Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment

POLE mutations in endometrial carcinoma: Clinical and genomic landscape from a large prospective single-center cohort

BACKGROUND

To date, 11 DNA polymerase epsilon (POLE) pathogenic variants have been declared "hotspot" mutations. Patients with endometrial cancer (EC) characterized by POLE hotspot mutations (POLEmut) have exceptional survival outcomes. Whereas international guidelines encourage deescalation of adjuvant treatment in early-stage POLEmut EC, data regarding safety in POLEmut patients with unfavorable characteristics are still under investigation. On the other hand, the spread of comprehensive genome profiling programs has underscored the need to interpret POLE variants not considered to be hotspots.

METHODS

This study provides a comprehensive analysis of 596 sequenced patients with EC. The genomic landscape of POLEmut EC was compared with cases harboring nonhotspot POLE mutations within the exonuclease domain. Additionally, the genomic characteristics of multiple classifiers, as well as those exhibiting unfavorable histopathological and clinical features, were examined.

RESULTS

No significant genomic differences were observed among patients with POLEmut EC when comparing multiple classifiers to not-multiple classifiers or those with unfavorable clinical features. However, the tumor mutational burden differed in both comparisons, whereas the percentage of C>G mutations only differed in the comparison based on clinical features. Specific POLE mutations, even if not considered to be hotspots, have genomic features comparable to POLEmut.

CONCLUSIONS

The present findings confirm the absence of significant genomic differences among POLEmut patients regardless of multiple-classifier status or association with high-risk clinical features. Prognostic data will be essential to elucidate the clinical significance of POLE mutations not classified as hotspots that exhibit genomic characteristics similar to those in POLEmut patients.

Revealing SARS-CoV-2 Mpro mutation cold and hot spots: Dynamic residue network analysis meets machine learning

Deciphering the effect of evolutionary mutations of viruses and predicting future mutations is crucial for designing long-lasting and effective drugs. While understanding the impact of current mutations on protein drug targets is feasible, predicting future mutations due to natural evolution of viruses and environmental pressures remains challenging. Here, we leveraged existing mutation data during the evolution of the SARS-CoV-2 protein drug target main protease (Mpro) to test the predictive power of dynamic residue network (DRN) analysis in identifying mutation cold and hot spots. We conducted molecular dynamics simulations on the Mpro of SARS-CoV-2 (Wuhan strain) and calculated eight DRN metrics (averaged BC, CC, DC, EC, ECC, KC, L, PR), each of which identifies a unique network feature within the protein. The sets of residues with the highest and lowest values for each metric, comprising potential cold and hot spots, were compared to published biochemical analyses and per residue mutation frequencies observed across five SARS-CoV-2 lineages, encompassing a total of 191,878 sequences. Individual DRN metrics displayed only modest power to predict the mutation frequency of individual residues. However, integrating the eight DRN metrics with additional structural and sequence-derived metrics allowed us to develop machine learning models which significantly improved the prediction of residue mutation frequency. While further refinements should enhance accuracy, we demonstrated a robust method to understand pathogen evolution. This approach can also guide the development of long-lasting drugs by targeting functional residues located in and near active site, and allosteric sites, that are less prone to mutations.

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Genomic landscape of early-stage prostate adenocarcinoma in Mexican patients: an exploratory study

BACKGROUND

Health disparities have been highlighted among patient with prostate adenocarcinoma (PRAD) due to ethnicity. Mexican men present a more aggressive disease than other patients resulting in less favorable treatment outcome. We aimed to identify the mutational landscape which could help to reduce the health disparities among minority groups and generate the first genomics exploratory study of PRAD in Mexican patients.

METHODS

Paraffin-embedded formalin-fixed tumoral tissue from 20 Mexican patients with early-stage PRAD treated at The Instituto Nacional de Cancerología, Mexico City from 2017 to 2019 were analyzed. Tumoral DNA was prepared for whole exome sequencing, the resulting files were mapped against h19 using BWA-MEM. Strelka2 and Lancet packages were used to identify single nucleotide variants (SNV) and insertions or deletions. FACETS was used to determine somatic copy number alterations (SCNA). Cancer Genome Interpreter web interface was used to determine the clinical relevance of variants.

RESULTS

Patients were in an early clinical stage and had a mean age of 59.55 years (standard deviation [SD]: 7.1 years) with 90% of them having a Gleason Score of 7. Follow-up time was 48.50 months (SD: 32.77) with recurrences and progression in 30% and 15% of the patients, respectively. NUP98 (20%), CSMD3 (15%) and FAT1 (15%) were the genes most frequently affected by SNV; ARAF (75%) and ZNF419 (70%) were the most frequently affected by losses and gains SNCA's. One quarter of the patients had mutations useful as biomarkers for the use of PARP inhibitors, they comprise mutations in BRCA, RAD54L and ATM. SBS05, DBS03 and ID08 were the most common mutational signatures present in this cohort. No associations with recurrence or progression were identified.

CONCLUSIONS

This pilot study reveals the mutational landscape of early-stage prostate adenocarcinoma in Mexican men, providing a first approach to understand the mutational patterns and actionable mutations in early prostate cancer can inform personalized treatment approaches and reduce the underrepresentation in genomic cancer studies.

