The diversity of T cells in the human liver may reflect the composition of TILs in CRLM. Our ex vivo characterization of CRLM vs. adjacent liver tissue detected CD103+CD39+CD8+ T_RM cells predominantly in CRLM, which prompted further assessments. These T_RM cells responded to cognate antigens in vitro. As functional activities of autologous TILs are central to the implementation of personalized cancer treatments, we applied a patient-derived xenograft (PDX) model to monitor TILs’ capacity to control CRLM-derived tumors in vivo. We established PDX mice with CRLMs from two patients, and in vitro expansion of their respective TILs resulted in opposing CD4+ vs. CD8+ TIL ratios. These CRLMs also displayed mutated KRAS, which enabled trametinib-mediated inhibition of MEK. Regardless of the TIL subset ratio, persistent or transient control of CRLM-derived tumors of limited size by the transferred TILs was observed only after trametinib treatment. Of note, a portion of transferred TILs was observed as CD103+CD8+ T_RM cells that strictly accumulated within the autologous CRLM-derived tumor rather than in the spleen or blood. Thus, the predominance of CD103+CD39+CD8+ T_RM cells in CRLM relative to the adjacent liver and the propensity of CD103+CD8+ T_RM cells to repopulate the autologous tumor may identify these TILs as strategic targets for therapies against advanced CRC.

Aims/hypothesis: Type 1 diabetes manifests after irreversible beta cell damage, highlighting the crucial need for markers of the presymptomatic phase to enable early and effective interventions. Current efforts to identify molecular markers of disease-triggering events lack resolution and convenience. Analysing frequently self-collected dried blood spots (DBS) could enable the detection of early disease-predictive markers and facilitate tailored interventions. Here, we present a novel strategy for monitoring transient molecular changes induced by environmental triggers that enable timely disease interception. Methods: Whole blood (10 μl) was sampled regularly (every 1–5 days) from adult NOD mice infected with Coxsackievirus B3 (CVB3) or treated with vehicle alone. Blood samples (5 μl) were dried on filter discs. DBS samples were analysed by proximity extension assay. Generalised additive models were used to assess linear and non-linear relationships between protein levels and the number of days post infection (p.i.). A multi-layer perceptron (MLP) classifier was developed to predict infection status. CVB3-infected SOCS-1-transgenic (tg) mice were treated with immune- or non-immune sera on days 2 and 3 p.i., followed by monitoring of diabetes development. Results: Frequent blood sampling and longitudinal measurement of the blood proteome revealed transient molecular changes in virus-infected animals that would have been missed with less frequent sampling. The MLP classifier predicted infection status after day 2 p.i. with over 90% accuracy. Treatment with immune sera on day 2 p.i. prevented diabetes development in all (100%) of CVB3-infected SOCS-1-tg NOD mice while five out of eight (62.5%) of the CVB3-infected controls treated with non-immune sera developed diabetes. Conclusions/interpretation: Our study demonstrates the utility of frequently collected DBS samples to monitor dynamic proteome changes induced by an environmental trigger during the presymptomatic phase of type 1 diabetes. This approach enables disease interception and can be translated into human initiatives, offering a new method for early detection and intervention in type 1 diabetes. Data and code availability: Additional data available at https://doi.org/10.17044/scilifelab.27368322. Additional visualisations are presented in the Shiny app interface https://mouse-dbs-profiling.serve.scilifelab.se/. Graphical

