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Bastian, B. C.

Publications and source records attributed to Bastian, B. C..

9 recordsLinked to original sources

WRN deficiency generates oncogenic rearrangements at TA-rich tandem repeats

Werner syndrome, a premature-aging disorder caused by inherited loss of the WRN helicase, predisposes to a narrow set of cancers, including melanoma and sarcoma, through mechanisms that have been unclear. WRN resolves the secondary structures that TA-dinucleotide repeats form, a role established for the expanded repeats of mismatch-repair-deficient cancers. We show that WRN loss also destabilizes native, unexpanded TA-rich tandem repeats, which become fragile sites where chromosomes break and rearrange. In melanoma these rearrangements recurrently produce an identical 15.7Mb-long deletion that transcriptionally activates TERT, the earliest driver of these tumors, and separately disrupt tumor suppressors such as CDKN2A/B and NF1. The same class of rearrangement occurs in WRN-deficient cancers of other types. WRN deficiency is thus a source of instability at TA-rich tandem repeats that generates oncogenic rearrangements.

cancer biology↗

Genetic evolution of keratinocytes to cutaneous squamous cell carcinoma

We performed multi-omic profiling of epidermal keratinocytes, precancerous actinic keratoses, and squamous cell carcinomas to understand the molecular transitions during skin carcinogenesis. Single-cell mutational analyses of normal skin cells showed that most keratinocytes have remarkably low mutation burdens, despite decades of sun exposure, however keratinocytes with TP53 or NOTCH1 mutations had substantially higher mutation burdens. These observations suggest that wild-type keratinocytes (i.e. without pathogenic mutations) are able to withstand high dosages of cumulative UV radiation, but certain pathogenic mutations break these adaptive mechanisms, priming keratinocytes for transformation by increasing their mutation rate. Mutational profiling of squamous cell carcinomas adjacent to actinic keratoses revealed TERT promoter and CDKN2A mutations emerging in actinic keratoses, whereas additional mutations inactivating ARID2 and activating the MAPK-pathway delineated the transition to squamous cell carcinomas. Surprisingly, actinic keratoses were often not related to their neighboring squamous cell carcinoma, indicating that collisions of unrelated neoplasms are common in the skin. Spatial variation in gene expression patterns was common in both tumor and immune cells, with high expression of checkpoint molecules at the invasive front of tumors. In conclusion, this study catalogues the key events during the evolution of cutaneous squamous cell carcinoma.

genomics↗

The genetic evolution of acral melanoma

Acral melanoma is an aggressive type of melanoma with unknown origins, arising on the sole, palm, or nail apparatus. It is the most common type of melanoma in individuals with dark skin and is notoriously challenging to treat. Our study examined exome sequencing data from 139 tissue samples, spanning different progression stages, collected from 37 patients. We found that 78.4% of the melanomas displayed one or more clustered copy number transitions with focal amplifications, recurring predominantly on chromosomes 5, 11, 12, and 22. These genomic "hailstorms" were typically shared across all progression stages within individual patients. Genetic alterations known to activate TERT also arose early. By contrast, mutations in the MAP- kinase pathway appeared later during progression, often leading to different tumor areas harboring non-overlapping driver mutations. We conclude that the evolutionary trajectories of acral melanomas substantially diverge from those of melanomas on sun-exposed skin, where MAP-kinase pathway activation initiates the neoplastic cascade followed by immortalization later. The punctuated formation of hailstorms, paired with early TERT activation, suggests a unique mutational mechanism underlying the origins of acral melanoma. Our findings highlight an essential role for telomerase, likely in re-stabilizing tumor genomes after hailstorms have initiated the tumors. The marked genetic heterogeneity, in particular of MAP-kinase pathway drivers, may partly explain the limited success of targeted and other therapies in treating this melanoma subtype.

cancer biology↗

Distinct senescence mechanisms restrain progression of dysplastic nevi

TERT promoter mutations (TPMs) are frequently found in different cancer types, including approximately 70% of sun-exposed skin melanomas. In melanoma, TPMs are among the earliest mutations and can be present during the transition from nevus to melanoma. However, the specific factors that contribute to the selection of TPMs in certain nevi subsets are not well understood. To investigate this, we analyzed a group of dysplastic nevi (DN) by sequencing genes commonly mutated in melanocytic neoplasms. We examined the relationship between the identified mutations, patient age, telomere length, histological features, and the expression of p16. Our findings reveal that TPMs are more prevalent in DN from older patients and are associated with shorter telomeres. Importantly, these TPMs were not found in nevi with BRAF V600E mutations. Conversely, DN with BRAF V600E mutations were observed in younger patients, had longer telomeres, and a higher proportion of p16-positive cells. This suggests that these nevi arrest growth independently of telomere shortening through a mechanism known as oncogene-induced senescence (OIS). These characteristics extend to melanoma sequencing data sets, where melanomas with BRAF V600E mutations were more likely to have CDKN2A inactivation, overriding OIS. In contrast, melanomas without BRAF V600E mutations showed a higher frequency of TPMs. Our data imply that TPMs are selected to bypass replicative senescence (RS) in cells that were not arrested by OIS. Overall, our results indicate that a subset of melanocytic neoplasms face constraints from RS, while others encounter OIS and RS. The order in which these barriers are overcome during progression to melanoma depends on the mutational context.

cancer biology↗

Visualizing somatic alterations in spatial transcriptomics data of skin cancer

Tools to visualize genetic alterations within tissues remain underdeveloped despite the growth of spatial transcriptomic technologies, which measure gene expression in different regions of tissues. Since genetic alterations can be detected in RNA-sequencing data, we explored the feasibility of observing somatic alterations in spatial transcriptomics data. Extracting genetic information from spatial transcriptomic data would illuminate the spatial distribution of clones and allow for correlations with regional changes in gene expression to support genotype-phenotype studies. Recent work demonstrates that copy number alterations can be inferred from spatial transcriptomics data1. Here, we describe new software to further enhance the inference of copy number from spatial transcriptomics data. Moreover, we demonstrate that single nucleotide variants are also detectable in spatial transcriptomic data. We applied these approaches to map the location of point mutations, copy number alterations, and allelic imbalances in spatial transcriptomic data of two cutaneous squamous cell carcinomas. We show that both tumors are dominated by a single clone of cells, suggesting that their regional variations in gene expression2 are likely driven by non-genetic factors. Furthermore, we observe mutant cells in histologically normal tissue surrounding one tumor, which were not discernible upon histopathologic evaluation. Finally, we detected mono-allelic expression of immunoglobulin heavy chains in B-cells, revealing clonal populations of plasma cells surrounding one tumor. In summary, we put forward solutions to add the genetic dimension to spatial transcriptomic datasets, augmenting the potential of this new technology.

genomics↗

The genomic landscapes of individual melanocytes from human skin

Every cell in the human body has a unique set of somatic mutations, yet it remains difficult to comprehensively genotype an individual cell. Here, we developed solutions to overcome this obstacle in the context of normal human skin, thus offering the first glimpse into the genomic landscapes of individual melanocytes from human skin. We comprehensively genotyped 133 melanocytes from 19 sites across 6 donors. As expected, sun-shielded melanocytes had fewer mutations than sun-exposed melanocytes. However, within sun-exposed sites, melanocytes on chronically sun-exposed skin (e.g. the face) displayed a lower mutation burden than melanocytes on intermittently sun-exposed skin (e.g. the back). Melanocytes located adjacent to a skin cancer had higher mutation burdens than melanocytes from donors without skin cancer, implying that the mutation burden of normal skin can be harnessed to measure cumulative sun damage and skin cancer risk. Moreover, melanocytes from healthy skin commonly harbor pathogenic mutations, likely explaining the origins of the melanomas that arise in the absence of a pre-existing nevus. Phylogenetic analyses identified groups of related melanocytes, suggesting that melanocytes spread throughout skin as fields of clonally related cells, invisible to the naked eye. Overall, our study offers an unprecedented view into the genomic landscapes of individual melanocytes, revealing key insights into the causes and origins of melanoma.

genomics↗

A machine-learning classifier trained with microRNA ratios to distinguish melanomas from nevi

The use of microRNAs as biomarkers has been proposed for many diseases including the diagnosis of melanoma. Although hundreds of microRNAs have been identified as differentially expressed in melanomas as compared to benign melanocytic lesions, limited consensus has been achieved across studies, constraining the effective use of these potentially useful markers. In this study we quantified microRNAs by next-generation sequencing from melanomas and their adjacent benign precursor nevi. We applied a machine learning-based pipeline to identify a microRNA signature that separated melanomas from nevi and was unaffected by confounding variables, such as patient age and tumor cell content. By employing the ratios of microRNAs that were either enriched or depleted in melanoma compared to nevi as a normalization strategy, the classifier performed similarly across multiple published microRNA datasets, obtained by microarray, small RNA sequencing, or RT-qPCR. Validation on separate cohorts of melanomas and nevi correctly classified lesions with 83% sensitivity and 71-83% specificity, independent of variation in tumor cell content of the sample or patient age.

cancer biology↗

Co-occurring genetic alterations in the RAS pathway promote resistance to MET inhibitor treatment in non-small cell lung cancer with a MET exon 14 skipping mutation

PURPOSEWhile patients with advanced-stage non-small cell lung cancers (NSCLCs) harboring MET exon 14 skipping mutations (METex14) often benefit from MET tyrosine kinase inhibitor (TKI) treatment, clinical benefit is limited by primary and acquired drug resistance. The molecular basis for this resistance remains incompletely understood.\n\nMETHODSTargeted sequencing analysis was performed on cell-free circulating tumor DNA obtained from 289 patients with advanced-stage METex14-mutated NSCLC.\n\nRESULTSProminent co-occurring RAS-MAPK pathway gene alterations (e.g. in KRAS, NF1) were detected in NSCLCs with METex14 skipping alterations as compared to EGFR-mutated NSCLCs. There was an association between decreased MET TKI treatment response and RAS-MAPK pathway co-occurring alterations. In a preclinical model expressing a canonical METex14 mutation, KRAS overexpression or NF1 downregulation hyperactivated MAPK signaling to promote MET TKI resistance. This resistance was overcome by co-treatment with crizotinib and the MEK inhibitor trametinib.\n\nCONCLUSIONOur study provides a genomic landscape of co-occurring alterations in advanced-stage METex14-mutated NSCLC and suggests a potential combination therapy strategy targeting MAPK pathway signaling to enhance clinical outcomes.

cancer biology↗

Novel computational method for predicting polytherapy switching strategies to overcome tumor heterogeneity and evolution

1The success of targeted cancer therapy is limited by drug resistance that can result from tumor genetic heterogeneity. The current approach to address resistance typically involves initiating a new treatment after clinical/radiographic disease progression, ultimately resulting in futility in most patients. Towards a potential alternative solution, we developed a novel computational framework that uses human cancer profiling data to systematically identify dynamic, pre-emptive, and sometimes non-intuitive treatment strategies that can better control tumors in real-time. By studying lung adenocarcinoma clinical specimens and preclinical models, our computational analyses revealed that the best anti-cancer strategies addressed existing resistant subpopulations as they emerged dynamically during treatment. In some cases, the best computed treatment strategy used unconventional therapy switching while the bulk tumor was responding, a prediction we confirmed in vitro. The new framework presented here could guide the principled implementation of dynamic molecular monitoring and treatment strategies to improve cancer control.

cancer biology↗