Genomic landscape characterization and comparative analysis of tissue and liquid-based next-generation sequencing in anaplastic thyroid carcinoma in Taiwan

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Genomic landscape characterization and comparative analysis of tissue and liquid-based next-generation sequencing in anaplastic thyroid carcinoma in Taiwan

https://doi.org/10.21203/rs.3.rs-4552876/v1

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Anaplastic thyroid carcinoma (ATC) is an aggressive disease that requires prompt diagnosis and multimodal treatment. Recent advancements in targeted therapies have offered new treatment options for patients with ATC, potentially improving their clinical outcomes. Ongoing progress in high-throughput next-generation sequencing (NGS) has enabled clinicians to comprehensively characterize the genomic landscape of tumors, guide treatment decisions, and facilitate clinical trial enrollment. The role of liquid NGS in ATC remains unclear, particularly in cases where tissue NGS is not feasible or yields inadequate results. This study assessed patients with ATC treated at Chang Gung Memorial Hospital, Linkou, between 2011 and 2023. Among these, 26 patients had adequate tissue for commercially available tissue NGS (ACTOnco®+, 440 genes), 15 had access to a commercially available liquid NGS platform (ACTMonitor®+, 50 genes), and 13 patients underwent both tissue and liquid NGS. The genetic alterations observed in ATC exhibited a high degree of heterogeneity, involving several pathways, including RAS/RAF/MEK/ERK (73.1%), PI3K/AKT/mTOR (57.7%), cell cycle regulation (92.3%), other receptor tyrosine kinases (65.4%), DNA damage response (50.0%), DNA mismatch repair (MMR, 34.6%, including MLH1, MSH6, MSH2, and PMS1), and chromatin remodeling (76.9%). The most frequently mutated genes in tissue NGS were TP53 (17/26, 65.4%) and BRAF (8/26, 30.8%). Among the 13 pairs analyzed on both platforms, the concordance rates were 84.6% and 69.2% for BRAF and TP53, respectively. Among two patients without sufficient tissue for NGS, liquid NGS provided additional information on genetic alterations. Two ATC patients treated with dabrafenib and trametinib had treatment-naïve and post-treatment tissue samples for NGS, but only one patient (two samples; ATC01 after) showed copy number gain over genes, which may be associated with resistance. NGS platforms, whether applied to tissue or liquid samples, can empower clinicians to identify targetable oncogenic events in ATC. Liquid biopsy provides supplementary information when the tissue is insufficient for NGS. Additional studies are needed to understand the resistance mechanisms associated with BRAF-targeted therapy and explore strategies to overcome resistance.

Biological sciences/Cancer/Endocrine cancer/Thyroid cancer

Biological sciences/Biological techniques/Gene expression analysis

Anaplastic thyroid carcinoma (ATC)

Next-generation sequencing (NGS)

Genomic landscape

Liquid biopsy

Targeted therapeutics

Anaplastic thyroid cancer (ATC) accounted for 1.3–9.8% of all thyroid cancers based on various studies in worldwide¹. It is one of the most lethal malignancies with a median overall survival (OS) of only 4–6 months^2,3 and disease-specific mortality of nearly 100%. To enhance survival, previous studies have focused on surgical techniques improvement, radiotherapy design, and the development of novel systemic treatments, including targeted- and immuno-therapies^4–7, however, the treatment outcomes of ATC remain unsatisfactory. Several prognostic factors, including age, leukocytosis, acute symptoms, disease stage, tumor size, prior surgery, prior radiotherapy, and chemotherapy have been identified^4,8,9, however, novel treatments are still required to overcome the aggressiveness of ATC.