Dose-related Mutagenic and Clastogenic Effects of Benzo[b]fluoranthene in Mouse Somatic Tissues Detected by Duplex Sequencing and the Micronucleus Assay

Polycyclic aromatic hydrocarbons (PAHs) are common environmental pollutants that originate from the incomplete combustion of organic materials. We investigated the clastogenicity and mutagenicity of benzo[ b ]fluoranthene (BbF), one of 16 priority PAHs, in MutaMouse males after a 28-day oral exposure. BbF causes robust dose-dependent increases in micronucleus frequency in peripheral blood, indicative of chromosome damage. Duplex Sequencing (DS), an error-corrected sequencing technology, reveals that BbF induces dose-dependent increases in mutation frequencies in bone marrow (BM) and liver. Mutagenicity is increased in intergenic relative to genic regions, suggesting a role for transcription-coupled repair of BbF-induced DNA damage. At higher doses, the maximum mutagenic response to BbF is higher in liver, which has a lower mitotic index but higher metabolic capacity than BM; however, mutagenic potency is comparable between the two tissues. BbF induces primarily C:G>A:T mutations, followed by C:G>T:A and C:G>G:C, indicating that BbF metabolites mainly target guanines and cytosines. The mutation spectrum of BbF correlates with cancer mutational signatures associated with tobacco exposure, supporting its contribution to the carcinogenicity of combustion-derived PAHs in humans. Overall, BbF's mutagenic effects are similar to benzo[ a ]pyrene, a well-studied mutagenic PAH. Our work showcases the utility of DS for effective mutagenicity assessment of environmental pollutants.

Synopsis

We used Duplex Sequencing to study the mutagenicity of benzo[ b ]fluoranthene across the mouse genome. Dose-dependent changes in mutation frequency and spectrum quantify its role in PAH-induced carcinogenicity.

Whole genome and transcriptome integrated analyses guide clinical care of pediatric poor prognosis cancers

The role for routine whole genome and transcriptome analysis (WGTA) for poor prognosis pediatric cancers remains undetermined. Here, we characterize somatic mutations, structural rearrangements, copy number variants, gene expression, immuno-profiles and germline cancer predisposition variants in children and adolescents with relapsed, refractory or poor prognosis malignancies who underwent somatic WGTA and matched germline sequencing. Seventy-nine participants with a median age at enrollment of 8.8 y (range 6 months to 21.2 y) are included. Germline pathogenic/likely pathogenic variants are identified in 12% of participants, of which 60% were not known prior. Therapeutically actionable variants are identified by targeted gene report and whole genome in 32% and 62% of participants, respectively, and increase to 96% after integrating transcriptome analyses. Thirty-two molecularly informed therapies are pursued in 28 participants with 54% achieving a clinical benefit rate; objective response or stable disease ≥6 months. Integrated WGTA identifies therapeutically actionable variants in almost all tumors and are directly translatable to clinical care of children with poor prognosis cancers.

Arsenic is a potent co-mutagen of ultraviolet light

Arsenic enhances the carcinogenicity of ultraviolet radiation (UVR). However, the mechanisms of arsenic-driven oncogenesis are not well understood. Here, we utilize experimental systems to investigate the carcinogenic and mutagenic properties of co-exposure to arsenic and UVR. In vitro and in vivo exposures indicate that, by itself, arsenic is not mutagenic. However, in combination with UVR, arsenic exposure has a synergistic effect leading to an accelerated mouse skin carcinogenesis and to more than 2-fold enrichment of UVR mutational burden. Notably, mutational signature ID13, previously found only in UVR-associated human skin cancers, is observed exclusively in mouse skin tumors and cell lines jointly exposed to arsenic and UVR. This signature was not observed in any model system exposed purely to arsenic or purely to UVR, making ID13, to the best of our knowledge, the first co-exposure signature to be reported using controlled experimental conditions. Analysis of existing skin cancer genomics data reveals that only a subset of cancers harbor ID13 and these exhibit an elevated UVR mutagenesis. Our results report a unique mutational signature caused by a co-exposure to two environmental carcinogens and provide comprehensive evidence that arsenic is a potent co-mutagen and co-carcinogen of UVR.

Base-Excision Repair Mutational Signature in Two Sebaceous Carcinomas of the Eyelid

Personalized medicine aims to develop tailored treatments for individual patients based on specific mutations present in the affected organ. This approach has proven paramount in cancer treatment, as each tumor carries distinct driver mutations that respond to targeted drugs and, in some cases, may confer resistance to other therapies. Particularly for rare conditions, personalized medicine has the potential to revolutionize treatment strategies. Rare cancers often lack extensive datasets of molecular and pathological information, large-scale trials for novel therapies, and established treatment guidelines. Consequently, surgery is frequently the only viable option for many rare tumors, when feasible, as traditional multimodal approaches employed for more common cancers often play a limited role. Sebaceous carcinoma of the eyelid is an exceptionally rare cancer affecting the eye's adnexal tissues, most frequently reported in Asia, but whose prevalence is significantly increasing even in Europe and the US. The sole established curative treatment is surgical excision, which can lead to significant disfigurement. In cases of metastatic sebaceous carcinoma, validated drug options are currently lacking. In this project, we set out to characterize the mutational landscape of two sebaceous carcinomas of the eyelid following surgical excision. Utilizing available bioinformatics tools, we demonstrated our ability to identify common features promptly and accurately in both tumors. These features included a Base-Excision Repair mutational signature, a notably high tumor mutational burden, and key driver mutations in somatic tissues. These findings had not been previously reported in similar studies. This report underscores how, in the case of rare tumors, it is possible to comprehensively characterize the mutational landscape of each individual case, potentially opening doors to targeted therapeutic options.