Anaplastic thyroid cancer: genome-based search for new targeted therapy options

in Endocrine Connections
View More View Less
  • 1 Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
  • | 2 European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany
  • | 3 Department of General, Visceral, Tumor and Transplant Surgery, University Hospital Cologne, Cologne, Germany
  • | 4 Institute of Zoology, University of Cologne Germany, Cologne, Germany

Correspondence should be addressed to H Alakus: hakan.alakus@uk-koeln.de

*(D A Hescheler and M J M Hartmann contributed equally to this work)

Open access

Objective

Anaplastic thyroid cancer (ATC) is one of the most lethal human cancers with meager treatment options. We aimed to identify the targeted drugs already approved by the Food and Drug Administration (FDA) for solid cancer in general, which could be effective in ATC.

Design

Database mining.

Methods

FDA-approved drugs for targeted therapy were identified by screening the databases of MyCancerGenome and the National Cancer Institute. Drugs were linked to the target genes by querying Drugbank. Subsequently, MyCancerGenome, CIViC, TARGET and OncoKB were mined for genetic alterations which are predicted to lead to drug sensitivity or resistance. We searched the Cancer Genome Atlas database (TCGA) for patients with ATC and probed their sequencing data for genetic alterations which predict a drug response.

Results

In the study,155 FDA-approved drugs with 136 potentially targetable genes were identified. Seventeen (52%) of 33 patients found in TCGA had at least one genetic alteration in targetable genes. The point mutation BRAF V600E was seen in 45% of patients. PIK3CA occurred in 18% of cases. Amplifications of ALK and SRC were detected in 3% of cases, respectively. Fifteen percent of the patients displayed a co-mutation of BRAF and PIK3CA. Besides BRAF-inhibitors, the PIK3CA-inhibitor copanlisib showed a genetically predicted response. The 146 (94%) remaining drugs showed no or low (under 4% cases) genetically predicted drug response.

Conclusions

While ATC carrying BRAF mutations can benefit from BRAF inhibitors and this effect might be enhanced by a combined strategy including PIK3CA inhibitors in some of the patients, alterations in BRAFWT ATC are not directly targeted by currently FDA-approved options.

Abstract

Objective

Anaplastic thyroid cancer (ATC) is one of the most lethal human cancers with meager treatment options. We aimed to identify the targeted drugs already approved by the Food and Drug Administration (FDA) for solid cancer in general, which could be effective in ATC.

Design

Database mining.

Methods

FDA-approved drugs for targeted therapy were identified by screening the databases of MyCancerGenome and the National Cancer Institute. Drugs were linked to the target genes by querying Drugbank. Subsequently, MyCancerGenome, CIViC, TARGET and OncoKB were mined for genetic alterations which are predicted to lead to drug sensitivity or resistance. We searched the Cancer Genome Atlas database (TCGA) for patients with ATC and probed their sequencing data for genetic alterations which predict a drug response.

Results

In the study,155 FDA-approved drugs with 136 potentially targetable genes were identified. Seventeen (52%) of 33 patients found in TCGA had at least one genetic alteration in targetable genes. The point mutation BRAF V600E was seen in 45% of patients. PIK3CA occurred in 18% of cases. Amplifications of ALK and SRC were detected in 3% of cases, respectively. Fifteen percent of the patients displayed a co-mutation of BRAF and PIK3CA. Besides BRAF-inhibitors, the PIK3CA-inhibitor copanlisib showed a genetically predicted response. The 146 (94%) remaining drugs showed no or low (under 4% cases) genetically predicted drug response.

Conclusions

While ATC carrying BRAF mutations can benefit from BRAF inhibitors and this effect might be enhanced by a combined strategy including PIK3CA inhibitors in some of the patients, alterations in BRAFWT ATC are not directly targeted by currently FDA-approved options.

Introduction

Anaplastic thyroid cancer (ATC) is one of the most lethal human cancers with a historical median survival of 5–12 months and a 1-year survival rate of 20–60% (1, 2, 3). About 50% of patients have metastatic disease at the time of diagnosis (1) which generally requires a systemic therapy in addition to surgery and/or radiation therapy.

A recent single-institution retrospective study on 479 patients treated at the University of Texas MD Anderson Cancer Center over 20 years (3) revealed that targeted therapy and immunotherapy play an increasing role, resulting in significantly improved 1- and 2-year survival rates (59 and 42%, respectively). Median overall survival (OS) for patients treated with targeted therapy, regardless of their grouping, was 15.7 months compared with 7.6 months in patients not having received any targeted therapy (3). In another single-institution retrospective study with 120 Korean ATC patients, tyrosine kinase inhibition (TKI) was also associated with favorable OS in a multivariate analysis (4).

Although to date, half of the patients are still receiving cytotoxic chemotherapy (3), first-line therapy is progressively shifting toward targeted therapy options as precision medicine and the increasing role of molecular testing in clinical routine is evolving (5). The Food and Drug Administration (FDA) approval of the combination BRAF/MEK inhibitor therapy for the management of BRAF V600E-positive ATC in 2018 was a major first step in this direction. Besides BRAF (dabrafenib and vemurafenib) and MEK inhibitors (trametinib and cobimetinib), TKI like cabozantinib, lenvatinib, sorafenib and pazopanib, the mTOR inhibitor sapanisertib, PPAR-γ agonist efatutazone, the ALK inhibitor ceritinib, the VEGF inhibitor bevacizumab and several combined treatment and immunotherapeutic agents (pembrolizumab, ipilimumab, nivolumab, durvalumab, tremelimumab, spartalizumab and atezolizumab) are currently being tested in clinical trials (Table 1) (2).

Table 1

Overview of clinical trials involving ATC (data from Al-Jundi et al.(37)). The table lists the clinical trials on BRAF/MEK inhibitors, kinase inhibitors, mTOR inhibitors and combination therapies in anaplastic thyroid cancer in terms of study design, primary outcomes and reported adverse events. Data from Al-Jundi et al.(37) has been updated with current clinical trials still recruiting. Many trials do not focus on ATC exclusively, but rather include ATC among other thyroid cancer types.

Drug/clinicalTrials.gov ID/referenceMechanism of actionEnrolled patientsaPrimary outcomeStudy designResultsReported adverse events
BRAF inhibitors
 Vemurafenib

 Hyman et al. (38)
BRAFV600EATC: 7 (multiple BRAFV600E mutant tumors)ORRPhase II, basket trialPR: 14%

CR: 14%
Rash, fatigue, arthralgia
BRAF/MEK inhibitor combination
 Dabrafenib and Trametinib

 Subbiah et al. (17)
Dabrafenib: BRAFV600E

Trametinib: MEK1, MEK2
ATC: 16 locally advanced or metastatic BRAFV600Emutant diseaseORRPhase II, single arm, open labelPR: 63%

CR: 6%
Skin papilloma hyperkeratosis, alopecia, fatigue, fever, diarrhea, acneiform rash
 Trametinib and Dabrafenib

 NCT04739566
BRAF-positive ATC, neoadjuvant estimated enrolment: 18ORRPhase II, single arm, open label, recruitingN/A

estimated end date: 01/26 (clinicaltrials.gov)
N/A
Tyrosine kinase inhibitors
 Axitinib

 Cohen et al. (39)
VEGFR, PDGFR, KITDTC: 45 (resistant to or not appropriate for RAI)

MTC: 11

ATC 11
ORRPhase II, single arm, open labelORR of 30%

SD for _ 16 weeks: 38%

PFS: 18.1 months
Fatigue, diarrhea, nausea, anorexia, hypertension, stomatitis
 Lenvatinib

 Tahara et al. (28)
VEGFR, PDGFR, EGFR, RET, KITEnrolled all types of thyroid cancer, but results reported one cohort for 17 patients with ATCSerious/non-serious AEPhase II, single arm, open labelMost frequent AE (decreased appetite, 82%; HTN, 82%; fatigue, 59%; nausea, 59%; proteinuria, 59%)

Secondary endpoints: ORR: 24%

Median PFS: 7.4 months

Median OS
Hypertension, diarrhea, fatigue, anorexia, weight loss, nausea
 Lenvatinib

 NCT02726503
ATC

estimated enrolment: 39
OSPhase II, single arm, open labelN/A

completed 03/20, no results published yet
 Pazopanib

 Bible et al. (27)
VEGFR, FGFR, PDGFR, RET, KITATC: 15 (advanced or metastatic disease)Tumor response ratePhase II, two arms, open labelNo responseFatigue, skin and hair hypopigmentation, diarrhea, nausea
 Selpercatinib

 NCT04759911
VEGFR, FGFR, RETThyroid cancer with RET alterations (including ATC)

estimated enrolment: 30
ORRPhase II, single arm, open label, recruitingN/A

estimated end date: September 24 (clinicaltrials.gov)
N/A
 Sorafenib

 Capdevila et al. (40)
VEGFR, PDGFR, RET, KIT, FLTDTC: 16

MTC: 15

ATC: 3 (metastatic progressive unsuitable for surgery, RAI, or radiotherapy)
ORRRetrospective, Spanish o_-label-sorafenib-use programDTC PR: 19%

MTC PR: 47%

ATC PR: 33%
Hand–foot skin reaction, diarrhea, alopecia, skin rash or desquamation
 Sunitinib

 Ravaud et al. (26)
VEGFR, PDGFR, RET, KIT, FLTDTC: 41 (RAI resistant)

MTC: 26

ATC: 4 (sunitinib as a first-line anti-angiogenic therapy)
ORRPhase II, single arm, open labelDTC PR: 22%

MTC PR: 38.5%

ATC: no response
Cytopenia, diarrhea, fatigue, hand–foot skin reaction, nausea, musculoskeletal pain, hypertension
Serine/threonine kinase inhibitors
 Abemaciclib

 NCT04552769
CDK4

CDK6
Metastatic or locally advanced anaplastic/undifferentiated thyroid cancer

estimated enrolment: 17
ORRPhase II, single arm, open label, recruitingN/A

estimated end date: September 23 (clinicaltrials.gov)
N/A
mTOR inhibitors
 Everolimus

 Lim et al. (41)
mTORThyroid cancer (all subtypes): 38Disease control rate (PR + SD > 12 weeks)Phase II, single arm, open labelPR: 5% (2/38, one PTC patient and one FTC)

SD: 76%
Mucositis, anorexia, abnormal, liver enzymes, acneiform rash
 Everolimus

 Hanna et al. (42)
DTC: 33

MTC: 10

ATC: 7
PFSPhase II, single arm, open labelDTC: Median PFS 12.9 months, PR 1/38

MTC: Median PFS 13.1 months, PR 1/10

ATC: Median PFS 2.2 months, PR 1/7
 MLN0128

 NCT02244463
Metastatic ATC

estimated Patients: 25
PFSPhase II, single arm, open label, recruitingN/A

estimated end date: January 22 (clinicaltrials.gov)
N/A
Combination therapies under investigation
 Atezolizumab

 Bevacizumab

 Cobimetinib

 Vemurafenib

 Paclitaxel

 Nab-Paclitaxel

 NCT03181100
Atezolizumab: PD-1L

Bevacizumab: VEGFR

Cobimetinib: MEK1, MEK2

Vemurafenib: BRAFV600E

Paclitaxel: antimicrotubule agent

Nab-Paclitaxel: albumin-stabilized antimicrotubule agent
ATC and poorly differentiated thyroid cancer

estimated enrolment: 50
OSPhase II, open label, parallel assignment, recruitingN/A

estimated end date: July 23 (clinicaltrials.gov)
N/A
 BCA101 and Pembrolizumab

 NCT04429542
BCA101: EGFR, TGFb

Pembrolizumab: PD-1 receptor
EGFR-driven Advanced solid tumors (including ATC)

estimated enrolment: 292
Safety and tolerability of BCA101, MTDPhase I/Ib, open label, parallel assignment, recruitingN/A

estimated end date: June 23
N/A
 Cabozantinib and Atezolizumab

 The CABATEN study

 NCT04400474
Cabozantinib: VEGF, RET, KIT, FLT-3, TEI-2, TRKB, AXL

Atezolizumab: PD-1L
Neuroendocrine tumor, ATC, adenocarcinoma, pheochromocytoma, paraganglioma

estimated enrolment: 144
ORRPhase II, single arm, open label, recruitingN/A

estimated end date: March 2 (clinicaltrials.gov)
N/A
 Cemiplimab, Trametinib and Dabrafenib

 NCT04238624
Cemiplimab: PD-1 receptor

Dabrafenib: BRAFV600E

Trametinib: MEK1, MEK2
BRAF-V600E mutant ATC

Estimated enrolment: 25
ORRPhase II, single arm, open label, recruitingN/A

estimated end date: June 22 (clinicaltrials.gov)
N/A
 Lenvatinib and Pembrolizumab

 NCT04171622
Lenvatinib: VEGFR, PDGFR, EGFR, RET, KIT

Pembrolizumab: PD-1 receptor
Stage IVB locally advanced and unresectable or Stage IVC metastatic anaplastic thyroid cancer

estimated patients enrolled: 25
OSPhase II, simgle arm, open label, recruitingN/A

estimated end date: September 22 (clinicaltrials.gov)
N/A
 Pazopanib, Paclitaxel and IMRT

 NCT01236547
Pazopanib: VEGFR, FGFR, PDGFR, RET, KIT

Paclitaxel: antimicrotubule agent

IMRT: intensity-modulated radiation therapy
ATC: 36OSPhase II, randomized, two arms, double blind, placebo controlled, active – not recruitingOS Placebo: 29.0%

OS Pazopanib: 37.1% (clinicaltrials.gov)
N/A
 Pembrolizumab, Trametinib and Dabrafenib

 NCT04675710
Pembrolizumab: PD-1 receptor

Dabrafenib: BRAFV600E

Trametinib: MEK1, MEK2
BRAF-V600E mutant ATC, neoadjuvant

Estimated enrolment: 30
ORRPhase II, single arm, open label, recruitingN/A

estimated end date: June 24 (clinicaltrials.gov)
N/A
 Trametinib and Paclitaxel

 NCT03085056
Trametinib: MEK1, MEK2

Paclitaxel: antimicrotubule agent
ATC

estimated enrolment: 12
PFSPhase I, single arm, open label, recruitingN/A

estimated end date: September 23 (clinicaltrials.gov)
N/A

aFor placebo-controlled studies, only the number for patients enrolled under the treatment arm is mentioned (data from Al-Jundi et al.(37)).

AE, adverse event; ATC, anaplastic thyroid cancer; CR, complete response; DCR, disease control rate; DTC, differentiated thyroid cancer; FDA, US Food and Drug Administration; FTC, follicular thyroid cancer; FGFR, fibroblast growth factor receptor; FTL-3, FMS-like receptor tyrosine kinase-3; HR, hazard ratio; MTC, medullary thyroid cancer; MTD, maximum tolerated dose; N/A, not available; ORR, objective response rate; OS, overall survival; PD, progressive disease; PD-1, programmed cell death protein 1; PDGFR, platelet-derived growth factor receptor PD; PFS, progression-free survival; PR, partial response; PTC, papillary thyroid cancer; RAI, radioactive iodine; SD, stable disease; TKI, tyrosine kinase inhibitor; RET, rearranged during transfection; VEGFR, vascular endothelial growth factor receptor.

However, ATC is an orphan disease, accounting for only 3% of thyroid cancers (1). Given the low number of patients that can consequently be recruited for clinical studies, a thorough in silico screening of possible treatment strategies offers an intriguing approach for planning future targeted therapy trials.

The aim of this study is to explore if any of the 155 drugs which have been approved by the FDA for targeted therapy of other solid cancers may play a role in the treatment of ATC based on such an in silico analysis of genetic alterations in ATC.

Methods

All data were obtained from open access databases and referenced accordingly. The study was conducted in accordance with the provisions of the Declaration of Helsinki and local laws, as previously described (6).

Genetic alterations in anaplastic thyroid cancer

We identified 15 studies that reported genomic data on a total of 809 ATC patients (Table 2). The data set of Landa et al.(7) provides the largest available whole-exome sequencing (WES) data set and we therefore based our drugability estimates on this study. Systematic tumor genomics data of ATC generated mutation significance as indicated by MutSig and putative copy number alterations as indicated by GISTIC 2.0 were extracted from Landa et al.(7). We included datasets of anaplastic thyroid cancers (n  = 33) and excluded poorly differentiated thyroid cancers (n  = 84 pat). Mutation variants and copy number variations (CNVs) directly or indirectly affecting genes of potentially targeted therapy options were identified. As the validation study for our work, we used the study by Pozdeyev et al.(8), which provides information on the targeted sequencing of 196 ATC tumors.

Table 2

Genomic data concerning ATC. The table lists all genomic data found involving anaplastic thyroid cancer. Shown are the number of samples, the main alternated genes in % of the whole sample group and their nationality, gender distribution in % and median age accordingly.

Studyn of samplesType of sequencing/number of genesGenes % of totalNationalityGender in % m/f (/NA)

Median age in years

BRAFPIK3CATP53TERTKRASNRASHRAS
Nikiforova et al. 2013 (43)27TS 1226%11%30%N/A4%19%0%USAN/AN/A
Kunstmann et al. 2015 (44)22WES27%12%29%N/A9%6%4%USA/Sweden41/5973
Jeon et al. 2016 (45)11TS 52091%18%73%N/A9%N/AN/AKorea27/7375
Landa et al. 2016 (7)33TS 34145%18%73%73%9%18%6%USA27/24(/49)66
Latteyer et al. 2016 (21)30TS 96%N/A%60%N/A3%13%7%Germany55/4570
Tiedje et al. 2017 (46)118TS 1711%12%55%73%8%8%4%Germany48/5265
Ibrahimpasic et al. 2017 (47)57TS 41040%4%9%60%0%25%4%USA44/56>45
Bonhomme et al. 2017 (48)94TS 5014%6%54%54%4%30%8%France40/6068
Chen et al. 2018 (49)12TS 46/5025%0%25%N/A11%17%11%USA48/5255
Pozdeyev et al. 2018 (8)196TS 22941%14%65%65%27%USAN/AN/A
Duan et al. 2019 (50)25TS 1856%44%60%63%12%16%0%China48/5264
Yoo et al. 2019 (51)13WGS41%11%48%59%0%30%15%Korea37/6361
14TGS – 71 genes
Ravi et al. 2019 (52)11WES18%18%55%36%0%13%13%SwedenN/A71
12RNA-Seq
Xu et al. 2020 (53)107TS (multiple platforms)45%18%63%75%24%USA/Australia46/5468
Lai et al. 2020 (54)27TS 726%15%70%82%11%30%0%Taiwan49/5175

ATC, anaplastic thyroid cancer; BRAF, v-Raf murine sarcoma viral oncogene homolog B; f, female; HRAS, gene encoding for the H-Ras (Harvey Rat sarcoma virus) protein; KRAS, gene encoding for the K-Ras (Kirsten rat sarcoma virus) protein; n, number; NRAS, neuroblastoma RAS viral oncogene homolog; N/A, not available; m, male; PIK3CA, gene coding for phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha; TGS, third generation sequencing; TERT, gene encoding for telomerase reverse transcriptase; tp53, gene encoding for tumor protein p53; TS, target sequencing; WES, whole exome sequencing; WGS, whole genome sequencing.

FDA-approved targeted therapy and their biological targets

In order to find new therapeutic options in anaplastic thyroid cancer, we first identified all FDA-approved drugs for any cancer therapy by searching the databases of National Cancer Institute (https://www.cancer.gov/news-events/cancer-currents-blog/2017/aliqopa-fda-follicular-lymphoma) and MyCancerGenome (https://www.mycancergenome.org/content/page/what-is-my-cancer-genome/), as previously described (6) (database query 09/2021) (Supplementary Table 1 (http://doi.org/10.6084/m9.figshare.14937117), see section on supplementary materials given at the end of this article). We identified 155 FDA/EMA-approved drugs targeting cancer genetic alterations. These drug lists were linked to 136 genes by querying databases of the University of Texas MD Anderson Cancer Center (https://pct.mdanderson.org/) and Drugbank (9), which encode the potential sites of binding and action of each drug (Supplementary Table 1 (http://doi.org/10.6084/m9.figshare.14937117)). Special attention was given to specific genetic alterations resulting in either drug sensitivity or drug resistance to targeted therapy. Hereby the expert-crowdsourced, publication-based databases from MyCancerGenome (https://www.mycancergenome.org/content/page/what-is-my-cancer-genome/), CIViC (10), TARGET (https://software.broadinstitute.org/cancer/cga/target) and OncoKB (11) (Supplementary Table 2 (http://doi.org/10.6084/m9.figshare.14937117)) were mined.

Drug response prediction

Drug response prediction was calculated as previously described (6). Briefly, the genetic datasets of ATC were searched for (i) gain of function; (ii) CNV-amplification; (iii) specific genetic alterations.

The data on approved drugs and their targets were integrated with data on genomic alterations from patients annotated with the biologically relevant genetic alterations. The prediction of whether a patient might respond to a given drug is based on the following criteria:

  1. The gene underlying the FDA-approved drug target shows a copy number increase in the ATC dataset of the TCGA study.

  2. The drug targets a gene whose product shows a gain of function in the TCGA dataset.

  3. The drug shows literature-based effectiveness on a specific alteration found in the TCGA dataset such as indicated in the FDA guidelines (7).

Gain of function

Gene alterations resulting in gain of function were determined by querying the databases OncoKB (11) and CIViC (10). These databases derive a biological effect score from publications. Gene alterations were defined as ‘gain of function’ according to the OncoKB-score (gain of function or like gain of function), CIViC score (pathogenetic, likely pathogenetic or positive), as well as mutations affecting Chang´s mutational hotspots (12).

CNV-amplification

The data from cBioPortal (13) is annotated with a copy number analysis algorithm (GISTIC 2.0 (14)), which indicates the copy number level per gene: ‘− 2’ deep loose, ‘− 1’ shallow loose, ‘0’ diploid, ‘1’ low-level gain and ‘2’ high-level amplification. The threshold of high-level amplification ‘2’ was chosen to signify an occurrence of a copy number increase in each tissue sample.

Specific gene alterations

The expert-crowdsourced, publication-based databases (MyCancerGenome, CIVIC, TARGET and OncoKB) list-specific genetic alterations affecting targeted therapy, which were checked on the dataset of anaplastic thyroid cancer (7).

Special attention was given as well to indirect gene alterations affecting the resistance or sensitivity of the drug response. Because of partially overlapping data, the algorithm favored gene alterations affecting drug resistance more than drug sensitivity and secondly favored in order of higher level of evidence.

Mutation hotspot analysis

Since mutation hotspots play an important role in thyroid cancer, the mutation datasets were screened to detect mutation hotspots and their frequency. Mutation variants known to be responsive to FDA-approved drugs according to the database DOCM (15) were also searched.

Analysis of genetic coalterations

A co-alteration analysis was performed by querying cBioPortal (13). All genes which were altered in ≥3 (9%) patients were included in this analysis. χ2-tests were performed to identify different distributions of genetic alterations between BRAF-unalterated and BRAF-alterated groups.

Currently recruiting studies on ATC

The databases of the International Conference on Harmonisation of technical requirements for registration of pharmaceuticals for human use – Good clinical practice network (https://ichgcp.net/clinical-trials-registry) and ClinicalTrials.gov (https://clinicaltrials.gov/) were searched for the following terms to identify trials currently recruiting and including patients with ATC: ‘anaplastic thyroid cancer’, ‘thyroid cancer’ and ‘ATC’.

Results

Genetic alterations in targeted genes

To date there are 155 already FDA-approved targeted drugs which could potentially aid ATC patients. According to the National Cancer Institute (https://www.cancer.gov/news-events/cancer-currents-blog/2017/aliqopa-fda-follicular-lymphoma) and MyCancerGenome (https://www.mycancergenome.org/content/page/what-is-my-cancer-genome/ ) databases, these 155 approved drugs target 136 genes (Supplementary Table 1 (http://doi.org/10.6084/m9.figshare.14937117)).

Twenty-six (79%) of 33 ATC patients from Landa et al. (7) had at least one genetic alteration in the target genes; there were 53 genetic alterations in 24 (17.6%) of 136 targetable genes, with 23 putative driver genetic alterations in 4 genes (BRAF, PIK3CA, ALK and SRCFig. 1A). Activating point mutations in the oncogene BRAF were seen in 15 (45.5%) of 33 cases – in all cases occurring as a BRAF V600E mutation. Putative driver PIK3CAmutations were seen in 18% of cases. A similar prevalence of alterations in BRAF and PIK3CA is reported for the 196 tumors examined by Pozdeyev et al.(8) (41 and 14% respectively, Table 2). Genetic alterations in BRAF and PIK3CAwere not mutually exclusive (P  = 0.13) and occurred in 15% of all and 33% of BRAF-mutated cases. Amplifications of ALK and SRC were detected in 3% of cases respectively (Fig. 1).

Figure 1
Figure 1

This figure shows the results of potential targetable genetic alterations in anaplastic thyroid cancer. (A) Seventeen (52%) of 33 patients had at least one putative activating genetic alteration in the targetable genes. There were 53 genetic alterations in 24 genes, respectively 23 known putative driver genetic alterations in 4 genes (BRAF, PIK3CA, ALK and SRC) as shown in the bar chart. (B) In the mutation analysis besides BRAF V600E, other mutation hotspots occurred in NRAS Q61 (18%, 6/33), PIK3CA E545 (9%, 3/33), PIK3CA E542 (6%, 2/33), HRAS G13 (6%, 2/33) and others. (C) The figure shows Co-Alterations in comparison BRAF altered group (n  = 15) to BRAF unaltered group (n  = 18); created by cBioPortal (13). BRAF mutation occurred together with TERT-alterations rather than in the BRAF-unaltered group (14/15 vs 10/18 pat, P  = 0.0183) and PIK3CA (5/15 vs 2/18, P  = 0.13). On the other hand, TP53 alterations occurred more frequently in the BRAF unalterated group (8/15 vs 16/18 pat, P  = 0.029), as well as NRAS, PTEN and others.

Citation: Endocrine Connections 11, 4; 10.1530/EC-21-0624

Mutational hotspot analysis

The most frequently affected pathway was the RAS pathway, including the BRAFV600 mutational hotspot (45%), followed by the NRASQ61 (18.2%, 6/33 cases). The PIK3CA pathway was affected by activating mutations in 6 (18%) of 33 cases, including PIK3CAE545 (9.1%, 3/33 cases), PIK3CA E542 (6%, 2/33 cases) and PIK3CA E81K (Fig. 1B).

Analysis of genetic co-alterations

In the BRAF-mutated group, TERT-alterations were significantly more common than in the WT group (93.3% vs 55.6%, P  = 0.0183). In the WT group TP53 (88.9% vs 53.3%, P  = 0.029), NRAS (33.3% vs 0%, P  = 0.017) and PTEN (27.8% vs 0%, P  = 0.036) alterations were significantly more frequent (Fig. 1C).

Potential drug options

We predicted the drug response in the ATC tumor samples as previously described (6). The in silico analysis specifically identified BRAF inhibitors (selective BRAF inhibitors or multikinase i.a. BRAF inhibitors). The PIK3CA-inhibitor copanlisib showed a predicted response in 18% of cases. The 146 remaining drugs showed no or low (under 4% cases) genetically predicted drug response in ATC (Fig. 2).

Figure 2
Figure 2

Percentages of ATC cases, harboring a targetable genetic alteration, predicting drug responsiveness for FDA-approved drugs. BRAF-inhibitors (selective or multikinase BRAF inhibitors) are genetically predicted for drug response in ATC. PIK3CA is a targetable alteration found in 18% of patients, making the PIK3CA inhibitor copanlisib an additional genetically predicted therapy option, followed by 3% for VEGFR2/SRC inhibitor apatinib and the ALK inhibitors.

Citation: Endocrine Connections 11, 4; 10.1530/EC-21-0624

Discussion

Several randomized and non-randomized clinical trials have been conducted in ATC during the last years (Table 1). While in 2019 the Surveillance, Epidemiology, and End Results database still reported no improvement in OS between 1986 and 2015 (16) there are clear signs of progress. In 2020, a retrospective analysis of 479 patients treated at the MD Anderson Cancer Center over the course of 20 years revealed a significant increase in BRAF screening from 17% between 2000 and 2013 to 97% between 2017 and 2019. Further, the number of patients receiving targeted therapy increased from 9 to 61% and the median OS for patients treated with targeted therapy increased from 7.6 months in patients not having received any targeted therapy to 15.7 months for the same time-frames (3). Targeted therapies administered to patients at MD Anderson included dabrafenib, trametinib, vemurafenib, cobimetinib, larotrectinib, everolimus, pazopanib, bevacizumab, lenvatinib, selpercatinib, lenalidomide and cetuximab. The median OS increased regardless of the specific therapy scheme (3).

The focus of the present study was to screen targeted cancer drugs approved by the FDA for other solid cancers and to identify those that may play any role in ATC based on its genetic alterations. Since these drugs are already approved, the side-effect profile is known which would lead to a faster approval in another cancer moiety such as ATC. While ATC prognosis is particularly poor, it is also relatively seldom, accounting for only 3% of all thyroid cancer (1). This hinders recruitment for clinical studies, and we consequently tried to build a systematic, in silico theoretical framework for future clinical targeted therapy research.

Fifteen studies covering more than 800 ATC samples were identified (Table 2). The largest WES dataset (7) was used for the discovery of druggability and the largest ATC cohort based on targeted sequencing (8) was defined for validation. Potentially targetable genes of FDA-approved targeted therapy included BRAF, PIK3CA, ALK and SRC (Fig. 1A). It needs to be mentioned that in 13 (39.4%) of 33 patients, the data set of Landa et al.(7) did not cover the whole gene set of 136 druggable genes. Therefore, some genes could be underrepresented (Supplementary Table 6).

The in silico analysis identified BRAF inhibitors, in particular the PIK3 inhibitor copanlisib, the VEGFR-2/c-SRC inhibitor apatinib, and the ALK inhibitors brigatinib, ceritinib, crizotinib and lorlatinib as possible targeted therapy agents for ATC (Fig. 2) (21). Although NRAS-Q61 was the second-highest frequency mutation hotspot (Fig. 1B and C), there are currently no FDA-approved drugs targeting this specific mutation. Besides BI1701963 targeting KRAS and Tipifarnib targeting HRAS(both being tested in ongoing studies), to the best of our knowledge, there is currently no drug targeting NRAS.

For the treatment of the BRAF-mutant ATC, the approval of combined BRAF and MEK inhibition with dabrafenib and trametinib in 2018 represented a major breakthrough with an objective response rate (ORR) of 69% and a stable disease (SD) rate of 19%, although almost all patients experienced adverse events (AE) and 42% grade ≥3 Aes (17). Heterogeneous mechanisms of resistance can modulate the efficacy of BRAF-inhibition, including activation of ERBB3, EGFR, PI3K, IL6, HGF/MET and the reactivation of the MAPK pathway through an acquired KRAS G12D mutation. Inhibition of ERK, a strategy for overcoming BRAF and MEKinhibition resistance in melanoma still needs to be tested in ATC (8).

Due to the coexistence of BRAF and PIK3CA mutations in 15% of tumors, future clinical trials might consider synchronous or metachronous combination therapies with PIK3 inhibitors, as described by Gibson et al.(18). The authors performed a multiregional genomic analysis of an exceptional responder to dual inhibition and demonstrated that this exceptional response was due to coexisting alterations in the MAPK and PI3K/AKT pathways. The PIK3CA inhibitor copanlisib has recently proved very successful in recurrent, indolent non-Hodgkin lymphoma (CHRONOS-3 study (19)) and is currently being tested in trials on radioiodine refractory thyroid cancer in order to improve radioiodine response (NCT04462471). To our best knowledge, there are no current trials testing copanlisib in combined treatments for ATC (Table 1).

ALK overexpression and mutation have been described in 11–20% of ATC patient samples (20, 21)). In the TCGA data, only amplifications of ALK were detected in 3% of ATC cases (7). The use of ceritinib, a well-tolerated, highly potent oral ALK-inhibitor, is documented in case reports (22) and is currently being tested in a multicenter, open-label trial (NCT02289144, Table 1).

There are case reports, describing the pre- (23) and postoperative (24) use of the selective VEGFR-2/c-SRC inhibitor apatinib in single patients, but no clinical studies have thus far been published.

BRAF inhibitors provide a good option in patients displaying this mutation. Small studies have used multikinase inhibitors for BRAF V600 WT patients. Sorafenib however exhibited a low ORR (10%), short median progression-free survival (PFS) (1.9 months) and OS (3.9 months) (25). In phase 2 trials, both sunitinib and pazopanib showed no overall response (26, 27). In phase 2 trials including 5–-17patients with ATC, there were PRs of 24–60% under lenvatinib treatment (28, 29). Thus, the two first-line agents for differentiated thyroid cancer (DTC) sorafenib and lenvatinib seem to have a poor response in ATC.

The genetic RET/PTCand NTRKrearrangements observed in papillary thyroid cancer have also been described in ATC (30). Selective RET inhibitors such as selpercatinib and pralsetinib have been approved by the FDA for RAI-refractory RET fusion thyroid cancer. Phase I–II trials including previously treated non-medullary TC (n  = 19) report a high response rate (79%) and a 1-year PFS of 64% (31). However, only 2 of the 19 non-medullary TC samples were anaplastic. RET mutations occur rather rarely in ATC (32). Instead, TRK fusions have been reported in 25% of ATC (32). For larotrectinib, a highly potent and selective inhibitor of all TRKs approved for the treatment of adult and pediatric patients with neurotrophic tyrosine receptor kinase (NTRK) fusions, the reported objective response rate for ATC pooled from available phase I/II trials was 29% (33). Additionally, larotrectinib was very well tolerated.

In the study by Pozdeyev et al.(8), TERT promoter mutations were common (65%). The reported coexistence with DTC (34, 35) suggests that they might contribute to the more aggressive DTC phenotype which is prone to conversion to ATC when an ATC-related ‘second hit’ genetic event occurs (8). Whether telomerase inhibitors like INO5401, Telomelysin and Imeltestat, which are currently being tested on myeloid malignancy, might also play a role in the treatment of ATC in the future is still unclear.

Since TP53 seems to be mutated in 9–73% of ATCs (Table 2), p53-activating compounds that are currently being tested on myeloid neoplasms and sarcomas (36) might also offer an option in the future.

The better understanding of the genetic basis of ATC with the identification of BRAF-mutant ATC led to an improvement for the treatment of some ATC patients, however, the median survival of 1.3 years is still quite poor and there is still no satisfying treatment for BRAF WT patients. Here we present the first systematic analysis of all currently available FDA-approved drug options in ATC based on genomic alterations reported from ATC tumor sequencing studies. We restricted this first in silico analysis on already FDA-approved studies as the hurdle to progress to further studies would be relatively low with a drug that has already been approved through clinical trials. However, our data show no new or surprising candidate drug. This could be due to the limited dataset of only 33 patients. We restricted our analysis to these 33 patients as these patients could be clearly identified as having ATC as opposed to poorly differentiated thyroid cancer or other types of TC. It would be interesting to repeat this analysis as more tumor samples are sequenced and are deposited on databases. Further, the drug panel could be expanded significantly beyond FDA-approved drugs in order to identify drugs that could be tested in ATC cell lines as a screening tool before going into cell lines and then patients. Lastly, our software algorithm considers only direct gene targets rather than pathways. Therefore, drugs acting indirectly (like the MEK inhibitor selumetinib for NF1 alterations) might not have been considered sufficiently.

Conclusion

Based on the currently available genomic data, targeted therapy options for ATC are limited. PIK3 inhibition might be an option for combined strategies with BRAF inhibitors. Few patients might also benefit from VEGFR-2 or ALKinhibitors. However, even this limited dataset identified significant heterogeneity amongst tumor samples. Targeting treatment for BRAF WT tumors seems to be very limited and much more challenging.

Supplementary materials

This is linked to the online version of the paper at https://doi.org/10.1530/EC-21-0624.

Declaration of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This work did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.

Data availability

The datasets generated during and/or analyzed during the current study are available in the figshare repository, http://doi.org/10.6084/m9.figshare.14937117.

Code availability

The codes generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Author contribution statement

Daniel Hescheler and Hakan Alakus designed the computational model and framework. Daniel Hescheler, Hakan Alakus and Costanza Chiapponi carried out the implementation. Daniel Hescheler, Milan Hartmann, Burkhard Riemann, Maximilian Michel, Christiane Bruns, Hakan Alakus and Costanza Chiapponi contributed to the interpretation of the results. Daniel Hescheler, Milan Hartmann, Burkhard Riemann, Maximilian Michel, Christiane Bruns, Hakan Alakus and Costanza Chiapponi contributed critical feedback and helped shape the research, analysis and manuscript. Costanza Chiapponi and Daniel Hescheler wrote the first draft of the manuscript, and all authors critically revised the manuscript. All authors approved the final version of the manuscript. All authors decided to submit this study and agreed to be accountable for all aspects of the work as recommended by the ‘International Committee of Medical Journal Editors’ (ICMJE) authorship criteria.

References

  • 1

    Bible KC, Kebebew E, Brierley J, Brito JP, Cabanillas ME, Clark TJ, Di Cristofano A, Foote R, Giordano T & Kasperbauer J et al.2021 American Thyroid Association guidelines for management of patients with anaplastic thyroid cancer. Thyroid 2021 31 337386. (https://doi.org/10.1089/thy.2020.0944)

    • Search Google Scholar
    • Export Citation
  • 2

    Araque KA, Gubbi S, Klubo-Gwiezdzinska J. Updates on the management of thyroid cancer. Hormone and Metabolic Research 2020 52 562577. (https://doi.org/10.1055/a-1089-7870)

    • Search Google Scholar
    • Export Citation
  • 3

    Maniakas A, Dadu R, Busaidy NL, Wang JR, Ferrarotto R, Lu C, Williams MD, Gunn GB, Hofmann MC & Cote G et al.Evaluation of overall survival in patients with anaplastic thyroid carcinoma, 2000–2019. JAMA Oncology 2020 6 13971404. (https://doi.org/10.1001/JAMAONCOL.2020.3362)

    • Search Google Scholar
    • Export Citation
  • 4

    Park J, Jung HA, Shim JH, Park WY, Kim TH, Lee SH, Kim SW, Ahn MJ, Park K, Chung JH. Multimodal treatments and outcomes for anaplastic thyroid cancer before and after tyrosine kinase inhibitor therapy: a real-world experience. European Journal of Endocrinology 2021 184 837845. (https://doi.org/10.1530/EJE-20-1482)

    • Search Google Scholar
    • Export Citation
  • 5

    Salgado SA Evolution of anaplastic thyroid cancer management: perspectives in the era of precision oncology. Therapeutic Advances in Endocrinology and Metabolism 2021 12 20420188211054692. (https://doi.org/10.1177/20420188211054692)

    • Search Google Scholar
    • Export Citation
  • 6

    Hescheler DA, Plum PS, Zander T, Quaas A, Korenkov M, Gassa A, Michel M, Bruns CJ, Alakus H. Identification of targeted therapy options for gastric adenocarcinoma by comprehensive analysis of genomic data. Gastric Cancer 2020 23 627638. (https://doi.org/10.1007/s10120-020-01045-9)

    • Search Google Scholar
    • Export Citation
  • 7

    Landa I, Ibrahimpasic T, Boucai L, Sinha R, Knauf JA, Shah RH, Dogan S, Ricarte-Filho JC, Krishnamoorthy GP & Xu B et al.Genomic and transcriptomic hallmarks of poorly differentiated and anaplastic thyroid cancers. Journal of Clinical Investigation 2016 126 10521066. (https://doi.org/10.1172/JCI85271)

    • Search Google Scholar
    • Export Citation
  • 8

    Pozdeyev N, Gay LM, Sokol ES, Hartmaier R, Deaver KE, Davis S, French JD, Borre Vanden PV, LaBarbera DV & Tan AC et al.Genetic analysis of 779 advanced differentiated and anaplastic thyroid cancers. Clinical Cancer Research 2018 24 30593068. (https://doi.org/10.1158/1078-0432.CCR-18-0373)

    • Search Google Scholar
    • Export Citation
  • 9

    Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A, Grant JR, Sajed T, Johnson D, Li C & Sayeeda Z et al.DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Research 2018 46 D1074D1082. (https://doi.org/10.1093/nar/gkx1037)

    • Search Google Scholar
    • Export Citation
  • 10

    Griffith M, Spies NC, Krysiak K, McMichael JF, Coffman AC, Danos AM, Ainscough BJ, Ramirez CA, Rieke DT & Kujan L et al.CIViC is a community KnowledgeBase for expert crowdsourcing the clinical interpretation of variants in cancer. Nature Genetics 2017 49 170174. (https://doi.org/10.1038/ng.3774)

    • Search Google Scholar
    • Export Citation
  • 11

    Chakravarty D, Gao J, Phillips SM, Kundra R, Zhang H, Wang J, Rudolph JE, Yaeger R, Soumerai T & Nissan MH et al.OncoKB: a precision oncology knowledge base. JCO Precision Oncology 2017 2017 116. (https://doi.org/10.1200/PO.17.00011)

    • Search Google Scholar
    • Export Citation
  • 12

    Chang MT, Shrestha Bhattarai TS, Schram AM, Bielski CM, Donoghue MTA, Jonsson P, Chakravarty D, Phillips S, Kandoth C & Penson A et al.Accelerating discovery of functional mutant alleles in cancer. Cancer Discovery 2018 8 174183. (https://doi.org/10.1158/2159-8290.CD-17-0321)

    • Search Google Scholar
    • Export Citation
  • 13

    Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, Jacobsen A, Byrne CJ, Heuer ML & Larsson E et al.The cBio Cancer Genomics Portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discovery 2012 2 401404. (https://doi.org/10.1158/2159-8290.CD-12-0095)

    • Search Google Scholar
    • Export Citation
  • 14

    Mermel CH, Schumacher SE, Hill B, Meyerson ML, Beroukhim R, Getz G. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biology 2011 12 R41. (https://doi.org/10.1186/gb-2011-12-4-r41)

    • Search Google Scholar
    • Export Citation
  • 15

    Ainscough BJ, Griffith M, Coffman AC, Wagner AH, Kunisaki J, Choudhary MNK, McMichael JF, Fulton RS, Wilson RK & Griffith OL et al.DoCM: A database of curated mutations in cancer [Internet]. Nature Methods 2016 13 806807. (https://doi.org/10.1038/nmeth.4000)

    • Search Google Scholar
    • Export Citation
  • 16

    Lin B, Ma H, Ma M, Zhang Z, Sun Z, Hsieh IY, Okenwa O, Guan H, Li J, Lv W. The incidence and survival analysis for anaplastic thyroid cancer: a SEER database analysis. American Journal of Translational Research 2019 11 58885896. (available at: https://pubmed.ncbi.nlm.nih.gov/31632557/)

    • Search Google Scholar
    • Export Citation
  • 17

    Subbiah V, Kreitman RJ, Wainberg ZA, Cho JY, Schellens JHM, Soria JC, Wen PY, Zielinski C, Cabanillas ME & Urbanowitz G et al.Dabrafenib and trametinib treatment in patients with locally advanced or metastatic BRAF V600-mutant anaplastic thyroid cancer. Journal of Clinical Oncology 2018 36 713. (https://doi.org/10.1200/JCO.2017.73.6785)

    • Search Google Scholar
    • Export Citation
  • 18

    Gibson WJ, Ruan DT, Paulson VA, Barletta JA, Hanna GJ, Kraft S, Calles A, Nehs MA, Moore FD & Taylor-Weiner A et al.Genomic heterogeneity and exceptional response to dual pathway inhibition in anaplastic thyroid cancer. Clinical Cancer Research 2017 23 23672373. (https://doi.org/10.1158/1078-0432.CCR-16-2154-T)

    • Search Google Scholar
    • Export Citation
  • 19

    Matasar MJ, Capra M, Özcan M, Lv F, Li W, Yañez E, Sapunarova K, Lin T, Jin J & Jurczak W et al.Copanlisib plus rituximab versus placebo plus rituximab in patients with relapsed indolent non-Hodgkin lymphoma (CHRONOS-3): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet: Oncology 2021 22 678689. (https://doi.org/10.1016/S1470-2045(2100145-5)

    • Search Google Scholar
    • Export Citation
  • 20

    Murugan AK, Xing MM. Anaplastic thyroid cancers harbor novel oncogenic mutations of the ALK gene. Cancer Research 2011 71 44034411. (https://doi.org/10.1158/0008-5472.CAN-10-4041)

    • Search Google Scholar
    • Export Citation
  • 21

    Latteyer S, Tiedje V, König K, Ting S, Heukamp LC, Meder L, Schmid KW, Führer D, Moeller LC. Targeted next-generation sequencing for TP53, RAS, BRAF, ALK and NF1 mutations in anaplastic thyroid cancer. Endocrine 2016 54 733741. (https://doi.org/10.1007/S12020-016-1080-9)

    • Search Google Scholar
    • Export Citation
  • 22

    Godbert Y, De Figueiredo BH, Bonichon F, Chibon F, Hostein I, Pérot G, Dupin C, Daubech A, Belleannée G & Gros A et al.Remarkable response to crizotinib in woman with anaplastic lymphoma kinase-rearranged anaplastic thyroid carcinoma. Journal of Clinical Oncology 2015 33 e84e87. (https://doi.org/10.1200/JCO.2013.49.6596)

    • Search Google Scholar
    • Export Citation
  • 23

    Niu Y, Ding Z, Deng X, Guo B, Kang J, Wu B, Fan Y. A novel multimodal therapy for anaplastic thyroid carcinoma: 125I seed implantation plus apatinib after surgery. Frontiers in Endocrinology 2020 11 207. (https://doi.org/10.3389/fendo.2020.00207)

    • Search Google Scholar
    • Export Citation
  • 24

    Cheng L, Jiao Q, Jin Y, Fu H, Zhang H, Chen L. Initial therapy of advanced anaplastic thyroid cancer via targeting VEGFR-2: a case report. OncoTargets and Therapy 2019 12 1049510500. (https://doi.org/10.2147/OTT.S223727)

    • Search Google Scholar
    • Export Citation
  • 25

    Savvides P, Nagaiah G, Lavertu P, Fu P, Wright JJ, Chapman R, Wasman J, Dowlati A, Remick SC. Phase II trial of sorafenib in patients with advanced anaplastic carcinoma of the thyroid. Thyroid 2013 23 600604. (https://doi.org/10.1089/thy.2012.0103)

    • Search Google Scholar
    • Export Citation
  • 26

    Ravaud A, de la Fouchardière C, Caron P, Doussau A, Do Cao C, Asselineau J, Rodien P, Pouessel D, Nicolli-Sire P & Klein M et al.A multicenter phase II study of sunitinib in patients with locally advanced or metastatic differentiated, anaplastic or medullary thyroid carcinomas: mature data from the THYSU study. European Journal of Cancer 2017 76 110117. (https://doi.org/10.1016/j.ejca.2017.01.029)

    • Search Google Scholar
    • Export Citation
  • 27

    Bible KC, Suman VJ, Menefee ME, Smallridge RC, Molina JR, Maples WJ, Karlin NJ, Traynor AM, Kumar P & Goh BC et al.A multiinstitutional phase 2 trial of pazopanib monotherapy in advanced anaplastic thyroid cancer. Journal of Clinical Endocrinology and Metabolism 2012 97 31793184. (https://doi.org/10.1210/jc.2012-1520)

    • Search Google Scholar
    • Export Citation
  • 28

    Tahara M, Kiyota N, Yamazaki T, Chayahara N, Nakano K, Inagaki L, Toda K, Enokida T, Minami H & Imamura Y et al.Lenvatinib for anaplastic thyroid cancer. Frontiers in Oncology 2017 7 25. (https://doi.org/10.3389/fonc.2017.00025)

    • Search Google Scholar
    • Export Citation
  • 29

    Iyer PC, Dadu R, Ferrarotto R, Busaidy NL, Habra MA, Zafereo M, Gross N, Hess KR, Gule-Monroe M & Williams MD et al.Real-world experience with targeted therapy for the treatment of anaplastic thyroid carcinoma. Thyroid 2018 28 7987. (https://doi.org/10.1089/thy.2017.0285)

    • Search Google Scholar
    • Export Citation
  • 30

    Cabanillas ME, Ryder M, Jimenez C. Targeted therapy for advanced thyroid cancer: kinase inhibitors and beyond. Endocrine Reviews 2019 40 15731604. (https://doi.org/10.1210/er.2019-00007)

    • Search Google Scholar
    • Export Citation
  • 31

    Wirth LJ, Sherman E, Robinson B, Solomon B, Kang H, Lorch J, Worden F, Brose M, Patel J & Leboulleux S et al.Efficacy of selpercatinib in RET-altered thyroid cancers. New England Journal of Medicine 2020 383 825835. (https://doi.org/10.1056/NEJMoa2005651)

    • Search Google Scholar
    • Export Citation
  • 32

    Fullmer T, Cabanillas ME, Zafereo M. Novel therapeutics in radioactive iodine-resistant thyroid cancer. Frontiers in Endocrinology 2021 12 836. (https://doi.org/10.3389/FENDO.2021.720723/BIBTEX)

    • Search Google Scholar
    • Export Citation
  • 33

    Cabanillas ME, Drilon A, Farago AF, Brose MS, McDermott R, Sohal D, Oh D, Almubarak M, Bauman J & Chu E et al.Abstract 1916P: Larotrectinib treatment of advanced TRK fusion thyroid cancer. Annals of Oncology 31 (Suppl 4) 2020 S1086. (https://doi.org/10.1016/j.annonc.2020.08.1404)

    • Search Google Scholar
    • Export Citation
  • 34

    Oishi N, Kondo T, Ebina A, Sato Y, Akaishi J, Hino R, Yamamoto N, Mochizuki K, Nakazawa T & Yokomichi H et al.Molecular alterations of coexisting thyroid papillary carcinoma and anaplastic carcinoma: identification of tert mutation as an independent risk factor for transformation. Modern Pathology 2017 30 15271537. (https://doi.org/10.1038/MODPATHOL.2017.75)

    • Search Google Scholar
    • Export Citation
  • 35

    McKelvey BA, Umbricht CB, Zeiger MA. Telomerase reverse transcriptase (TERT) regulation in thyroid cancer: a review. Frontiers in Endocrinology 2020 11 485. (https://doi.org/10.3389/FENDO.2020.00485)

    • Search Google Scholar
    • Export Citation
  • 36

    Sanz G, Singh M, Peuget S, Selivanova G. Inhibition of p53 inhibitors: progress, challenges and perspectives. Journal of Molecular Cell Biology 2019 11 586599. (https://doi.org/10.1093/jmcb/mjz075)

    • Search Google Scholar
    • Export Citation
  • 37

    Al-Jundi M, Thakur S, Gubbi S, Klubo-Gwiezdzinska J. Novel targeted therapies for metastatic thyroid cancer – a comprehensive review. Cancers 2020 12 137. (https://doi.org/10.3390/cancers12082104)

    • Search Google Scholar
    • Export Citation
  • 38

    Hyman DM, Puzanov I, Subbiah V, Faris JE, Chau I, Blay JY, Wolf J, Raje NS, Diamond EL & Hollebecque A et al.Vemurafenib in multiple nonmelanoma cancers with BRAF V600 mutations. New England Journal of Medicine 2015 373 726736. (https://doi.org/10.1056/NEJMoa1502309)

    • Search Google Scholar
    • Export Citation
  • 39

    Cohen EEW, Rosen LS, Vokes EE, Kies MS, Forastiere AA, Worden FP, Kane MA, Sherman E, Kim S & Bycott P et al.Axitinib is an active treatment for all histologic subtypes of advanced thyroid cancer: results from a phase II study. Journal of Clinical Oncology 2008 26 47084713. (https://doi.org/10.1200/JCO.2007.15.9566)

    • Search Google Scholar
    • Export Citation
  • 40

    Capdevila J, Iglesias L, Halperin I, Segura A, Martínez-Trufero J, Vaz , Corral J, Obiols G, Grande E & Grau JJ et al.Sorafenib in metastatic thyroid cancer. Endocrine-Related Cancer 2012 19 209216. (https://doi.org/10.1530/ERC-11-0351)

    • Search Google Scholar
    • Export Citation
  • 41

    Lim SM, Chang H, Yoon MJ, Hong YK, Kim H, Chung WY, Park CS, Nam KH, Kang SW & Kim MK et al.A multicenter, phase II trial of everolimus in locally advanced or metastatic thyroid cancer of all histologic subtypes. Annals of Oncology 2013 24 30893094. (https://doi.org/10.1093/annonc/mdt379)

    • Search Google Scholar
    • Export Citation
  • 42

    Hanna GJ, Busaidy NL, Chau NG, Wirth LJ, Barletta JA, Calles A, Haddad RI, Kraft S, Cabanillas ME & Rabinowits G et al.Genomic correlates of response to everolimus in aggressive radioiodine-refractory thyroid cancer: a phase II study. Clinical Cancer Research 2018 24 15461553. (https://doi.org/10.1158/1078-0432.CCR-17-2297)

    • Search Google Scholar
    • Export Citation
  • 43

    Nikiforova MN, Wald AI, Roy S, Durso MB, Nikiforov YE. Targeted next-generation sequencing panel (ThyroSeq) for detection of mutations in thyroid cancer. Journal of Clinical Endocrinology and Metabolism 2013 98 E1852–E1860. (https://doi.org/10.1210/JC.2013-2292)

    • Search Google Scholar
    • Export Citation
  • 44

    Kunstman JW, Christofer Juhlin CC, Goh G, Brown TC, Stenman A, Healy JM, Rubinstein JC, Choi M, Kiss N & Nelson-Williams C et al.Characterization of the mutational landscape of anaplastic thyroid cancer via whole-exome sequencing. Human Molecular Genetics 2015 24 23182329. (https://doi.org/10.1093/hmg/ddu749)

    • Search Google Scholar
    • Export Citation
  • 45

    Jeon MJ, Chun SM, Kim D, Kwon H, Jang EK, Kim TY, Kim WB, Shong YK, Jang SJ & Song DE et al.Genomic alterations of anaplastic thyroid carcinoma detected by targeted massive parallel sequencing in a BRAFV600E mutation-prevalent area. Thyroid 2016 26 683690. (https://doi.org/10.1089/thy.2015.0506)

    • Search Google Scholar
    • Export Citation
  • 46

    Tiedje V, Ting S, Herold T, Synoracki S, Latteyer S, Moeller LC, Zwanziger D, Stuschke M, Fuehrer D, Schmid KW. NGS based identification of mutational hotspots for targeted therapy in anaplastic thyroid carcinoma. Oncotarget 2017 8 42613–42620. (https://doi.org/10.18632/ONCOTARGET.17300)

    • Search Google Scholar
    • Export Citation
  • 47

    Ibrahimpasic T, Xu B, Landa I, Dogan S, Middha S, Seshan V, Deraje S, Carlson DL, Migliecci J & Knauf JA et al.Genomic alterations in fatal forms of non-anaplastic thyroid cancer: identification of MED12 and RBM10 as novel thyroid cancer genes associated with tumor virulence. Clinical Cancer Research 2017 23 5970–5980. (https://doi.org/10.1158/1078-0432.CCR-17-1183)

    • Search Google Scholar
    • Export Citation
  • 48

    Bonhomme B, Godbert Y, Perot G, Al Ghuzlan A, Bardet S, Belleannée G, Crinière L, Do Cao C, Fouilloux G & Guyetant S et al.Molecular pathology of anaplastic thyroid carcinomas: a retrospective study of 144 cases. Thyroid 2017 27 682692. (https://doi.org/10.1089/thy.2016.0254)

    • Search Google Scholar
    • Export Citation
  • 49

    Chen H, Luthra R, Routbort MJ, Patel KP, Cabanillas ME, Broaddus RR, Williams MD. Molecular profile of advanced thyroid carcinomas by next-generation sequencing: characterizing tumors beyond diagnosis for targeted therapy. Molecular Cancer Therapeutics 2018 17 15751584. (https://doi.org/10.1158/1535-7163.MCT-17-0871)

    • Search Google Scholar
    • Export Citation
  • 50

    Duan H, Li Y, Hu P, Gao J, Ying J, Xu W, Zhao D, Wang Z, Ye J & Lizaso A et al.Mutational profiling of poorly differentiated and anaplastic thyroid carcinoma by the use of targeted next-generation sequencing. Histopathology 2019 75 890899. (https://doi.org/10.1111/HIS.13942)

    • Search Google Scholar
    • Export Citation
  • 51

    Yoo S-K, Song YS, Lee EK, Hwang J, Kim HH, Jung G, Kim YA, Kim S, Cho SW & Won J-K et al.Integrative analysis of genomic and transcriptomic characteristics associated with progression of aggressive thyroid cancer. Nature Communications 2019 10 112. (https://doi.org/10.1038/s41467-019-10680-5)

    • Search Google Scholar
    • Export Citation
  • 52

    Ravi N, Yang M, Gretarsson S, Jansson C, Mylona N, Sydow SR, Woodward EL, Ekblad L, Wennerberg J, Paulsson K. Identification of targetable lesions in anaplastic thyroid cancer by genome profiling. Cancers 2019 11 402. (https://doi.org/10.3390/CANCERS11030402)

    • Search Google Scholar
    • Export Citation
  • 53

    Xu B, Fuchs T, Dogan S, Landa I, Katabi N, Fagin JA, Tuttle RM, Sherman E, Gill AJ, Ghossein R. Dissecting anaplastic thyroid carcinoma: a comprehensive clinical, histologic, immunophenotypic, and molecular study of 360 cases. Thyroid 2020 30 15051517. (https://doi.org/10.1089/THY.2020.0086)

    • Search Google Scholar
    • Export Citation
  • 54

    Lai WA, Liu CY, Lin SY, Chen CC, Hang JF. Characterization of driver mutations in anaplastic thyroid carcinoma identifies RAS and PIK3CA mutations as negative survival predictors. Cancers 2020 12 113. (https://doi.org/10.3390/CANCERS12071973)

    • Search Google Scholar
    • Export Citation

Supplementary Materials

 

     European Society of Endocrinology logo

     Society for Endocrinology logo

Sept 2018 onwards Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 607 607 92
PDF Downloads 324 324 61
  • View in gallery

    This figure shows the results of potential targetable genetic alterations in anaplastic thyroid cancer. (A) Seventeen (52%) of 33 patients had at least one putative activating genetic alteration in the targetable genes. There were 53 genetic alterations in 24 genes, respectively 23 known putative driver genetic alterations in 4 genes (BRAF, PIK3CA, ALK and SRC) as shown in the bar chart. (B) In the mutation analysis besides BRAF V600E, other mutation hotspots occurred in NRAS Q61 (18%, 6/33), PIK3CA E545 (9%, 3/33), PIK3CA E542 (6%, 2/33), HRAS G13 (6%, 2/33) and others. (C) The figure shows Co-Alterations in comparison BRAF altered group (n  = 15) to BRAF unaltered group (n  = 18); created by cBioPortal (13). BRAF mutation occurred together with TERT-alterations rather than in the BRAF-unaltered group (14/15 vs 10/18 pat, P  = 0.0183) and PIK3CA (5/15 vs 2/18, P  = 0.13). On the other hand, TP53 alterations occurred more frequently in the BRAF unalterated group (8/15 vs 16/18 pat, P  = 0.029), as well as NRAS, PTEN and others.

  • View in gallery

    Percentages of ATC cases, harboring a targetable genetic alteration, predicting drug responsiveness for FDA-approved drugs. BRAF-inhibitors (selective or multikinase BRAF inhibitors) are genetically predicted for drug response in ATC. PIK3CA is a targetable alteration found in 18% of patients, making the PIK3CA inhibitor copanlisib an additional genetically predicted therapy option, followed by 3% for VEGFR2/SRC inhibitor apatinib and the ALK inhibitors.

  • 1

    Bible KC, Kebebew E, Brierley J, Brito JP, Cabanillas ME, Clark TJ, Di Cristofano A, Foote R, Giordano T & Kasperbauer J et al.2021 American Thyroid Association guidelines for management of patients with anaplastic thyroid cancer. Thyroid 2021 31 337386. (https://doi.org/10.1089/thy.2020.0944)

    • Search Google Scholar
    • Export Citation
  • 2

    Araque KA, Gubbi S, Klubo-Gwiezdzinska J. Updates on the management of thyroid cancer. Hormone and Metabolic Research 2020 52 562577. (https://doi.org/10.1055/a-1089-7870)

    • Search Google Scholar
    • Export Citation
  • 3

    Maniakas A, Dadu R, Busaidy NL, Wang JR, Ferrarotto R, Lu C, Williams MD, Gunn GB, Hofmann MC & Cote G et al.Evaluation of overall survival in patients with anaplastic thyroid carcinoma, 2000–2019. JAMA Oncology 2020 6 13971404. (https://doi.org/10.1001/JAMAONCOL.2020.3362)

    • Search Google Scholar
    • Export Citation
  • 4

    Park J, Jung HA, Shim JH, Park WY, Kim TH, Lee SH, Kim SW, Ahn MJ, Park K, Chung JH. Multimodal treatments and outcomes for anaplastic thyroid cancer before and after tyrosine kinase inhibitor therapy: a real-world experience. European Journal of Endocrinology 2021 184 837845. (https://doi.org/10.1530/EJE-20-1482)

    • Search Google Scholar
    • Export Citation
  • 5

    Salgado SA Evolution of anaplastic thyroid cancer management: perspectives in the era of precision oncology. Therapeutic Advances in Endocrinology and Metabolism 2021 12 20420188211054692. (https://doi.org/10.1177/20420188211054692)

    • Search Google Scholar
    • Export Citation
  • 6

    Hescheler DA, Plum PS, Zander T, Quaas A, Korenkov M, Gassa A, Michel M, Bruns CJ, Alakus H. Identification of targeted therapy options for gastric adenocarcinoma by comprehensive analysis of genomic data. Gastric Cancer 2020 23 627638. (https://doi.org/10.1007/s10120-020-01045-9)

    • Search Google Scholar
    • Export Citation
  • 7

    Landa I, Ibrahimpasic T, Boucai L, Sinha R, Knauf JA, Shah RH, Dogan S, Ricarte-Filho JC, Krishnamoorthy GP & Xu B et al.Genomic and transcriptomic hallmarks of poorly differentiated and anaplastic thyroid cancers. Journal of Clinical Investigation 2016 126 10521066. (https://doi.org/10.1172/JCI85271)

    • Search Google Scholar
    • Export Citation
  • 8

    Pozdeyev N, Gay LM, Sokol ES, Hartmaier R, Deaver KE, Davis S, French JD, Borre Vanden PV, LaBarbera DV & Tan AC et al.Genetic analysis of 779 advanced differentiated and anaplastic thyroid cancers. Clinical Cancer Research 2018 24 30593068. (https://doi.org/10.1158/1078-0432.CCR-18-0373)

    • Search Google Scholar
    • Export Citation
  • 9

    Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A, Grant JR, Sajed T, Johnson D, Li C & Sayeeda Z et al.DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Research 2018 46 D1074D1082. (https://doi.org/10.1093/nar/gkx1037)

    • Search Google Scholar
    • Export Citation
  • 10

    Griffith M, Spies NC, Krysiak K, McMichael JF, Coffman AC, Danos AM, Ainscough BJ, Ramirez CA, Rieke DT & Kujan L et al.CIViC is a community KnowledgeBase for expert crowdsourcing the clinical interpretation of variants in cancer. Nature Genetics 2017 49 170174. (https://doi.org/10.1038/ng.3774)

    • Search Google Scholar
    • Export Citation
  • 11

    Chakravarty D, Gao J, Phillips SM, Kundra R, Zhang H, Wang J, Rudolph JE, Yaeger R, Soumerai T & Nissan MH et al.OncoKB: a precision oncology knowledge base. JCO Precision Oncology 2017 2017 116. (https://doi.org/10.1200/PO.17.00011)

    • Search Google Scholar
    • Export Citation
  • 12

    Chang MT, Shrestha Bhattarai TS, Schram AM, Bielski CM, Donoghue MTA, Jonsson P, Chakravarty D, Phillips S, Kandoth C & Penson A et al.Accelerating discovery of functional mutant alleles in cancer. Cancer Discovery 2018 8 174183. (https://doi.org/10.1158/2159-8290.CD-17-0321)

    • Search Google Scholar
    • Export Citation
  • 13

    Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, Jacobsen A, Byrne CJ, Heuer ML & Larsson E et al.The cBio Cancer Genomics Portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discovery 2012 2 401404. (https://doi.org/10.1158/2159-8290.CD-12-0095)

    • Search Google Scholar
    • Export Citation
  • 14

    Mermel CH, Schumacher SE, Hill B, Meyerson ML, Beroukhim R, Getz G. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biology 2011 12 R41. (https://doi.org/10.1186/gb-2011-12-4-r41)

    • Search Google Scholar
    • Export Citation
  • 15

    Ainscough BJ, Griffith M, Coffman AC, Wagner AH, Kunisaki J, Choudhary MNK, McMichael JF, Fulton RS, Wilson RK & Griffith OL et al.DoCM: A database of curated mutations in cancer [Internet]. Nature Methods 2016 13 806807. (https://doi.org/10.1038/nmeth.4000)

    • Search Google Scholar
    • Export Citation
  • 16

    Lin B, Ma H, Ma M, Zhang Z, Sun Z, Hsieh IY, Okenwa O, Guan H, Li J, Lv W. The incidence and survival analysis for anaplastic thyroid cancer: a SEER database analysis. American Journal of Translational Research 2019 11 58885896. (available at: https://pubmed.ncbi.nlm.nih.gov/31632557/)

    • Search Google Scholar
    • Export Citation
  • 17

    Subbiah V, Kreitman RJ, Wainberg ZA, Cho JY, Schellens JHM, Soria JC, Wen PY, Zielinski C, Cabanillas ME & Urbanowitz G et al.Dabrafenib and trametinib treatment in patients with locally advanced or metastatic BRAF V600-mutant anaplastic thyroid cancer. Journal of Clinical Oncology 2018 36 713. (https://doi.org/10.1200/JCO.2017.73.6785)

    • Search Google Scholar
    • Export Citation
  • 18

    Gibson WJ, Ruan DT, Paulson VA, Barletta JA, Hanna GJ, Kraft S, Calles A, Nehs MA, Moore FD & Taylor-Weiner A et al.Genomic heterogeneity and exceptional response to dual pathway inhibition in anaplastic thyroid cancer. Clinical Cancer Research 2017 23 23672373. (https://doi.org/10.1158/1078-0432.CCR-16-2154-T)

    • Search Google Scholar
    • Export Citation
  • 19

    Matasar MJ, Capra M, Özcan M, Lv F, Li W, Yañez E, Sapunarova K, Lin T, Jin J & Jurczak W et al.Copanlisib plus rituximab versus placebo plus rituximab in patients with relapsed indolent non-Hodgkin lymphoma (CHRONOS-3): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet: Oncology 2021 22 678689. (https://doi.org/10.1016/S1470-2045(2100145-5)

    • Search Google Scholar
    • Export Citation
  • 20

    Murugan AK, Xing MM. Anaplastic thyroid cancers harbor novel oncogenic mutations of the ALK gene. Cancer Research 2011 71 44034411. (https://doi.org/10.1158/0008-5472.CAN-10-4041)

    • Search Google Scholar
    • Export Citation
  • 21

    Latteyer S, Tiedje V, König K, Ting S, Heukamp LC, Meder L, Schmid KW, Führer D, Moeller LC. Targeted next-generation sequencing for TP53, RAS, BRAF, ALK and NF1 mutations in anaplastic thyroid cancer. Endocrine 2016 54 733741. (https://doi.org/10.1007/S12020-016-1080-9)

    • Search Google Scholar
    • Export Citation
  • 22

    Godbert Y, De Figueiredo BH, Bonichon F, Chibon F, Hostein I, Pérot G, Dupin C, Daubech A, Belleannée G & Gros A et al.Remarkable response to crizotinib in woman with anaplastic lymphoma kinase-rearranged anaplastic thyroid carcinoma. Journal of Clinical Oncology 2015 33 e84e87. (https://doi.org/10.1200/JCO.2013.49.6596)

    • Search Google Scholar
    • Export Citation
  • 23

    Niu Y, Ding Z, Deng X, Guo B, Kang J, Wu B, Fan Y. A novel multimodal therapy for anaplastic thyroid carcinoma: 125I seed implantation plus apatinib after surgery. Frontiers in Endocrinology 2020 11 207. (https://doi.org/10.3389/fendo.2020.00207)

    • Search Google Scholar
    • Export Citation
  • 24

    Cheng L, Jiao Q, Jin Y, Fu H, Zhang H, Chen L. Initial therapy of advanced anaplastic thyroid cancer via targeting VEGFR-2: a case report. OncoTargets and Therapy 2019 12 1049510500. (https://doi.org/10.2147/OTT.S223727)

    • Search Google Scholar
    • Export Citation
  • 25

    Savvides P, Nagaiah G, Lavertu P, Fu P, Wright JJ, Chapman R, Wasman J, Dowlati A, Remick SC. Phase II trial of sorafenib in patients with advanced anaplastic carcinoma of the thyroid. Thyroid 2013 23 600604. (https://doi.org/10.1089/thy.2012.0103)

    • Search Google Scholar
    • Export Citation
  • 26

    Ravaud A, de la Fouchardière C, Caron P, Doussau A, Do Cao C, Asselineau J, Rodien P, Pouessel D, Nicolli-Sire P & Klein M et al.A multicenter phase II study of sunitinib in patients with locally advanced or metastatic differentiated, anaplastic or medullary thyroid carcinomas: mature data from the THYSU study. European Journal of Cancer 2017 76 110117. (https://doi.org/10.1016/j.ejca.2017.01.029)

    • Search Google Scholar
    • Export Citation
  • 27

    Bible KC, Suman VJ, Menefee ME, Smallridge RC, Molina JR, Maples WJ, Karlin NJ, Traynor AM, Kumar P & Goh BC et al.A multiinstitutional phase 2 trial of pazopanib monotherapy in advanced anaplastic thyroid cancer. Journal of Clinical Endocrinology and Metabolism 2012 97 31793184. (https://doi.org/10.1210/jc.2012-1520)

    • Search Google Scholar
    • Export Citation
  • 28

    Tahara M, Kiyota N, Yamazaki T, Chayahara N, Nakano K, Inagaki L, Toda K, Enokida T, Minami H & Imamura Y et al.Lenvatinib for anaplastic thyroid cancer. Frontiers in Oncology 2017 7 25. (https://doi.org/10.3389/fonc.2017.00025)