The BRAF (V600E) mutation is commonly found in thyroid carcinoma, and the prevalence of BRAF mutations in ATC has been reported to be 35%-40%¹⁰. Dabrafenib and trametinib are tyrosine kinase inhibitors (TKIs) against BRAF V600E and MEK1/2, respectively, and have demonstrated promising effects in BRAF-mutant ATC^11,12. In our previous study, we retrospectively analyzed the effect of dabrafenib and trametinib on BRAF-mutated ATC in real-world practice and found that dabrafenib and trametinib were effective and significantly improved the OS of patients with ATC. However, the benefit was limited in BRAF-mutated ATC. Resistance inevitably occurs, and patients succumb to the disease soon after progression. Identifying additional possible targets and mechanisms of resistance to targeted therapy is critical for improving the survival of patients with ATC.

This study aimed to conduct comprehensive genomic profiling to identify common driver mutations in Taiwanese patients with ATC, assess the frequency of established genetic events in tumorigenesis, identify potential novel driver genetic events, and characterize candidates for targeted therapy. Furthermore, we aimed to investigate the role of liquid next-generation sequencing (NGS) and elucidate the resistance mechanisms associated with BRAF-targeted therapy.

The baseline characteristics of 26 patients with ATC enrolled in the current study

The overall cohort in the current study comprised 26 samples subjected to tissue NGS and 15 samples subjected to liquid NGS (Fig. 1a). Among the 26 patients who underwent tissue NGS, the median follow-up time was 5.4 months (range 0.3 to 35.7 months) until January 2024. The median age of the patients was 72.7 years, and their sex distribution was equal. Most patients exhibited a good or intermediate performance status (Eastern Cooperative Oncology Group Performance Status 0–1:61.5%), had no previous history of differentiated thyroid cancer (de novo ATC: 69.2%), and were diagnosed with distant metastases at the time of the initial ATC diagnosis (stage IVC: 57.7%). The detailed baseline characteristics are summarized in Table 1. Median OS was 6.3 months (95% CI: 1.8–10.8 months, Fig. 1b).

Table 1

Basic characteristics of patients (n = 26).
Characteristics	No. of patients	%
Age (years) (Medium \(\pm\) SD)	72.7\(\pm\)10.6
≤ 65	6	23.1
> 65	20	76.9
Sex
Male	13	50.0
Female	13	50.0
Performance score
0–1	16	61.5
2–4	10	38.5
De novo ATC
Yes	18	69.2
No	8	30.8
Stage
IVA	2	7.7
IVB	9	34.6
IVC	15	57.7
Metastatic site
Lung	13	50.0
Bone	3	11.5
Brain	2	7.7
Operation
Curative	9	34.6
Palliative	5	19.2
Radiotherapy	15	57.7
Systemic treatment
Chemotherapy	9	34.6
Pembrolizumab	5	19.2
Sorafenib	3	11.5
Lenvatinib	6	23.1
Dabrafenib + Trametinib	9	34.6

Tissue NGS

The genetic alterations of SNV in ATC were highly heterogeneous, involving several pathways, including RAS/RAF/MEK/ERK (73.1%), PI3K/AKT/mTOR (57.7%), cell cycle regulation (92.3%), other receptor tyrosine kinases (65.4%), DNA damage response (50.0%), and DNA mismatch repair (MMR, 34.6% including MLH1, MSH6, MSH2, and PMS1), and chromatin remodeling (76.9%) (Fig. 2 and supplementary Fig. 1–2). Although 34.6% of patients with ATC harbor MMR mutations, all mutations were variants of uncertain significance (VUS), leading to the absence of MSI-H in the current cohort. Among 24 ATCs with evaluable TMB, only one ATC (TMB: 7.5 mut/Mb) had TMB-H (≥ 7.5 mut/Mb).

TP53 mutations were the most prevalent (65.4%) in this cohort. BRAF, NF1, NRAS, KRAS, and HRAS mutations accounted for 30.8%, 19.2%, 19.2%, 11.5%, and 3.8% of cases, respectively. All BRAF mutations were the V600E mutation. The KRAS mutations comprised one G12V, one Q61H, and one Q61K. The NRAS mutations included four Q61R mutations and one G13R mutation. Only one HRAS mutation (Q61R) was identified. Mutations in other receptor tyrosine kinases, including FGFR3 (19.2%) and ALK (15.4%), were the most frequent. Mutations in HER, FGFR, NTRK, KIT, PDGFR, MET, and ROS-1 were also found (Supplementary Fig. 2).

