CD8+ Tumor-Infiltrating Lymphocyte Abundance is a Positive Prognostic Indicator in Nasopharyngeal Cancer
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ABSTRACT: A retrospective tissue study to explore the prognostic significance of tumor-infiltrating lymphocyte (TIL) populations in Nasopharyngeal Cancer, using a combination of RNA sequencing and immunohistochemistry.
Project description:A significant percentage of HIV-infected individuals experience a sharp decline in CD4+ T cell counts and progress to AIDS quickly after primary infection. Identification of biomarkers distinguishing rapid progressors (RPs) versus chronic progressors (CPs) is critical for early clinical intervention and could provide novel strategies to facilitate vaccine design and immune therapy. mRNA and miRNA expression profiles in the peripheral blood mononuclear cells (PBMCs) of RPs and CPs were investigated at 111±22 days (Mean±SD) of HIV infection. The association of mRNA and miRNA expression with disease progression was examined by receiver operating characteristic analysis and Kaplan-Meier survival analysis. Pathway enrichment analysis showed that genes with deregulated expression in RPs are primarily involved in apoptosis pathways. Furthermore, we found that 5 miRNAs (miR-31, -200c, -526a, -99a and -503) in RPs were significantly decreased compared to those in CPs (P<0.05). The decreased expression of these miRNAs was associated with rapid disease progression of HIV infection with a 94% predictive value as measured by the area under the curve. The upregulated predicted targets from the 5 signature miRNAs and all upregulated genes identified from mRNA microarray converged to the apoptosis pathway. Moreover, overexpression of miR-31 in primary human T cells promoted their survival. Our results have identified a distinct transcriptomic signature in PBMCs of RPs and provided novel insights to the pathogenesis of HIV infection. The initial 347 miRNA array was performed in 11 RPs, 6 CPs and 4 corresponding matched normal controls (training group); and only the miRNAs differentially expressed between RPs and CPs (P<0.05) in training group were detected in a subsequent validation group (19 RPs versus 10 CPs). miRNAs differentially expressed in 17 early HIV infected patients (including 11 RPs and 6 CPs) and 4 healthy controls in training cohort were firstly identified. Then, miRNAs differed RPs from CPs were compared in both training and validation cohort.
Project description:Artificial intelligence (AI) applications in biomedical settings face challenges such as data privacy and regulatory compliance. Federated Deep Learning (FDL) effectively addresses these issues. We developed ProCanFDL, where local models were trained on simulated sites using proteomic data drawn from a pan-cancer cohort (n = 1,260) and 29 other cohorts (n = 6,265), representing 4,956 patients and 19,930 mass spectrometry (MS) runs, all held behind private firewalls. Local parameter updates were aggregated to build the global model, achieving a 43% performance gain over local models on the hold-out test set (n = 625) in 14 cancer subtyping tasks. Additionally, ProCanFDL preserved data privacy while matching centralized model performance. External validation assessed generalization by retraining the global model with data from two external cohorts (n = 55) and eight (n = 832) using a different MS technology. ProCanFDL presents a solution for internationally collaborative machine learning initiatives using proteomic data while maintaining data privacy.
Project description:There are currently no screening methods for high grade ovarian cancer (HGOC) that guarantee effective early detection for high risk women such as germline BRCA mutation carriers. Therefore, the standard-of-care remains risk reducing salpingo-oophorectomy (RRSO) around age 40. Proximal liquid biopsy has been shown to be a promising source of biomarkers, but sensitivity has not yet qualified for clinical implementation. We report the discriminant performance of a novel proteomic classifier for detection of HGOC in high-risk population, and the safety and feasibility of simplified utero-tubal lavage (UtL) as a method for sampling proximal liquid biopsy.The training set included 93 women with high-risk for HGOC (BRCA1 and BRCA2 mutation carriers), including: 16 HGOC patients and 77 asymptomatic women, who donated UtL liquid biopsies, in 3 Israeli medical centers (Biomarkers for Early Detection of Ovarian Cancer Using Uterine Lavage (BEDOCA); ClinicalTrials.gov Identifier: NCT03150121). The proteome of the microvesicle fraction of the samples was profiled by mass spectrometry and a classifier was developed using logistic regression. An independent cohort of 104 BRCA mutation carriers was used as validation. Safety information was collected for all women who opted to UtL in a clinic setting.
Project description:The purpose of this study is to identify signaling pathways that are differentially regulated in Hypertrophic Cardiomyopathy (HCM), using proteomic profiling of human myocardium.
Project description:Background: Timely diagnosis is important for successful treatment of cutaneous melanoma. Currently, Breslow tumor thickness and mitotic rate are used for malignant melanoma classification and prognosis, but these parameters can assess disease progression risk only to a certain degree. Therefore, there is a need for new melanoma protein biomarkers that would aid early and accurate diagnosis and prediction of their metastatic potential. Methodology and Findings: This retrospective case control study is based on proteomic profiling of formalin-fixed archival tissues of 31 early-stage head and neck cutaneous malignant melanoma samples using liquid chromatography / mass spectrometry. A melanoma proteomic profile was identified and protein expression levels were compared to the proteome profile of melanocytic naevi and correlated to established prognostic factors and disease-specific survival. In accordance with the American Joint Committee on Cancer guidelines, recursive partitioning multivariate analysis was used to identify potential biomarkers associated with metastatic potential of early-melanoma. Heterogeneous nuclear ribonucleoprotein M and heat shock protein 90 alpha were profiled as independent prognostic factors. Their elevated expression was clinically relevant for predicting an exceedingly high metastatic hazard ratio. These proteins were superior in estimating disease progression risk when compared to Breslow thickness and mitotic rate. Conclusions and Significance: Identification of biomarkers in early stage cutaneous head and neck melanoma is an important step towards predicting metastatic potential and prognosis of the disease. Clinical confirmation and further validation of the proteins identified in this study would provide a novel tool for identifying patients at risk for developing metastatic disease.
