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  1. Proteomics of endometrial cancer diagnosis, treatment, and prognosis
    Mittal P, Klingler-Hoffmann M, Arentz G, Zhang C, Kaur G, Oehler MK, et al.
    Proteomics Clin Appl, 2016 Mar;10(3):217-29.
    PMID: 26541900 DOI: 10.1002/prca.201500055
    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.
  2. Fulltext An evaluation of medication appropriateness and frailty among residents of aged care homes in Malaysia: A cross-sectional study
    Hasan SS, Kow CS, Verma RK, Ahmed SI, Mittal P, Chong DWK
    Medicine (Baltimore), 2017 Sep;96(35):e7929.
    PMID: 28858118 DOI: 10.1097/MD.0000000000007929
    Aging is significantly associated with the development of comorbid chronic conditions. These conditions indicate the use of multiple medications, and are often warranted by clinical guidelines. The aim of the present study was to evaluate medication appropriateness and frailty among Malaysian aged care home residents with chronic disease. The participants were 202 elderly (≥65 years) individuals, a cross-sectional sample from 17 aged care homes. After ethics approval, each participant was interviewed to collect data on sociodemographics, frailty status (Groningen Frailty Indicator [GFI]), medication appropriateness (Medication Appropriateness Index (MAI), the 2015 Beers' criteria (Potentially Inappropriate Medication [PIM]), and 2014 STOPP criteria (Potentially Inappropriate Prescribing [PIP]). The findings show that 81% (n = 164) and 42% (n = 85) were taking medications for cardiovascular and central nervous system-related conditions, respectively, and 34% were using medications for diabetes (n = 69). Each participant had a mean of 2.9 ± 1.5 chronic diseases, with an average GFI score of 6.4 ± 3.6. More than three-quarters of the participants (76%) were frail and polypharmacy was a factor in nearly half (48%); 41% and 36% were prescribed at least one PIP and PIM, respectively, whereas the average MAI score was 0.6 (range: 0-6). The number of medications used per participant correlated significantly and positively (0.21, P = .002) with GFI score. These findings reinforce the need for participants of aged care homes to receive periodic medication review aimed at minimizing morbidity associated with inappropriate pharmacotherapy.
  3. Uncovering Tumor-Stroma Inter-relationships Using MALDI Mass Spectrometry Imaging
    Boyle ST, Mittal P, Kaur G, Hoffmann P, Samuel MS, Klingler-Hoffmann M
    J Proteome Res, 2020 10 02;19(10):4093-4103.
    PMID: 32870688 DOI: 10.1021/acs.jproteome.0c00511
    Tumorigenesis involves a complex interplay between genetically modified cancer cells and their adjacent normal tissue, the stroma. We used an established breast cancer mouse model to investigate this inter-relationship. Conditional activation of Rho-associated protein kinase (ROCK) in a model of mammary tumorigenesis enhances tumor growth and progression by educating the stroma and enhancing the production and remodeling of the extracellular matrix. We used peptide matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to quantify the proteomic changes occurring within tumors and their stroma in their regular spatial context. Peptides were ranked according to their ability to discriminate between the two groups, using a receiver operating characteristic tool. Peptides were identified by liquid chromatography tandem mass spectrometry, and protein expression was validated by quantitative immunofluorescence using an independent set of tumor samples. We have identified and validated four key proteins upregulated in ROCK-activated mammary tumors relative to those expressing kinase-dead ROCK, namely, collagen I, α-SMA, Rab14, and tubulin-β4. Rab14 and tubulin-β4 are expressed within tumor cells, whereas collagen I is localized within the stroma. α-SMA is predominantly localized within the stroma but is also expressed at higher levels in the epithelia of ROCK-activated tumors. High expression of COL1A, the gene encoding the pro-α 1 chain of collagen, correlates with cancer progression in two human breast cancer genomic data sets, and high expression of COL1A and ACTA2 (the gene encoding α-SMA) are associated with a low survival probability (COLIA, p = 0.00013; ACTA2, p = 0.0076) in estrogen receptor-negative breast cancer patients. To investigate whether ROCK-activated tumor cells cause stromal cancer-associated fibroblasts (CAFs) to upregulate expression of collagen I and α-SMA, we treated CAFs with medium conditioned by primary mammary tumor cells in which ROCK had been activated. This led to abundant production of both proteins in CAFs, clearly highlighting the inter-relationship between tumor cells and CAFs and identifying CAFs as the potential source of high levels of collagen 1 and α-SMA and associated enhancement of tissue stiffness. Our research emphasizes the capacity of MALDI-MSI to quantitatively assess tumor-stroma inter-relationships and to identify potential prognostic factors for cancer progression in human patients, using sophisticated mouse cancer models.
  4. Lapatinib nano-delivery systems: a promising future for breast cancer treatment
    Bonde GV, Yadav SK, Chauhan S, Mittal P, Ajmal G, Thokala S, et al.
    Expert Opin Drug Deliv, 2018 05;15(5):495-507.
    PMID: 29521126 DOI: 10.1080/17425247.2018.1449832
    INTRODUCTION: Breast cancer stands the second prominent cause of death among women. For its efficient treatment, Lapatinib (LAPA) was developed as a selective tyrosine kinase inhibitor of receptors, overexpressed by breast cancer cells. Various explored delivery strategies for LAPA indicated its controlled release with enhanced aqueous solubility, improved bioavailability, decreased plasma protein binding, reduced dose and toxicity to the other organs with maximized clinical efficacy, compared to its marketed tablet formulation.

    AREAS COVERED: This comprehensive review deals with the survey, performed through different electronic databases, regarding various challenges and their solutions attained by fabricating delivery systems like nanoparticles, micelle, nanocapsules, nanochannels, and liposomes. It also covers the synthesis of novel LAPA-conjugates for diagnostic purpose.

    EXPERT OPINION: Unfortunately, clinical use of LAPA is restricted because of its extensive albumin binding capacity, poor oral bioavailability, and poor aqueous solubility. LAPA is marketed as the oral tablet only. Therefore, it becomes imperative to formulate alternate efficient multiparticulate or nano-delivery systems for administration through non-oral routes, for active/passive targeting, and to scale-up by pharmaceutical scientists followed by their clinical trials by clinical experts. LAPA combinations with capecitabine and letrozole should also be tried for breast cancer treatment.

  5. Altered N-linked glycosylation in endometrial cancer
    Mittal P, Briggs M, Klingler-Hoffmann M, Kaur G, Packer NH, Oehler MK, et al.
    Anal Bioanal Chem, 2021 Apr;413(10):2721-2733.
    PMID: 33222001 DOI: 10.1007/s00216-020-03039-z
    It is well established that cell surface glycans play a vital role in biological processes and their altered form can lead to carcinogenesis. Mass spectrometry-based techniques have become prominent for analysing N-linked glycans, for example using matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). Additionally, MALDI MS can be used to spatially map N-linked glycans directly from cancer tissue using a technique termed MALDI MS imaging (MALDI MSI). This powerful technique combines mass spectrometry and histology to visualise the spatial distribution of N-linked glycans on a single tissue section. Here, we performed N-glycan MALDI MSI on six endometrial cancer (EC) formalin-fixed paraffin-embedded (FFPE) tissue sections and tissue microarrays (TMA) consisting of eight EC patients with lymph node metastasis (LNM) and twenty without LNM. By doing so, several putative N-linked glycan compositions were detected that could significantly distinguish normal from cancerous endometrium. Furthermore, a complex core-fucosylated N-linked glycan was detected that could discriminate a primary tumour with and without LNM. Structural identification of these putative N-linked glycans was performed using porous graphitized carbon liquid chromatography tandem mass spectrometry (PGC-LC-MS/MS). Overall, we observed higher abundance of oligomannose glycans in tumour compared to normal regions with AUC ranging from 0.85-0.99, and lower abundance of complex N-linked glycans with AUC ranges from 0.03-0.28. A comparison of N-linked glycans between primary tumours with and without LNM indicated a reduced abundance of a complex core-fucosylated N-glycan (Hex)2(HexNAc)2(Deoxyhexose)1+(Man)3(GlcNAc)2, in primary tumour with associated lymph node metastasis. In summary, N-linked glycan MALDI MSI can be used to differentiate cancerous endometrium from normal, and endometrial cancer with LNM from endometrial cancer without.
  6. Fulltext Protein Profiling in Human Papillomavirus-Associated Cervical Carcinogenesis: Cornulin as a Biomarker for Disease Progression
    Kumarasamy G, Ismail MN, Tuan Sharif SE, Desire C, Mittal P, Hoffmann P, et al.
    Curr Issues Mol Biol, 2023 Apr 20;45(4):3603-3627.
    PMID: 37185759 DOI: 10.3390/cimb45040235
    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.
  7. Fulltext Association between beliefs about medicines and self-medication with analgesics among patients with dental pain
    Mittal P, Chan OY, Kanneppady SK, Verma RK, Hasan SS
    PLoS One, 2018;13(8):e0201776.
    PMID: 30071006 DOI: 10.1371/journal.pone.0201776
    Self-medication with analgesics in dental pain management is a common practice as most of these medicines are available over-the-counter (OTC). The study aims to examine the relationship between beliefs about medicines and self-medication with analgesics in dental pain management in Malaysia. This cross-sectional study was conducted among conveniently sampled patients attending dental clinics, located in Kuala Lumpur, Malaysia to assess association between self-medication with analgesics and patient's beliefs about medicines via Beliefs about Medicines Questionnaire. Participants were evaluated for their self-medication practices via 4 items. Further assessment was done via Quantitative Analgesic Questionnaire (QAQ) regarding the analgesics taken. Statistical analyses were performed using SPSS version 24, with 0.05 as level of significance. The prevalence of self-medication with analgesics was 29.4%, with 95.6% of the participants took analgesics when necessary. Participants practising self-medication for dental pain reported more positive beliefs in General-Necessity (13.04 vs. 9.98, p = 0.001) than those not practising self-medication. However, these participants had weaker beliefs in General-Harm (12.00 vs. 10.29, p = 0.006) and General-Overuse (11.38 vs. 10.31, p = 0.032) than those not practising self-medication. Participants beliefs in General-Harm (r = -0.243; p = 0.003) and General-Overuse (r = -0.203; p = 0.012) were negatively correlated with total QAQ point. The study found that individuals who practised self-medication had stronger beliefs about the benefits of medicines and weaker beliefs in viewing medicines as harmful and overused. Findings can guide public education to improve the safety aspects of self-medication with analgesics in dental practice.
  8. MALDI Mass Spectrometry Imaging of Early- and Late-Stage Serous Ovarian Cancer Tissue Reveals Stage-Specific N-Glycans
    Briggs MT, Condina MR, Ho YY, Everest-Dass AV, Mittal P, Kaur G, et al.
    Proteomics, 2019 11;19(21-22):e1800482.
    PMID: 31364262 DOI: 10.1002/pmic.201800482
    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)6 + (Man)3 (GlcNAc)2 , and the complex neutral structure, (Hex)2 (HexNAc)2 (Deoxyhexose)1 + (Man)3 (GlcNAc)2 . The distribution of these markers is evaluated using a tissue microarray of early- and late-stage patients.
  9. Lymph node metastasis of primary endometrial cancers: Associated proteins revealed by MALDI imaging
    Mittal P, Klingler-Hoffmann M, Arentz G, Winderbaum L, Lokman NA, Zhang C, et al.
    Proteomics, 2016 06;16(11-12):1793-801.
    PMID: 27061135 DOI: 10.1002/pmic.201500455
    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 samples 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 samples. 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 samples.
  10. Annexin A2 and alpha actinin 4 expression correlates with metastatic potential of primary endometrial cancer
    Mittal P, Klingler-Hoffmann M, Arentz G, Winderbaum L, Kaur G, Anderson L, et al.
    Biochim Biophys Acta Proteins Proteom, 2017 Jul;1865(7):846-857.
    PMID: 27784647 DOI: 10.1016/j.bbapap.2016.10.010
    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.
  11. Fulltext Cancer Tissue Classification Using Supervised Machine Learning Applied to MALDI Mass Spectrometry Imaging
    Mittal P, Condina MR, Klingler-Hoffmann M, Kaur G, Oehler MK, Sieber OM, et al.
    Cancers (Basel), 2021 Oct 27;13(21).
    PMID: 34771551 DOI: 10.3390/cancers13215388
    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.