Regarding the PI3K/AKT/mTOR pathway, 57.5% of patients with ATC harbored genetic alterations. PTEN loss (19.2%) was the most common, followed by MTOR (11.5%) and PI3KCA (11.5%) mutations. In terms of the DNA damage response, BRCA2 and BRCA1 accounted for 15.4% and 11.5%, respectively. Due to the lack of paired normal tissue for further analysis, germline BRCA1/2 was suspected in some cases based on the variant allele frequency. Other genes involved in the DNA damage response were also identified.

CNV was also evaluated. Genes involved in receptor tyrosine kinase (42.3%), cell cycle (42.3%), and DNA damage response (38.5%) were the major pathways in ATC. The CNV details of specific genes are shown in Fig. 3 and Supplementary Fig. 3.

Liquid NGS

Overall, 15 patients underwent liquid NGS, including 13 with paired tissue NGS and two with insufficient tissue for NGS. TP53 and BRAF mutations were detected in four out of 15 (26.7%) patients (Fig. 4), which was lower than that detected by tissue NGS. In cases with limited tissue availability or where tissue NGS is not feasible, liquid biopsy, which detects a BRAF mutation, serves as a complementary method for genetic profiling. However, eight out of 15 patients had no detectable genetic alterations and required paired samples to assess the concordance between tissue and liquid NGS.

Paired tissue and liquid NGS

Among the 13 paired tissue and liquid NGS samples, no genetic alterations were found in seven liquid NGS reports, suggesting that liquid NGS has an intrinsic limitation in identifying genetic alterations in ATC (Fig. 5). Generally, liquid NGS did not reveal additional genetic alterations compared with tissue NGS, except for two samples that reported ATM and EGFR mutations that were not detected by tissue NGS (Fig. 5).

In five of the 13 ATC patients with BRAF mutations by tissue NGS, 3 (60%) were detected by liquid NGS, resulting in a sensitivity of 60% and specificity of 100% for BRAF detection by liquid NGS. The concordance rate for BRAF mutations was 84.6% and for TP53 was 69.2%.

Resistance

Two patients with ATC were treated with dabrafenib and trametinib, and on progression on targeted therapy (Fig. 6), they underwent a series of NGS analyses. The first patient experienced progression twice, which led to two additional tissue NGS analyses. No differences were found in terms of SNV, but a gain in copy number (copy number: 4–6) was observed for some genes (GNAS, AURKA, SRC, TOP1, etc.) in one patient.

The poor prognosis associated with ATC is primarily attributed to the limited efficacy of conventional treatment modalities and an incomplete understanding of the underlying mechanisms driving ATC tumorigenesis. This study aimed to address these challenges by conducting comprehensive genomic profiling of 26 ATC cases in Taiwan and assessing the concordance between tissue and liquid NGS in 13 ATC cases. The genomic landscape of ATC revealed the intricate involvement of multiple pathways, including RAS/RAF/MEK/ERK (73.1%), PI3K/AKT/mTOR (57.7%), cell cycle regulation (92.3%), other receptor tyrosine kinases (65.4%), DNA damage response (50.0%), DNA mismatch repair (34.6%), and chromatin remodeling (76.9%). Liquid NGS demonstrated the capability to detect more BRAF mutations in cases where tissue was either unavailable or insufficient¹³. These findings underscore the highly heterogeneous genetic background of ATC, revealing previously unexplored genetic events. Notably, mutations in HER1/2/3, FGFR2/4, NTRK 1/2/3, and genes associated with the DNA damage response have been identified, presenting intriguing possibilities, as pharmaceuticals targeting these genes are currently in clinical or experimental use. Finally, the mutation landscape of the cohort was characterized, revealing diverse frequencies of recognized thyroid malignancy genes in the majority, though not all, of ATC cases.

