You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Introduction {#Sec1}
============

More and more knowledge has become available aiding our understanding of the genetic background of cancer. Chromosomal translocations or gene mutations can give the cells in which they arise a growth advantage, ultimately leading to cancer. For bone and soft tissue tumors, an increasing amount of tumor-specific genetic data has become available. Approximately 15--20% of mesenchymal tumors carry a specific translocation \[[@CR1]\] and have relatively simple karyotypes. These translocations are restricted to specific tumor types; in Ewing sarcoma, synovial sarcoma, and myxoid liposarcoma up to 90--95% of the tumors carry a tumor type-specific translocation. In addition, some tumors carry specific somatic gene mutations (e.g., KIT or PDGFRA mutations in gastrointestinal stromal tumors). In contrast, in the more frequent sarcomas such as osteosarcoma, chondrosarcoma, leiomyosarcoma, or high-grade pleomorphic sarcoma, more complex karyotypes are found with numerous gains and losses, without specific genetic alterations \[[@CR2]\].

These molecular data help us to understand the pathogenesis of sarcomas. Moreover, they constitute the basis of the 2002 WHO classification of bone and soft tissue tumors, integrating morphology with genetics \[[@CR3], [@CR4]\]. Tumor-specific molecular changes have found their way in daily clinical practice as molecular diagnostic tools to assist the pathologist in diagnosing these lesions, but may also serve as markers to detect minimal residual disease and to predict clinical outcome, although the latter is still somewhat controversial. Finally, our increasing knowledge of the genetic background of sarcomas, including the ones without specific genetic changes, will hopefully enable the development of more types of targeted therapeutic strategies.

Clues about sarcoma pathogenesis {#Sec2}
================================

Sarcomas with specific reciprocal translocations {#Sec3}
------------------------------------------------

For translocation-derived sarcomas, such as Ewing sarcoma, the occurrence of the translocation is considered a very early step in tumorigenesis \[[@CR5]\]. In many of the translocations in sarcomas, the EWSR1 or the FUS gene is involved. These promiscuous genes are strongly homologous and encode RNA-binding proteins. Most probably, EWSR1 and FUS have a similar effect when they are involved in a chromosomal translocation. The type of DNA-binding domain originating from the fusion partner probably determines the tumor type that is induced by the translocation.

These hybrid oncoproteins subsequently act as aberrant transcription factors dysregulating gene expression patterns initiating tumor formation. Target genes of the EWSR1-ETS fusion products were shown to stimulate cell proliferation (upregulation of PDGF-C, CCDN1, *c-MYC*), evade growth inhibition (downregulation of cyclin-dependent kinase inhibitors and TGF-beta receptor type II), escape from senescence (upregulation of hTERT), escape from apoptosis (repression of IGFBP-3 promoter), induce angiogenesis (VEGF), invasion and metastases (MMPs) \[[@CR6]\].

Alternative to aberrant transcription factor activity of fusion products, some other mechanisms of translocation-based tumorigenesis have been described. One of the genes involved in a translocation can be placed under control of the other gene involved in the translocation, which usually leads to over expression. The growth factor PDGFB is placed under control of the COL1A1 promoter in the COL1A1-PDGFB fusion in dermatofibrosarcoma protuberans \[[@CR7]\]. This leads to autocrine stimulation and tumor cell proliferation through the PDGF receptor \[[@CR7], [@CR8]\]. Similarly, in aneurysmal bone cyst, many different translocations have been described \[[@CR9], [@CR10]\], all resulting in oncogenic activation of the USP6 (TRE2 and TRE17) gene on chromosome 17p13 by placing it under transcriptional control of other, highly active promoters \[[@CR11]\]. The mechanism by which upregulation of USP6, involved in actin remodeling \[[@CR12]\], causes ABC formation is so far unknown. Finally, in congenital fibrosarcoma, the ETV6-NTRK3 fusion product represents a chimeric tyrosine kinase in itself leading to constitutively active Ras/MAPK mitogenic pathway and PI3K/Akt pathway-mediated cell survival \[[@CR13]\].

