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.

Systemic alterations in neutrophils and their precursors in early-stage chronic obstructive pulmonary disease

Systemic inflammation is established as part of late-stage severe lung disease, but molecular, functional, and phenotypic changes in peripheral immune cells in early disease stages remain ill defined. Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small-airway inflammation, emphysema, and severe breathing difficulties. Using single-cell analyses we demonstrate that blood neutrophils are already increased in early-stage COPD, and changes in molecular and functional neutrophil states correlate with lung function decline. Assessing neutrophils and their bone marrow precursors in a murine cigarette smoke exposure model identified similar molecular changes in blood neutrophils and precursor populations that also occur in the blood and lung. Our study shows that systemic molecular alterations in neutrophils and their precursors are part of early-stage COPD, a finding to be further explored for potential therapeutic targets and biomarkers for early diagnosis and patient stratification.

Using genomic scars to select immunotherapy beneficiaries in advanced non-small cell lung cancer

In advanced non-small cell lung cancer (NSCLC), response to immunotherapy is difficult to predict from pre-treatment information. Given the toxicity of immunotherapy and its financial burden on the healthcare system, we set out to identify patients for whom treatment is effective. To this end, we used mutational signatures from DNA mutations in pre-treatment tissue. Single base substitutions, doublet base substitutions, indels, and copy number alteration signatures were analysed in [Formula: see text] patients (the discovery set). We found that tobacco smoking signature (SBS4) and thiopurine chemotherapy exposure-associated signature (SBS87) were linked to durable benefit. Combining both signatures in a machine learning model separated patients with a progression-free survival hazard ratio of 0.40[Formula: see text] on the cross-validated discovery set and 0.24[Formula: see text] on an independent external validation set ([Formula: see text]). This paper demonstrates that the fingerprints of mutagenesis, codified through mutational signatures, select advanced NSCLC patients who may benefit from immunotherapy, thus potentially reducing unnecessary patient burden.

Multi-source data approach for personalized outcome prediction in lung cancer screening: update from the NELSON trial

Trials show that low-dose computed tomography (CT) lung cancer screening in long-term (ex-)smokers reduces lung cancer mortality. However, many individuals were exposed to unnecessary diagnostic procedures. This project aims to improve the efficiency of lung cancer screening by identifying high-risk participants, and improving risk discrimination for nodules. This study is an extension of the Dutch-Belgian Randomized Lung Cancer Screening Trial, with a focus on personalized outcome prediction (NELSON-POP). New data will be added on genetics, air pollution, malignancy risk for lung nodules, and CT biomarkers beyond lung nodules (emphysema, coronary calcification, bone density, vertebral height and body composition). The roles of polygenic risk scores and air pollution in screen-detected lung cancer diagnosis and survival will be established. The association between the AI-based nodule malignancy score and lung cancer will be evaluated at baseline and incident screening rounds. The association of chest CT imaging biomarkers with outcomes will be established. Based on these results, multisource prediction models for pre-screening and post-baseline-screening participant selection and nodule management will be developed. The new models will be externally validated. We hypothesize that we can identify 15-20% participants with low-risk of lung cancer or short life expectancy and thus prevent ~140,000 Dutch individuals from being screened unnecessarily. We hypothesize that our models will improve the specificity of nodule management by 10% without loss of sensitivity as compared to assessment of nodule size/growth alone, and reduce unnecessary work-up by 40-50%.

Dynamic Changes of Circulating Tumor DNA Predict Clinical Outcome in Patients With Advanced Non-Small-Cell Lung Cancer Treated With Immune Checkpoint Inhibitors

PURPOSE

Immune checkpoint inhibitors (ICIs) are increasingly being used in non-small-cell lung cancer (NSCLC), yet biomarkers predicting their benefit are lacking. We evaluated if on-treatment changes of circulating tumor DNA (ctDNA) from ICI start (t₀) to after two cycles (t₁) assessed with a commercial panel could identify patients with NSCLC who would benefit from ICI.

PATIENTS AND METHODS

The molecular ctDNA response was evaluated as a predictor of radiographic tumor response and long-term survival benefit of ICI. To maximize the yield of ctDNA detection, de novo mutation calling was performed. Furthermore, the impact of clonal hematopoiesis (CH)-related variants as a source of biologic noise was investigated.