The detection of driver mutations is a key factor in ATC treatment, as most patients cannot be cured by surgery alone. The commonly mutated genes were TP53 in 17/26 (65.4%) patients, and BRAF in 8/26 (30.8%) patients, which is consistent with previous reports^14–17. In addition to tumor agnostic therapy, combination therapy with dabrafenib and trametinib is the only targeted therapy that has been approved for ATC harboring the BRAF V600E mutation since 2018, based on the ROAR study (BRF117019 study, NCT02034110)^11,18. A few retrospective studies also confirmed the role of targeted therapy for BRAF-mutated ATC^19,20. Tumor agnostic treatment was applied for ATC with NTRK fusion, RET fusion, MSI-H, and TMB-H, which were not found in the current cohort. However, other possible novel targets have been identified, providing evidence for the development of targeted therapies.

Regarding KRAS mutations, we identified one G12V, one Q61H, and one Q61K mutation. Sotorasib and adagrasib have been approved for patients with non-small cell lung cancer (NSCLC) harboring the KRAS G12C²¹. In 14 patients (10 with pancreatic ductal adenocarcinoma (PDAC) and four with NSCLC) harboring G12X mutations other than G12C and treated with RMC-6236 at least 8 weeks before the data cut-off date, the objective response rate was 36%²². Ongoing investigations into targeted therapies offer hope for the treatment of cancers with various KRAS mutations²¹.

Four patients with NRAS mutations were identified, including four with Q61R and one with G13R mutations. Currently, there is no approved treatment for cancers with NRAS mutations. However, MEK inhibitors such as cobimetinib, trametinib, and binimetinib may stabilize NRAS-mutated metastatic melanoma, with an objective response rate (ORR) of 18.2% and a disease control rate (DCR) of 48.5%²³. Recently, the ORR reported was 46.7% in patients with NRAS-mutated melanoma treated with naporafenib (a pan-RAF kinase inhibitor, 200 mg twice a day) plus trametinib (1 mg once daily)²⁴. SEACRAFT-1 is an open-label study designed to assess the safety and efficacy of naporafenib administered with trametinib in previously treated patients with locally advanced unresectable or metastatic RAS Q61X solid tumor malignancies including thyroid cancer (ClinicalTrials.gov Identifier: NCT05907304).

Other genetic alterations involving the DNA damage response (DDR) and cell cycle may have implications in specific targeted therapies. Currently, homologous recombination deficiency (HRD) is the only available predictive biomarker that can identify patients more likely to benefit from PARP inhibitors²⁵. PARP inhibitor monotherapy has been extensively investigated in cancer subtypes commonly associated with HRD²⁶. Furthermore, clinical trials of combination strategies with anti-angiogenesis and immunotherapy have aimed to enhance the efficacy of PARP inhibitors²⁶. Studies targeting cell cycle checkpoints²⁷, such as ATM²⁸, ATR, and Wee1²⁹, are ongoing to tackle the DDR.

In our study, the rate of BRAFV600E detection by circulating tumor DNA (ctDNA) was 26.7%. This is comparable to the findings in 92 cases of ATC using the Guardant360 plasma NGS test, which showed a BRAFV600E detection rate of 27.2%³⁰. However, this was lower than that reported in historical cohorts^14–17 and in our tissue NGS (30.8%).

In the current cohort of 13 NGS pairs, the concordance rates were 84.6% for BRAF and 69.2% for TP53. This discrepancy in detection rates could potentially be attributed to the specific characteristics of ATC, including tumor burden and shedding. Supporting this, another study involving 23 patients with ATC at the University of Texas MD Anderson Cancer Center revealed that the reliability of inference based on concordance was highest in patients who underwent dual-platform sequencing before initiating definitive treatment¹⁷. In contrast, it was the lowest in patients who underwent cell-free circulating DNA (cfDNA) analysis after treatment¹⁷. Therefore, tissue NGS should remain the standard of care for determining therapeutic options for ATC unless the tissue is unavailable or insufficient for tissue NGS.

