LAUSR

Background: It has been recognized that gut microbiome has impact on the cancer immunotherapy efficacy and Cancer Microbiome-Immune Axis is reported. Also, it is important to discover and identify clinically translatable predictive biomarker in gut microbiome to inform the treatment selections. Multiple pre-analytical and analytical steps & factors including the sample collection, DNA extraction, library preparation, sequencing and bioinformatics analysis are associated with the microbiome data interpretation as well as its potential clinical application. 16S amplicon-sequencing coupled with bioinformatics approach for advance analysis provides end-to-end solution. It is therefore essential to develop a clinical-grade assay for targeting & characterization of taxa at genus and species level microbes in stool samples, which is designed as two-phase approach: firstly, identification the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary bioinformatics solution; secondly, exploratory analysis of patient samples. Methods: Healthy stool samples (n = 30, gender ratio 1:1, 10 from US west coast, 10 from US mid-west, 10 from US east coast) were extracted across extraction kits (kit A, B and C). Following isolation, bacterial 16S rRNA amplicons were generated and sequenced using a 2 × 300 bp paired-end configuration on the Illumina MiSeq. FASTQ files were analyzed using the Sigma-Aldrich® M-CAMPTM web platform1. Results: We previously compared 5 kits using ATCC® microbiome standards (MSA 2002 and MSA 2003). Kit A, B & C were identified as high yield DNA with the similar relative abundance of microbial family. In current study, we performed the taxonomical classification, diversity analysis and comparative analysis of 16S amplicon-seq using 30 healthy stool samples. The beta diversity showed all 3 kits clustered closely together which indicated the relative abundance of microbial families were similar across the extraction kits. The Weighted Unifrac showed significant difference among the kits (P = 0.046). Kit C species abundance is significantly difference than that of Kit A & Kit B (Pairwise Permanova P = 0.027 (Kit A vs C); P = 0.017 (Kit B vs C); P = 0.991 (Kit A vs B)). Relative frequency-based group-sample level composition at phylum and species level show high level similarity. Conclusion: The comprehensive qualification approaches including the analytically optimized extraction condition and post-analytically implement the bioinformatics solution assures the characterization of microbiota for enabling biomarker driven precision oncology. Analytical performance assessment using colorectal cancer patients’ samples is ongoing for further exploring its potential clinical utilities. Citation Format: Danyi Wang, Brajendra Kumar, Aaron Tenney, Ravi Kiron, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng. Characterizing and developing the clinical grade next generation sequencing based gut microbiome assay with the bioinformatics solution. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4704.