Tumor Profiling and Preclinical Models

The primary objective is to gather and analyze tumor samples to gain valuable insights into their molecular characteristics. Our researchers aim to unravel important details about the genetic and molecular makeup of tumors, which can lead to a deeper understanding of their behavior and potential targetable vulnerabilities. Furthermore, we seek to bridge the gap between scientific discoveries and their practical application in the clinical setting, ultimately contributing to improved patient outcomes.

Coordinating PI: Vincenzo Cerullo

Our immune system has the potential to protect us from cancer, but tumor cells have many strategies to hide from immune cells or turn off the immune attack. Immunotherapy is a way of helping our immune system recognize the cancer and give it the right weapons to fight and destroy it. Immunotherapies have shown great promise as cancer patients’ treatment, but only for a fraction of patients. Our research goal is to improve immune therapies and their effectiveness in patients. We will develop therapies that more precisely target a patient tumor, and can overcome the tumor defense mechanisms, and build better pre-clinical models to test therapies before they are used on patients. Our findings of tumor profiling will be delivered to the clinicians treating the patients with urological cancers (later also lung and pediatric cancers), when additional therapy options, e.g. in metastatic cancer, are required. We also plan to initiate new clinical trials. The progress will be communicated to the patients and public through patient organizations. We currently have involvement with international patient organizations and have established an initial communication plan with POTKU, including discussion events with Association of Cancer Patients in Finland on urological cancers.

Coordinating PI: Anniina Färkkilä

The overall goal is to characterize the immunogenomic landscapes and discover biomarkers for effective combination therapies in aggressive ovarian cancer, which is the most common and most lethal gynecologic cancer. We have recently shown that the tumor genetic mutations define how the tumor cells interact with immune cells and dictate therapy responses (58-59). Here, we will characterize the spatial immunogenomic landscapes with unprecedented detail in an internationally unique and large patient cohort. Using innovative patient-derived models, we will test new combination immunotherapies for ovarian cancer. We aim to discover genomic and immunological biomarkers for improved tailoring of treatments for precision oncology to improve the treatment and outcomes of patients with ovarian cancer. Our work has already produced direct and immediate benefit to ovarian cancer patients by implementing a genetic test to the clinics in Finland (60). This test is required to get PARP inhibitor targeted treatment reimbursed benefitting up to 500 ovarian cancer patients yearly in Finland. We will communicate our findings to the public using social media, press and presentations directly to the cancer patients and to the society.

Coordinating PI: Minna Koskenvuo

Approximately 150 new pediatric cancers are diagnosed in Finland annually. Current treatment strategies have improved the overall survival of pediatric cancer patients, however, there is still a portion of patients without any effective treatment or suffering from adverse effects, impairing their quality-of-life. iCAN-PEDI project aims to improve the selection of right treatment for a right patient. To this aim, we study how a patient’s tumor cells respond to the drugs, and what are the molecular alterations resulting in cancer. We develop new analytical methods to improve diagnosis and treatment of patients with pediatric solid cancers. iCAN integrated Molecular Tumor Board (iCAN-iMTB), to be established within iCAN Data Lake, will be used to report our research results to the clinicians rapidly, to affect patient treatment within weeks. For next term, our aim is to further utilize our findings by directing the patients to clinical trials based on our molecular and functional profiling, and by establishing novel clinical trials. We also propose to expand our study as a longitudinal follow-up study for childhood cancer survivors, to enable their healthier adulthood. Throughout the study, we work in close collaboration with patient/parent organizations.

Coordinating PI: Outi Monni

Rare cancers comprise about 25% of all malignancies worldwide. Despite advancements in the molecular classification, the current treatment options are often limited and thus, there is an unmet clinical need to improve diagnostics, harmonize treatment and allow possibilities for the patients to personalized treatment. The purpose of this proposal is 1) to establish a national network of clinicians involved in the treatment of patients with rare tumors to enhance tumor sample collection and to harmonize treatment protocols, 2) to perform drug screening from cultured patient samples to find novel therapeutic options and drug response-related cellular mechanisms and 3) to use bioinformatics and modern technologies such as artificial intelligence to improve the diagnostics and survival estimates from biological samples. The expected outcomes are 1) to identify diagnostically important genetic aberrations and molecular markers particularly from tumor types from which molecular profiling data are limited, 2) to accomplish standardized national treatment protocols, and 3) to identify actionable molecular alterations that may lead to clinical testing of targeted drugs. Patient involvement is considered when feasible and the progress is communicated for patients in general scientific lectures.

