Samples for research
Auria Biobank offers high-quality human biological samples for biomedical research.
The biobank’s samples consist of, for example, tissue, blood or DNA/RNA isolated from cells. Related clinical data that are significant from a research point of view can be linked to the samples. New samples from patients who have given their consent are saved in the biobank in the context of regular diagnostic and treatment measures carried out in the hospital. The studies conducted by the biobank must help promote the health of the public, and access to the material requires a scientific research plan and a statement of approval from Auria Biobank’s Scientific Steering Committee.
Clinical data taken from electronic health record systems and genotype data analyzed from a sample can be linked to Auria Biobank’s samples.
The biobank’s data analysts conduct high-quality analyses using clinical patient data. The data used in a study can consist of either the biobank’s material, which includes the information of people who have given their biobank consent, or it can consist of patient data that has been assigned to the biobank by virtue of the researcher’s permission to conduct register research. The genome data available from some samples can also be combined with health information and data analyzed from the samples to find links between individual genetic abnormalities and disease or drug responses.
Sample collection and storage
The collection of new samples can also be arranged with Auria Biobank in co-operation with hospital and medical staff.
We plan and realize, among other things, the collection of tissue, blood or bodily fluids as needed together with hospital and medical staff. We routinely collect blood samples for the biobank in connection with a regular diagnostic or clinical blood sample from all patients who have given their biobank consent. We additionally collect fresh tissue samples that are left over from diagnostic procedures.
With Auria Biobank’s automated sample-processing technology, even large batches of liquid samples can be distributed in 2D-coded tubes (Micronic, FluidX or Matrix, etc.). We have experience of various tube-sealing methods, and we are the only laboratory in Finland using the capping method to seal individual tubes.
Joint development projects
Auria Biobank engages in scientific collaboration with academic researchers and companies.
Such collaboration consists of public-private partnerships, academic collaboration and co-operation based on information sharing. Research ideas may come from an outside party or from within the biobank, and the research is carried out as agreed by the partners.
Auria Biobank produces high-quality tissue microarray (TMA) blocks.
We plan and produce tailored TMA blocks from tissue samples according to the customer’s needs. In addition, a considerable amount of clinical data can be attached to all of the samples. The samples are digitalized, and the pathologist or researcher uses his or her own computer to select the areas of interest to be transferred from the sample to the TMA block. The TMAs are prepared automatically by a TMA Grand Master machine. Auria Biobank’s TMAs are prepared, for the most part, from FFPE (formalin-fixed-paraffin-embedded) samples collected in the Pathology Unit of Tyks, but a TMA can also be made using sample blocks that are in the customer’s possession.
| TMA | Disease | Patients | Years | Blocks(#) | Cylinders/patient (#) | Diameter (mm) | Normal tissue from same sample included | Marker samples |
|---|---|---|---|---|---|---|---|---|
| Prostate Cancer | Removal of prostate due to adenocarcinoma (Gleason ~8) | 222 | 2004-2010 | 18 | 2 from the core of tumour | 1,5 | yes | Liver tissue and tonsillas |
| Pancreatic cancer | Pancreatic adenocarcinoma | 40 | 1993-2012 | 2 | 2 from the core of tumour | 1,5 | - | |
| Gastric cancer | Intestinal-type adenoca of the stomach, gastro-esophageal junction or distal esophagus |
~200 | 1993-2012 | 12 | 2 from the core and 2 from invasive front | 1 | yes | |
| Colorectal cancer | Stage II colorectal cancer | 250 | 2005-2012 | 11 | 2 from the core and 2 from invasive front | 1 | yes | |
| Glioma | Glioblastoma and diffuse glioma | ~200 | 2005-2013 | 5 | 2 from the core of tumour | 1,5 | - | Liver tissue |
| Lung cancer | Non-small cell lung cancer | ~500 | 1993-2013 | 27 | 1-2 from the core and from invasive front | 1,5 | yes | Liver tissue and tonsillas |
| Breast cancer | Breast cancer (triple negative) | ~200 | 1998-2012 | 10 | 2 cylinders from the core of tumour, metastatic lymph node or inflamed area | 1,5 | yes | ER+, HER+ and liver tissue. |
