Multiplex Detection of Clinically Relevant Mutations in Liquid Biopsies of Cancer Patients Using a Hybridization-Based Platform

Identification of DNA variants at ultra-low variant allele frequencies via Taq polymerase cleavage of wild-specific blockers

Detecting mutations related to tumors holds immense clinical significance for cancer diagnosis and treatment. However, the presence of highly redundant wild DNA poses a challenge for the advancement of low-copy mutant ctDNA genotyping in cancer cases. To address this, a Taqman qPCR strategy to identify rare mutations at low variant allele fractions (VAFs) has been developed. This strategy combines mutant-specific primers with wild-specific blockers. Diverging from other blocker-mediated PCRs, which rely on primer-induced strand displacement or the use of modified oligos resistant to Taq polymerase, our innovation is built upon the cleavage of specific blockers by Taq polymerase. Given its unique design, which does not hinge on strand displacement or base modification, we refer to this novel method as unmodified-blocker cleavage PCR (UBC-PCR). Multiple experiments consistently confirmed that variant distinction was improved significantly by introduction of 5' unmatched blockers into the reaction. Moreover, UBC-PCR successfully detected mutant DNA at VAFs as low as 0.01% across six different variant contexts. Multiplex UBC-PCR was also performed to identify a reference target and three mutations with a sensitivity of 0.01% VAFs in one single tube. In profiling the gene status from 12 lung cancer ctDNA samples and 22 thyroid cancer FNA DNA samples, UBC-PCR exhibited a 100% concordance rate with ddPCR and a commercial ARMS kit, respectively. Our work demonstrates that UBC-PCR can identify low-abundance variants with high sensitivity in multiplex reactions, independent of strand displacement and base modification. This strategy holds the potential to significantly impact clinical practice and precision medicine.

Gene expression signatures in conjunctival fornix aspirates of patients with dry eye disease associated with Meibomian gland dysfunction. A proof-of-concept study

BACKGROUND

Meibomian gland dysfunction (MGD) is one of the most common conditions in ophthalmic practice and the most frequent cause of evaporative dry eye disease (DED). However, the immune mechanisms leading to this pathology are not fully understood and the diagnostic tests available are limited. Here, we used the nCounter technology to analyze immune gene expression in DED-MGD that can be used for developing diagnostic signatures for DED.

METHODS

Conjunctival cell samples were obtained by aspiration from patients with DED-MGD (n = 27) and asymptomatic controls (n = 22). RNA was purified, converted to cDNA, preamplified and analyzed using the Gene Expression Human Immune V2 panel (NanoString), which includes 579 target and 15 housekeeping genes. A machine learning (ML) algorithm was applied to design a signature associated with DED-MGD.

RESULTS

Forty-five immune genes were found upregulated in DED-MGD vs. controls, involved in eight signaling pathways, IFN I/II, MHC class I/II, immunometabolism, B cell receptor, T Cell receptor, and T helper-17 (Th-17) differentiation. Additionally, statistically significant correlations were found between 31 genes and clinical characteristics of the disease such as lid margin or tear osmolarity (Pearson's r < 0.05). ML analysis using a recursive feature elimination (RFE) algorithm selected a 4-gene mRNA signature that discriminated DED-MGD from control samples with an area under the ROC curve (AUC ROC) of 0.86 and an accuracy of 77.5%.

CONCLUSIONS

Multiplexed mRNA analysis of conjunctival cells can be used to analyze immune gene expression patterns in patients with DED-MGD and to generate diagnostic signatures.

Detecting ALK, ROS1, and RET fusions and the METΔex14 splicing variant in liquid biopsies of non-small-cell lung cancer patients using RNA-based techniques

ALK, ROS1, and RET fusions and MET∆ex14 variant associate with response to targeted therapies in non-small-cell lung cancer (NSCLC). Technologies for fusion testing in tissue must be adapted to liquid biopsies, which are often the only material available. In this study, circulating-free RNA (cfRNA) and extracellular vesicle RNA (EV-RNA) were purified from liquid biopsies. Fusion and MET∆ex14 transcripts were analyzed by nCounter (Nanostring) and digital PCR (dPCR) using the QuantStudio® System (Applied Biosystems). We found that nCounter detected ALK, ROS1, RET, or MET∆ex14 aberrant transcripts in 28/40 cfRNA samples from positive patients and 0/16 of control individuals (70% sensitivity). Regarding dPCR, aberrant transcripts were detected in the cfRNA of 25/40 positive patients. Concordance between the two techniques was 58%. Inferior results were obtained when analyzing EV-RNA, where nCounter often failed due to a low amount of input RNA. Finally, results of dPCR testing in serial liquid biopsies of five patients correlated with response to targeted therapy. We conclude that nCounter can be used for multiplex detection of fusion and MET∆ex14 transcripts in liquid biopsies, showing a performance comparable with next-generation sequencing platforms. dPCR could be employed for disease follow-up in patients with a known alteration. cfRNA should be preferred over EV-RNA for these analyses.

Liquid Biopsy in Lung Cancer: Biomarkers for the Management of Recurrence and Metastasis

Liquid biopsies have emerged as a promising tool for the detection of metastases as well as local and regional recurrence in lung cancer. Liquid biopsy tests involve analyzing a patient's blood, urine, or other body fluids for the detection of biomarkers, including circulating tumor cells or tumor-derived DNA/RNA that have been shed into the bloodstream. Studies have shown that liquid biopsies can detect lung cancer metastases with high accuracy and sensitivity, even before they are visible on imaging scans. Such tests are valuable for early intervention and personalized treatment, aiming to improve patient outcomes. Liquid biopsies are also minimally invasive compared to traditional tissue biopsies, which require the removal of a sample of the tumor for further analysis. This makes liquid biopsies a more convenient and less risky option for patients, particularly those who are not good candidates for invasive procedures due to other medical conditions. While liquid biopsies for lung cancer metastases and relapse are still being developed and validated, they hold great promise for improving the detection and treatment of this deadly disease. Herein, we summarize available and novel approaches to liquid biopsy tests for lung cancer metastases and recurrence detection and describe their applications in clinical practice.

Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection

Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.

Landscapes of synchronous multiple primary cancers detected by next-generation sequencing

An increase in the detection rate of multiple primary cancers has been accompanied with declining cancer death rates over the past few decades. However, synchronous multiple primary tumors have gradually increased, and the molecular mechanisms involved in the synchronous occurrence of multiple primary cancers of different origins are unclear. To investigate these mechanisms, we sequenced cancer tissues by FoundationOne CDx. Data were annotated with annovar, and we then performed pathway enrichment analysis. A total of 109 genes that were mutated in all samples were clustered into different diseases, biological processes, and molecular functions. GO and KEGG analyses indicated that the P53 and PKB signaling pathways may be relevant to the occurrence of synchronous multiple primary cancers. In summary, patients with a concordance of mutations in pathogenetic genes may have a higher risk of developing a second cancer. Our research may provide a basis for the development of individualized treatments for synchronous multiple primary cancers.

Multiplex Analysis of CircRNAs from Plasma Extracellular Vesicle-Enriched Samples for the Detection of Early-Stage Non-Small Cell Lung Cancer

BACKGROUND

The analysis of liquid biopsies brings new opportunities in the precision oncology field. Under this context, extracellular vesicle circular RNAs (EV-circRNAs) have gained interest as biomarkers for lung cancer (LC) detection. However, standardized and robust protocols need to be developed to boost their potential in the clinical setting. Although nCounter has been used for the analysis of other liquid biopsy substrates and biomarkers, it has never been employed for EV-circRNA analysis of LC patients.

METHODS

EVs were isolated from early-stage LC patients (n = 36) and controls (n = 30). Different volumes of plasma, together with different number of pre-amplification cycles, were tested to reach the best nCounter outcome. Differential expression analysis of circRNAs was performed, along with the testing of different machine learning (ML) methods for the development of a prognostic signature for LC.

RESULTS

A combination of 500 μL of plasma input with 10 cycles of pre-amplification was selected for the rest of the study. Eight circRNAs were found upregulated in LC. Further ML analysis selected a 10-circRNA signature able to discriminate LC from controls with AUC ROC of 0.86.

CONCLUSIONS

This study validates the use of the nCounter platform for multiplexed EV-circRNA expression studies in LC patient samples, allowing the development of prognostic signatures.

Rapid Multiplex Strip Test for the Detection of Circulating Tumor DNA Mutations for Liquid Biopsy Applications

In the era of personalized medicine, molecular profiling of patient tumors has become the standard practice, especially for patients with advanced disease. Activating point mutations of the KRAS proto-oncogene are clinically relevant for many types of cancer, including colorectal cancer (CRC). While several approaches have been developed for tumor genotyping, liquid biopsy has been gaining much attention in the clinical setting. Analysis of circulating tumor DNA for genetic alterations has been challenging, and many methodologies with both advantages and disadvantages have been developed. We here developed a gold nanoparticle-based rapid strip test that has been applied for the first time for the multiplex detection of KRAS mutations in circulating tumor DNA (ctDNA) of CRC patients. The method involved ctDNA isolation, PCR-amplification of the KRAS gene, multiplex primer extension (PEXT) reaction, and detection with a multiplex strip test. We have optimized the efficiency and specificity of the multiplex strip test in synthetic DNA targets, in colorectal cancer cell lines, in tissue samples, and in blood-derived ctDNA from patients with advanced colorectal cancer. The proposed strip test achieved rapid and easy multiplex detection (normal allele and three major single-point mutations) of the clinically relevant KRAS mutations in ctDNA in blood samples of CRC patients with high specificity and repeatability. This multiplex strip test represents a minimally invasive, rapid, low-cost, and promising diagnostic tool for the detection of clinically relevant mutations in cancer patients.

Targeted Sequencing of Ascites and Peritoneal Washing Fluid of Patients With Gastrointestinal Cancers and Their Clinical Applications and Limitations

Cytology from gastrointestinal (GI) cancers is frequently obtained from ascites and peritoneal washing fluids. Examination of ascites and peritoneal washing fluids from patients with GI cancers can help in the tumor staging and prognosis. Tumor-derived DNA in these cytology samples can be a target for next generation sequencing (NGS). Targeted NGS was evaluated in ascites and peritoneal washing samples obtained from 33 patients with GI cancers. These sequences were compared with those from tumor tissue samples, and correlated with cytopathologic findings of the ascites and peritoneal fluid samples. The correlation between fluid and tissue genotyping results was 25%, with a sensitivity of 21.43%. The volume of tumor contained within the fluid samples was low, ranging from ~0 to 10%. Importantly, the sensitivity of detection of somatic mutations in the fluid samples could be increased to 69.2% by assessing samples containing >2% tumor volume. Evaluation of cells from ascitic fluid showed the presence of KRAS, TP53, and CDH1 mutations in 33, 13, and 7%, respectively, of patients with pancreatic cancer, and the presence of KRAS, TP53, and APC mutations in 25, 12, and 13%, respectively, of patients with gastric cancer. Ascites of one of the latter patients acquired KRAS mutation, which was a novel mutation during metastasis. Targeted NGS of ascites and peritoneal washing fluid have clinical implications, as well as limitations, in patients with GI cancers. NGS-based cytology examination may expand cytomolecular practices in GI cancer patients.

Mutated circulating tumor DNA as a liquid biopsy in lung cancer detection and treatment

Over the past decade, substantial developments have been made in the detection of circulating tumor DNA (ctDNA)-cell-free DNA (cfDNA) fragments released into the circulation from tumor cells and displaying the genetic alterations of those cells. As such, ctDNA detected in liquid biopsies serves as a powerful tool for cancer patient stratification, therapy guidance, detection of resistance, and relapse monitoring. In this Review, we describe lung cancer diagnosis and monitoring strategies using ctDNA detection technologies and compile recent evidence regarding lung cancer-related mutation detection in liquid biopsy. We focus not only on epidermal growth factor receptor (EGFR) alterations, but also on significant co-mutations that shed more light on novel ctDNA-based liquid biopsy applications. Finally, we discuss future perspectives of early-cancer detection and clonal hematopoiesis filtering strategies, with possible inclusion of microbiome-driven liquid biopsy.

Analysis of extracellular vesicle mRNA derived from plasma using the nCounter platform

Extracellular vesicles (EVs) are double-layered phospholipid membrane vesicles that are released by most cells and can mediate intercellular communication through their RNA cargo. In this study, we tested if the NanoString nCounter platform can be used for the analysis of EV-mRNA. We developed and optimized a methodology for EV enrichment, EV-RNA extraction and nCounter analysis. Then, we demonstrated the validity of our workflow by analyzing EV-RNA profiles from the plasma of 19 cancer patients and 10 controls and developing a gene signature to differentiate cancer versus control samples. TRI reagent outperformed automated RNA extraction and, although lower plasma input is feasible, 500 μL provided highest total counts and number of transcripts detected. A 10-cycle pre-amplification followed by DNase treatment yielded reproducible mRNA target detection. However, appropriate probe design to prevent genomic DNA binding is preferred. A gene signature, created using a bioinformatic algorithm, was able to distinguish between control and cancer EV-mRNA profiles with an area under the ROC curve of 0.99. Hence, the nCounter platform can be used to detect mRNA targets and develop gene signatures from plasma-derived EVs.