Coordinating PI: Lauri Aaltonen

Uterine leiomyomas (ULs), benign smooth muscle tumors of the uterine wall, cause symptoms in 25% of women, and are particularly common in the black population. The symptoms include abnormal menstrual bleeding, anemia, pelvic pain, and infertility, posing a great burden on women’s health. Curative noninvasive treatments do not exist. The many recently established high-throughput methodologies have unraveled detailed molecular mechanisms of multiple cancer types, successfully translated into advanced diagnostics and targeted therapies. Unfortunately, progress in management of UL has lagged behind that seen in precision oncology. We and others have in recent years provided a foundation for the desired translation, as more data on the molecular basis of UL is now accumulating. The proposed project aims at better management of ULs by utilizing genome data, via improvements in risk prediction, diagnosis, as well as treatment. The effort will also create knowledge on genesis of neoplasia in general.

Coordinating PI: Sakari Vanharanta

Cancers are caused by mutations. However, mutations in individual cancer genes are typically associated with only a limited set of cancer types. This reflects the fact that different tissues regulate their genomes differently, which in turn influences the effects of mutations. To fully understand how cancers develop and how their growth could be inhibited in patients, we need to therefore know which mutations tumors carry and how their genomes are regulated. The goal of this project is to expand our understanding of genome regulation in cancer, and to utilize this knowledge together with the other data types within the iCAN Discovery Platform to identify new therapeutic approaches and biomarkers that can be used to guide therapy. We expect these analyses to pinpoint specific molecules and cellular pathways that support the growth of cancer. This information can then be used for the development of new tailored therapies for patients. Our results will be communicated through scientific publications to the professional audience and announcements aimed directly at the general public.

Coordinating PI: Pirjo Laakkonen

Malignant brain tumors are fatal diseases with no existing cure. Tumor cells communicate with healthy brain to acquire therapy resistance and rapid progression. It is imperative to understand and mute this dialogue to improve the very poor patient survival. We are profiling live tumor and non-tumor cells isolated from brain cancer patients operated at HUS. By investigating genes and proteins associated with clinical features provided by the pathologists, we can stratify patients according to the tumor and non-tumor cell signatures. Connecting tumor’s molecular signatures to large drug screening on patient cells, we hope to provide new therapeutic options to Finnish patients. We are also developing novel diagnostics and therapeutics that very precisely recognize tumor cells to increase the efficacy. Our recent findings are reported in several research articles (Le Joncour et al., 2019; Filppu et al., 2021), lab webpage (https://bit.ly/3Q7eXi8) and public media e.g. Iltalehti.

Coordinating PI: Ilkka Ilonen

The foundation of the subproject is to comprehensively collect lung and other thoracic cancer samples to ican basic profiling. Our deep profiling focuses immuno-oncology (IO) treatments that harness the patient’s own immune defense for cancer treatment instead of conventional chemotherapy. Before the advent of IO therapy, the focus was to identify and develop targeted therapies that inhibit signaling pathways functioning as oncogenic drivers. This approach’s limitation was that most lung cancer patients were ineligible for not having a target, and for most patients benefiting exhibit only a transient response. Our research aims to utilize a novel drug screening platform Solid-IO for cancer research and personalized medicine. While diagnostic lung cancer samples are being extracted for pathologists for cancer diagnostics; a parallel process is initiated to grow small tumorlets in microfluidic devices to yield 3D organoids that can be tested together with isolated immune cells from the matching patients’ blood-derived immune cells with or without targeted and IO drugs with different concentrations—having a potent diagnostic tool to predict the individual treatment responses before therapy would facilitate more precise delivery of therapy and a device for novel drug trials.