The identification of more novel targets and resistance mechanisms is required. However, no novel targets were identified in this study. We found some genes with increased copy numbers (copy number: 4–6) implying a possible resistance mechanism for BRAF-targeted therapy. However, more cases should be compiled and analyzed to confirm these data. Unlike the intrinsic and extrinsic acquired mutations in melanoma³¹ and NSCLC³², currently, there are not many reports on ATC. Recently, BRAF off-target resistance mechanisms in ATCs, including RAS mutations^33,34 RAC1 mutations³⁵, and copy number variations³⁵ have been described. Further studies are warranted to understand the mechanisms of resistance to BRAF-targeted therapy in ATC.

This study provides clinical insights into the genomic landscape of ATC and identifies potential novel targets worthy of further investigation. Considering the multiple aberrant pathways present in these tumors, a multi-targeted therapeutic strategy is essential. While liquid biopsy alone may not be sufficient to identify driver mutations, it offers complementary information when the tissue is inadequate for NGS. Further studies are warranted to understand the resistance mechanisms of BRAF-targeted therapy and to find ways to overcome this resistance.

Patients and clinical characteristics

This study included data from patients with histologically confirmed ATC at Chang Gung Memorial Hospital (CGMH), Linkou, between 2011 and 2023 and encompassed both prospective (after 2021/03/08) and retrospective (2000/01~2021/02) cohorts delineated by the date of IRB approval. The analysis focused on patients with adequate quality and quantity of archived tissues available for NGS assays. Additionally, liquid biopsy samples for NGS were collected from prospective cohorts of treatment-naïve ATC patients. The retrospective records encompassed clinical characteristics, including age at diagnosis, sex, staging, metastatic sites, treatment history (including prior surgery and radiotherapy), and OS outcomes.

Sample processing and next-generation sequencing (NGS)

Samples with inadequate quality that failed quality control were excluded from analysis by ACTOnco^®+ (ACT Genomics, Taipei, Taiwan), an NGS panel sequencing more than 440 genes. Nucleotide variation (SNV), copy number variation (CNV), microsatellite instability (MSI), and tumor mutational burden (TMB) were evaluated. For details of the NGS methodology, please refer to our earlier study ³⁶.
TMB was determined using the sequenced regions of ACTOnco^®+ to estimate the number of somatic nonsynonymous mutations per megabase across all protein-coding genes (whole exome). TMB calculation predicted somatic variants and applied a machine-learning model with cancer hotspot correction. TMB results are categorized as “TMB-High” (≥ 7.5 muts/Mb), “TMB-Low” (< 7.5 muts/Mb), or “Cannot Be Determined” (the tumor purity of the sample is < 30%).
The extracted RNA was reverse transcribed and used for library construction. Sequencing was conducted using an Ion Proton or Ion S5 sequencer. To ensure the sequencing quality, the average unique RNA Start Sites (SS) per control Gene Specific Primer 2 (GSP 2) should be ≥ 10.

For the fusion analysis, the sequenced reads were aligned to the human reference genome, non-contiguous genome regions were identified, filters were applied to exclude false-positive events, and annotated using the Quiver Gene Fusion Database maintained by ArcherDX. The samples with detected fusions were required to meet the following criteria: (1) Number of unique start sites (SS) for the GSP2 ≥ 3; (2) Number of supporting reads spanning the fusion junction ≥ 5; (3) Percentage of supporting reads spanning the fusion junction ≥ 10%; (4) Fusions annotated in Quiver Gene Fusion Database.

