MyMedR

Displaying all 18 publications

Abstract:

Sort:

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.
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.
Fulltext N-glycan MALDI Imaging Mass Spectrometry on Formalin-Fixed Paraffin-Embedded Tissue Enables the Delineation of Ovarian Cancer Tissues

Everest-Dass AV, Briggs MT, Kaur G, Oehler MK, Hoffmann P, Packer NH

Mol Cell Proteomics, 2016 09;15(9):3003-16.
PMID: 27412689 DOI: 10.1074/mcp.M116.059816

Ovarian cancer is a fatal gynaecological malignancy in adult women with a five-year overall survival rate of only 30%. Glycomic and glycoproteomic profiling studies have reported extensive protein glycosylation pattern alterations in ovarian cancer. Therefore, spatio-temporal investigation of these glycosylation changes may unearth tissue-specific changes that occur in the development and progression of ovarian cancer. A novel method for investigating tissue-specific N-linked glycans is using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) on formalin-fixed paraffin-embedded (FFPE) tissue sections that can spatially profile N-glycan compositions released from proteins in tissue-specific regions. In this study, tissue regions of interest (e.g. tumor, stroma, adipose tissue and necrotic areas) were isolated from FFPE tissue sections of advanced serous ovarian cancers (n = 3). PGC-LC-ESI-MS/MS and MALDI-MSI were used as complementary techniques to firstly generate structural information on the tissue-specific glycans in order to then obtain high resolution images of the glycan structure distribution in ovarian cancer tissue. The N-linked glycan repertoires carried by the proteins in these tissue regions were structurally characterized for the first time in FFPE ovarian cancer tissue regions, using enzymatic peptide-N-glycosidase F (PNGase F) release of N-glycans. The released glycans were analyzed by porous graphitized carbon liquid chromatography (PGC-LC) and collision induced electrospray negative mode MS fragmentation analysis. The N-glycan profiles identified by this analysis were then used to determine the location and distribution of each N-glycan on FFPE ovarian cancer sections that were treated with PNGase F using high resolution MALDI-MSI. A tissue-specific distribution of N-glycan structures identified particular regions of the ovarian cancer sections. For example, high mannose glycans were predominantly expressed in the tumor tissue region whereas complex/hybrid N-glycans were significantly abundant in the intervening stroma. Therefore, tumor and non-tumor tissue regions were clearly demarcated solely on their N-glycan structure distributions.
Fulltext In-House Packed Porous Graphitic Carbon Columns for Liquid Chromatography-Mass Spectrometry Analysis of N-Glycans

Young C, Condina MR, Briggs MT, Moh ESX, Kaur G, Oehler MK, et al.

Front Chem, 2021;9:653959.
PMID: 34178940 DOI: 10.3389/fchem.2021.653959

Protein glycosylation is a common post-translational modification that modulates biological processes such as the immune response and protein trafficking. Altered glycosylation profiles are associated with cancer and inflammatory diseases, as well as impacting the efficacy of therapeutic monoclonal antibodies. Consisting of oligosaccharides attached to asparagine residues, enzymatically released N-linked glycans are analytically challenging due to the diversity of isomeric structures that exist. A commonly used technique for quantitative N-glycan analysis is liquid chromatography-mass spectrometry (LC-MS), which performs glycan separation and characterization. Although many reversed and normal stationary phases have been utilized for the separation of N-glycans, porous graphitic carbon (PGC) chromatography has become desirable because of its higher resolving capability, but is difficult to implement in a robust and reproducible manner. Herein, we demonstrate the analytical properties of a 15 cm fused silica capillary (75 µm i.d., 360 µm o.d.) packed in-house with Hypercarb PGC (3 µm) coupled to an Agilent 6550 Q-TOF mass spectrometer for N-glycan analysis in positive ion mode. In repeatability and intermediate precision measurements conducted on released N-glycans from a glycoprotein standard mixture, the majority of N-glycans reported low coefficients of variation with respect to retention times (≤4.2%) and peak areas (≤14.4%). N-glycans released from complex samples were also examined by PGC LC-MS. A total of 120 N-glycan structural and compositional isomers were obtained from formalin-fixed paraffin-embedded ovarian cancer tissue sections. Finally, a comparison between early- and late-stage formalin-fixed paraffin-embedded ovarian cancer tissues revealed qualitative changes in the α2,3- and α2,6-sialic acid linkage of a fucosylated bi-antennary complex N-glycan. Although the α2,3-linkage was predominant in late-stage ovarian cancer, the alternate α2,6-linkage was more prevalent in early-stage ovarian cancer. This study establishes the utility of in-house packed PGC columns for the robust and reproducible LC-MS analysis of N-glycans.
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.
Novel IEF Peptide Fractionation Method Reveals a Detailed Profile of N-Terminal Acetylation in Chemotherapy-Responsive and -Resistant Ovarian Cancer Cells

Weiland F, Arentz G, Klingler-Hoffmann M, McCarthy P, Lokman NA, Kaur G, et al.