Tailored treatment for patients with rectal cancer requires clinically available markers to predict their response to neoadjuvant treatment. The quantity of tumor-infiltrating lymphocytes (TILs) in pre-operative tumor biopsies has been suggested to predict a favorable response, but opposing results exist. A biopsy-adapted Immunoscore (IS_B) based on TILs has recently emerged as a promising predictor of tumor regression and prognosis in (colo)rectal cancer. We aimed to refine the IS_B for prediction of response using multiplex immunofluorescence (mIF) on pre-operative rectal cancer biopsies. We combined the distribution and density of conventional T cell subsets and γδT cells with a type I Interferon (IFN)-driven response assessed using Myxovirus resistance protein A (MxA) expression. We found that pathological complete response (pCR) following neoadjuvant treatment was associated with type I IFN. Stratification of patients according to the density of CD8⁺ in the entire tumor tissue and MxA⁺ cells in tumor stroma, where equal weight was assigned to both parameters, resulted in improved predictive quality compared to the IS_B. This novel stratification approach using these two independent parameters in pre-operative biopsies could potentially aid in identifying patients with a good chance of achieving a pCR following neoadjuvant treatment.

Symptoms of immune-mediated diseases (IMIDs) typically appear after irreversible tissue damage, making early interventions based on pre-symptomatic indicators crucial. Current efforts to identify molecular markers of early disease lack the resolution, convenience and cost efficiency required to prevent irreversible tissue damage. Analyzing frequently self-collected samples, such as dried blood spots (DBS), could enable the earlier detection of diseases, identify disease-predictive markers and facilitate tailored interventions. To test this, we regularly microsampled a mouse model infected with a type 1-diabetes (T1D)-associated virus. This longitudinal DBS sample collection was analyzed for 92 circulating proteins, revealing transient molecular changes in virus-infected animals that would have been missed with less frequent sampling. Machine learning predicted infection status after day 2 post-infection with >90% accuracy, enabling well-timed treatment of virus-infected animals and diabetes prevention. Our study demonstrates the utility of frequent blood microsampling to monitor disease during the pre-symptomatic phase, allowing for timely interventions. Teaser: Frequent blood microsampling detects early biomarkers, enabling timely intervention in immune-mediated diseases

Characterizing the composition of immune cells in the tumor microenvironment (TME) has shown promise in understanding variable responses to neoadjuvant treatment in rectal cancer. Despite this, no method has been established that can confidently predict the response to pre-operative chemoradiotherapy. Tumor-associated macrophages (TAMs) in the TME can be polarized by the biochemical milieu to adopt pro-inflammatory (M1-like) and anti-inflammatory (M2-like) phenotypes. Utilizing the spectrum of TAM polarization as a biomarker to predict patient response to neoadjuvant therapy in rectal cancer patients has not been fully explored. We address this using 7-plex immunofluorescence staining to quantify 16 subsets of TAMs in rectal adenocarcinoma pretreatment biopsies. Pretreatment biopsies were obtained from 128 patients with known tumor regression grades (TRG). Through quantifying the prevalence of TAM subsets, we identified a higher density of the completely M1-polarized subset and a lower density of the completely M2-polarized subset in patients with a complete pathological response, the absence of detectable tumor cells following treatment. Predictive modeling using TAM subsets showed that only the densities of two completely polarized subsets were predictors of therapeutic response in patients with rectal cancer. Significantly, we demonstrate that the full panel of markers we employed were required to define predictive populations, as total TAMs or TAM subsets defined by fewer markers were incapable of predicting treatment response. Taken together, we validate the utility of a multiplex approach to define the spectrum of TAM polarization, which can be leveraged to identify patients that will have a complete pathological response to neoadjuvant treatment.