Coordinating PI: Pauli Puolakkainen

Gastric cancer (GC) is the 5th most common cancer and the 4th most common cause of cancer death worldwide. Intensive chemotherapy followed by surgery is the only curative option, but often the disease has already spread and not all patients can tolerate the aggressive regimen. Also, there is considerable variation in how the tumors in different patients respond both to conventional drugs and new investigational therapies. We would need to identify which treatments to use for which patients. Recently, new molecular cancer hallmarks associated with better or worse outcomes following aggressive treatments in gastric cancer have been identified (van Ende et al., 2019, Cancers). Importantly, the non-tumor cells, such as fibroblasts and T-cells, as well as the non-cellular components inside the tumor tissue, play a critical role in the success or failure of many of these therapies. Using state-of the-art organoid drug sensitivity assays and tissue diagnostics, we aim to build a molecular and tumor tissue map for each patient. We hope this information can be of use in drafting individual patient treatment plans, and possibly apply it to clinical use as soon as possible.

Coordinating PI: Hanna Seppänen

Pancreatic cancer (PC) is an aggressive disease. Only a minority of the patients are eligible for potentially life-saving surgery. Many of these patients would benefit from treatment before the operation, but PC is difficult to diagnose correctly. There is therefore a pressing need for more accurate diagnostic methods. PC is also resistant to most treatments, creating an urgent need for ways to study the disease biology and to discover more effective treatments. Culture and testing of living tumor tissue, made possible by so called 3D organoid technology, could offer an improvement for both diagnosis and new treatment discovery. Serial blood and tumor sampling at diagnosis, surgery and metastatic disease reveals the changing biology and mutational status of the patient. Therapies in the neoadjuvant, adjuvant and palliative settings may vary in one patient as the mutational status varies. Using molecularly profiled organoids, we can finally approach this issue experimentally. Drug sensitivity testing may be useful in revealing patients that might benefit from new and repurposed regimens. Clinical trials are planned accordingly. The overall aim is to develop the diagnostics and treatment of PC towards a chronic, manageable disease.

Coordinating PI: Satu Mustjoki

Immunotherapies are treatments that engage patients’ immune system to fight cancer cells. Despite impressive results using these novel therapies in different types of cancers, treatment responses in selected malignancies have been poor. Immunotherapy works only in a small subset of patients and even the responsive subjects develop resistance to the treatment with time. Thus, it is crucial to understand the mechanisms behind patients’ resistance or responsiveness to treatments, to be able to target the correct subset of patients with the most effective therapies. To reach this important goal, we are planning to study the effect of different immunotherapies on the cancer cells, focusing especially on blood cancer and renal cell carcinoma patients. We will analyze how the cancer cells change upon treatment and which specific characteristics in the immune system that make a person more susceptible to each therapy type. We will also study which drugs can boost the immune system’s ability to defeat cancer cells and will test novel combinations of immunotherapies with known drugs previously used in other cancers. In addition, we aim to understand both tumor and tumor microenvironment factors that contribute to immunosuppression. Overall, these results will be important in our collective endeavor of finding effective and personalized treatments for currently uncurable cancers.

Coordinating PI: Markku Varjosalo

The iCAN-DETECT initiative is a pioneering endeavor aimed at unraveling the complex proteomic and phosphoproteomic architecture underpinning oncogenesis and tumor progression. At its core, this research is predicated on the postulate that cancer’s heterogeneity is encoded within its proteome, particularly within the subset of proteins post-translationally modified by phosphorylation. Through meticulous quantification and analysis of these proteins, our project endeavors to delineate the molecular idiosyncrasies of diverse cancer types, thereby fostering the development of personalized oncological therapies.

Employing state-of-the-art mass spectrometry and phospho-enrichment techniques, we will systematically catalogue the tumor and blood sample proteomes to establish a correlation between peripheral biomarkers and cancer pathophysiology. This will enable the inception of less invasive diagnostic modalities and facilitate early detection of malignancies. Moreover, by profiling the dynamic proteomic landscape of tumors in response to therapeutic interventions, our study aspires to craft a predictive framework for treatment efficacy, aligning oncological therapies with individual molecular profiles.