Sarcomas with specific somatic mutations {#Sec4}
----------------------------------------

In addition, some mesenchymal tumors carry specific somatic mutations that upon their discovery elucidated the pathogenesis of these tumors. For instance, KIT mutations in GIST revealed its relation with the interstitial cells of Cajal. Another example is fibrous dysplasia, a benign fibro-osseous lesion in the medulla of the bone. Polyostotic fibrous dysplasia can be associated with endocrine abnormalities and cafe au lait pigmentation in nonhereditary Mc Cune Albright Syndrome (Online Mendelian inheritance in man NCBI number MIM 174800). Fibrous dysplasia has for long been regarded a nonneoplastic process. Its neoplastic nature was suggested by the occurrence of clonal chromosomal abnormalities found in cytogenetic studies \[[@CR14]\]. Fibrous dysplasia is characterized by activating mutations in the Gs alpha (GNAS1) gene localized on chromosome 20q12--q13.3, encoding the alpha subunit of the stimulatory guanine nucleotide-binding protein (G-protein) \[[@CR15]\]. G-proteins couple extracellular receptors to intracellular effector enzymes and ion channels, mediating the cellular response to an external stimulus. The identification of GNAS1 mutations also in Mc Cune Albright syndrome (postzygotic) and nonskeletal-isolated endocrine lesions clarified that these disorders represent a spectrum of phenotypic expressions of the same basic disorder, probably reflecting different patterns of somatic mosaicism \[[@CR15]\]. Moreover, GNAS1 mutations are also found in (intramuscular and cellular) myxomas \[[@CR16]\] and the cooccurrence of fibrous dysplasia and myxomas is known as Mazabraud syndrome \[[@CR17]\]. Interestingly, GNAS1 mutations are found in the cooccurring myxomas as well and are absent in a morphological mimic of myxoma: low-grade myxofibrosarcoma \[[@CR18]\]. Finally, inactivating mutations of the hSNF5/INI1 gene are found in rhabdoid tumors. hSNF5 is a core member of the SWI/SNF chromatin remodeling complex and hSNF5 loss leads to epigenetically based changes in transcription resulting in cell cycle progression \[[@CR19]\] and genomically stable tumors \[[@CR20]\].

Sarcomas with more or less specific amplifications {#Sec5}
--------------------------------------------------

While in principle not tumor specific, some sarcomas are characterized by a highly reproducible amplification such as in case of atypical lipomatous tumor/ well-differentiated liposarcoma/dedifferentiated liposarcoma the amplification of CDK4 and MDM2 \[[@CR21]--[@CR23]\]. While most if not all of the aforementioned tumors harbor such an amplification and as such it can be used to recognize a lipogenic origin in the dedifferentiated areas of dedifferentiated liposarcoma, it is by no means tumor specific as similar amplifications occur for instance in osteosarcoma or chondrosarcoma \[[@CR24]\]. This genetic marker however is in context quite useful for diagnostic purposes.

Sarcomas with nonspecific complex karyotypes {#Sec6}
--------------------------------------------

The more frequent sarcomas, like high-grade pleomorphic sarcoma, myxofibrosarcoma \[[@CR25]\] or leiomyosarcoma \[[@CR26]\], have complex karyotypes lacking specific genetic aberrations.

For instance, for chondrosarcoma development, a multistep genetic model is presumed. Chondrosarcomas can be either central (arising in the medullar cavity of bone) or peripheral (at the surface of bone). Peripheral chondrosarcomas arise secondarily within the cartilaginous cap of a benign osteochondroma. Osteochondromas can occur within an autosomal dominantly inherited syndrome, Multiple Osteochondromas, in which mutations occur in either EXT1 or EXT2 \[[@CR27]\]. These encode glycosyltransferases catalyzing heparan sulphate chain elongation on heparan sulphate proteoglycans, which are important for cellular signaling of Hedgehog, Fibroblast Growth Factor, Wnt, Bone Morphogenetic Protein and Transforming Growth Factor beta. Thus, while it is clear that inactivation of EXT underlies osteochondroma development \[[@CR28], [@CR29]\], so far, unidentified additional genetic changes are required for malignant transformation towards secondary peripheral chondrosarcoma, resulting in more complex karyotypes including near-haploidy and polyploidization \[[@CR30], [@CR31]\]. In contrast, in the more common central chondrosarcoma EXT is not involved \[[@CR32]\]. Instead, complex karyotypes are found especially in high-grade chondrosarcoma \[[@CR31], [@CR33], [@CR34]\], and 96% of them contains alterations at some level in the pRb pathway \[[@CR35]\]. Thus, the genetic background of tumors without specific genetic aberrations is slowly being elucidated.

Classification of sarcomas {#Sec7}
==========================

Since soft tissue tumors are relatively rare compared with epithelial malignancies, they are generally regarded difficult by surgical pathologists. Soft tissue tumors constitute a very heterogeneous group of tumors containing \>100 histological types and subtypes. The considerable morphological overlap between the different diagnostic entities further adds to difficulties in classification \[[@CR36]\]. Classification is however essential since these different entities require different treatment strategies and have a different outcome. In classifying tumors, the pathologist can be assisted by immunohistochemistry and molecular diagnostics \[[@CR37]\]. Immunohistochemistry is used to confirm the line of differentiation, while molecular techniques can identify specific chromosomal translocations or mutations. The 2002 WHO classification of bone and soft tissue tumors is mainly based on the integration of morphology and genetics \[[@CR36]\]. This classification is at present widely accepted and used.

