| Literature DB >> 35775706 |
Antonio Marchetti1, Benedetta Ferro1, Maria Paola Pasciuto1, Claudia Zampacorta1, Fiamma Buttitta1, Emanuela D'Angelo1.
Abstract
A number of innovative drugs, developed for precision medicine, have shown impressive activity in neoplastic patients with rare molecular targets, independently from the site and type of tumor. This gave rise to the concept of agnostic treatments in oncology. The detection of such rare targets is a prerequisite for these treatments and is nowadays one of the main challenges in diagnostic molecular pathology. Various algorithms, new diagnostic strategies and pathological workflows have been suggested to help pathologists in the detection of these rare molecular alterations. An emblematic example of biological targets for agnostic treatments is represented by genetic rearrangements affecting members of the Neurotrophic Tyrosine Receptor Kinase (NTRK) gene family. These gene rearrangements have an unusual dual mode of distribution: the first, at high frequency in some very rare neoplasms, and the second with extremely lower frequencies in more common tumors. Even in the context of an agnostic approach, knowledge of site, histotype and prevalence of the tumors carrying these genetic lesions may be helpful to guide the pathologist in the daily effort in search of these molecular alterations. This review examines the prevalence of NTRK gene fusions in different forms of solid tumors, based on the largest studies to date, reports a comprehensive diagnostic algorithm and an innovative pathological workflow for rapid screening.Entities:
Keywords: Neurotrophic Tyrosine; Next Generation Sequencing (NGS); Receptor Kinase (NTRK); targeted therapy; tumor agnostic treatments
Mesh:
Year: 2022 PMID: 35775706 PMCID: PMC9248239 DOI: 10.32074/1591-951X-787
Source DB: PubMed Journal: Pathologica ISSN: 0031-2983
Figure 1.Frequency of NTRK gene fusions in rare tumors (data obtained from Westphalen et al.).
Figure 2.Prevalence of NTRK gene fusions in tumors in the adult population (data obtained from Westphalen et al, Rosen et al, Solomon et al.) CRC, colorectal cancer; CUP, cancer of unknown primary; GIST, gastrointestinal stromal tumor; NSCLC, non-small cell lung cancer.
Figure 3.Prevalence of the different tumor types that were positive for NTRK gene fusions in the adult population (data obtained from Westphalen et al.). CRC, colorectal cancer; CUP, cancer of unknown primary; GIST, gastrointestinal stromal tumor; NSCLC, non-small cell lung cancer.
Figure 4.Major fusion partners of NTRK genes in the adult population by frequency (modified from Westphalen et al.).
Prevalence of NTRK gene fusions in the most common solid tumors, as reported in different studies. NOS, not-otherwise specified.
| Histotype | Westphalen et al. (2021) (n = 290.431) | Rosen et al. (2020) (n = 26.312) | Solomon et al. (2019) (n = 33.997) | Gatalica et al. (2019) (n = 11.502) | ||||
|---|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | n | % | |
| Salivary gland carcinoma | 35/1440 | 2.43% | 12/227 | 5.29% | 13/256 | 5.08% | / | / |
| Sarcoma NOS | 79/6216 | 1.27% | 9/770 | 1.17% | 13/1915 | 0.68% | 1/478 | 0.2% |
| Thyroid carcinoma | 29/2314 | 1.25% | 10/451 | 2.22% | 13/571 | 2.28% | 4/70 | 6% |
| Uterine sarcoma | 5/5494 | 1.01% | 2/174 | 1.15% | / | / | 1/478 | 0.2% |
| Breast carcinoma | 117/30075 | 0.39% | 3/3775 | 0.08% | 6/4458 | 0.13% | 1/769 | 0.1% |
| Melanoma | 19/8028 | 0.24% | 5/932 | 0.54% | 4/1125 | 0.36% | / | / |
| Lung adenocarcinoma | 136/56440 | 0.24% | 6/3658 | 0.16% | 9/3993 | 0.23% | 4/4073 | 0.1% |
| Biliary tract cancer | 7/3150 | 0.22% | 2/553 | 0.36% | 2/787 | 0.25% | / | / |
| Colorectal carcinoma | 77/34590 | 0.22% | 8/2306 | 0.35% | 9/2929 | 0.31% | 2/1272 | 0.2% |
| Pancreatic adenocarcinoma | 28/16769 | 0.17% | 4/1315 | 0.30% | 5/1492 | 0.34% | / | / |
Types of NTRK gene fusions most frequently reported in thyroid tumors (modified from Pekova et al.)