Type 1 diabetes is a chronic, potentially lethal disease that is affecting millions worldwide and to which there is currently no cure. It is believed to be caused by autoimmune destruction of the pancreatic beta cells, and the disease has been proposed to occur long before onset of symptoms, but the mechanisms that cause the initial trigger of type 1 diabetes are not fully understood. Viral infections, in particular those by coxsackievirus group B, have been associated with type 1 diabetes and may constitute one mechanism by which some individuals develop the disease. However, means to detect an ongoing coxsackievirus B infection that may lead to type 1 diabetes, or antiviral treatments that may prevent disease onset, are currently lacking.This thesis work aimed to expand our understanding of innate immunity in the development of type 1 diabetes, explore potential biomarkers that could detect early stages of the disease, and investigate drugs with promise as novel antivirals.In Study I, we investigated the expression and function of type III interferons - a class of interferons part of the innate antiviral defence - in the pancreas and in models of pancreatic islets and beta cells. We showed that type III interferons are expressed in the pancreas at onset of type 1 diabetes and that these cytokines confer the expression of classical interferon-stimulated genes that both lead to a robust antiviral defence and to increased susceptibility to T cell-mediated killing of beta cells, which could be attenuated by inhibitors of the JAK/STAT pathway.Study II explored novel potential biomarkers for coxsackievirus B infection and early stages of diabetes, detectable in plasma from preclinical in vivo models, using advanced transcriptomics and proteomics technologies. By measuring miRNAs and proteins in plasma and plasma fractions enriched for extracellular vesicles, we observed significant changes to hundreds of miRNAs and proteins upon infection, several of which were validated in new sample batches and with different methods. These findings could lead to the establishment of novel biomarkers of the earliest stages of diabetes triggered by a diabetogenic virus.Study III continues the approach of leveraging liquid biopsy proteomics for early virus detection. Here, we performed preclinical in vivo microsampling of blood, stored as dried blood spots, and leveraged proteomics analysis of 92 proteins and machine learning technologies to develop a classifier that could accurately predict infection prior to symptom onset. We showed that this information allows for timely antiviral treatment that prevents diabetes caused by virus infection. This proof-of-concept study shows a method by which infection can be detected early and thus prevented.Finally, Study IV examined the antiviral effects of a cancer drug - Vemurafenib - and its analogue in clinically relevant models of enterovirus infection. Using in vitro models of intestinal epithelial cells, beta cells and pancreatic islets, we showed that the drugs conferred antiviral effect, and could be used for the development of repurposed drugs that intercepts infection of enteroviruses such as coxsackievirus B.In sum, the work described in this thesis provides insights into the underlying factors that may contribute to type 1 diabetes, and describes novel ways for the early detection of and treatment against infection by a potentially diabetogenic virus.List of scientific papersI. Ringqvist EE, Tuomela S, Byvald F, Burgos-Morales O, Krogvold L, Fernandez Moro C, Mazur M, Burdsall K, Bendes A, Vasylovska S, Castro M, Stone VM, Parajuli A, Sork H, Mjösberg J, Buggert M, Jorns C, Schwenk JM, Lau J, Matthews CE, Gerling IC, Richardson SJ, Dahl- Jorgensen K, Mallone R, Flodström-Tullberg M. Type III interferons (IFN-Às) are expressed in human pancreas at type 1 diabetes onset and induce immunostimulatory activities in human beta cells. [Manuscript]II. Byvald F, Sork H*, Diaz Lozano I*, Stone VM, Ringqvist EE, Koxha B, Eldh M, Mowoe M, EL Andaloussi S, Gabrielsson S, Flodström- Tullberg M. Plasma miRNA and Protein Biomarkers in an Experimental Model of Coxsackievirus Infection and Virus-Induced Diabetes. [Manuscript]III. Parajuli A*, Bendes A*, Byvald F, Stone VM, Ringqvist EE, Butrym M, Angelis E, Kipper S, Bauer S, Roxhed N, Schwenk JM ** , Flodström- Tullberg M **. Longitudinal blood microsampling and proteome monitoring uncover early disease markers and facilitate intervention in experimental type 1 diabetes. Diabetologia. 2025 Oct;68(10):2277-2289. https://doi.org/10.1007/s00125-025-06502-7IV. Butrym M, Byvald F, Blanter M, Ringqvist EE, Vasylovska S, Marjomäki V, Lau J, Stone VM, Flodström-Tullberg M. Vemurafenib inhibits the replication of diabetogenic enteroviruses in intestinal epithelial and pancreatic beta cells. Antiviral Res. 2024:106021. https://doi.org/10.1016/j.antiviral.2024.106021* Equal contribution** Joint senior authors