RESULTS

After correction for CH-related variants, which were detected in 75 patients (44.9%), ctDNA was detected in 152 of 167 (91.0%) patients. We observed only a fair agreement of the molecular and radiographic response, which was even more impaired by the inclusion of CH-related variants. After exclusion of those, a ≥ 50% molecular response improved progression-free survival (10 v 2 months; hazard ratio [HR], 0.55; 95% CI, 0.39 to 0.77; P = .0011) and overall survival (18.4 v 5.9 months; HR, 0.44; 95% CI, 0.31 to 0.62; P < .0001) compared with patients not achieving this end point. After adjusting for clinical variables, ctDNA response and STK11/KEAP1 mutations (HR, 2.08; 95% CI, 1.4 to 3.0; P < .001) remained independent predictors for overall survival, irrespective of programmed death ligand-1 expression. A landmark survival analysis at 2 months (n = 129) provided similar results.

CONCLUSION

On-treatment changes of ctDNA in plasma reveal predictive information for long-term clinical benefit in ICI-treated patients with NSCLC. A broader NSCLC patient coverage through de novo mutation calling and the use of a variant call set excluding CH-related variants improved the classification of molecular responders, but had no significant impact on survival.

Cell water balance of white button mushrooms (Agaricus bisporus) during its post-harvest lifetime studied by quantitative magnetic resonance imaging

A combination of quantitative water density and T2 MRI and changes therein observed after infiltration with 'invisible' Gd-DTPA solution was used to study cell water balances, cell water potentials and cell integrity. This method was applied to reveal the evolution and mechanism of redistribution of water in harvested mushrooms. Even when mushrooms did not lose water during the storage period, a redistribution of water was observed from stipe to cap and gills. When the storage condition resulted in a net loss of water, the stipe lost more water than the cap. The water density in the gill increased, probably due to development of spores. Deterioration effects (i.e. leakage of cells, decrease in osmotic water potential) were found in the outer stipe. They were not found in the cap, even at prolonged storage at 293 K and R.H.=70%. The changes in osmotic potential were partly accounted for by changes in the mannitol concentration. Changes in membrane permeability were also indicated. Cells in the cap had a constant low membrane (water) permeability. They developed a decreasing osmotic potential (more negative), whereas the osmotic potential in the outer stipe increased, together with the permeability of cells.

Quantitative 1H-NMR imaging of water in white button mushrooms (Agaricus bisporus)

MRI represents a valuable tool for studying the amount and physical status of water in plants and agricultural products, for example, mushrooms (Agaricus bisporus). Contrast in NMR images originates from the mixed influence of the fundamental NMR parameters, amongst others, spin-density, T2- and T1 relaxation processes. Maps of these parameters contain valuable anatomical and physiological information. They can, however, be severely distorted, depending on the combination of parameter settings and anatomy of the object under study. The influence of the tissue structure of mushrooms, for example, tissue density (susceptibility inhomogeneity) and cell shape on the amplitude, T2, and T1 images is analyzed. This is achieved by vacuum infiltration of the cavities in the mushroom's spongy structure with Gd-DTPA solutions and acquiring Saturation Recovery-Multispin Echo images. It is demonstrated that the intrinsic long T2 values in the cap and outer stipe tissue strongly relate to the size and geometry of the highly vacuolated cells in these spongy tissues. All observed T2 values are strongly affected by susceptibility effects. The T2 of gill tissue is shorter than T2 of the cap and outer stipe, probably because these cells are less vacuolized and smaller in size. The calculated amplitude images are not directly influenced by susceptibility inhomogeneities as long as the observed relaxation times remained sufficient long. They reflect the water distribution in mushrooms best if short echo times are applied in a multispin echo imaging sequence at low magnetic field strength.

NMR imaging of white button mushroom (Agaricus bisporis) at various magnetic fields

Nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) have been applied to visualize physiological phenomena in plants and agricultural crops. Imaging sequences that result in contrast of a combination of parameters (e.g., proton density, T1, T2, T2*) cannot be used for a correct and unique interpretation of the results. In this study multiecho imaging together with monoexponential T2 decay fitting was applied to determine reliable proton density and T2 distributions over a mushroom. This was done at three magnetic field strengths (9.4, 4.7, and 0.47 T) because susceptibility inhomogeneities were suspected to influence the T2 relaxation times negatively, and because the influences of susceptibility inhomogeneities increase with a rise in magnetic field strength. Electron microscopy was used to understand the different T2's for the various tissue types in mushrooms. Large influences of the tissue ultrastructure on the observed T2 relaxation times were found and explained. Based on the results, it is concluded that imaging mushrooms at low fields (around or below 0.47 T) and short echo times has strong advantages over its high-field counterpart, especially with respect to quantitative imaging of the water balance of mushrooms. These conclusions indicate general validity whenever NMR imaging contrast is influenced by susceptibility inhomogeneities.