Biology subjects

Hakkinen, A.

Publications and source records attributed to Hakkinen, A..

6 recordsLinked to original sources

bioRxiv2025

Multi-modal characterization of transcriptional programs that drive metastatic cascades to solid sites and ascites in ovarian cancer

Ovarian high-grade serous carcinoma (HGSC) is characterized by extensive intra-peritoneal dissemination and tumor heterogeneity. In the metastatic cascade, tumors utilize several transcriptional programs to translocate and survive in distant tissues. Here, we analyzed multi-modal, real-world data from 350 tumor samples across 160 patients with HGSC to identify transcriptional programs that drive intra-peritoneal metastasis and heterogeneity. We identified nine transcriptional programs, including those regulating epithelial-mesenchymal transition and immune modulation and cytoskeletal reorganization, which shape distinct metastatic trajectories to solid and ascitic environments and are associated to treatment response. Our results reveal pronounced intra-patient transcriptional heterogeneity, which in some cases surpassed inter-patient heterogeneity, highlighting the importance of multi-site sampling for accurate prognostication and combinatorial treatments in HGSC. Our extensive characterization offers novel insights into intra-peritoneal metastasis with significant prognostic implications, reveals histomorphological biomarkers for patient stratification and paves the way for innovative therapeutic strategies aimed at impairing cancer cell adaptability and limiting metastasis.

cancer biology↗

bioRxiv2022

Lineage-specific oncogenes drive growth of major forms of human cancer using common downstream mechanisms

Mutations in hundreds of genes have been associated with formation of human cancer, with different oncogenic lesions prevalent in different cancer types. Yet, the malignant phenotype is simple, characterized by unrestricted growth of cells that invade neighboring healthy tissue and in many cases metastasize to distant organs. One possible hypothesis explaining this dichotomy is that the cancer genes regulate a common set of target genes, which then function as master regulators of essential cancer phenotypes, such as growth, invasion and metastasis. To identify mechanisms that drive the most fundamental feature shared by all tumors - unrestricted cell proliferation - we used a multiomic approach to identify common transcriptional and posttranslational targets of major oncogenic pathways active in different cancer types, and combined this analysis with known regulators of the cell cycle. We identified translation and ribosome biogenesis as common targets of both transcriptional and posttranslational oncogenic pathways. By combining proteomic analysis of clinical samples with functional studies of cell cultures, we also establish NOLC1 as a key node whose convergent regulation both at transcriptional and posttranslational level is critical for tumor cell proliferation. Our results indicate that lineage-specific oncogenic pathways commonly regulate the same set of targets important for growth control, revealing novel key downstream nodes that could be targeted for cancer therapy or chemoprevention.

cancer biology↗

bioRxiv2022

The transcription factor network of E. coli steers global responses to shifts in RNAP concentration

The robustness and sensitivity of gene networks to environmental changes is critical for cell survival. How gene networks produce specific, chronologically ordered responses to genome-wide perturbations, while robustly maintaining homeostasis, remains an open question. We analysed if short- and mid-term genome-wide responses to shifts in RNA polymerase (RNAP) concentration are influenced by the known topology and logic of the transcription factor network (TFN) of Escherichia coli. We found that, at the gene cohort level, the magnitude of the single-gene, mid-term transcriptional responses to changes in RNAP concentration can be explained by the absolute difference between the genes numbers of activating and repressing input transcription factors (TFs). Interestingly, this difference is strongly positively correlated with the number of input TFs of the gene. Meanwhile, short-term responses showed only weak influence from the TFN. Our results suggest that the global topological traits of the TFN of E. coli shape which gene cohorts respond to genome-wide stresses.

systems biology↗

bioRxiv2020

In vivo single-cell analysis using calcofluor - white staining detects high expression phenotype in L. lactis cultures engineered for hyaluronic acid production.

