Im Vergleich zu anderen Krebsentitäten, konnten Patienten mit PDAC bisher kaum von Therapieerfolgen der Präzisionsmedizin profitieren. Um diese Problematik zu adressieren, habe ich eine umfassende molekularbiologische Studie durchgeführt, um prädiktive Biomarker zu identifizieren und die Risikostratifizierung der Patienten zu verfeinern. Mittels gen-spezifischer Sequenzierung und gezielter RNA-Expressionsanalyse wurden 293 R0-resezierte Patienten aus einer multizentrischen Phase-III-Studie untersucht. Ziel der klinischen Studie war der Vergleich von adjuvanter Chemotherapie mit Gemcitabin entweder mit oder ohne Zusatz von Erlotinib. Für meine Arbeit wurden die Patientenproben unter Verwendung einer nicht-negativen Matrixfaktorisierung (NMF) basierend auf ihren Einzelnukleotidvarianten (SNV) und ihren Kopienzahlveränderungen (CNA) gruppiert und auf klinische und molekularbiologische Unterschiede untersucht. Um die biologischen Hintergründe der identifizierten genetischen Besonderheiten zu verstehen, wurden anschließend Zelllinien genetisch modifiziert und in vitro modelliert. Es wurden 1086 SNVs und 4157 CNAs identifiziert. Dabei wiesen 99% aller Patienten mindestens eine genetische Veränderung auf, mit durchschnittlich 18 Aberrationen pro Patient. In Übereinstimmung mit früheren Berichten waren KRAS, TP53, CDKN2A und SMAD4 die am häufigsten betroffenen Gene. Alterationen in diesen Genen konnten in 63-93 % der Fälle nachgewiesen werden. Basierend darauf konnte ich fünf Patientengruppen identifizieren die sich in ihren biologischen Charakteristika unterscheiden und Angriffspunkte für gezielte Therapien bieten. Mittels NMF wurden zudem SMAD4alt MAPK9low als prognostische Biomarker für Erlotinib identifiziert. Anschließende in vitro Experimente zeigten, dass dies nicht auf eine Erhöhung der Erlotinib-Zelltoxizität zurückzuführen ist. Zuletzt definiere ich einen prognostischen Score der genutzt werden kann um das Überleben von R0-resizierten PDAC Patienten abzuschätzen. / In contrast to other cancer entities, PDAC patients have not benefited from recent improvements in precision medicine. To address this gap, I embarked on a comprehensive molecular study to identify predictive biomarkers and refine risk stratification. I performed targeted sequencing and targeted RNA expression analysis of 293 R0-resected patients from a multicenter phase III trial comparing adjuvant chemotherapy of gemcitabine with or without erlotinib. Patients were clustered using non-negative matrix factorization (NMF) based on their single nucleotide variant (SNV) and copy number alteration (CNA) statuses. Overall (OS) and disease-free survival (DFS) were analysed with the multivariate cox hazard and log rank tests. Finally, using a method based on CRISPR/Cas, findings from the patient cohort where modeled in vitro to assess their biological backgrounds. A total of 1,086 SNVs and 4,157 CNAs were found with at least one genetic alteration in 99% of all patients, and an average of 18 aberrations per patient. In line with previous reports, KRAS, TP53, CDKN2A, and SMAD4 were the most frequently affected genes, detected in 63–93 % of cases. In this thesis, I identified five biologically distinct patient subgroups with different actionable lesions that may serve for refined PDAC classification and tailored treatment approaches. NMF based clustering and subsequent differential expression analysis revealed SMAD4alt (SNV and/or CAN in SMAD4) MAPK9low (MAPK9 expression below median) as prognostic erlotinib biomarker. Modeling of SMAD4alt MAPK9low status in vitro showed that the effect is not based on increased erlotinib toxicity. Finally, I proposed a genetic risk score for prognostic evaluation of newly diagnosed R0-resected PDAC patients.