Our approach is inherently multidisciplinary, amalgamating expertise from clinical oncology, proteomics, and bioinformatics to interpret the vast datasets we will generate. The ultimate goal of iCAN-DETECT is to transcend conventional ‘one-size-fits-all’ cancer treatments, paving the way for bespoke therapeutic strategies that are tailored to the molecular blueprint of each patient’s cancer. By achieving this, we aim to significantly enhance the precision and effectiveness of cancer treatments, thereby improving patient outcomes and prognoses.

Coordinating PI: Tuula Salo

Oral cancer is still challenging; globally, almost half of the patients die of this disease. The treatment modalities are based mainly on surgery and radiotherapy. In advanced cases with lymph node metastases, chemo- and, more recently, in some cases, immunotherapies are used. However, less than 15% of the patients benefit from those treatments. Therefore, it would be important to select treatments that might be best for each patient.  We have developed several fast in vitro and in vivo assays to test drug and irradiation response, and based on our preliminary published data, they showed 77% assurance in predicting the outcome of the therapy.

Coordinating PI: Johanna Mattson

Deep characterization of breast tumors helps to better understand biologic factors behind tumor genesis, progression and response to treatments. Within iCAN Breast clinical data on the diagnostics, surgery, radiotherapy and systemic therapies are collected from electronic medical patient records. Efficacy of different treatment modalities will be analyzed. Follow-up data will include response to neoadjuvant systemic therapy, disease-free survival, and overall survival for early breast cancer as well as best response to systemic therapies, progression-free survival and overall survival for metastatic breast cancer. Electronic quality of life questionnaires are sent to all patients in the beginning and during the patient path as part of standard treatment. Additionally, bio-banking specimens are continuously collected by informing all new patient by a study nurse on the possibility to give the Helsinki bio-banking sample after consent. As the leading center of the EU-funded Oncovalue-study capabilities for automated collection of structured real world clinical data is being built in the breast cancer patient path at the HUS CCC. Once successfully implemented, the concept can be copied to other tumor types to enhance value-based oncology.

Coordinating PI: Esa Pitkänen

Liquid biopsies offer a way to detect cancer early and make informed decisions about treatment using blood or urine samples. Recent studies have shown that analysis of cell-free DNA (cfDNA) can provide valuable insights into cancer types, treatment options, and patient prognosis. In this project we will analyze cfDNA from 100 cancer patients with enzymatic methylation sequencing (EM-seq). This method allows us to comprehensively profile disease states without access to tumor tissue, yielding insights into cancer characteristics and behavior. We will develop machine learning models to integrate EM-seq data with patient data already available on the iCAN Discovery Platform (iCAN-DP) to provide actionable insights for personalized cancer treatment. By comparing cfDNA data with existing molecular and clinical profiles from the same patients, we will determine whether we can accurately identify important genetic alterations, track tumor evolution, and predict treatment outcomes. This study paves the way for cfDNA-based liquid biopsies to become a powerful tool in guiding cancer treatment and improving patient outcomes.

Coordinating PI: Eero Castrén

Cell plasticity is the foundation of our great diversity of cells and tissue, and the formation of memories in the adult brain. However, cancer plasticity also allows tumor cells to rapidly adapt to therapy. We are studying plasticity controlled by molecules found on neurons, called TrkB. In the brain, TrkB controls interactions between neurons, but also between neurons and cancer cells. TrkB receptors exist in different forms, each with their own function. These variations of TrkB could be linked with increased cancer aggressiveness for tumors in the brain, lung, stomach and thyroid. With iCAN, we will screen HUS patient data to identify distinct TRKB isoforms and determine how they are connected to health and clinical data. We will then analyze iCAN patient samples in biobanks to better understand cancer cell plasticity regulated by TRKB. Using live patient cells and a precision medicine approach, we will identify drugs targeting TRKB to abolish cancer plasticity. Our findings will provide improved diagnostic solutions and therapeutic opportunities for Finnish patients.