| Ovarian cancer I | Ovarian granulosa cell tumours | 44 | 1993-2013 | 2 | 4 from the core of tumour | 1 | - | Liver tissue |
| Ovarian cancer II | High-grade serous ovarian carcinoma | ~400 | 1994-2007 | 12 | 2 from the core of tumour | 1,5 | - | Liver tissue |
| Vulvar cancer | Precancerous lesions and primary tumours of vulva, metastatic lymph nodes | 140 | 1999-2013 | 4 | 2 from the core and
2 from invasive front; 2 from LSA; 2 from metastatic lymph nodes |
1 | yes | Liver tissue |
| Gastrointestinal stromal tumour | Gastrointestinal stromal tumour (GIST) | ~100 | 1993-2016 | 4 | 1-2 cylinders from the core of the tumour | 1,5 | - | Liver tissue |
| Head and neck cancer | Squamous cell carcinoma (head and neck and salivary gland cancer) | ~400 | 2004-2015 | 11 | 2 cylinders from the core of the tumour, 2 from the invasive front, 2 from metastatic lymph nodes (2 cores from stroma) |
1 | - | Liver tissue |
| cSCC | Squamous cell carcinoma, actinic keratosis and Cutaneous squamous cell carcinoma (cSCC) (skin) Patient with metastatis and without metastatis |
64+15 | 1994-2013 | 3+2 | Cylinders from the tumour, cylinders from the normal tissue |
1 | yes | Liver tissue |
| Breast cancer | Infiltrating ductal carcinoma (Her2 negative) | ~200 | 2003-2006 | 3 | 1 cylinder from the core of the tumour | 1 | - | Liver tissue |
| Lung cancer | Biomarkers in lung carsinoid tumours (NETs) | 36 | 1990-2013 | 2 | cylinders from the core of the tumour, cylinders from bening lung tissue, cylinders from bronchus cylinders from the border, cylinders from metastatic lymph nodes |
1 | yes | Liver tissue |
| Pediatric | Carsinoma samples from children (kidney, brain/meninges, sarcoma, lymphoma/leukemia, thyroid, others) | 57 | 1993-2012 | 6 | 1-2 core from tumour, 1-2 core from control |
1 | yes | Liver tissue |
| Adenomyosis | Adenomyosis samples | ~140 | 2012-2016 | 12 | 1-2 cylinders from adenomyosis 1-2 cylinders from myometrium 1-2 cylinders from myometrium |
2 | - | Liver tissue |
| Endometrial cancer | Twenty endometrioid G3 cancers and 20 non-endometriod cancers. | 63 | 2011-2015 | 2 | 2-4 cylinders from tumour 0-1 cylinders from normal |
2 | few | |
| Kidney | Clear cell carcinomas | 271 | 2004-2015 | 14+4 | 2 cylinders from the core of the tumour, 2 from the invasive front, 1 from normal to normal TMA blocks |
1,5 | yes | Liver, tonsilla, testis, lymphatic tissue |
| Breast cancer | HER2 positive breast cancers | 79 | 2008-2013 | 1 | 1 cylinder from the core of the tumour, 1 from the invasive front |
1 | - | |
| Breast cancer | Triple-negative breast cancers | 103 | 2013-2018 | 3 | 1 cylinder from the core of the tumour, 1 from the invasive front |
1,5 | - | Liver tissue |
| Breast cancer | HR+ HER2- breast cancers | 205 | 1998-2013 | 4 | 1 cylinder from the core of the tumour, 1 from the invasive front |
1,5 | - | Liver tissue |
Algorithm development for text mining
Although considerable data already exist in a structured form in electronic health record systems (EHRS), the majority of clinical data remains in dictations in unstructured reports. Auria Biobank’s data analysts develop algorithms that can be used to mine the relevant information from the large data sets. We also convert the data into a form that is easier to analyze.
Deep learning and making use of AI
Cancer histology reflects the underlying molecular processes as well as the disease’s progression. Current applications, such as convolutional neural networks (CNNs) in digital pathology, even include the revelation of invisible or previously unknown tumor characteristics. At Auria Biobank, we use deep learning technology, for example, to predict the path of a patient’s disease or treatment outcomes from digitized histopathology images. Applications utilizing CNNs can, in principle, be applied to any type of cancer or other diseases where tissue samples are collected as part of normal diagnostics or treatment.
Feasibility studies and recall
Auria Biobank is a partner in clinical trials.
Through biobank consent, the patient gives permission for samples and data collected from him or her during regular diagnostic and treatment measures to be used in biobank research. The biobank consent form also enquires about the possibility to contact the patient to discuss his or her willingness to provide more samples or to participate in research that is not covered by the biobank consent. The biobank can select candidates suitable for various clinical trials from among groups of patients who have given their consent and contact them.
