Is precision medicine the solution to improve organ preservation in laryngeal/hypopharyngeal cancer? A position paper by the Preserve Research Group.

In locally advanced (LA) laryngeal/hypopharyngeal squamous cell carcinoma (LHSCC), larynx preservation (LP) strategies aim at the cure of the disease while preserving a functional larynx, thus avoiding total laryngectomy and the associated impact on the quality of life. In the last decades, apart from transoral and open-neck organ preservation approaches, several non-surgical regimens have been investigated: radiotherapy alone, alternate, concurrent or sequential chemoradiation, and bioradiotherapy. Despite major progress, the identification of reliable and effective predictors for treatment response remains a clinical challenge. This review examines the current state of LP in LA-LHSCC and the need for predictive factors, highlighting the importance of the PRESERVE trial in addressing this gap. The PRESERVE trial represents a pivotal initiative aimed at finding the optimal therapy for laryngeal preservation specific to each patient through a retrospective analysis of data from previous LP trials and prospectively validating findings. The goal of the PRESERVE trial is to develop a comprehensive predictive classifier that integrates clinical, molecular, and multi-omics data, thereby enhancing the precision and efficacy of patient selection for LP protocols.

Chromosomal instability and a deregulated cell cycle are intrinsic features of high-risk gastrointestinal stromal tumours with a metastatic potential.

Patients with localised, high-risk gastrointestinal stromal tumours (GIST) benefit from adjuvant imatinib treatment. Still, approximately 40% of patients relapse within 3 years after adjuvant therapy and the clinical and histopathological features currently used for risk classification cannot precisely predict poor outcomes after standard treatment. This study aimed to identify genomic and transcriptomic profiles that could be associated with disease relapse and thus a more aggressive phenotype. Using a multi-omics approach, we analysed a cohort of primary tumours from patients with untreated, resectable high-risk GISTs. We compared patients who developed metastatic disease within 3 years after finishing adjuvant imatinib treatment and patients without disease relapse after more than 5 years of follow-up. Combining genomics and transcriptomics data, we identified somatic mutations and deregulated mRNA and miRNA genes intrinsic to each group. Our study shows that increased chromosomal instability (CIN), including chromothripsis and deregulated kinetochore and cell cycle signalling, separates high-risk samples according to metastatic potential. The increased CIN seems to be an intrinsic feature for tumours that metastasise and should be further validated as a novel prognostic biomarker for high-risk GIST.

NucBreak: location of structural errors in a genome assembly by using paired-end Illumina reads.

BACKGROUND: Advances in whole genome sequencing strategies have provided the opportunity for genomic and comparative genomic analysis of a vast variety of organisms. The analysis results are highly dependent on the quality of the genome assemblies used. Assessment of the assembly accuracy may significantly increase the reliability of the analysis results and is therefore of great importance. RESULTS: Here, we present a new tool called NucBreak aimed at localizing structural errors in assemblies, including insertions, deletions, duplications, inversions, and different inter- and intra-chromosomal rearrangements. The approach taken by existing alternative tools is based on analysing reads that do not map properly to the assembly, for instance discordantly mapped reads, soft-clipped reads and singletons. NucBreak uses an entirely different and unique method to localise the errors. It is based on analysing the alignments of reads that are properly mapped to an assembly and exploit information about the alternative read alignments. It does not annotate detected errors. We have compared NucBreak with other existing assembly accuracy assessment tools, namely Pilon, REAPR, and FRCbam as well as with several structural variant detection tools, including BreakDancer, Lumpy, and Wham, by using both simulated and real datasets. CONCLUSIONS: The benchmarking results have shown that NucBreak in general predicts assembly errors of different types and sizes with relatively high sensitivity and with lower false discovery rate than the other tools. Such a balance between sensitivity and false discovery rate makes NucBreak a good alternative to the existing assembly accuracy assessment tools and SV detection tools. NucBreak is freely available at https://github.com/uio-bmi/NucBreak under the MPL license.

NucDiff: in-depth characterization and annotation of differences between two sets of DNA sequences.

BACKGROUND: Comparing sets of sequences is a situation frequently encountered in bioinformatics, examples being comparing an assembly to a reference genome, or two genomes to each other. The purpose of the comparison is usually to find where the two sets differ, e.g. to find where a subsequence is repeated or deleted, or where insertions have been introduced. Such comparisons can be done using whole-genome alignments. Several tools for making such alignments exist, but none of them 1) provides detailed information about the types and locations of all differences between the two sets of sequences, 2) enables visualisation of alignment results at different levels of detail, and 3) carefully takes genomic repeats into consideration. RESULTS: We here present NucDiff, a tool aimed at locating and categorizing differences between two sets of closely related DNA sequences. NucDiff is able to deal with very fragmented genomes, repeated sequences, and various local differences and structural rearrangements. NucDiff determines differences by a rigorous analysis of alignment results obtained by the NUCmer, delta-filter and show-snps programs in the MUMmer sequence alignment package. All differences found are categorized according to a carefully defined classification scheme covering all possible differences between two sequences. Information about the differences is made available as GFF3 files, thus enabling visualisation using genome browsers as well as usage of the results as a component in an analysis pipeline. NucDiff was tested with varying parameters for the alignment step and compared with existing alternatives, called QUAST and dnadiff. CONCLUSIONS: We have developed a whole genome alignment difference classification scheme together with the program NucDiff for finding such differences. The proposed classification scheme is comprehensive and can be used by other tools. NucDiff performs comparably to QUAST and dnadiff but gives much more detailed results that can easily be visualized. NucDiff is freely available on https://github.com/uio-cels/NucDiff under the MPL license.