capability of MALDI MSI for complementing classic histopathological examination for cancer diagnostic applications.
Publisher: Elsevier BV
Date: 10-2023
Publisher: Elsevier
Date: 2017
DOI: 10.1016/BS.ACR.2016.11.002
Abstract: Pathologists play an essential role in the diagnosis and prognosis of benign and cancerous tumors. Clinicians provide tissue s les, for ex le, from a biopsy, which are then processed and thin sections are placed onto glass slides, followed by staining of the tissue with visible dyes. Upon processing and microscopic examination, a pathology report is provided, which relies on the pathologist's interpretation of the phenotypical presentation of the tissue. Targeted analysis of single proteins provide further insight and together with clinical data these results influence clinical decision making. Recent developments in mass spectrometry facilitate the collection of molecular information about such tissue specimens. These relatively new techniques generate label-free mass spectra across tissue sections providing nonbiased, nontargeted molecular information. At each pixel with spatial coordinates (x/y) a mass spectrum is acquired. The acquired mass spectrums can be visualized as intensity maps displaying the distribution of single m/z values of interest. Based on the s le preparation, proteins, peptides, lipids, small molecules, or glycans can be analyzed. The generated intensity maps/images allow new insights into tumor tissues. The technique has the ability to detect and characterize tumor cells and their environment in a spatial context and combined with histological staining, can be used to aid pathologists and clinicians in the diagnosis and management of cancer. Moreover, such data may help classify patients to aid therapy decisions and predict outcomes. The novel complementary mass spectrometry-based methods described in this chapter will contribute to the transformation of pathology services around the world.
Publisher: Elsevier BV
Date: 12-2020
Publisher: Springer Science and Business Media LLC
Date: 24-03-2022
DOI: 10.1038/S41419-022-04693-0
Abstract: Mutations in N -glycanase 1 (NGLY1), which deglycosylates misfolded glycoproteins for degradation, can cause NGLY1 deficiency in patients and their abnormal fetal development in multiple organs, including microcephaly and other neurological disorders. Using cerebral organoids (COs) developed from human embryonic stem cells (hESCs) and induced pluripotent stem cells (hiPSCs), we investigate how NGLY1 dysfunction disturbs early brain development. While NGLY1 loss had limited impact on the undifferentiated cells, COs developed from NGLY1-deficient hESCs showed defective formation of SATB2-positive upper-layer neurons, and attenuation of STAT3 and HES1 signaling critical for sustaining radial glia. Bulk and single-cell transcriptomic analysis revealed premature neuronal differentiation accompanied by downregulation of secreted and transcription factors, including TTR, IGFBP2, and ID4 in NGLY1-deficient COs. NGLY1 malfunction also dysregulated ID4 and enhanced neuronal differentiation in CO transplants developed in vivo. NGLY1-deficient CO cells were more vulnerable to multiple stressors treating the deficient cells with recombinant TTR reduced their susceptibility to stress from proteasome inactivation, likely through LRP2-mediated activation of MAPK signaling. Expressing NGLY1 led to IGFBP2 and ID4 upregulation in CO cells developed from NGLY1-deficiency patient’s hiPSCs. In addition, treatment with recombinant IGFBP2 enhanced ID4 expression, STAT3 signaling, and proliferation of NGLY1-deficient CO cells. Overall, our discoveries suggest that dysregulation of stress responses and neural precursor differentiation underlies the brain abnormalities observed in NGLY1-deficient in iduals.
No related grants have been discovered for Parul Mittal.