Mutant-allele fraction heterogeneity is associated with non-small cell lung cancer patient survival

Mutant-allele dispersion correlates with prognosis risk in patients with advanced non-small cell lung cancer

BACKGROUND

Intra-tumor heterogeneity (ITH) contributes to lung cancer progression and resistance to therapy. To evaluate ITH and determine whether it may be employed as a predictive biomarker of prognosis in patients with advanced non-small cell lung cancer (NSCLC), we used a novel algorithm called mutant-allele dispersion (MAD).

METHODS

In the study, 103 patients with advanced NSCLC were enrolled. Using a panel of 425 cancer-related genes, next-generation sequencing (NGS) was performed on tumor specimens that had been collected. From NGS data, we derived MAD values, and we next looked into their relationships with clinical variables and different mutation subtypes.

RESULTS

The median MAD among 103 NSCLC patients was 0.73. EGFR mutation, tyrosine kinase inhibitor (TKI) therapy, radiotherapy, and chemotherapy cycles were all substantially correlated with the MAD score. In patients with lung adenocarcinoma (LUAD), correlation analysis revealed that the MAD score was substantially linked with Notch pathway mutation (P = 0.021). A significant relationship between high MAD and shorter progression-free survival (PFS) was found (HR = 2.004, 95%CI 1.269-3.163, P = 0.003). In patients with advanced NSCLC, histological type (P = 0.004), SMARCA4 mutation (P = 0.038), and LRP1B mutation (P = 0.006) were all independently associated with prognosis. The disease control rate was considerably greater in the low MAD group compared to the high MAD group in 19 LUAD patients receiving immunotherapy (92.9% vs. 40%, P = 0.037). TKI-PFS was longer in 37 patients with low MAD who received first-line TKI therapy (P = 0.014).

CONCLUSION

Our findings suggested that MAD is a practical and simple algorithm for assessing ITH, and populations with high MAD values are more likely to have EGFR mutations. MAD can be used as a potential biomarker to predict not only the prognosis of NSCLC but also the efficacy of immunotherapy and TKI therapy in patients with advanced NSCLC.

Molecular characterization of advanced non-small cell lung cancer patients by cfDNA analysis: experience from routine laboratory practice

BACKGROUND

Analysis of circulating free DNA (cfDNA) by the real-time PCR cobas® EGFR Mutation Test v2 (cobas® EGFR Test) is a diagnostic approach used in clinical practice for the characterization of advanced non-small cell lung cancer (NSCLC) patients. The test additionally outputs a semiquantitative index (SQI) which reflects the proportion of mutated versus wild-type copies of the EGFR gene in cfDNA with potential use as a biomarker. CfDNA concentration and cfDNA fragmentation pattern have also shown potential utility as biomarkers for cancer patients. We evaluated the implementation of EGFR testing and cfDNA related parameters in NSCLC patients in routine clinical setting as biomarkers for disease stage and diagnosis.

METHODS

A prospective cohort of 173 locally advanced or metastatic NSCLC TKI-naïve patients analyzed by the cobas® EGFR Test were included in the study. Reproducibility of the test was assessed in 56 patients. The concentration of cfDNA and fragment size pattern was measured using fluorometry and microchip electrophoresis respectively.

RESULTS

The test showed high diagnostic accuracy when compared to the gold standard of biopsy tumor tissue testing. The SQI value showed a moderate reproducibility (r2=0.70) and did not correlate with cfDNA concentration (r2=0.17, P=0.28) or disease stage (stage III patients SQI =9.1±3.1 and stage IV patients SQI =11.5±4.8, P=0.41). We found differences in SQI values according to the type of EGFR mutation (Ex19Del mutations, SQI =13.6; p.L858R, SQI =8.88; P=0.001). Stage IV patients had higher concentrations of cfDNA (P<0.0001) and higher fractions of cfDNA 100-250 base pairs (bp) fragments (P=0.01) compared to stage III patients. From the ROC curve analysis, cfDNA concentration showed higher AUC compared to cfDNA 100-250 bp fragments (0.86 vs. 0.71). We obtained a cut-off value for cfDNA concentration of 20.3 ng/mL with 72.3% sensitivity and 95% specificity for predicting disease stage in TKI-naïve advanced NSCLC patients.

CONCLUSIONS

The study indicates that cfDNA analysis in plasma for EGFR testing by RT-PCR is an accurate and fast method to initially stratify NSCLC patients in a real-world clinical setting. However, the SQI has limited clinical value. The cfDNA concentration and fragmentation pattern have clear potential clinical utility for tumor staging in NSCLC patients.

Detection of the EGFR G719S Mutation in Non-small Cell Lung Cancer Using Droplet Digital PCR

Objectives: The main objectives of the study were (1) to set-up a droplet digital PCR (ddPCR) assay for the non-invasive detection of G719S EGFR mutation in NSCLC patients; (2) to determine the limits of detection of the ddPCR assay for G719S mutation and (3) to compare COBAS® and ddPCR System for G719S quantification in plasma.

Materials and Methods: Blood samples were collected from 22 patients diagnosed with advanced NSCLC. Then, plasma ctDNA was extracted with the Qiagen Circulating Nucleic Acids kit and quantified by QuantiFluor® dsDNA System. The mutational study of EGFR was carried out by digital droplet PCR (ddPCR) with the QX200 Droplet Digital PCR System with specific probes and primers.

Results: We observed the lowest percentage of G719S mutant allele could be detected in a wildtype background was 0.058%. In the specificity analysis, low levels of G719S mutation were detected in healthy volunteers with a peak of 21.65 mutant copies per milliliter of plasma and 6.35 MAFs. In those patients whose tissue biopsy was positive for G719S mutation, mutant alleles could also be detected in plasma using both ddPCR and COBAS® System. Finally, when mutational status was studied using both genotyping techniques, higher mutant copies/ml and higher mutant allele fraction (MAF) correlated with higher Semiquantitative Index obtained by COBAS®.

Conclusions: Although tissue biopsies cannot be replaced due to the large amount of information they provide regarding tumor type and structure, liquid biopsy and ddPCR represents a new promising strategy for genetic analysis of tumors from plasma samples. In the present study, G719S mutation was detected in a highly sensitive manner, allowing its monitorization with a non-invasive technique.

Targeted Next-Generation Sequencing Validates the Use of Diagnostic Biopsies as a Suitable Alternative to Resection Material for Mutation Screening in Colorectal Cancer

BACKGROUND

Mutation testing in the context of neoadjuvant therapy must be performed on biopsy samples. Given the issue of tumour heterogeneity, this raises the question of whether the biopsies are representative of the whole tumour. Here we have compared the mutation profiles of colorectal biopsies with their matched resection specimens.

METHODS

We performed next-generation sequencing (NGS) analysis on 25 paired formalin-fixed, paraffin-embedded colorectal cancer biopsy and primary resection samples. DNA was extracted and analysed using the TruSight tumour kit, allowing the interrogation of 26 cancer driver genes. Samples were run on an Illumina MiSeq. Mutations were validated using quick-multiplex-consensus (QMC)-polymerase chain reaction (PCR) in conjunction with high resolution melting (HRM). The paired biopsy and resection tumour samples were assessed for presence or absence of mutations, mutant allele frequency ratios, and allelic imbalance status.

RESULTS

A total of 81 mutations were detected, in ten of the 26 genes in the TruSight kit. Two of the 25 paired cases were wild-type across all genes. The mutational profiles, allelic imbalance status, and mutant allele frequency ratios of the paired biopsy and resection samples were highly concordant (88.75-98.85%), with all but three (3.7%) of the mutations identified in the resection specimens also being present in the biopsy specimens. All 81 mutations were confirmed by QMC-PCR and HRM analysis, although four low-level mutations required a co-amplification at lower denaturation temperature (COLD)-PCR protocol to enrich for the mutant alleles.

CONCLUSIONS

Diagnostic biopsies are adequate and reliable materials for molecular testing by NGS. The use of biopsies for molecular screening will enhance targeted neoadjuvant therapy.

Novel prognostic molecular markers in lung cancer

Lung carcinoma, especially in its most commonly diagnosed non-small cell histological form, is a challenge to diagnose and treat worldwide, due to the prognosis in patients with this type of cancer being poor and mortality rates being high. However, a number of patients with this type of lung carcinoma exhibit a longer than average overall survival. The specific molecular background of non-small-cell lung cancer that favors longer survival has not yet been determined. The aim of the current study was to review articles published in the years 2017-2018 and create a list of the most important and strongest non-conventional factors that could be used in the future assessment of the prognosis of patients with adenocarcinoma and squamous cell carcinoma of the lung who cannot undergo current targeted therapy. Analysis identified multiple prognostic factors in non-small cell lung carcinoma, including tumor mutational burden, which was revealed to be independent of the tumor stage or grade as well as other factors, including age, sex or targeted therapy effects. The selected molecular factors exhibit the potential to be used in the treatment of patients with specific problematic lung cancer, and may contribute to setting recommendations for the diagnosis, prognosis and treatment of individual patients with lung cancer.

Mutant-allele tumor heterogeneity in malignant glioma effectively predicts neoplastic recurrence

Intra-tumor heterogeneity (ITH) is one of the most important causes of therapy resistance, which eventually leads to the poor outcomes observed in patients with glioma. Mutant-allele tumor heterogeneity (MATH) values are based on whole-exon sequencing and precisely reflect genetic ITH. However, the significance of MATH values in predicting glioma recurrence remains unclear. Information of patients with glioma was obtained from The Cancer Genome Atlas database. The present study calculated the MATH value for each patient, analyzed the distributions of MATH values in different subtypes and investigated the rates of clinical recurrence in patients with different MATH values. Gene enrichment and Cox regression analyses were performed to determine which factors influenced recurrence. A nomogram table was established to predict 1-, 2- and 5-year recurrence probabilities. MATH values were increased in patients with glioma with the wild-type isocitrate dehydrogenase (NADP⁽⁺⁾) (IDH)1/2 (IDH-wt) gene (P=0.001) and glioblastoma (GBM; P=0.001). MATH values were negatively associated with the 2- and 5-year recurrence-free survival (RFS) rates in patients with glioma, particularly in the IDH1/2-wt and GBM cohorts (P=0.001 and P=0.017, respectively). Furthermore, glioma cases with different MATH levels had distinct patterns of gene mutation frequencies and gene expression enrichment. Finally, a nomogram table that contained MATH values could be used to accurately predict the probabilities of the 1-, 2- and 5-year RFS of patients with glioma. In conclusion, the MATH value of a patient may be an independent predictor that influences glioma recurrence. The nomogram model presented in the current study was an appropriate method to predict 1-, 2- and 5-year RFS probabilities in patients with glioma.

Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening

Lung cancer shows substantial genetic and phenotypic heterogeneity across individuals, driving a need for personalised medicine. Here, we report lung cancer organoids and normal bronchial organoids established from patient tissues comprising five histological subtypes of lung cancer and non-neoplastic bronchial mucosa as in vitro models representing individual patient. The lung cancer organoids recapitulate the tissue architecture of the primary lung tumours and maintain the genomic alterations of the original tumours during long-term expansion in vitro. The normal bronchial organoids maintain cellular components of normal bronchial mucosa. Lung cancer organoids respond to drugs based on their genomic alterations: a BRCA2-mutant organoid to olaparib, an EGFR-mutant organoid to erlotinib, and an EGFR-mutant/MET-amplified organoid to crizotinib. Considering the short length of time from organoid establishment to drug testing, our newly developed model may prove useful for predicting patient-specific drug responses through in vitro patient-specific drug trials.

Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures

Human cancers accumulate various mutations during development and consist of highly heterogeneous cell populations. This phenomenon is called intratumor heterogeneity (ITH). ITH is known to be involved in tumor growth, progression, invasion, and metastasis, presenting obstacles to accurate diagnoses and effective treatments. Numerous studies have explored the dynamics of ITH, including constructions of phylogenetic trees in cancer samples using multiregional ultradeep sequencing and simulations of evolution using statistical models. Although ITH is associated with prognosis, it is still challenging to use the characteristics of ITH as prognostic factors because of difficulties in quantifying ITH precisely. In this study, we analyzed the relationship between patient prognosis and the distribution of variant allele frequencies (VAFs) in cancer samples (n = 6,064) across 16 cancer types registered in The Cancer Genome Atlas. To measure VAF distributions multidimensionally, we adopted parameters that define the shape of VAF distributions and evaluated the relationships between these parameters and prognosis. In seven cancer types, we found significant relationships between prognosis and VAF distributions. Moreover, we observed that samples with a larger amount of mutations were not necessarily linked to worse prognosis. By evaluating the ITH from multidimensional viewpoints, it will be possible to provide a more accurate prediction of cancer prognosis.