ACTMonitor^®+Genomic DNA was extracted from patients' plasma, followed by library construction and sequencing for the hotspot regions of 50 genes. Sequencing was performed using an Ion Torrent sequencing system (Thermo Fisher Scientific). Variants that met the following criteria were retained: variants with an allele frequency of ≥ 0.5%, and hotspot variants with an allele frequency of ≥ 0.2%. This test provided a uniform coverage of the targeted regions, enabling target base coverage at 2000x of ≥ 70% with a mean coverage of ≥ 7000x.

Statistical analysis

Continuous variables were expressed as median ± SD, while categorical variables were presented as numbers (%). OS was defined as the duration from the date of diagnosis to the date of death or the last follow-up and is presented as the median (95% confidence interval [CI]). Concordance between the two platforms was calculated using the following formula: concordance = number of concordant results/overall population.

ETHICAL CONSIDERATION

This study was approved by the Institutional Review Board of Chang Gung Medical Foundation (202100148B0). The requirement for informed consent was waived for the retrospective cohort and was obtained from the prospective cohort.

REPORTING SUMMARY

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

DATA AVAILABILITY

All data and materials used in this study are available upon reasonable request.

ACKNOWLEDGEMENTS

We thank the Research Specimen Processing Laboratory and Common Laboratory of Chang Gung Memorial Hospital, Linkou, for technical and funding support. This work was financially supported by grants from Linkou Chang-Gung Memorial Hospital (NMRPG3K6201, NZRPG3K0221, NZRPD1M3231, CMRPG3L0911~3, CMRPG3M0521~2, and CMRPG3P0181 to CEW) and the National Science and Technology Council (109-2314-B-182-080-MY3 and 111-2811-B-182-017 to CEW).

AUTHOR CONTRIBUTIONS

C.N. Y. contributed to conceptualization, investigation, visualization, draft-review and editing; S.F. L. was involved in conceptualization, investigation, and visualization; C.L. W. contributed to methodology and investigation; M.J. L. and I.W. C. carried out methodology and formal analysis; C.P. C. was involved in visualization andinvestigation; C.F. C. contributed to methodology and formal analysis; Q.A. W. carried out methodology and investigation; C.E. W. was in charge of conceptualization, methodology, supervision, writing original draft, and draft-review and editing.

COMPETING INTERESTS

The authors declare no competing interests.

ADDITIONAL INFORMATION

Correspondence and requests for materials should be addressed to Chiao-En Wu.

