Gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are a subset of NETs that arise from neuroendocrine cells in the gastrointestinal tract and pancreas. Although these tumours may look similar under a microscope, their behaviour can vary significantly. Some GEP-NETs grow slowly and may be managed for many years, while others progress rapidly and require more aggressive treatment. One of the most important tools used to understand how a GEP-NET might behave is its grade.
Tumour grading provides insight into how abnormal the cells appear and how quickly they are dividing. This article explains the key principles of GEP-NET grading, how it impacts treatment and prognosis, and the challenges clinicians face in interpreting and applying this information in patient care.
Neuroendocrine Cancer Australia (NECA), is dedicated to assisting individuals diagnosed with NETs and their loved ones. NECA offers a wealth of resources, educational programs, and advocacy efforts aimed at deepening the understanding of NETs, improving patient care, and encouraging research advancements. Patients can engage with NECA’s comprehensive support and information by calling the NET nurse line.
Tumour grading is a method used to classify cancer cells based on how different they look from normal cells (differentiation) and how actively they are multiplying (proliferation). For neuroendocrine tumours, grading plays a central role in predicting the tumour’s behaviour and guiding treatment decisions.
Unlike cancer staging, which describes the extent and spread of the disease, grading is focused on the biological characteristics of the tumour itself. In GEP-NETs, the grading process helps clinicians understand how aggressive the tumour is likely to be and how it might respond to treatment.
The World Health Organisation (WHO) has established a grading system specifically for GEP-NETs. This system uses two key factors to determine grade: the Ki-67 proliferation index and the mitotic count (the number of cells undergoing division in a given area). Tumours are categorised into three grades:
Grade 1 GEP-NETs are well-differentiated tumours with a Ki-67 index of less than 3%. These tumours are typically slow-growing and associated with a good prognosis. Patients with Grade 1 tumours may not need immediate treatment if the tumour is small and not causing symptoms, and surveillance may be appropriate in some cases.
Grade 2 tumours are also well-differentiated but show a moderate level of proliferation, with a Ki-67 index between 3% and 20%. The behaviour of Grade 2 tumours can be more variable — some behave like Grade 1 tumours, while others may be more aggressive. This group often requires individualised treatment planning, and decisions are typically based on both grade and other clinical factors such as tumour burden and symptoms.
Grade 3 GEP-NETs have a Ki-67 index above 20%. These tumours are more aggressive and associated with a higher risk of progression and metastasis. Importantly, Grade 3 tumours are now subdivided into two categories: well-differentiated Grade 3 NETs and poorly differentiated neuroendocrine carcinomas (NECs).
While both are high grade, the well-differentiated tumours retain neuroendocrine features and may respond to different treatments compared to poorly differentiated NECs.
The Ki-67 index is a key marker used in grading GEP-NETs. Ki-67 is a protein found in cells that are actively dividing, and its presence can be measured through immunohistochemistry on biopsy or surgical tissue samples. The percentage of Ki-67-positive cells is then used to assess the tumour’s proliferative activity.
Although Ki-67 is essential for grading, interpreting it accurately can be challenging. The results may vary depending on how the tissue sample was processed, the area of the tumour that was sampled, and the method used for counting. For this reason, experienced pathology review (ideally by a NET specialist) is recommended for consistent and reliable grading.
Tumour grade is one of the most important factors influencing treatment choices in GEP-NETs. For example:
Understanding the tumour’s grade allows the healthcare team to tailor treatment to the individual’s needs, balancing effectiveness with quality of life.
Tumour grade is strongly correlated with prognosis. Patients with Grade 1 tumours often live many years with slow disease progression, especially when the tumour is localised or has limited metastatic spread. Grade 2 tumours are more variable, with outcomes depending on both proliferation rate and other clinical factors.
Grade 3 tumours, particularly poorly differentiated NECs, tend to progress quickly and are more likely to spread to other organs. However, patients with well-differentiated Grade 3 NETs may still respond to NET-targeted therapies, and their outlook can be more favourable than those with NECs.
Tumour grade also influences how often patients require follow-up imaging and clinical review.
Surveillance plans should always be individualised, taking into account the patient’s overall condition, tumour burden, treatment response, and personal preferences.
One of the key challenges in tumour grading is sampling error. NETs can be heterogeneous, meaning different parts of the tumour may have different proliferation rates. If a biopsy is taken from a less active area, the tumour may be under-graded, leading to under-treatment. Conversely, sampling a more aggressive area might result in over-grading.
For this reason, grading based on surgical specimens (when available) is usually more accurate than grading from small biopsy samples. In cases where treatment decisions hinge on grade, repeat biopsy or review by a specialist pathologist may be recommended and combined with imaging.
The classification of NETs has evolved significantly in recent years. Previously, all Grade 3 tumours were grouped together and considered to be poorly differentiated carcinomas. However, it is now recognised that some Grade 3 tumours are well-differentiated and behave differently. The current WHO guidelines reflect this distinction, helping clinicians choose treatments more effectively.
As research continues, further refinements to grading and classification may emerge, potentially leading to more personalised and precise treatment approaches.
Accurate tumour grading requires expertise in pathology, imaging, and clinical oncology. In most cases, grading should be confirmed by a multidisciplinary team (MDT) that includes:
An MDT approach ensures that tumour grade is considered alongside other clinical and imaging findings to create a comprehensive management plan. This integrated care model is especially important for NETs, which often require long-term management and coordinated input from multiple specialists.
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