Hyaluronic acid (HA) is a biopolymer with wide applications in the field of medicine and cosmetics. Bacterial production of HA has a huge market globally. Certain species of Streptococcus are native producers of HA but they are pathogenic. Therefore, safer organisms such as L. lactis are engineered for HA production. However, there are challenges such as low yield, low molecular weight and polydispersity of HA obtained from these cultures. Optimisation of bioprocess parameters and downstream purification parameters are being addressed to overcome these challenges. We explore these problems from the perspective of microbial heterogeneity, since variations in phenotype affect the yield and properties of the product in a bioreactor. For this perspective, a method to quantitatively assess the occurrence of heterogenous phenotypes depending on the amount of HA produced at the single-cell level is required. Here, we evaluated for the first time the use of calcofluor white staining method combined with in vivo fluorescence confocal microscopy to quantify the heterogeneity in phenotypes of L. lactis cells engineered for HA production. From the microscopy image analysis, we found that the population harbours significant heterogeneity with respect to HA production and our novel approach successfully differentiates these phenotypes. Using the fluorescence intensity levels, first we were able to confidently differentiate cells not expressing HA (Host cells without HA genes for expression) from cells with genes for HA production (GJP2) and induced for expression, as there is a consistently two-fold higher level of expression in the GJP2 cells independently of the cell size. Further, this method revealed the occurrence of two different phenotypes in GJP2 cultures, one of a high-expression phenotype (40% of the population) and the other one of a low-expression (remaining 60% of the population), and it is the high expression phenotype that contributes to the increase in the HA expression of the GJP2 population compared with the host cells. Thus, it is essential to identify the extrinsic and intrinsic factors that can favour most of the cells in the population to switch and stabilise into the high-expression phenotype state in a bioreactor, for higher yield and possibly reduced heterogeneity of the product, such as polydispersity in chain lengths. For such optimisation studies, this in vivo method serves as a promising tool for rapid detection of phenotypes in the bioreactor samples under varying conditions, allowing fine tuning of the factors to stabilise high-expression phenotypes thereby maximizing the yield. Graphical Abstractdone. Key PointsO_LICalcofluor staining successfully differentiated the phenotypes based on HA levels. C_LIO_LIThis study revealed the occurrence of significant heterogeneity in HA expression. C_LIO_LIThis method will aid for rapid optimization of factors for improved HA production. C_LI

bioengineering↗

bioRxiv2020

Analysis of single-cell RNA-seq data from ovarian cancer samples before and after chemotherapy links stress-related transcriptional profile withchemotherapy resistance

Chemotherapy resistance is the greatest contributor to cancer mortality and the most urgent unmet challenge in oncology. In order to reveal transcriptomics changes due to platinum-based chemotherapy we analyzed single-cell RNA-seq data from fresh tissue samples taken at the time of diagnosis and after neoadjuvant chemotherapy from 11 high-grade serous ovarian cancer (HGSOC) patients. With a novel clustering method accounting for patient-specific variability and technical confounders, we identified 12 clusters. Of these, a stress-related transcriptional profile was enriched during chemotherapy and associated significantly to poor progression-free survival (PFS) and disease-free interval (DFI) in deconvoluted bulk RNA-seq data analysis of treatment-naive samples in TCGA cohort. Pan-cancer cell line analysis suggests that patients with high stress-related transcriptional profile may benefit from MEK1/2 inhibitors instead of platinum. Further, high proportion of stromal components and high interaction score between tumor and stromal suggest the tumor cells with high-stress profile actively interact with and potentially recruit stromal cells to their microenvironment already prior to chemotherapy, potentially facilitating protection from chemotherapeutic treatments. In summary, we have identified a stress-related transcriptional profile, which is present at the time of diagnosis, enriched during platinum treatment, independent predictor for poor PFS and DFI, and, based on in vitro data, targetable with MEK1/2 inhibitors. Translational relevanceWe discovered a stress-related transcriptional profile that is significantly enriched in fresh tissue samples after chemotherapy and is significantly associated with poor progression-free survival in an independent patient cohort. The survival association is independent of age, tumor purity or BRCAness. Therefore, this chemotherapy resistance associated profile is intrinsic and could thus be targeted already in treatment-naive patients. The translation potential of the stress-related transcriptomics profile was further supported by pan-cancer cell line analysis that showed that cell lines with high stress-related transcriptional profile are not affected by platinum, corroborating our results, whereas they were more sensitive to MEK1/2 inhibitors. Taken together, the stress-related transcriptional profile, quantifiable with a set of 35 marker genes, provides a basis for improved prediction of platinum response as well as novel avenues to treat this patient group more effectively.

bioinformatics↗

bioRxiv2019

Transcription closed and open complex formation coordinate expression of genes with a shared promoter region

Many genes are spaced closely, allowing coordination without explicit control through shared regulatory elements and molecular interactions. We study the dynamics of a stochastic model of a gene-pair in a head-to-head configuration, sharing promoter elements, which accounts for the rate-limiting steps in transcription initiation. We find that only in specific regions of the parameter space of the rate-limiting steps is orderly co-expression exhibited, suggesting that successful cooperation between closely spaced genes requires the co-evolution of compatible rate-limiting step configuration. The model predictions are validated by in vivo single-cell, single-RNA measurements of the dynamics of pairs of genes sharing promoter elements. Our results suggest that, in E. coli, the kinetics of the rate-limiting steps in active transcription can play a central role in the dynamics of pairs of genes sharing promoter elements.

biophysics↗