Smallridge, R. C. & Copland, J. A. Anaplastic thyroid carcinoma: pathogenesis and emerging therapies. Clin Oncol (R Coll Radiol) 22, 486-497, doi:10.1016/j.clon.2010.03.013 (2010).
Lee, D. Y. et al. Recurrence and Survival After Gross Total Removal of Resectable Undifferentiated or Poorly Differentiated Thyroid Carcinoma. Thyroid 26, 1259-1268, doi:10.1089/thy.2016.0147 (2016).
Zhang, L. et al. Novel recurrent altered genes in chinese patients with anaplastic thyroid cancer. The Journal of clinical endocrinology and metabolism 106, 988-998, doi:10.1210/clinem/dgab014 (2021).
Are, C. & Shaha, A. R. Anaplastic thyroid carcinoma: biology, pathogenesis, prognostic factors, and treatment approaches. Ann Surg Oncol 13, 453-464, doi:10.1245/ASO.2006.05.042 (2006).
McIver, B. et al. Anaplastic thyroid carcinoma: a 50-year experience at a single institution. Surgery 130, 1028-1034, doi:10.1067/msy.2001.118266 (2001).
Smallridge, R. C. et al. American thyroid association guidelines for management of patients with anaplastic thyroid cancer. Thyroid : official journal of the American Thyroid Association 22, 1104-1139, doi:10.1089/thy.2012.0302 (2012).
Dierks, C. et al. Combination of lenvatinib and pembrolizumab is an effective treatment option for anaplastic and poorly differentiated thyroid carcinoma. Thyroid 31, 1076-1085 (2021).
O'Neill, J. P. & Shaha, A. R. Anaplastic thyroid cancer. Oral Oncol 49, 702-706, doi:10.1016/j.oraloncology.2013.03.440 (2013).
Sugitani, I. et al. Prognostic factors and treatment outcomes for anaplastic thyroid carcinoma: ATC Research Consortium of Japan cohort study of 677 patients. World J Surg 36, 1247-1254, doi:10.1007/s00268-012-1437-z (2012).
Cabanillas, M. E., Ryder, M. & Jimenez, C. Targeted Therapy for Advanced Thyroid Cancer: Kinase Inhibitors and Beyond. Endocr Rev 40, 1573-1604, doi:10.1210/er.2019-00007 (2019).
Subbiah, V. et al. Dabrafenib and Trametinib Treatment in Patients With Locally Advanced or Metastatic BRAF V600-Mutant Anaplastic Thyroid Cancer. J Clin Oncol 36, 7-13, doi:10.1200/JCO.2017.73.6785 (2018).
Subbiah, V. et al. Dabrafenib plus trametinib in patients with BRAF V600E-mutant anaplastic thyroid cancer: updated analysis from the phase II ROAR basket study. Ann Oncol 33, 406-415 (2022).
Yang, C. Y. et al. Upfront liquid next-generation sequencing in treatment-naive advanced non-small cell lung cancer patients: A prospective randomised study in the Taiwanese health system. Eur J Cancer 193, 113310, doi:10.1016/j.ejca.2023.113310 (2023).
Wu, H. et al. Anaplastic thyroid cancer: outcome and the mutation/expression profiles of potential targets. Pathol Oncol Res 21, 695-701, doi:10.1007/s12253-014-9876-5 (2015).
Kunstman, J. W. et al. Characterization of the mutational landscape of anaplastic thyroid cancer via whole-exome sequencing. Hum Mol Genet 24, 2318-2329, doi:10.1093/hmg/ddu749 (2015).
Kasaian, K. et al. The genomic and transcriptomic landscape of anaplastic thyroid cancer: implications for therapy. Bmc Cancer 15, 984, doi:10.1186/s12885-015-1955-9 (2015).
Sandulache, V. C. et al. Real-time genomic characterization utilizing circulating cell-free DNA in patients with anaplastic thyroid carcinoma. Thyroid : official journal of the American Thyroid Association 27, 81-87, doi:10.1089/thy.2016.0076 (2017).
Subbiah, V. et al. Dabrafenib plus trametinib in patients with BRAF V600E-mutant anaplastic thyroid cancer: updated analysis from the phase II ROAR basket study. Ann Oncol 33, 406-415, doi:10.1016/j.annonc.2021.12.014 (2022).
Chang, C. F. et al. The impact of BRAF targeting agents in advanced anaplastic thyroid cancer: a multi-institutional retrospective study in Taiwan. Am J Cancer Res 12, 5342-5350 (2022).
da Silva, T. N. et al. Target therapy for BRAF mutated anaplastic thyroid cancer: a clinical and molecular study. Eur J Endocrinol 188, doi:10.1093/ejendo/lvac011 (2023).
Santarpia, M. et al. Targeted therapies for KRAS-mutant non-small cell lung cancer: from preclinical studies to clinical development-a narrative review. Transl Lung Cancer Res 12, 346-368, doi:10.21037/tlcr-22-639 (2023).
