Göran Landberg

Flower-Win/Lose signaling underlies a tumor–host fitness conflict in ovarian cancer, in which tumor-derived exosomal Tu-stroma reduces the fitness of surrounding host cells, favoring tumor expansion within host tissues. High-grade serous carcinoma (HGSC), the most prevalent histotype of epithelial ovarian cancer and leading cause of ovarian-cancer-related mortality, arises from serous tubal intraepithelial carcinoma (STIC), a noninvasive precursor typically identifiable only by histopathologic examination of excised fallopian tube tissue. Here we evaluated Tu-stroma, a tumor-associated long noncoding RNA enriched in serum extracellular vesicles (EVs), as a circulating biomarker in STIC and early-stage HGSC, representing the earliest histopathologically defined phases of disease. Tu-stroma was quantified in serum EVs from 506 individuals with histologically normal adnexa, benign-adnexal lesions, isolated STIC and HGSC across International Federation of Gynecology and Obstetrics (FIGO) stages I–IV. Normalized EV Tu-stroma ΔC_T values were elevated in STIC (n = 43) and HGSC (n = 232) versus controls (n = 143) and benign-adnexal lesions (n = 88), including premenopausal women (controls = 57, benign = 34, STIC = 32, HGSC = 88). In paired receiver operating characteristic analyses, Tu-stroma showed higher discrimination than cancer antigen 125 (CA125) for STIC versus controls (area under the curve (AUC) = 0.99 versus 0.59, P < 0.001) and benign-adnexal masses (0.99 versus 0.31, P < 0.001), and for HGSC versus controls (AUC = 0.99 versus 0.96, P = 0.001) and benign-adnexal masses (0.98 versus 0.84, P < 0.001). Tu-stroma showed no systematic elevation across inflammatory or physiologic comparators (n = 116) or nonovarian malignancies (n = 160), each assessed against healthy controls (n = 100), supporting disease-context specificity. Modeled risk-enriched contexts yielded predictive values compatible with intended-use populations. These findings identify Tu-stroma as a candidate EV-RNA marker associated with pre-invasive and early HGSC biology. Prospective evaluation in consecutively enrolled real-world cohorts is required to validate diagnostic performance, predictive value and clinical utility.

Peritoneal metastases from colorectal cancer are associated with poor survival and limited therapeutic efficacy. To model patient-specific treatment responses, we generated patient-derived scaffolds (PDS) through tumor decellularization, preserving critical microenvironmental features for functional ex vivo analysis. PDS from 75 metastases were recellularized with HT29 cells and treated with 5-fluorouracil (5-FU), mitomycin C, or oxaliplatin. Gene expression related to proliferation, epithelial phenotype, epithelial-mesenchymal transition, and stemness was quantified and integrated into a composite treatment score to estimate the most favorable therapy for each patient. Treatment responses were influenced by both drug exposure and the patient-specific microenvironment. Importantly, subcluster distributions differed across treatment arms, supporting the concept that therapeutic response is modulated by microenvironmental context rather than being solely drug dependent. These findings were supported in a smaller validation cohort using HCT116 and DLD-1 cells recellularized into selected PDS. Treatment scoring based on HT29 cells revealed heterogeneous sensitivity patterns, with 38.7% of PDS responding best to 5-FU, 36% to mitomycin C, and 25.3% to oxaliplatin. Patients with more than two favorable treatment scores had improved disease-free survival ( p = 0.0415). The PDS platform enables functional profiling of chemotherapy-response and may support individualized treatment strategies for colorectal cancer patients with peritoneal metastases.

Recent advances as well as obstacles for immune-based cancer treatment strategies, highlight the notable impact of patient cancer microenvironments on the immune cells and immune targets. Here, we use patient-derived scaffolds (PDS) generated from 110 primary breast cancers to monitor the impact of the cancer microenvironment on immune regulators. Pronounced variation in PD-L1 expression is observed in cancer cells adapted to different patient scaffolds. This variation is further linked to clinical observations and correlated with specific proteins detected in the cell-free PDSs using mass spectrometry. When adding T cells to the PDS-based cancer cultures, the killing efficiency of activated T cells vary between the cultures, whereas non-activated T cells modulate the cancer cell PD-L1 expression to treatment-predictive values, matching killing capacities of activated T cells. Surviving cancer cells show enrichment in cancer stem cell and epithelial-to-mesenchymal transition (EMT) features, suggesting that T cells may not efficiently target cells with metastatic potential. We conclude that clinically relevant insights in how to optimally target and guide immune-based cancer therapies can be obtained by including patient-derived scaffolds and cues from the cancer microenvironment in cancer patient handling and drug development.