Project description:AML is a molecularly heterogenous disease that harbors multiple genomic, epigenomic, and transcriptomic abnormalities. Despite the use of newer therapeutic agents and identification of multiple prognostic markers, most patients with AML still relapse or succumb to their disease. Therefore, understanding biological factors especially at protein level that determine relapse is of major clinical interest in AML. Few studies have examined the global proteome in AML. Therefore, we have developed an integrated approach utilizing mass spectrometry-based proteomics and leveraging next generation RNA sequencing (RNAseq) to identify novel protein biomarkers associated with clinical outcome in a homogeneous population of undifferentiated viable leukemic blasts (uVLBs) from AML patients (Discovery cohort, n=27). Analyses identified 6761 unique proteins, with 238 and 460 proteins significantly associated with complete response (CR) and overall survival (OS), respectively. There was modest overlap between the prognostically significant transcript and protein biomarkers. We also were able to identify and quantify aberrant proteins arising from genomic mutations such as NPM1 and RUNX1. For validation of prognostic associations, TMT-based LC-MS/MS quantified protein expression across pooled patients from an independent patient cohort (validation cohort) and analyses examined the prognostic significance of the 238 proteins from the SWOG analyses associated with CR. Thirteen of the most promising candidates were significantly associated with CR prognosis, many of which are associated with cancer biology. Together, these studies show the feasibility and biological importance of examining the proteome in uVLBs. Studies examining for biomarkers in the proteome may be a powerful tool to uncover novel prognostic biomarkers that would otherwise not be identified by examining the genome or transcriptome. Furthermore, the multi-omics approach can be used to confirm the translation of potential neoantigens into actionable protein targets, which may lead to more cost-effective mechanisms for the development of innovative adoptive immunotherapies.
Project description:Here we describe the development of a robust method for RNA extraction and exome-capture RNA-sequencing of laser-capture microdissected (LCM) tumor cells (TC) and stromal immune cells (TIL) based on their morphology. We applied this method on seven tumor specimens and microbiopsies of triple-negative breast cancers (TNBC) stored in FFPE blocks. Together, we showed that combining LCM and RNA-sequencing on archived FFPE blocks is feasible and allows spatial transcriptional characterization of the tumor microenvironment.
Project description:Tissue biopsies are most commonly archived in a paraffin block following tissue fixation with formaldehyde (FFPE) or as fresh frozen tissue (FFT). While both methods preserve biological samples, little is known about how they affect the quantifiable proteome. We performed a ‘bottom-up’ proteomic analysis (N=20) of short and long-term archived FFPE surgical samples of human meningiomas and compared them to matched FFT specimens. FFT facilitated identification of a slightly higher number of proteins compared with matched FFPE specimens (5735 vs 5670 proteins, respectively (p < 0.05), regardless of archival time. However, marked differences in the proteome composition were apparent between FFPE and FFT specimens. Twenty-three percent of FFPE-derived peptides and 8% of FFT-derived peptides contained at least one chemical modification. Methylation and formylation were most prominent in FFPE-derives peptides (36% and 17% of modified FFPE peptides, respectively) while, most of phosphorylation and iron modifications appeared in FFT-derived peptides (p<0.001). A mean 14% (2.9) of peptides identified in FFPE contained at least one modified Lysine residue. Importantly, larger proteins were significantly overrepresented in FFT specimens, while FFPE specimens were enriched with smaller proteins. This work cautions against comparing results of proteomic studies derived from different archival methods.
Project description:Objectives: Formalin-fixed paraffin-embedded (FFPE) tissue is the standard material for di-agnostic pathology but poses relevant hurdles to accurate protein extraction due to cross-linking and chemical alterations. While numerous extraction pro-tocols and chemicals have been described, systematic comparative analyses are limited. Various parameters were thus investigated in their qualitative and quantitative effects on protein extraction (PE) efficacy. Special emphasis was put on preservation of membrane proteins (MP) as key subgroup of func-tionally relevant proteins. Methods: Using the example of urothelial carcinoma, FFPE tissue sections were subjected to various deparaffinization, protein extraction and antigen retrieval protocols and buffers as well as different extraction techniques. Performance was meas-ured by protein concentration and western blot analysis of cellular compart-ment markers as well as liquid chromatography-coupled mass spectrometry (LC-MS). Results: Commercially available extraction buffers showed reduced extraction of MPs and came at considerably increased costs. On-slide extraction did not improve PE whereas several other preanalytical steps could be simplified. Systematic variation of temperature and exposure duration demonstrated a quantitatively relevant corridor of optimal antigen retrieval. Conclusions: Preanalytical protein extraction can be optimized at various levels to improve unbiased protein extraction and to reduce time and costs.