Bioinformatics pipeline development for analyses of data generated by target capture-based Next-Generation Sequencing, to characterise mutations and the utility of using off-target sequences to detect genomic imbalances in Multiple Myeloma patients.

Greater Multiple Myeloma (MM) genomics understanding is required to improve patient care and outcomes, currently limited by available methods, especially regarding structural variant (SV)/copy number alteration (CNA) detection. This study aimed to exemplify target-capture Next-Generation Sequencing data utility in bioinformatics-mediated sequence variant/SV/CNA detection, using a 1,138-gene cancer gene panel (CGP)/Immunoglobulin Heavy Locus (IGH) tiling array on paired germline/peripheral blood and tumour/bone marrow samples from sixMM patients (aka MM1-MM6). All quality metrics confirmed successful sequencing, genomic alignment and enrichment, corroborating sufficiency for downstream analyses. Germline/tumour batch effects were identified from insert-size, coverage, and enrichment data. Systematic literature reviewal elucidated 105-MM-associated genes recurrently targeted in MM patients, in which MM1-MM6 sequence variant annotation/filtering extracted 86- high/moderate effect impact MM-associated variants, with 34/86 most likely MMrelevant/interesting (e.g., previously reported variants, known disease-causing mutations, tumour suppressors with two-hits, recurrently targeted genes, clinically-associated genes, all with MM-relevant pathogenic mechanisms). Congruent with typical MM sequencing observations, high-interest somatic variant allele frequencies of ~15-20%, estimated MM1- MM6 tumour purities at 30-40%. IGH-associated SV analyses failed MM1/MM4 t(11;14)/positive-control detection, subsequently explained by bait/coverage visualisations showing baits/reads only spanning large exons, incapable of capturing split reads in intronic breakpoint regions. Proof-of-principle off-target coverage analyses utilising Acute Myeloid Leukaemia (AML) gene panel data successfully identified +8/positive control, sex chromosome differences, and a previously unknown AML-relevant distal +8q amplification. Using an average normal karyotype reference achieved higher autosomal CNA acuity over single reference samples. Adapted to MM1-MM6 CGP data, all tumour-germline comparisons had extensive background noise preventing autosomal CNA inference, both with single/multiple average sample references. However, individual tumour-tumour comparisons were successful in detecting sex chromosome differences (I.e., MM1/MM3-MM5=XY, MM2/MM6=XX) and autosomal CNAs in MM3/MM5 (I.e. MM3=+1q/positive-control, del(6q), del(13q; MM5=+1q, +6p, del(6q), del(8p), +9, del(14q)), +18 centromere, +19q)). Many of these are recurrent MM-associated CNAs conferring diagnostic/prognostic-relevance. All variants/CNAs identified need future validation, and although some interesting gene/SV patterns emerge, six patients are too small to conclude significant MM signatures/associations. Study findings significantly contributed towards advancing MM genomics understanding, and future study method application may facilitate more streamlined, routine and detailed MM genomics analyses, likely improving MM diagnoses, prognoses, management, and treatment.

Name thesis:degree_name

PhD

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Biomedical Sciences

Grantor dc:publisher

ResearchSpace@Auckland

Year dc:date.issued

2023

Author dc:creator

• Coysh, Alix

Advisor dc:contributor.advisor

• Bohlander, Stefan

Statement dc:rights

• Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Licence dc:rights.uri

• https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm

Handle dc:identifier.uri

https://hdl.handle.net/2292/66404

OAI identifier oai:identifier

oai:researchspace.auckland.ac.nz:2292/66404