Dataset Information

Identification of drug- resistance mutations in majority and minority subpopulations of HIV-1 quasispecies

ABSTRACT: The response of human immunodeficiency virus type 1 (HIV-1) quasispecies to antiretroviral therapy is influenced by the ensemble of mutants that composes the evolving population. Low-abundance subpopulations within HIV-1 quasispecies may determine the viral response to the administered drug combinations. However, routine sequencing assays available to clinical laboratories do not recognize HIV-1 minority variants representing less than 25% of the population. Although several alternative and more sensitive genotyping techniques have been developed, including next-generation sequencing (NGS) methods, they are usually very time consuming, expensive and require highly trained personnel, thus becoming unrealistic approaches in daily clinical practice. Here we describe the development and testing of a HIV-1 genotyping DNA microarray that detects and quantifies, in majority and minority viral subpopulations, relevant mutations and amino acid insertions in 42 codons of the pol gene associated with resistance and multidrug resistance to protease (PR) and reverse transcriptase (RT) inhibitors. A customized bioinformatics protocol has been implemented to analyze the microarray hybridization data by including a new normalization procedure and a stepwise filtering algorithm which resulted in the highly accurate (96.33%) detection of positive/negative signals. This microarray has been tested with 57 subtype B HIV-1 clinical samples extracted from multi-treated patients, showing an overall identification of 95.53% and 89.24% of the queried PR and RT codons, respectively, and enough sensitivity to detect minority subpopulations representing as low as 5-10% of the total quasispecies. Such a genotyping platform represents an efficient diagnostic and prognostic tool useful to personalize antiviral treatments in clinical practice.

ORGANISM(S): Simian-Human immunodeficiency virus

PROVIDER: GSE90621 | GEO | 2016/11/30

SECONDARY ACCESSION(S): PRJNA355237

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: Colorectal cancer is the third most common and the fourth most lethal cancer in the world. In the majority of cases, patients are diagnosed at an advanced stage or even metastatic, thus explaining the high mortality. The standard protocol for treating patients with locally advanced non-metastatic colorectal cancer (CRC) is neoadjuvant radio-chemotherapy (NRCT) with 5-fluorouracil (5-FU), but the resistance rate to this treatment remains high with approximately 30% of non-responders. The lack of evidence available in clinical practice to predict NRCT resistance to 5-FU and to guide clinical practice therefore encourages the search for biomarkers of this resistance. Methods: From twenty-three formalin-fixed paraffin-embedded (FFPE) biopsies performed before NRCT with 5-FU of locally advanced non-metastatic CRC patients, we extracted and analysed the tumor proteome of these patients. From clinical data, we were able to classify the twenty-two patients in our cohort into three treatment response groups: non-responders (NR), partial responders (PR) and total responders (TR), and to compare the proteomes of these different groups. Results: We have highlighted 384 differentially expressed proteins between NR and PR, 248 between NR and TR and 417 between PR and TR. Among these proteins, we have identified many differentially expressed proteins identified as having a role in cancer (IFIT1, FASTKD2, PIP4K2B, ARID1B, SLC25A33: overexpressed in TR; CALD1, CPA3, B3GALT5, CD177, RIPK1: overexpressed in NR). We have also identified that DPYD, the main degradation enzyme of 5-FU, was overexpressed in NR, as well as several ribosomal and mitochondrial proteins also overexpressed in NR. Conclusions: From these retrospective study, we implemented a protein extraction protocol from FFPE biopsy to highlight protein differences between different response groups to RCTN with 5-FU in patients with locally advanced non-metastatic CRC. These results will pave the way for a larger cohort for better sensitivity and specificity of the signature to guide decisions in the choice of treatment.

Project description:BACKGROUND: Combination antiretroviral therapy (cART) is able to control HIV-1 viral replication, however long-lived latent infection in resting memory CD4+ T-cells persist. The mechanisms for establishment and maintenance of latent infection in resting memory CD4+ T-cells remain unclear. Previously we have shown that HIV-1 infection of resting CD4+ T-cells co-cultured with CD11c+ myeloid dendritic cells (mDC) produced a population of non-proliferating T-cells with latent infection. Here we asked whether different antigen presenting cells (APC), including subpopulations of DC and monocytes, were able to induce post-integration latent infection in resting CD4+ T-cells, and examined potential cell interactions that may be involved using RNA-seq. RESULTS: mDC (CD1c+), SLAN+ DC and CD14+ monocytes were most efficient in stimulating proliferation of CD4+ T-cells during syngeneic culture and in generating post-integration latent infection in non-proliferating CD4+ T-cells following HIV-1 infection of APC-T-cell co-cultures. In comparison, plasmacytoid DC (pDC) and B-cells did not induce latent infection in APC-T-cell co-cultures. We compared the RNA expression profiles of APC subpopulations that could and could not induce latency in non-proliferating CD4+ T-cells. Gene expression analysis, comparing the mDC, SLAN+ DC and CD14+ monocyte subpopulations to pDC identified 53 upregulated genes that encode proteins expressed on the plasma membrane that could signal to CD4+ T-cells via cell-cell interactions (32 genes), immune checkpoints (IC) (5 genes), T-cell activation (9 genes), regulation of apoptosis (5 genes), antigen presentation (1 gene) and through unknown ligands (1 gene). CONCLUSIONS: APC subpopulations from the myeloid lineage, specifically mDC subpopulations and CD14+ monocytes, were able to efficiently induce post-integration HIV-1 latency in non-proliferating CD4+ T-cells in vitro. Inhibition of key pathways involved in mDC-T-cell interactions and HIV-1 latency may provide novel targets to eliminate HIV latency. mRNA profiles of sorted, pure antigen presenting cells including, CD1c+ myleoid dendirtic cells (mDC), SLAN+ mDC, CD14+ monocytes and plasmacytoid DC (pDC), were generated using next generation sequencing in triplicate, using Illumina Illumina Hiseq 2000.

Dataset Information

Identification of drug- resistance mutations in majority and minority subpopulations of HIV-1 quasispecies

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets