Prospective Assessment of Fluorine-18-Fluorodeoxyglucose-Positron Emission Tomography/Computed Tomography (FDG-PET/CT) for Early Identification of Checkpoint-Inhibitor-Induced Pseudoprogression.

The activity of immune checkpoint inhibitors (ICIs) in patients with metastatic melanoma is often monitored using fluorine-18-fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) scans. However, distinguishing disease progression (PD) from pseudoprogression (PsPD), where increased FDG uptake might reflect immune cell activity rather than tumor growth, remains a challenge. This prospective study compared the efficacy of dual-time point (DTP) FDG-PET/CT with modified response criteria (PERCIMT) in differentiating PsPD from PD. From July 2017-January 2021, 41 patients suspected to have PsPD on an evaluation scan were prospectively included (29 evaluable). A subsequent DTP FDG-PET/CT scan was conducted within 14 days, followed by a confirmatory FDG-PET/CT scan. Additionally, PERCIMT were applied. DTP FDG-PET/CT identified 24% with PsPD and 76% with PD. Applying PERCIMT criteria, 69% showed PsPD, while 31% had PD. On follow-up, 10 patients (34%) demonstrated confirmed PsPD, while 19 (66%) exhibited PD. The sensitivity and specificity of DTP FDG-PET/CT were 20% and 74%, respectively, and for PERCIMT this was 80% and 37%, respectively. Our findings suggest limited efficacy of DTP FDG-PET/CT in distinguishing PsPD from PD in ICI-treated patients with metastatic melanoma. The use of PERCIMT could complement clinical assessment and be incorporated in multidisciplinary team conferences for enhanced decision-making.

Sequence dependencies and mutation rates of localized mutational processes in cancer.

BACKGROUND: Cancer mutations accumulate through replication errors and DNA damage coupled with incomplete repair. Individual mutational processes often show nucleotide sequence and functional region preferences. As a result, some sequence contexts mutate at much higher rates than others, with additional variation found between functional regions. Mutational hotspots, with recurrent mutations across cancer samples, represent genomic positions with elevated mutation rates, often caused by highly localized mutational processes. METHODS: We count the 11-mer genomic sequences across the genome, and using the PCAWG set of 2583 pan-cancer whole genomes, we associate 11-mers with mutational signatures, hotspots of single nucleotide variants, and specific genomic regions. We evaluate the mutation rates of individual and combined sets of 11-mers and derive mutational sequence motifs. RESULTS: We show that hotspots generally identify highly mutable sequence contexts. Using these, we show that some mutational signatures are enriched in hotspot sequence contexts, corresponding to well-defined sequence preferences for the underlying localized mutational processes. This includes signature 17b (of unknown etiology) and signatures 62 (POLE deficiency), 7a (UV), and 72 (linked to lymphomas). In some cases, the mutation rate and sequence preference increase further when focusing on certain genomic regions, such as signature 62 in transcribed regions, where the mutation rate is increased up to 9-folds over cancer type and mutational signature average. CONCLUSIONS: We summarize our findings in a catalog of localized mutational processes, their sequence preferences, and their estimated mutation rates.

Pan-cancer association of DNA repair deficiencies with whole-genome mutational patterns.

DNA repair deficiencies in cancers may result in characteristic mutational patterns, as exemplified by deficiency of BRCA1/2 and efficacy prediction for PARP inhibitors. We trained and evaluated predictive models for loss-of-function (LOF) of 145 individual DNA damage response genes based on genome-wide mutational patterns, including structural variants, indels, and base-substitution signatures. We identified 24 genes whose deficiency could be predicted with good accuracy, including expected mutational patterns for BRCA1/2, MSH3/6, TP53, and CDK12 LOF variants. CDK12 is associated with tandem duplications, and we here demonstrate that this association can accurately predict gene deficiency in prostate cancers (area under the receiver operator characteristic curve = 0.97). Our novel associations include mono- or biallelic LOF variants of ATRX, IDH1, HERC2, CDKN2A, PTEN, and SMARCA4, and our systematic approach yielded a catalogue of predictive models, which may provide targets for further research and development of treatment, and potentially help guide therapy.

Many different aspects of the environment ­ such as ultraviolet radiation, carcinogens in food and drink, and the ageing process itself ­ damage the DNA in human cells. Normally, cells can repair these sites by activating a mechanism known as the DNA damage response. However, the hundreds of genes that orchestrate this response are also themselves often lost or damaged, allowing the unrepaired sites to turn into permanent mutations that accumulate across the genome of the cancer cell. By studying the DNA of cancer cells, it has been possible to identify characteristic patterns of mutations, called mutational signatures, that appear in different types of cancer. One specific pattern has been linked to the loss of either the BRCA1 or BRCA2 gene, both of which are part of the DNA damage response. However, it remained unclear how many other genes involved in the DNA damage response also lead to detectable mutational signatures when lost. To investigate, Sørensen et al. computationally analysed data from over six thousand cancer patients. They looked for associations between over 700 DNA damage response genes and 80 different mutational signatures. As expected, the analysis revealed a strong connection between the loss of BRCA1/BRCA2 and their known mutational signature. However, it also found 23 other associations between DNA damage response genes that had been lost or damaged and particular patterns of mutations in a variety of cancers. These findings suggest that mutational signatures could be used more widely to predict which DNA damage response genes are no longer functioning in the genome of cancer cells. The mutational signature caused by the loss of BRAC1/BRAC2 has been shown to make patients more responsive to a certain type of chemotherapy. Further experiments are needed to determine whether the connections identified by Sørensen et al. could also provide information on which treatment would benefit a cancer patient the most. In the future, this might help medical practitioners provide more personalized treatment.