| NTRK fusion | Frequency (%) |
|---|---|
| ETV6-NTRK3 | 64.4 % |
| TPM3-NTRK1 | 8.4 % |
| SQSTM1-NTRK3 | 6.8 % |
| EML4-NTRK3 | 6.8 % |
| RBPMS-NTRK3 | 5.1 % |
| IRF2BP2-NTRK1 | 5.1 % |
| SQSTM1-NTRK1 | 1.7 % |
| TPR-NTRK1 | 1.7 % |
Types of NTRK gene fusions most frequently reported in colorectal cancer (modified from Lasota et al.).
| NTRK fusion | Number of cases (%) |
|---|---|
| LMNA-NTRK1 | 6 (14%) |
| PLEKHAG-NTRK1 | 1 (2.3%) |
| SCYL3-NTRK1 | 1 (2.3%) |
| TPM3-NTRK1 | 22 (51.2%) |
| TPR-NTRK1 | 3 (7%) |
| COX5A-NTRK3 | 1 (2.3%) |
| ELM4-NTRK3 | 2 (4.6%) |
| ETV6-NTRK3 | 6 (14%) |
| VPS18-NTRK3 | 1 (2.3%) |
| Total | 43 (100%) |
Frequency and type of NTRK gene fusions in NSCLC in various studies (Russo et al.). ADC, adenocarcinoma, NSCLC, non-small cell lung cancer.
| Study | Population (n) | Frequency (%) | NTRK | Fusion partner |
|---|---|---|---|---|
| Farago, 2018 | NSCLC (4872) | 0,23% | NTRK1 | SQSTM1, TPR, IRF2BP2, TM3, MPRIP, ETV6 |
| NTRK3 | ||||
| Vaishnavi, 2013 | ADC (91) | 3,3% | NTRK1 | MPRIP, CD74 |
| Stransky, 2014 | ADC (513) | 0,19% | NTRK2 | TRIM24 |
| Miyamoto, 2019 | NSCLC (non-squamous) (4874) | 0,05% | NTRK3 | NR |
| Gatalica, 2018 | ADC (4073) | 0,1% | NTRK1 | TPM3, SQSTM1, ETV6 |
| NTRK3 | ||||
| Ou, 2019 | NSCLC (42791) | 0,1% | NTRK1 | IRF2BP2, TPM3 |
| NTRK3 | ||||
| Xia, 2019 | NSCLC (21155) | 0,056% | NTRK1 | CD74, IRF2BP2, LMNA, PHF20, SQSTM1, TPM3, TRP |
Types of NTRK gene fusions in patients with NSCLC according to the histotype and smoking history (modified from Da Farago et al.). ADC, adenocarcinoma; NE, neuroendocrine carcinoma.
| Case | NTRK fusion | Histotype | Smoking history |
|---|---|---|---|
| 1 | NTRK1-SQSTM1 | ADC | 30 pack-years |
| 2 | NTRK1-TPR | ADC/NE | / |
| 3 | NTRK1-IRF2BP2 | ADC | / |
| 4 | NTRK1-TPM3 | ADC | 2 pack-years |
| 5 | NTRK1-MPRIP | ADC | / |
| 6 | NTRK3-ETV6 | ADC | / |
| 7 | NTRK1-IRF2BP2 | ADC | 30 pack-years |
| 8 | NTRK3-ETV6 | SCC | 58 pack-years |
| 9 | NTRK1-SQSTM1 | ADC | / |
| 10 | NTRK3-ETV6 | ADC | / |
| 11 | NTRK3-SQSTM1 | NE | 1 pack-years |
Types of NTRK gene fusions in patients with NSCLC according to the gender and the different histologic variants of adenocarcinoma (ADC) (modified from Ruiying et al.). M, male; F, female; ADC, adenocarcinoma.
| Case | Sex | Age | NTRK fusion | Histotype |
|---|---|---|---|---|
| 1 | M | 53 | NTRK1-C14orf2 | ADC |
| 2 | M | 41 | NTRK1-RRNAD1 | ADC (papillary) |
| 3 | F | 64 | NTRK1-NBPF25P | ADC (acinar) |
| 4 | M | 54 | NTRK1-ARHGEF11 | ADC |
| 5 | F | 56 | NTRK1-FMN2 | ADC |
| 6 | F | 31 | NTRK1-TPM3 | ADC in situ |
| 7 | M | 51 | NTRK1-TPM3 | ADC (papillary) |
| 8 | F | 39 | / | ADC (acinar) |
| 9 | M | 36 | / | ADC minimally invasive |
Prevalence and type of NTRK gene fusions in pediatric cancers (data from Zhao et al.).
| Histological diagnosis | Prevalence of fusions in NTRK genes | Type of fusion |
|---|---|---|
| Papillary thyroid cancer (PTC) | 10/76 cases (13%) | ETV6-NTRK3 |
| IRF2BP2-NTRK1 | ||
| SQSTM1-NTRK1 | ||
| TPR-NTRK1 | ||
| Tumors of the central nervous system (CNS) | 7/364 cases (1.9%) | KANK1-NTRK2 |
| C2orf44-NTRK2 | ||
| QKI-NTRK2 | ||
| KCTD16-NTRK2 | ||
| TRIM24-NTRK2 | ||
| SPECC1L-NTRK2 | ||
| ETV6-NTRK3 | ||
| Solid tumors, non-CNS, non-PTC, including sarcomas of soft tissues | 8/435 cases (1.8%) | TFG-NTRK3 |
| RBPMS-NTRK3 | ||
| ETV6-NTRK3 | ||
| SPECC1L-NTRK3 | ||
| STRN3-NTRK3 | ||
| PRDX1-NTRK1 | ||
| Hematological tumors | 2/472 cases (0.4%) | RBPMS-NTRK3 |
| TPM3-NTRK1 |
NTRK gene rearrangements in high-grade uterine sarcomas-endometrial stroma sarcomas (modified from Akaev et al.).
| Gene partner involved | Most frequent NTRK fusion | Traslocation |
|---|---|---|
| TPR | TPR-NTRK1 | 1q31.1-1q23.1 |
| LMNA | LMNA-NTRK1 | 1q22-1q23.1 |
| TPM3 | TPM3-NTRK1 | 1q21.3-1q23.1 |
| RBPMS | RBPMS-NTRK3 | t(8;15) |
| (p12;q25.3) | ||
| EML4 | EML4-NTRK3 | t(2;15) |
| (p21;q25.3) | ||
| STRN | STRN-NTRK3 | t(2;15) |
| (p22.2;q25.3) |
Frequency and type of fusion of NTRK genes in melanomas (modified from Forschner et al.).
| Type of melanoma | Frequency of NTRK gene fusions | Types of NTRK fusions |
|---|---|---|
| Spitzoid melanoma (Wiesner et al. 2014) | 7/33 cases (21.2%) | LMNA-NTRK1 |
| TP53-NTRK1 | ||
| Spitzoid melanoma (Wu et al. 2016) | 2/7 cases (28.5%) | TPM3-NTRK1 |
| Acral melanoma (Yeh et al. 2019) | 3/122 cases (2.5%) | MYO5A-NTRK3 |
| TUBGCP3-NTRK3 | ||
| Difficult to classify melanocytic lesions (Yeh et al. 2016) | 22/1202 cases (1.8%) | ETV6-NTRK3 |
| MYO5A-NTRK3 | ||
| MYH9-NTRK3 | ||
| Metastatic amelanotic mucosal/paramucosal melanoma (Lezcano et al. 2018) | 1/751 cases (0.9%) | TRIM63-NTRK1 |
| DDR2-NTRK1 | ||
| Metastatic amelanotic cutaneous melanoma (Lezcano et al.2018) | 3/751 cases (0.8%) | GON4L-NTRK1 |
| TRAF-NTRK2 |
Advantages and disadvantages of the described techniques.
| Advantages | Disadvantages | |
|---|---|---|
|
| Evaluation of actual protein expression | Inability to identify the fusion partner |
| Low costs | Can only be used on formalin-fixed, paraffin-embedded samples | |
| Short turnaround time (TAT) | Reduced specificity in nervous system cells (constitutive expression of NTRK) | |
| High sensitivity (95%) and specificity (100%) | Evaluation of a single analyte only | |
|
| Widespread and well recognized method | Complex interpretation of results |
| Commercially-available kits | Higher costs compared to IHC | |
| Useful to evaluate NTRK3-ETV6 fusion | Evaluation of a single gene | |
|
| Commercially-available kits | Can detect only a limited number of already known fusions |
| Specificity (specific primers) | Impossible to detect translocations > 200 bp | |
| Low cost | Variable sensitivity and specificity (based on quality of the nucleic acid) | |
|
| Possibility to identify fusion partners | High costs |
| High sensitivity and specificity | Longer TAT vs. other techniques | |
| Can analyse small quantities of samples | Operators need a high level of training | |
| Simultaneous analysis of other clinically relevant markers | Limited territorial diffusion |
Figure 5.Diagnostic algorithm based on the prevalence (high, > 50%: low, 1-5%; very low, < 1%) of NTRK gene fusions and the molecular tests planned in routine diagnostics.
Figure 6.A simplified diagnostic workflow for testing rare biomarkers and select patients for tumor-agnostic treatments. A more detailed workflow for diagnostic screening in clinical practice is reported in Marchetti et al, 2019 [2], from which the figure was derived.