J Proteome Res, 2016 11 04;15(11):4073-4081.
PMID: 27569743

Although acetylation is regarded as a common protein modification, a detailed proteome-wide profile of this post-translational modification may reveal important biological insight regarding differential acetylation of individual proteins. Here we optimized a novel peptide IEF fractionation method for use prior to LC-MS/MS analysis to obtain a more in depth coverage of N-terminally acetylated proteins from complex samples. Application of the method to the analysis of the serous ovarian cancer cell line OVCAR-5 identified 344 N-terminally acetylated proteins, 12 of which are previously unreported. The protein peptidyl-prolyl cis-trans isomerase A (PPIA) was detected in both the N-terminally acetylated and unmodified forms and was further analyzed by data-independent acquisition in carboplatin-responsive parental OVCAR-5 cells and carboplatin-resistant OVCAR-5 cells. This revealed a higher ratio of unacetylated to acetylated N-terminal PPIA in the parental compared with the carboplatin-resistant OVCAR-5 cells and a 4.1-fold increase in PPIA abundance overall in the parental cells relative to carboplatin-resistant OVCAR-5 cells (P = 0.015). In summary, the novel IEF peptide fractionation method presented here is robust, reproducible, and can be applied to the profiling of N-terminally acetylated proteins. All mass spectrometry data is available as a ProteomeXchange repository (PXD003547).
N-Glycan matrix-assisted laser desorption/ionization mass spectrometry imaging protocol for formalin-fixed paraffin-embedded tissues

Briggs MT, Ho YY, Kaur G, Oehler MK, Everest-Dass AV, Packer NH, et al.

Rapid Commun Mass Spectrom, 2017 May 30;31(10):825-841.
PMID: 28271569 DOI: 10.1002/rcm.7845

RATIONALE: Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) of the proteome of a tissue has been an established technique for the past decade. In the last few years, MALDI-MSI of the N-glycome has emerged as a novel MALDI-MSI technique. To assess the accuracy and clinical significance of the N-linked glycan spatial distribution, we have developed a method that utilises MALDI-MSI followed by liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS) in order to assign glycan structures to the differentiating MALDI-MSI glycan masses released from the tissue glycoproteins.
METHODS AND RESULTS: Our workflow presents a comprehensive list of instructions on how to (i) apply MALDI-MSI to spatially map the N-glycome across formalin-fixed paraffin-embedded (FFPE) clinical samples, (ii) structurally characterise N-glycans extracted from consecutive FFPE tissue sections by LC/MS/MS, and (iii) match relevant N-glycan masses from MALDI-MSI with confirmed N-glycan structures determined by LC/MS/MS.
CONCLUSIONS: Our protocol provides groups that are new to this technique with instructions how to establish N-glycan MALDI-MSI in their laboratory. Furthermore, the method assigns N-glycan structural detail to the masses obtained in the MALDI-MS image. Copyright © 2017 John Wiley & Sons, Ltd.
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.
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.
Translating N-Glycan Analytical Applications into Clinical Strategies for Ovarian Cancer

Briggs MT, Condina MR, Klingler-Hoffmann M, Arentz G, Everest-Dass AV, Kaur G, et al.

Proteomics Clin Appl, 2019 05;13(3):e1800099.
PMID: 30367710 DOI: 10.1002/prca.201800099

Protein glycosylation, particularly N-linked glycosylation, is a complex posttranslational modification (PTM), which plays an important role in protein folding and conformation, regulating protein stability and activity, cell-cell interaction, and cell signaling pathways. This review focuses on analytical techniques, primarily MS-based techniques, to qualitatively and quantitatively assess N-glycosylation while successfully characterizing compositional, structural, and linkage features with high specificity and sensitivity. The analytical techniques explored in this review include LC-ESI-MS/MS and MALDI time-of-flight MS (MALDI-TOF-MS), which have been used to analyze clinical samples, such as serum, plasma, ascites, and tissue. Targeting the aberrant N-glycosylation patterns observed in MALDI-MS imaging (MSI) offers a platform to visualize N-glycans in tissue-specific regions. The studies on the intra-patient (i.e., a comparison of tissue-specific regions from the same patient) and inter-patient (i.e., a comparison of tissue-specific regions between different patients) variation of early- and late-stage ovarian cancer (OC) patients identify specific N-glycan differences that improve understanding of the tumor microenvironment and potentially improve therapeutic strategies for the clinic.
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.
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.
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.
Fulltext 11th Asia Oceania Human Proteome Organization Congress Report

Grey AC, Lin Q, Low TY, Wu W, Haynes PA, Chung MCM, et al.

