Dataset Information

Microbial Product Cocktails for Personalized Cancer Immunotherapy

ABSTRACT:

The human immune system has evolved to interact with various commensal and pathogenic bacteria in intricate and nuanced ways. While the diversity of bacteria presents fundamental challenges in understanding immune-microbe interactions, it also offers ample opportunities for developing effective immunomodulatory therapies. We introduce microbial product cocktails as a novel class of immunotherapy for cancer. Using freshly resected tumors from bladder cancer patients, an immuno-comparative analysis of recruitment and enhancement assay, and an AI-guided optimization workflow, we established a personalized platform for identifying potent MPCs that promote recruitment, infiltration, and activation of immune cells for cancer treatment. In an orthotopic mouse bladder cancer model, MPCs demonstrated immunoenhancement and improved survival rates compared with standard bacillus Calmette–Guérin immunotherapy.

INSTRUMENT(S): Liquid Chromatography MS - negative - reverse phase, Liquid Chromatography MS - positive - reverse phase

PROVIDER: MTBLS12666 | MetaboLights | 2025-07-01

REPOSITORIES: MetaboLights

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	a_MTBLS12666_LC-MS_negative_reverse-phase_metabolite_profiling.txt	Txt
	a_MTBLS12666_LC-MS_positive_reverse-phase_metabolite_profiling.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS12666_LC-MS_negative_reverse-phase_metabolite_profiling_v2_maf.tsv	Tabular
	m_MTBLS12666_LC-MS_positive_reverse-phase_metabolite_profiling_v2_maf.tsv	Tabular

Items per page:

1 - 5 of 6

Similar Datasets

Project description:Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus Calmetteâ??GuÃ©rin (BCG) Immunotherapy in Primary pT1 Bladder Cancers Intravesical BCG immunotherapy is effective in prevention of recurrence and progression in many cases of non-muscle invasive bladder cancer, but many patients fail to respond. This study identified predictive gene signatures in primary pT1 bladder cancer with BCG immunotherapy. Fourty-Eight patients with primary pT1 bladder cancer treated with BCG immunotherapy were used. Microarray gene expression analysis of the 48 primary bladder cancers was carried out. Predictive gene signatures were individually selected based on the recurrence and progression status. Among 43,148 unique genes, 424 and 287 candidate predictive genes that could predict recurrence and progression, respectively, were selected. Time to recurrence or progression was shorter for patients with poor-predictive gene signatures than good-predictive gene signatures (log-rank test, p <0.001, respectively). Validation of predictive gene signatures with RT-PCR was nearly identical to those of microarray (log-rank test, p <0.05, respectively). In multivariate regression analysis, predictive gene signatures were the only independent predictors of recurrence (HR 3.38, p = 0.048) or progression (HR 10.49, p = 0.048) in validation cohorts. Predictive gene signatures have strong diagnostic value for determining the response to intravesical BCG immunotherapy in primary pT1 bladder cancer. Keywords: Gene expression, Bladder cancer, BCG Total RNA, extracted from the fresh frozen tissues of 48 pT1 bladder cancers, was isolated by TRIzol reagent (Life Technologies, NY, USA), according to the manufacturer's protocol. The quality and integrity of the RNA were confirmed by agarose gel electrophoresis and ethidium bromide staining, followed by visual examination under ultraviolet light. Five-hundred nanograms of total RNA were used for labeling hybridization according to the manufacturerâ??s protocol (Illumina HumanWG-6 BeadChip, version 2, Illumina, Inc., San Diego, CA, USA). Arrays were scanned with an Illumina Bead Array Reader confocal scanner (BeadStation 500GXDW; Illumina, Inc.) according to the manufacturer's instructions. Initial microarray gene expression data were obtained using Bead Studio software with gene expression analysis module (version 3.1.3, Illumina, Inc.).

Dataset Information

Microbial Product Cocktails for Personalized Cancer Immunotherapy

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets