scholarly journals Detection of circulating tumor DNA by digital droplet PCR in resectable lung cancer as a predictive tool for recurrence

Lung Cancer ◽  
2021 ◽  
Vol 151 ◽  
pp. 91-96
Author(s):  
Asmae Gassa ◽  
Jana Fassunke ◽  
Sarah Schueten ◽  
Luca Kuhlmann ◽  
Marie Scherer ◽  
...  
2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 9546-9546
Author(s):  
Jenny HJ Lee ◽  
Georgina V. Long ◽  
Alexander M. Menzies ◽  
Alexander David Guminski ◽  
Richard Kefford ◽  
...  

9546 Background: We have previously shown that undetectable ctDNA either at baseline or during therapy predicted response in mm patients (pts) treated with anti-PD1 antibodies (aPD1). Pseudoprogression, defined as radiological progression prior to response, occurs in 8% of pts treated with aPD1. We sought to determine if ctDNA could differentiate pseudoprogression from true progression, defined as continued clinical or radiological disease progression. Methods: Between July 2014 and May 2016, pts receiving aPD1 had serial bloods for ctDNA. Included pts either had RECIST PD at first restaging or early clinical progression. Those with untreated brain metastases were excluded from the analysis. ctDNA was quantified using digital droplet PCR for mutations (BRAF/NRAS) at baseline and during the first 12 wks of treatment. Based on our prior studies, ctDNA results were grouped in to ‘favorable’ and ‘unfavorable’ ctDNA profiles (see Table), and these were compared in pts with true and pseudoprogression. Results: 29 pts were included, 28 with RECIST PD at first restaging and one with early clinical progression. 9 (31%) pts had a subsequent RECIST PR or SD and were considered pseudoprogression and 20 (69%) had true progression. Of the pseudoprogressors, 7/9 pts remained in response with a median follow-up of 20 months (mths). 2/9 pts had disease progression at 7 and 18 mths, with ctDNA that remained detectable with a > 10-fold decrease during treatment in both patients. Of those with true progression and a favourable profile, 1 had a > 10-fold decrease in ctDNA by wk 12 and was switched to MAPK therapy prior to further imaging, and the other had an undetectable ctDNA at wk 6 which increased again at wk 12. The latter pt had a new lesion on first restaging CT scan despite PR in all existing lesions with true PD on second restaging at wk 24. Conclusions: ctDNA in patients with mm at baseline and early on aPD1 treatment differentiates pseudo from true progression. [Table: see text]


2021 ◽  
Vol 67 (2) ◽  
pp. 260-267
Author(s):  
Aglaya Iyevleva ◽  
Tatiana Gorodnova ◽  
Svetlana Aleksakhina ◽  
Elena Anisimova ◽  
Larisa Gigolaeva ◽  
...  

Background. The analysis of circulating tumor DNA provides wide opportunities for monitoring the results of cancer treatment. Somatic mutations in TP53 gene are present in almost all breast carcinomas developing in hereditary BRCA1 mutation carriers, as well as in the majority of high-grade serous ovarian tumors, which makes it possible to use them for effective monitoring of these diseases. The aim of the study was to analyze the content of tumor-specific TP53 mutations in plasma of patients with high-grade serous ovarian cancer (OC) and BRCA1-associated breast cancer (BC). Materials and methods. At least one plasma sample was obtained from 10 patients with OC and 7 patients with BRCA1-associated BC. The primary intratumoral status of TP53 gene was determined in the archival tumor material by targeted next generation sequencing. Digital droplet PCR was applied for testing of plasma samples for the presence of tumor-specific TP53 mutations, and in one case, BRAF V600E mutation. Results. All 8 plasma samples obtained from OC patients at the time of disease progression, before or during neoadjuvant chemotherapy, were positive for TP53 mutations. In contrast, 8 OC plasma samples obtained during remission, after surgery, or after neoadjuvant chemotherapy did not contain tumor-specific mutations. In breast cancer, circulating tumor DNA was detected in 2 of 4 samples obtained before treatment, and was not detected after the end of therapy or in remission. Conclusion. There is a good correlation between the presence of tumor-specific TP53 mutations in circulating DNA and the disease status in OC patients, therefore TP53 is a promising marker for clinical monitoring of ovarian cancer. In breast cancer, circulating tumor DNA is less abundant, therefore TP53 mutations cannot be reliably detected by digital droplet PCR in the plasma of patients with moderate disease burden.


2019 ◽  
Vol 28 (5) ◽  
pp. 909-916 ◽  
Author(s):  
Luca Cavallone ◽  
Mohammed Aldamry ◽  
Josiane Lafleur ◽  
Cathy Lan ◽  
Pablo Gonzalez Ginestet ◽  
...  

2019 ◽  
Vol 65 (5) ◽  
pp. 701-707
Author(s):  
Vitaliy Shubin ◽  
Yuriy Shelygin ◽  
Sergey Achkasov ◽  
Yevgeniy Rybakov ◽  
Aleksey Ponomarenko ◽  
...  

To determine mutations in the plasma KRAS gene in patients with colorectal cancer was the aim of this study. The material was obtained from 44 patients with colorectal cancer of different stages (T1-4N0-2bM0-1c). Plasma for the presence of KRAS gene mutation in circulating tumor DNA was investigated using digital droplet polymerase chain reaction (PCR). KRAS mutations in circulating tumor DNA isolated from 1 ml of plasma were detected in 13 (30%) patients with cancer of different stages. Of these, with stage II, there were 3 patients, with III - 5 and with IV - 5. Patients who did not have mutations in 1 ml of plasma were analyzed for mutations of KRAS in circulating tumor DNA isolated from 3 ml of plasma. Five more patients with KRAS mutations were found with II and III stages. The highest concentrations of circulating tumor DNA with KRAS mutation were found in patients with stage IV. The increase in plasma volume to 3 ml did not lead to the identification of mutations in I stage. This study showed that digital droplet PCR allows identification of circulating tumor DNA with the KRAS mutations in patients with stage II-IV of colon cancer. The results can be used to determine the degree of aggressiveness of the tumor at different stages of the disease, but not the 1st, and it is recommended to use a plasma volume of at least 3 ml.


Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3759
Author(s):  
Bryan Ulrich ◽  
Anne Pradines ◽  
Julien Mazières ◽  
Nicolas Guibert

Approximately 30% of patients with non-small-cell lung cancer (NSCLC) present with localized/non-metastatic disease and are eligible for surgical resection or other “treatment with curative intent”. Due to the high prevalence of recurrence after treatment, adjuvant therapy is standard care for most patients. The effect of adjuvant chemotherapy is, however, modest, and new tools are needed to identify candidates for adjuvant treatments (chemotherapy, immunotherapy, or targeted therapies), especially since expanded lung cancer screening programs will increase the rate of patients detected with localized NSCLC. Circulating tumor DNA (ctDNA) has shown strong potential to detect minimal residual disease (MRD) and to guide adjuvant therapies. In this manuscript, we review the technical aspects and performances of the main ctDNA sequencing platforms (TRACERx, CAPP-seq) investigated in this purpose, and discuss the potential of this approach to guide or spare adjuvant therapies after definitive treatment of NSCLC.


2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A18-A18
Author(s):  
Jaeyoun Choi ◽  
Myungwoo Nam ◽  
Stanislav Fridland ◽  
Jinyoung Hwang ◽  
Chan Mi Jung ◽  
...  

BackgroundTumor heterogeneity assessment may help predict response to immunotherapy. In melanoma mouse models, tumor heterogeneity impaired immune response.1 In addition, among lung cancer patients receiving immunotherapy, the high clonal neoantigen group had favorable survival and outcomes.2 Ideal methods of quantifying tumor heterogeneity are multiple biopsies or autopsy. However, these are not feasible in routine clinical practice. Circulating tumor DNA (ctDNA) is emerging as an alternative. Here, we reviewed the current state of tumor heterogeneity quantification from ctDNA. Furthermore, we propose a new tumor heterogeneity index(THI) based on our own scoring system, utilizing both ctDNA and tissue DNA.MethodsSystematic literature search on Pubmed was conducted up to August 18, 2020. A scoring system and THI were theoretically derived.ResultsTwo studies suggested their own methods of assessing tumor heterogeneity. One suggested clustering mutations with Pyclone,3 and the other suggested using the ratio of allele frequency (AF) to the maximum somatic allele frequency (MSAF).4 According to the former, the mutations in the highest cellular prevalence cluster can be defined as clonal mutations. According to the latter, the mutations with AF/MSAF<10% can be defined as subclonal mutations. To date, there have been no studies on utilizing both ctDNA and tissue DNA simultaneously to quantify tumor heterogeneity. We hypothesize that a mutation found in only one of either ctDNA or tissue DNA has a higher chance of being subclonal.We suggest a scoring system based on the previously mentioned methods to estimate the probability for a mutant allele to be subclonal. Adding up the points that correspond to the conditions results in a subclonality score (table 1). In a given ctDNA, the number of alleles with a subclonality score greater than or equal to 2 divided by the total number of alleles is defined as blood THI (bTHI) (figure 1). We can repeat the same calculation in a given tissue DNA for tissue THI (tTHI) (figure 2). Finally, we define composite THI (cTHI) as the mean of bTHI and tTHI.Abstract 18 Table 1Subclonality scoreAbstract 18 Figure 1Hypothetical distribution of all alleles found in ctDNA bTHI = the number of alleles with a subclonality score greater than or equal to 2/the total number of alleles found in ctDNA = 10/20 =50%Abstract 18 Figure 2Hypothetical distribution of all alleles found in tissue DNA tTHI= the number of alleles with a subclonality score greater than or equal to 2/the total number of alleles found in tissue DNA = 16/40 = 40% cTHI= (bTHI + tTHI)/2 = 45%ConclusionsTumor heterogeneity is becoming an important biomarker for predicting response to immunotherapy. Because autopsy and multiple biopsies are not feasible, utilizing both ctDNA and tissue DNA is the most comprehensive and practical approach. Therefore, we propose cTHI, for the first time, as a quantification measure of tumor heterogeneity.ReferencesWolf Y, Bartok O. UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma. Cell 2019;179:219–235.McGranahan N, Swanton C. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 2016;351:1463–1469.Ma F, Guan Y. Assessing tumor heterogeneity using ctDNA to predict and monitor therapeutic response in metastatic breast cancer. Int J Cancer 2020;146:1359–1368.Liu Z, Xie Z. Presence of allele frequency heterogeneity defined by ctDNA profiling predicts unfavorable overall survival of NSCLC. Transl Lung Cancer Res 2019;8:1045–1050.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yongliang Zhang ◽  
Yu Yao ◽  
Yaping Xu ◽  
Lifeng Li ◽  
Yan Gong ◽  
...  

AbstractCirculating tumor DNA (ctDNA) provides a noninvasive approach to elucidate a patient’s genomic landscape and actionable information. Here, we design a ctDNA-based study of over 10,000 pan-cancer Chinese patients. Using parallel sequencing between plasma and white blood cells, 14% of plasma cell-free DNA samples contain clonal hematopoiesis (CH) variants, for which detectability increases with age. After eliminating CH variants, ctDNA is detected in 73.5% of plasma samples, with small cell lung cancer (91.1%) and prostate cancer (87.9%) showing the highest detectability. The landscape of putative driver genes revealed by ctDNA profiling is similar to that in a tissue-based database (R2 = 0.87, p < 0.001) but also shows some discrepancies, such as higher EGFR (44.8% versus 25.2%) and lower KRAS (6.8% versus 27.2%) frequencies in non-small cell lung cancer, and a higher TP53 frequency in hepatocellular carcinoma (53.1% versus 28.6%). Up to 41.2% of plasma samples harbor drug-sensitive alterations. These findings may be helpful for identifying therapeutic targets and combined treatment strategies.


Author(s):  
A.A. Chaudhuri ◽  
A.F. Lovejoy ◽  
J.J. Chabon ◽  
A. Newman ◽  
H. Stehr ◽  
...  

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