Mol Cell Proteomics, 2023 Sep;22(9):100627.
PMID: 37532177 DOI: 10.1016/j.mcpro.2023.100627

As the first in-person Asia Oceania Human Proteomics Organization (AOHUPO) congress since 2018, the 11th AOHUPO congress was an opportune time for the research community to reconnect and to renew friendships after the long period of restricted travel due to the global pandemic. Moreover, this congress was a great opportunity for the many AO regional proteomics and mass spectrometry scientists to meet in Singapore to exchange ideas and to present their latest findings. Cohosted by the Singapore Society for Mass Spectrometry and the Malaysian Proteomics Society and held in conjunction with the seventh Asia Oceania Agricultural Proteomics Organization Congress and Singapore Society for Mass Spectrometry 2023, the meeting featured both human and agricultural proteomics. Over five hundred scientists from the AO region converged on the MAX Atria @ Singapore EXPO, Changi, Singapore from May 8 to 10 for the main congress. The diverse program was made up of 64 invited speakers and panellists for seven plenary lectures, 27 concurrent symposia, precongress and postcongress workshops, and 174 poster presentations. The AOHUPO society were able to celebrate not only their 20th anniversary but also the outstanding academic research from biological and agricultural proteomics and related 'omics fields being conducted across the Asia-Oceania region.
Use of tryptic peptide MALDI mass spectrometry imaging to identify the spatial proteomic landscape of colorectal cancer liver metastases

Li CMY, Briggs MT, Lee YR, Tin T, Young C, Pierides J, et al.

Clin Exp Med, 2024 Mar 16;24(1):53.
PMID: 38492056 DOI: 10.1007/s10238-024-01311-5

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC liver metastases (CRLM) are often resistant to conventional treatments, with high rates of recurrence. Therefore, it is crucial to identify biomarkers for CRLM patients that predict cancer progression. This study utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially map the CRLM tumour proteome. CRLM tissue microarrays (TMAs) of 84 patients were analysed using tryptic peptide MALDI-MSI to spatially monitor peptide abundances across CRLM tissues. Abundance of peptides was compared between tumour vs stroma, male vs female and across three groups of patients based on overall survival (0-3 years, 4-6 years, and 7+ years). Peptides were then characterised and matched using LC-MS/MS. A total of 471 potential peptides were identified by MALDI-MSI. Our results show that two unidentified m/z values (1589.876 and 1092.727) had significantly higher intensities in tumours compared to stroma. Ten m/z values were identified to have correlation with biological sex. Survival analysis identified three peptides (Histone H4, Haemoglobin subunit alpha, and Inosine-5'-monophosphate dehydrogenase 2) and two unidentified m/z values (1305.840 and 1661.060) that were significantly higher in patients with shorter survival (0-3 years relative to 4-6 years and 7+ years). This is the first study using MALDI-MSI, combined with LC-MS/MS, on a large cohort of CRLM patients to identify the spatial proteome in this malignancy. Further, we identify several protein candidates that may be suitable for drug targeting or for future prognostic biomarker development.
Fulltext Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders

Andlauer TFM, Guzman-Parra J, Streit F, Strohmaier J, González MJ, Gil Flores S, et al.

Mol Psychiatry, 2021 Apr;26(4):1286-1298.
PMID: 31712721 DOI: 10.1038/s41380-019-0558-2

Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development.
Fulltext Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Amare AT, Schubert KO, Hou L, Clark SR, Papiol S, Cearns M, et al.

Mol Psychiatry, 2021 Jun;26(6):2457-2470.
PMID: 32203155 DOI: 10.1038/s41380-020-0689-5

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.
Fulltext Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Mullins N, Kang J, Campos AI, Coleman JRI, Edwards AC, Galfalvy H, et al.

Biol Psychiatry, 2022 Feb 01;91(3):313-327.
PMID: 34861974 DOI: 10.1016/j.biopsych.2021.05.029

BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders.
METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.
RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.
CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

Filters

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links