    • Search Google Scholar
    • Export Citation
  • 29

    Iyer PC, Dadu R, Ferrarotto R, Busaidy NL, Habra MA, Zafereo M, Gross N, Hess KR, Gule-Monroe M & Williams MD et al.Real-world experience with targeted therapy for the treatment of anaplastic thyroid carcinoma. Thyroid 2018 28 7987. (https://doi.org/10.1089/thy.2017.0285)

    • Search Google Scholar
    • Export Citation
  • 30

    Cabanillas ME, Ryder M, Jimenez C. Targeted therapy for advanced thyroid cancer: kinase inhibitors and beyond. Endocrine Reviews 2019 40 15731604. (https://doi.org/10.1210/er.2019-00007)

    • Search Google Scholar
    • Export Citation
  • 31

    Wirth LJ, Sherman E, Robinson B, Solomon B, Kang H, Lorch J, Worden F, Brose M, Patel J & Leboulleux S et al.Efficacy of selpercatinib in RET-altered thyroid cancers. New England Journal of Medicine 2020 383 825835. (https://doi.org/10.1056/NEJMoa2005651)

    • Search Google Scholar
    • Export Citation
  • 32

    Fullmer T, Cabanillas ME, Zafereo M. Novel therapeutics in radioactive iodine-resistant thyroid cancer. Frontiers in Endocrinology 2021 12 836. (https://doi.org/10.3389/FENDO.2021.720723/BIBTEX)

    • Search Google Scholar
    • Export Citation
  • 33

    Cabanillas ME, Drilon A, Farago AF, Brose MS, McDermott R, Sohal D, Oh D, Almubarak M, Bauman J & Chu E et al.Abstract 1916P: Larotrectinib treatment of advanced TRK fusion thyroid cancer. Annals of Oncology 31 (Suppl 4) 2020 S1086. (https://doi.org/10.1016/j.annonc.2020.08.1404)

    • Search Google Scholar
    • Export Citation
  • 34

    Oishi N, Kondo T, Ebina A, Sato Y, Akaishi J, Hino R, Yamamoto N, Mochizuki K, Nakazawa T & Yokomichi H et al.Molecular alterations of coexisting thyroid papillary carcinoma and anaplastic carcinoma: identification of tert mutation as an independent risk factor for transformation. Modern Pathology 2017 30 15271537. (https://doi.org/10.1038/MODPATHOL.2017.75)

    • Search Google Scholar
    • Export Citation
  • 35

    McKelvey BA, Umbricht CB, Zeiger MA. Telomerase reverse transcriptase (TERT) regulation in thyroid cancer: a review. Frontiers in Endocrinology 2020 11 485. (https://doi.org/10.3389/FENDO.2020.00485)

    • Search Google Scholar
    • Export Citation
  • 36

    Sanz G, Singh M, Peuget S, Selivanova G. Inhibition of p53 inhibitors: progress, challenges and perspectives. Journal of Molecular Cell Biology 2019 11 586599. (https://doi.org/10.1093/jmcb/mjz075)

    • Search Google Scholar
    • Export Citation
  • 37

    Al-Jundi M, Thakur S, Gubbi S, Klubo-Gwiezdzinska J. Novel targeted therapies for metastatic thyroid cancer – a comprehensive review. Cancers 2020 12 137. (https://doi.org/10.3390/cancers12082104)

    • Search Google Scholar
    • Export Citation
  • 38

    Hyman DM, Puzanov I, Subbiah V, Faris JE, Chau I, Blay JY, Wolf J, Raje NS, Diamond EL & Hollebecque A et al.Vemurafenib in multiple nonmelanoma cancers with BRAF V600 mutations. New England Journal of Medicine 2015 373 726736. (https://doi.org/10.1056/NEJMoa1502309)

    • Search Google Scholar
    • Export Citation
  • 39

    Cohen EEW, Rosen LS, Vokes EE, Kies MS, Forastiere AA, Worden FP, Kane MA, Sherman E, Kim S & Bycott P et al.Axitinib is an active treatment for all histologic subtypes of advanced thyroid cancer: results from a phase II study. Journal of Clinical Oncology 2008 26 47084713. (https://doi.org/10.1200/JCO.2007.15.9566)

    • Search Google Scholar
    • Export Citation
  • 40

    Capdevila J, Iglesias L, Halperin I, Segura A, Martínez-Trufero J, Vaz , Corral J, Obiols G, Grande E & Grau JJ et al.Sorafenib in metastatic thyroid cancer. Endocrine-Related Cancer 2012 19 209216. (https://doi.org/10.1530/ERC-11-0351)

    • Search Google Scholar
    • Export Citation
  • 41

    Lim SM, Chang H, Yoon MJ, Hong YK, Kim H, Chung WY, Park CS, Nam KH, Kang SW & Kim MK et al.A multicenter, phase II trial of everolimus in locally advanced or metastatic thyroid cancer of all histologic subtypes. Annals of Oncology 2013 24 30893094. (https://doi.org/10.1093/annonc/mdt379)

    • Search Google Scholar
    • Export Citation
  • 42

    Hanna GJ, Busaidy NL, Chau NG, Wirth LJ, Barletta JA, Calles A, Haddad RI, Kraft S, Cabanillas ME & Rabinowits G et al.Genomic correlates of response to everolimus in aggressive radioiodine-refractory thyroid cancer: a phase II study. Clinical Cancer Research 2018 24 15461553. (https://doi.org/10.1158/1078-0432.CCR-17-2297)

    • Search Google Scholar
    • Export Citation
  • 43

    Nikiforova MN, Wald AI, Roy S, Durso MB, Nikiforov YE. Targeted next-generation sequencing panel (ThyroSeq) for detection of mutations in thyroid cancer. Journal of Clinical Endocrinology and Metabolism 2013 98 E1852–E1860. (https://doi.org/10.1210/JC.2013-2292)

    • Search Google Scholar
    • Export Citation
  • 44

    Kunstman JW, Christofer Juhlin CC, Goh G, Brown TC, Stenman A, Healy JM, Rubinstein JC, Choi M, Kiss N & Nelson-Williams C et al.Characterization of the mutational landscape of anaplastic thyroid cancer via whole-exome sequencing. Human Molecular Genetics 2015 24 23182329. (https://doi.org/10.1093/hmg/ddu749)

    • Search Google Scholar
    • Export Citation
  • 45

    Jeon MJ, Chun SM, Kim D, Kwon H, Jang EK, Kim TY, Kim WB, Shong YK, Jang SJ & Song DE et al.Genomic alterations of anaplastic thyroid carcinoma detected by targeted massive parallel sequencing in a BRAFV600E mutation-prevalent area. Thyroid 2016 26 683690. (https://doi.org/10.1089/thy.2015.0506)

    • Search Google Scholar
    • Export Citation
  • 46

    Tiedje V, Ting S, Herold T, Synoracki S, Latteyer S, Moeller LC, Zwanziger D, Stuschke M, Fuehrer D, Schmid KW. NGS based identification of mutational hotspots for targeted therapy in anaplastic thyroid carcinoma. Oncotarget 2017 8 42613–42620. (https://doi.org/10.18632/ONCOTARGET.17300)

    • Search Google Scholar
    • Export Citation
  • 47

    Ibrahimpasic T, Xu B, Landa I, Dogan S, Middha S, Seshan V, Deraje S, Carlson DL, Migliecci J & Knauf JA et al.Genomic alterations in fatal forms of non-anaplastic thyroid cancer: identification of MED12 and RBM10 as novel thyroid cancer genes associated with tumor virulence. Clinical Cancer Research 2017 23 5970–5980. (https://doi.org/10.1158/1078-0432.CCR-17-1183)

    • Search Google Scholar
    • Export Citation
  • 48

    Bonhomme B, Godbert Y, Perot G, Al Ghuzlan A, Bardet S, Belleannée G, Crinière L, Do Cao C, Fouilloux G & Guyetant S et al.Molecular pathology of anaplastic thyroid carcinomas: a retrospective study of 144 cases. Thyroid 2017 27 682692. (https://doi.org/10.1089/thy.2016.0254)

    • Search Google Scholar
    • Export Citation
  • 49

    Chen H, Luthra R, Routbort MJ, Patel KP, Cabanillas ME, Broaddus RR, Williams MD. Molecular profile of advanced thyroid carcinomas by next-generation sequencing: characterizing tumors beyond diagnosis for targeted therapy. Molecular Cancer Therapeutics 2018 17 15751584. (https://doi.org/10.1158/1535-7163.MCT-17-0871)

    • Search Google Scholar
    • Export Citation
  • 50

    Duan H, Li Y, Hu P, Gao J, Ying J, Xu W, Zhao D, Wang Z, Ye J & Lizaso A et al.Mutational profiling of poorly differentiated and anaplastic thyroid carcinoma by the use of targeted next-generation sequencing. Histopathology 2019 75 890899. (https://doi.org/10.1111/HIS.13942)

    • Search Google Scholar
    • Export Citation
  • 51

    Yoo S-K, Song YS, Lee EK, Hwang J, Kim HH, Jung G, Kim YA, Kim S, Cho SW & Won J-K et al.Integrative analysis of genomic and transcriptomic characteristics associated with progression of aggressive thyroid cancer. Nature Communications 2019 10 112. (https://doi.org/10.1038/s41467-019-10680-5)

    • Search Google Scholar
    • Export Citation
  • 52

    Ravi N, Yang M, Gretarsson S, Jansson C, Mylona N, Sydow SR, Woodward EL, Ekblad L, Wennerberg J, Paulsson K. Identification of targetable lesions in anaplastic thyroid cancer by genome profiling. Cancers 2019 11 402. (https://doi.org/10.3390/CANCERS11030402)

    • Search Google Scholar
    • Export Citation
  • 53

    Xu B, Fuchs T, Dogan S, Landa I, Katabi N, Fagin JA, Tuttle RM, Sherman E, Gill AJ, Ghossein R. Dissecting anaplastic thyroid carcinoma: a comprehensive clinical, histologic, immunophenotypic, and molecular study of 360 cases. Thyroid 2020 30 15051517. (https://doi.org/10.1089/THY.2020.0086)

    • Search Google Scholar
    • Export Citation
  • 54

    Lai WA, Liu CY, Lin SY, Chen CC, Hang JF. Characterization of driver mutations in anaplastic thyroid carcinoma identifies RAS and PIK3CA mutations as negative survival predictors. Cancers 2020 12 113. (https://doi.org/10.3390/CANCERS12071973)

    • Search Google Scholar
    • Export Citation