Use of specific molecular changes in differential diagnosis {#Sec8}
===========================================================

The differential diagnosis among the groups of small blue round cell tumors and spindle cell tumors can be very difficult for pathologists due to the high number of entities and their morphological overlap. Although the morphology and immunohistochemistry remain at the cornerstone of the diagnosis, the detection of specific genetic alterations, either translocations or somatic mutations, can be very helpful. Molecular diagnostics is especially important in those cases with unusual morphology, immunohistochemistry or clinical presentation.

The term "small blue round cell" tumor encompasses a heterogeneous group of tumors that share the presence of undifferentiated small round cells with scant cytoplasm at histology. The differential diagnosis includes Ewing sarcoma/PNET, neuroblastoma, non-Hodgkin lymphoma, poorly differentiated (round cell) synovial sarcoma, rhabdomyosarcoma, small cell osteosarcoma, desmoplastic round cell tumor, and mesenchymal chondrosarcoma (Table [1](#Tab1){ref-type="table"}). Due to the absence of distinguishing morphological features, their distinction can be difficult. Using immunohistochemistry and conventional histochemical stainings, many of these entities can already be distinguished. In addition, molecular diagnostics can be used to detect specific reciprocal translocations in Ewing sarcoma, rhabdomyosarcoma, synovial sarcoma or desmoplastic small round cell tumor. Either (Real-Time) PCR \[[@CR38]\] on RNA isolated from frozen or paraffin-embedded tumor tissue,or FISH on paraffin-embedded slides can be used to detect these translocations. Especially in case of poorly differentiated synovial sarcoma versus Ewing sarcoma /PNET the morphology and the immunohistochemical profile can be identical requiring the demonstration of a EWSR1 or SS18 rearrangement to come to a correct diagnosis and therapy. Table 1Distinguishing features in small blue round cell tumorsHistochemical stainingImmunohistochemistryMolecular diagnosticsEwing sarcoma/PNETPAS positiveCD99+Translocation EWSR1Neuroblastoma--CD99−, CD56+MYCN amplificationAlveolar rhabdomyosarcoma--MYF4 (myogenin)+, Desmin+Translocation FKHR (FOXO1A)Non-Hodgkin lymphoma/leukemiaPAS negativeCD45+Depending on subtypeSmall cell carcinoma--Keratin+, neuroendocrine markers--(Poorly differentiated) synovial sarcoma--CD99+, BCL-2+Translocation SS18 (SYT)Small cell osteosarcomaDeposition of bone (alkaline phosphatase)----Mesenchymal chondrosarcomaDeposition of cartilage----Desmoplastic small round cell tumor--Coexpression keratin and desminTranslocation EWSR1Melanoma--Melanocytic markers+--

Spindle cell tumors share, as their name implies, a spindle cell morphology of the tumor cells. The differential diagnosis includes monophasic synovial sarcoma, leiomyosarcoma, solitary fibrous tumor, malignant peripheral nerve sheath tumor, clear cell sarcoma, fibrohistiocytic tumors, dedifferentiated liposarcoma, spindle cell rhabdomyosarcoma, and in abdominal localization, gastrointestinal stromal tumor (Table [2](#Tab2){ref-type="table"}). Monophasic synovial sarcoma and clear cell sarcoma carry specific chromosomal translocations that can be used. This is especially helpful in the distinction of MPNST and monophasic synovial sarcoma, which can be morphologically and immunohistochemically indistinguishable. KIT or PDGFRA mutation analysis can be helpful to diagnose gastrointestinal stromal tumor, especially in the small proportion in which CD117 is negative. The diagnosis of dedifferentiated liposarcoma especially if the well-differentiated liposarcoma component is not present at morphology can be facilitated by demonstrating the 12q13 amplification that is characteristic for these lesions, either by immunohistochemistry or FISH for amplification of MDM2 \[[@CR39], [@CR40]\]. Table 2Distinguishing features in spindle cell tumorsHistochemical stainingsImmunohistochemistryMolecular diagnosticsMonophasic synovial sarcoma--EMA+, keratin+Translocation SS18 (SYT)Leiomyosarcoma--Smooth muscle markers+--Solitary fibrous tumor--CD34+--MPNSTReticulin stainingS100 protein in a subset of cases--Clear cell sarcoma--Melanocytic markers+Translocation EWSR1GIST--CD117+, DOG1+KIT/PDGFRA mutationDedifferentiated liposarcoma--MDM2, CDK4 over expressionMDM2 amplification

