Decoding circulating tumor DNA to identify durable benefit from immunotherapy in lung cancer

Donker, Hylke C.; Schuuring, Ed; Heitzer, Ellen; Groen, Harry J.M.

doi:10.1016/j.lungcan.2022.05.013

Cited by 3 publications

(3 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…S4 ). With an estimated patients with DB 29 as our classification probability threshold, a sensitivity of 0.56 , a specificity of 0.86 , and an accuracy of 0.74 was achieved (Table 2 ) with 8 false positive and 16 false negative classifications (Supplementary Table 3 ). The classifier was not perfectly calibrated (Fig.…”

Section: Resultsmentioning

confidence: 99%

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

Donker

Tamminga

et al. 2023

Sci Rep

View full text Add to dashboard Cite

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 $$m=101$$ m = 101 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$$_{-0.17}^{+0.28}$$ - 0.17 + 0.28 on the cross-validated discovery set and 0.24$$_{-0.14}^{+0.31}$$ - 0.14 + 0.31 on an independent external validation set ($$m=56$$ m = 56 ). 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.

show abstract

Section: Resultsmentioning

confidence: 99%

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

Donker

Tamminga

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…S5). With an estimated 43.8% patients with DB [31] as our classification probability threshold, a sensitivity of , a specificity of , and an accuracy of was achieved (Table 2) with 8 false positive and 16 false negative classifications (Supplementary Table 3). The classifier was not perfectly calibrated (Fig.…”

Section: Resultsmentioning

confidence: 99%

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

Donker¹,

Es²,

Tamminga³

et al. 2022

Preprint

View full text Add to dashboard Cite

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 using mutational signatures from DNA mutations in pre-treatment tissue. Analysis of single base substitutions, doublet base substitutions, indels, and copy number alteration signatures in the discovery set (m=101 patients) linked tobacco smoking signature (SBS4) and thiopurine chemotherapy exposure-associated signature (SBS87) to durable benefit. Combining both signatures in a machine learning model separated patients with a progression free survival hazard ratio of 0.40-0.17+0.28 on the cross validated discovery set and 0.24-0.14+0.31 on an independent external validation set (m=56). This paper demonstrates that the fingerprints of mutagenesis, codified through mutational signatures, can be used to select advanced NSCLC patients who may benefit from immunotherapy, thus reducing unnecessary patient burden.

show abstract

“…Different advantages and disadvantages are related to either a tumor-agnostic or tumor-informed strategy and the optimal strategy has not yet been defined ( 53 ). A recent published study with pooled data from five different immunotherapy-treated NSCLC cohorts ( n = 365), proposed a predictive model of durable response, consisting of seven of the most predictive genes ( 54 ).…”

Section: Discussionmentioning

confidence: 99%

Circulating Tumor DNA Monitoring Reveals Molecular Progression before Radiologic Progression in a Real-life Cohort of Patients with Advanced Non–small Cell Lung Cancer

Frank

Andersen

Ahlborn

et al. 2022

Cancer Research Communications

View full text Add to dashboard Cite

Purpose The clinical potential of liquid biopsy in advanced cancer patients is real-time monitoring for early detection of treatment failure. Our study aimed to investigate the clinical validity of circulating tumor DNA (ctDNA) treatment monitoring in a real-life cohort of advanced Non-Small Cell Lung Cancer (NSCLC) patients. Patients and Methods Advanced or non-curative locally advanced NSCLC patients were prospectively included in an exploratory study (NCT03512847). Selected cancer-specific mutations were measured in plasma by standard or uniquely designed digital droplet PCR (ddPCR) assays before every treatment-cycle during first line treatment until progressive disease (PD). Correlation between an increase in ctDNA (=molecular progression) and radiologic PD was investigated, defined as lead time, and the corresponding numbers of likely futile treatment cycles were determined. Utility of ctDNA measurements in clarifying the results of non-conclusive radiologic evaluation scans was evaluated. Results Cancer-specific mutations and longitudinal plasma sampling were present in 132 of 150 patients. CtDNA was detectable in 88 (67%) of 132 patients treated by respectively chemotherapy (n=41), immunotherapy (n=43), or combination-treatment (n=4). In 66 (90%) of 73 patients experiencing PD, a ctDNA increase was observed with a median lead time of 1.5 months before radiologic PD. Overall, 119 (33%) of 365 treatment-cycles were administered after molecular progression. Additionally, ctDNA measurements could clarify the results in 38 (79%) of 48 non-conclusive radiologic evaluations. Conclusions ctDNA monitoring leads to earlier detection of treatment failure, and clarifies the majority of non-conclusive radiologic evaluations, giving the potential of sparing patients from likely futile treatments and needless adverse events.

show abstract

Decoding circulating tumor DNA to identify durable benefit from immunotherapy in lung cancer

Cited by 3 publications

References 26 publications

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

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

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

Circulating Tumor DNA Monitoring Reveals Molecular Progression before Radiologic Progression in a Real-life Cohort of Patients with Advanced Non–small Cell Lung Cancer

Contact Info

Product

Resources

About