Arbour, K. et al. 652O Preliminary clinical activity of RMC-6236, a first-in-class, RAS-selective, tri-complex RAS-MULTI (ON) inhibitor in patients with KRAS mutant pancreatic ductal adenocarcinoma (PDAC) and non-small cell lung cancer (NSCLC). Ann Oncol 34, S458 (2023).
Salzmann, M. et al. MEK inhibitors for pre-treated, NRAS-mutated metastatic melanoma: A multi-centre, retrospective study. Eur J Cancer 166, 24-32, doi:10.1016/j.ejca.2022.02.008 (2022).
de Braud, F. et al. Initial evidence for the efficacy of naporafenib in combination with trametinib in nras-mutant melanoma: Results from the expansion arm of a phase ib, open-label study. J Clin Oncol 41, 2651-2660, doi:10.1200/JCO.22.02018 (2023).
Konstantinopoulos, P. A., Ceccaldi, R., Shapiro, G. I. & D'Andrea, A. D. Homologous Recombination Deficiency: Exploiting the Fundamental Vulnerability of Ovarian Cancer. Cancer Discov 5, 1137-1154, doi:10.1158/2159-8290.CD-15-0714 (2015).
Genta, S., Martorana, F., Stathis, A. & Colombo, I. Targeting the DNA damage response: PARP inhibitors and new perspectives in the landscape of cancer treatment. Crit Rev Oncol Hematol 168, 103539, doi:10.1016/j.critrevonc.2021.103539 (2021).
Wu, C. E., Pan, Y. R., Yeh, C. N. & Lunec, J. Targeting P53 as a Future Strategy to Overcome Gemcitabine Resistance in Biliary Tract Cancers. Biomolecules 10, doi:10.3390/biom10111474 (2020).
Pan, Y. R., Wu, C. E. & Yeh, C. N. ATM Inhibitor Suppresses Gemcitabine-Resistant BTC Growth in a Polymerase theta Deficiency-Dependent Manner. Biomolecules 10, doi:10.3390/biom10111529 (2020).
Chen, C. P. et al. Wee1 inhibition by MK1775 potentiates gemcitabine through accumulated replication stress leading to apoptosis in biliary tract cancer. Biomed Pharmacother 166, 115389, doi:10.1016/j.biopha.2023.115389 (2023).
Tarasova, V. D. et al. Characterization of the Thyroid Cancer Genomic Landscape by Plasma-Based Circulating Tumor DNA Next-Generation Sequencing. Thyroid, doi:10.1089/thy.2023.0204 (2023).
Tangella, L. P., Clark, M. E. & Gray, E. S. Resistance mechanisms to targeted therapy in BRAF-mutant melanoma - A mini review. Biochim Biophys Acta Gen Subj 1865, 129736, doi:10.1016/j.bbagen.2020.129736 (2021).
Facchinetti, F. et al. Molecular mechanisms of resistance to BRAF and MEK inhibitors in BRAF(V600E) non-small cell lung cancer. Eur J Cancer 132, 211-223, doi:10.1016/j.ejca.2020.03.025 (2020).
Porter, A. & Wong, D. J. Perspectives on the treatment of advanced thyroid cancer: Approved therapies, resistance mechanisms, and future directions. Front Oncol 10, 592202, doi:10.3389/fonc.2020.592202 (2020).
Cabanillas, M. E. et al. Acquired secondary ras mutation in BRAF(V600E)-mutated thyroid cancer patients treated with BRAF inhibitors. Thyroid : official journal of the American Thyroid Association 30, 1288-1296, doi:10.1089/thy.2019.0514 (2020).
Bagheri-Yarmand, R. et al. RAC1 alterations induce acquired dabrafenib resistance in association with anaplastic transformation in a papillary thyroid cancer patient. Cancers 13, doi:10.3390/cancers13194950 (2021).
Chang, J. W. et al. Genomic and tumour microenvironmental biomarkers of immune checkpoint inhibitor response in advanced Taiwanese melanoma. Clin Transl Immunology 12, e1465, doi:10.1002/cti2.1465 (2023).

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Genomic landscape characterization and comparative analysis of tissue and liquid-based next-generation sequencing in anaplastic thyroid carcinoma in Taiwan

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Abstract

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INTRODUCTION

RESULTS

The baseline characteristics of 26 patients with ATC enrolled in the current study

Tissue NGS

Liquid NGS

Paired tissue and liquid NGS

Resistance

DISCUSSION

MATERIALS AND METHODS

Declarations

References

Additional Declarations

Supplementary Files

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