Detection of minimal residual disease {#Sec9}
=====================================

Following exciting results in molecular screening of lymph nodes for micrometastases of colonic cancer and bone marrow for minimal residual disease after lymphoma treatment, efforts have been made to do the same for sarcomas harboring a tumor-specific translocation as for instance Ewing sarcomas \[[@CR41], [@CR42]\]. Presence of tumor cells in bone marrow but not in blood was claimed to be associated with adverse prognosis \[[@CR43]\], while others showed an increased risk of systemic relapses associated with bone marrow micrometastasis and circulating tumor cells in localized Ewing tumor.\[[@CR44]\]. Tumor cells were shown to be present in a subset of stem cell harvests of Ewings sarcoma patients and their persistence following transplantation was claimed to be associated with relapse. Large prospective multinational randomized trials have been designed such as the EuroEwing 99 trial to investigate these questions. Although this trial is now open for 10 years, still, the data are not mature to draw final conclusions with regard to this question, implying that when a difference is present, this should be minimal at best for the individual patient. For alveolar rhabdomyosarcoma, molecular markers have been advocated for early detection of tumor relapses as well as using a reverse transcriptase-polymerase chain reaction method \[[@CR45]\].

Prediction of outcome {#Sec10}
=====================

Some tumors like Ewing sarcoma or synovial sarcoma may carry individually one of a spectrum of tumor specific cytogenetic or molecular genetic abnormalities. In retrospective studies, it has been claimed that the prognoses for these tumor entities was influenced by the specific molecular-defined translocation type \[[@CR46]--[@CR48]\]. These appeared in these first studies a powerful prognostic indicator and in case of synovial sarcoma even a predictor of the biphasic versus the monophasic subtype. In due course however, based on either prospectively collected cases treated in the context of a clinical trial or large national sarcoma databases, the prognostic value of these subtypes of translocations has been questioned for both tumor types \[[@CR49]--[@CR52]\]. Next to the specific translocations, some sarcomas, especially well documented in Ewing sarcoma, harbor numerical chromosomal abnormalities, deletions of the p16 region or additional point mutations in p53 \[[@CR53]--[@CR57]\]. These abnormalities are most often grossly overlooked when applying an RT-PCR approach just focusing on the known fusion breakpoints. An important role in tumor progression and prognosis has been claimed for these additional, nontumor-specific events. In case of metastatic GIST, the prognosis is highly correlated to the response to tyrosine kinase-inhibiting drugs \[[@CR58]\]. While also immunohistochemical phenotypic markers have been studied with potential prognostic impact \[[@CR59]\], these failed to show prognostic impact in contrast to clinical \[[@CR60]\] and morphological \[[@CR61]\] parameters. Here, especially the type of mutation in KIT or PDGFRA appears to have an important impact on response to tyrosine kinase inhibition \[[@CR62], [@CR63]\]while additional molecular events superimposed to the original tumor-specific ones like those described earlier for Ewing sarcoma are increasingly more of interest in studying resistance \[[@CR64],[@CR65]\] and tumor progression \[[@CR66]\].

Identification of molecular targets for treatment {#Sec11}
=================================================

With the identification of some of the specific changes in sarcomas, therapeutic targets were disclosed. The most well-known example is KIT/PDGFRA mutations in gastrointestinal stromal tumors of which the constitutively active signaling and subsequent tumor growth can be inhibited using tyrosine kinase inhibitors such as imatinib (STI571, Gleevec) \[[@CR67]\]. Also, specific translocations have revealed targets for therapy. The COL1A1-PDGFB fusion product in dermatofibrosarcoma protuberans signals through the PDGF receptor in an autocrine loop \[[@CR8]\], of which the signaling can be blocked using tyrosine kinase inhibitors acting at PDGFR such as imatinib. Imatinib treatment of this superficially located low-grade sarcoma can be beneficial to reduce tumor size in otherwise inoperable tumors.

Conclusion {#Sec12}
==========

Molecular and cytogenetic studies performed over the past decades have been proven to have major impact in identification, classification, and in some cases, prognostication of a large variety of sarcomas. With regard to diagnosis, the use of molecular techniques for an array of tumor entities has found their way into routine clinicopathological practice. Like the treatment of sarcomas, the application of molecular techniques needs to be under strict protocol and in morphological context in order to avoid disastrous mistakes in tumor classification. Here, a need for vigorous (multi) national quality control assessments, centralization not only of treatment but also of (molecular) diagnosis and development of (multi) national guidelines \[[@CR68]--[@CR71]\] is a future view which needs attention of the pathology community as well as health-care decision makers.

**Conflict of interest statement** We declare that we have no conflicts of interest.

**Open Access** This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.