Reliability of panel-based mutational signatures for immune-checkpoint-inhibition efficacy prediction in non-small cell lung cancer

OBJECTIVES: Mutational signatures (MS) are gaining traction for deriving therapeutic insights for immune checkpoint inhibition (ICI). We asked if MS attributions from comprehensive targeted sequencing assays are reliable enough for predicting ICI efficacy in non-small cell lung cancer (NSCLC).METHODS: Somatic mutations of m = 126 patients were assayed using panel-based sequencing of 523 cancer-related genes. In silico simulations of MS attributions for various panels were performed on a separate dataset of m = 101 whole genome sequenced patients. Non-synonymous mutations were deconvoluted using COSMIC v3.3 signatures and used to test a previously published machine learning classifier.RESULTS: The ICI efficacy predictor performed poorly with an accuracy of 0.51 -0.09 +0.09, average precision of 0.52 -0.11 +0.11, and an area under the receiver operating characteristic curve of 0.50 -0.09 +0.10. Theoretical arguments, experimental data, and in silico simulations pointed to false negative rates (FNR) related to panel size. A secondary effect was observed, where deconvolution of small ensembles of point mutations lead to reconstruction errors and misattributions. CONCLUSION: MS attributions from current targeted panel sequencing are not reliable enough to predict ICI efficacy. We suggest that, for downstream classification tasks in NSCLC, signature attributions be based on whole exome or genome sequencing instead.</p

Asthma and COPD in cystic fibrosis intron-8 5T carriers. A population-based study

BACKGROUND: Carriers of cystic fibrosis intron-8 5T alleles with high exon-9 skipping could have increased annual lung function decline and increased risk for asthma or chronic obstructive pulmonary disease (COPD). METHODS: We genotyped 9131 individuals from the adult Danish population for cystic fibrosis 5T, 7T, 9T, and F508del alleles, and examined associations between 11 different genotype combinations, and annual FEV(1 )decline and risk of asthma or COPD. RESULTS: 5T heterozygotes vs. 7T homozygous controls had no increase in annual FEV(1 )decline, self-reported asthma, spirometry-defined COPD, or incidence of hospitalization from asthma or COPD. In 5T/7T heterozygotes vs. 7T homozygous controls we had 90% power to detect an increase in FEV(1 )decline of 8 ml, an odds ratio for self-reported asthma and spirometry-defined COPD of 1.9 and 1.7, and a hazard ratio for asthma and COPD hospitalization of 1.8 and 1.6, respectively. Both 5T homozygotes identified in the study showed evidence of asthma, while none of four 5T/F508del compound heterozygotes had severe pulmonary disease. 7T/9T individuals had annual decline in FEV(1 )of 19 ml compared with 21 ml in 7T homozygous controls (t-test:P = 0.03). 6.7% of 7T homozygotes without an F508del allele in the cystic fibrosis transmembrane conductance regulator gene reported asthma vs. 11% of 7T/9T individuals with an F508del allele (χ(2):P = 0.01) and 40% of 7T homozygotes with an F508del allele (P = 0.04). 7T homozygotes with vs. without an F508del allele also had higher incidence of asthma hospitalization (log-rank:P = 0.003); unadjusted and adjusted equivalent hazard ratios for asthma hospitalization were 11 (95%CI:1.5–78) and 6.3 (0.84–47) in 7T homozygotes with vs. without an F508del allele. CONCLUSION: Polythymidine 5T heterozygosity is not associated with pulmonary dysfunction or disease in the adult Caucasian population. Furthermore, our results support that F508del heterozygosity is associated with increased asthma risk independently of the 5T allele

Haplotype block structure study of the CFTR gene. Most variants are associated with the M470 allele in several European populations

An average of about 1700 CFTR (cystic fibrosis transmembrane conductance regulator) alleles from normal individuals from different European populations were extensively screened for DNA sequence variation. A total of 80 variants were observed: 61 coding SNSs (results already published), 13 noncoding SNSs, three STRs, two short deletions, and one nucleotide insertion. Eight DNA variants were classified as non-CF causing due to their high frequency of occurrence. Through this survey the CFTR has become the most exhaustively studied gene for its coding sequence variability and, though to a lesser extent, for its noncoding sequence variability as well. Interestingly, most variation was associated with the M470 allele, while the V470 allele showed an 'extended haplotype homozygosity' (EHH). These findings make us suggest a role for selection acting either on the M470V itself or through an hitchhiking mechanism involving a second site. The possible ancient origin of the V allele in an 'out of Africa' time frame is discussed