  12. Fulltext Virtual Learning during COVID-19: Exploring Challenges and Identifying Highly Vulnerable Groups Based on Location
    Jafar A, Dollah R, Dambul R, Mittal P, Ahmad SA, Sakke N, et al.
    Int J Environ Res Public Health, 2022 Sep 05;19(17).
    PMID: 36078822 DOI: 10.3390/ijerph191711108
    Amid the outbreak of the COVID-19 pandemic in the year 2020, educational platforms have been forced to change and adapt from conventional physical learning to virtual learning. Nearly all higher learning institutions worldwide are forced to follow the new educational setting through virtual platforms. Sabah is one of the poorest states in Malaysia with the poorest infrastructure, with the technology and communication facilities in the state remaining inept. With the changes in virtual platforms in all higher education institutions in Malaysia, higher learning institutions in Sabah are expected to follow the lead, despite the state lagging in its development. This has certainly impacted the overall productivity and performance of students in Sabah. Therefore, this study aims to explore the challenges of the implementation of virtual learning among students in Sabah. More specifically, this study seeks to identify vulnerable groups among students based on their geographical location. To achieve the objective of this study, a survey has been conducted on a total of 1,371 students in both private and public higher learning institutions in Sabah. The sample selection for this study was determined using a purposive sampling technique. Based on Principal Component Analysis (PCA), it was found that there are five challenges in virtual learning faced by students in higher learning institutions in Sabah. These are the unconducive learning environment (var(X) = 20.12%), the deterioration of physical health (var(X) = 13.40%), the decline of mental health (var(X) = 12.10%), the limited educational facilities (var(X) = 10.14%) and social isolation (var(X) = 7.47%). The K-Means Clustering analysis found that there are six student clusters in Sabah (Cluster A, B, C, D, E & F), each of which faces different challenges in participating in virtual learning. Based on the assessment of location, almost half of the total number of districts in Sabah are dominated by students from Cluster A (9 districts) and Cluster B (4 districts). More worryingly, both Cluster A and Cluster B are classified as highly vulnerable groups in relation to the implementation of virtual learning. The results of this study can be used by the local authorities and policymakers in Malaysia to improve the implementation of virtual learning in Sabah so that the education system can be more effective and systematic. Additionally, the improvement and empowerment of the learning environment are crucial to ensuring education is accessible and inclusive for all societies, in line with the fourth of the Sustainable Development Goals (SDG-4).
  13. Fulltext Readiness and Challenges of E-Learning during the COVID-19 Pandemic Era: A Space Analysis in Peninsular Malaysia
    Jafar A, Dollah R, Mittal P, Idris A, Kim JE, Abdullah MS, et al.
    Int J Environ Res Public Health, 2023 Jan 04;20(2).
    PMID: 36673659 DOI: 10.3390/ijerph20020905
    During the COVID-19 era, most countries, including Malaysia, have shifted from face-to-face teaching systems to online teaching programs. The aim of this study is to identify the main challenges that higher education students face during e-learning based on their residential location throughout Peninsular Malaysia. This study further examines the readiness of higher education students to apply e-learning. Therefore, a cross-sectional survey approach is used to fulfil the outlined objectives. Accordingly, 761 public (95.3%) and private (4.7%) higher education students residing in Peninsular Malaysia are sampled in this study. The survey was administered online for 37 days, from 21 October 21 to 6 December 2021, using either WhatsApp or Facebook. The raw data is inferentially (Principal Component Analysis, K-Means Clustering, Kruskal Wallis, and spatial analysis) and descriptively (mean, standard deviation & percentage) analyzed. It has been revealed that six clusters of students in Peninsular Malaysia face various challenges while following the e-learning program. Most states in Peninsular Malaysia are dominated by students in Cluster D (Terengganu, Perlis, Penang, Selangor, WP Kuala Lumpur, and WP Putrajaya) and Cluster B categories (Melaka, Johor, Kelantan, and Kedah). Students in the Cluster D category tend to suffer from physical health disorders and social isolation, while students in the Cluster B category face problems with decreased focus in learning, mental health disorders, and social isolation. The outcomes further indicate that the more challenges students face during e-learning programs, the lower their willingness to continue with the program. The results of this study are significant in addressing the challenges of e-learning, which will help stakeholders address and strengthen student abilities.
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