Consensus on the use and interpretation of cystic fibrosis mutation analysis in clinical practice

It is often challenging for the clinician interested in cystic fibrosis (CF) to interpret molecular genetic results, and to integrate them in the diagnostic process. The limitations of genotyping technology, the choice of mutations to be tested, and the clinical context in which the test is administered can all influence how genetic information is interpreted. This paper describes the conclusions of a consensus conference to address the use and interpretation of CF mutation analysis in clinical settings

High Accuracy Mutation Detection in Leukemia on a Selected Panel of Cancer Genes

<div><p>With the advent of whole-genome and whole-exome sequencing, high-quality catalogs of recurrently mutated cancer genes are becoming available for many cancer types. Increasing access to sequencing technology, including bench-top sequencers, provide the opportunity to re-sequence a limited set of cancer genes across a patient cohort with limited processing time. Here, we re-sequenced a set of cancer genes in T-cell acute lymphoblastic leukemia (T-ALL) using Nimblegen sequence capture coupled with Roche/454 technology. First, we investigated how a maximal sensitivity and specificity of mutation detection can be achieved through a benchmark study. We tested nine combinations of different mapping and variant-calling methods, varied the variant calling parameters, and compared the predicted mutations with a large independent validation set obtained by capillary re-sequencing. We found that the combination of two mapping algorithms, namely <em>BWA-SW</em> and <em>SSAHA2</em>, coupled with the variant calling algorithm <em>Atlas-SNP2</em> yields the highest sensitivity (95%) and the highest specificity (93%). Next, we applied this analysis pipeline to identify mutations in a set of 58 cancer genes, in a panel of 18 T-ALL cell lines and 15 T-ALL patient samples. We confirmed mutations in known T-ALL drivers, including PHF6, NF1, FBXW7, NOTCH1, KRAS, NRAS, PIK3CA, and PTEN. Interestingly, we also found mutations in several cancer genes that had not been linked to T-ALL before, including JAK3. Finally, we re-sequenced a small set of 39 candidate genes and identified recurrent mutations in TET1, SPRY3 and SPRY4. In conclusion, we established an optimized analysis pipeline for Roche/454 data that can be applied to accurately detect gene mutations in cancer, which led to the identification of several new candidate T-ALL driver mutations.</p> </div

Identification of novel potential therapeutic targets in uterine sarcomas - From human sample analysis to preclinical validation

Uterine sarcomas account for only 3-4% of all uterine corpus malignancies, nevertheless they entail a high mortality rate due to their clinical aggressiveness and limited response to current treatments. All uterine sarcoma patients are first treated by complete surgical resection, whenever possible (hysterectomy, often associated with bilateral salpingo-oophorectomy). However, recurrence rates are high in most subtypes even after complete resection, underscoring the need for more effective therapies. Leiomyosarcoma (LMS) is the most frequently diagnosed and a very aggressive subtype (60% of all uterine sarcomas), followed by the less aggressive low-grade endometrial stromal sarcomas (LGESS; 20%). The remaining 20% of uterine sarcomas comprises high-grade ESS (HGESS), undifferentiated uterine sarcomas (UUS) and adenosarcomas (AS). Overall, the effect of available treatments for uterine sarcoma patients is limited and associated with substantial toxicity. Setting up clinical trials is challenging, especially for small patient groups, emphasizing the role of pre-clinical models in optimizing treatment regimens and biomarker identification, which will ideally lead to robust and reliable patient stratification criteria. The lack of effective treatment strategies and the poor prognosis for uterine sarcoma patients underscore the need for prognostic markers and for personalized, new therapeutic approaches. The final aims of this PhD project are to identify prognostic biomarkers and novel therapeutic options for uterine sarcoma patients. To this end, the following research objectives are pursued: 1) Identification of potential therapeutic targets and prognostic markers in uterine sarcomas, by: a) immunohistochemistry (IHC) screening of therapeutic targets for which targeted therapies are available, in a large sample set including all subtypes; b) integration of commonly detected alterations identified from next-generation sequencing (NGS) methods in uterine leiomyosarcomas; 2) Establishment and validation of patient-derived in vitro and in vivo uterine sarcoma models; 3) In vitro and/or in vivo pre-clinical validation of targets identified by the IHC screen and/or NGS integration.status: publishe