The tumor microenvironment (TME) comprising immune cells and stromal components, such as fibroblasts and vessels, emerged as one of the most significant predictors of patient survival in a variety of solid tumors. With T cells representing the major cellular effector cells of the adaptive immune system and B cells orchestrating the humoral immune response, both cell types acquire crucial roles in the antitumor immune response. Thus, a high abundance of tumor-infiltrating CD8+ T cells and B cells has been generally associated with longer survival, while immunosuppressive subsets such as regulatory T cells (Treg) and M2-polarized macrophages are frequently linked to poor prognosis. Besides the frequency, also the spatial organization emerged as a clinically relevant parameter. Hence, the formation of T and B cells in tertiary lymphoid structures (TLS) was found to favor improved clinical outcome of patients. It was further reported that besides the prognostic value, the baseline immune architecture harbors the ability to predict the response to immunotherapies such as immune checkpoint inhibitor treatment and even chemotherapy. In turn, standard cytotoxic treatment regimens like radio- and chemotherapy, as well as novel immunotherapeutic or targeted approaches, exhibit distinct effects on various immune cells. Depending on the tumor entity, therapy, and immune cell subsets, differing modulation of infiltrating immune cells after therapy was observed. While previous studies mainly investigated an altered abundance of T and B cells, changes in functional orientation and composition of lymphocyte populations are gaining increasing relevance. In this thesis, the aim was to uncover the phenotype, frequency, composition, spatial distribution, clinical significance, and therapeutic modulation of the T cell compartment in soft tissue sarcoma (STS), and B cell populations in pancreatic ductal adenocarcinoma (PDAC). Due to the low incidence and heterogeneous nature of STS, detailed analyses of distinct CD8+ and CD4+ T cell subsets are lacking. To assess the effect of multimodal treatment, comprising radiotherapy and locoregional hyperthermia with or without chemotherapy, on the immune architecture, the patient cohort included matched pre- and post-therapy tissue samples. By assessing both the peritumoral and intratumoral region, additional information about the spatial distribution of STS-infiltrating T cells was gained. In PDAC, the T cell compartment and its therapeutic modulation has been explored in detail recently, but equivalent insight into the B cell landscape is missing. Going beyond the abundance of pan B cells, the aim was to identify proliferating B and T cells, germinal center (GC) B cells, plasmablasts, and plasma cells to investigate their modulation by neoadjuvant chemo(radio)therapy (NeoTx). Further insight into the spatial composition was gained by analyzing different regions (intratumoral and peritumoral) and tissue compartments (epithelial, stromal, TLS). To achieve this, three novel multiplex immunohistochemistry panels were established enabling simultaneous staining of six markers plus DAPI. For CD4+ T helper (Th) cells, the master transcription factors for Th1 (T-box expressed in T cells), Th2 (GATA-binding protein 3), Th17 (retinoic acid receptor-related orphan receptor T), and Treg (Forkhead box protein 3) were included in addition to CD3 and the proliferation marker Ki67. The CD8+ T cell panel comprised the phenotypic marker CD8, the immune checkpoint molecules programmed cell death protein 1 and lymphocyte-activation gene 3 as well as the activation-associated molecules granzyme B and 4-1BB, in addition to Ki67. It was thus found that post-treatment STS samples displayed moderately reduced frequencies of both CD8+ and CD3+ T cells in comparison to the pretreatment biopsy. The Th cell landscape was dominated by Th2 cells, whose density was significantly reduced upon multimodal therapy and a moderate redistribution favoring Th1 and Th17 cells was observed. While high frequencies of CD3+ and CD8+ T cells in the posttreatment tissues were associated with significantly longer disease-free survival, these populations held no prognostic value in the biopsy obtained prior to treatment, suggesting a reshaping of the TME upon therapy. Furthermore, the spatial distribution, reflected by the ratio of intra- to peritumoral CD8+ T cells, emerged as an independent prognostic factor for the risk of recurrence. In PDAC, B cell subsets were identified by staining for CD3, CD20, Ki67, the transcription factor B cell lymphoma 6, and the plasma cell markers CD38 and CD138. While CD3+ T cells were unaffected, significantly lower frequencies of proliferating B cells, GC B cells, plasmablasts, and plasma cells were observed in the NeoTx group compared to patients undergoing primary resection (PR). Furthermore, neoadjuvant-treated patients exhibited a significantly lower abundance of TLS, which was validated in an independent cohort. These results indicate that NeoTx differentially affects distinct immune cell subsets, and that B cellmediated antitumor immunity may be inhibited by chemo(radio)therapy. Spatial analysis further revealed that plasma cell accumulations frequently localized close to TLS, being accompanied by C-X-C motif chemokine ligand 12-expressing fibroblasts. Furthermore, patients with TLS exhibited significantly higher plasma cell frequencies, suggesting that TLS can foster the generation of plasma cells whose migration is then guided by fibroblastic tracks. Lastly, a prognostic value of pan T and B cells was observed only in the PR group, while these populations provided no clinical significance in neoadjuvant-treated patients. However, proliferating Ki67+CD20+ B cells emerged as an independent prognostic factor for a lower risk of death in the NeoTx group, suggesting a restorative post-treatment TME in these patients. Altogether, this thesis provided novel insights into the TME of STS and PDAC and its therapeutic alteration. Spatial analyses further enabled an improved understanding of the immune architecture and potential cell-cell interactions within the TME. In addition, strong associations with patient survival highlight the enormous significance of the TME and may guide future therapy development. Although the results do not encourage a concomitant application of cytotoxic therapy regimens and immunotherapy, patients may benefit from sequential combination treatments. An enhanced understanding of the immunomodulatory effects of NeoTx is pivotal for overcoming the immunosuppressive TME of STS and PDAC by refining existing treatment regimens and developing novel therapy approaches in order to improve the long-term outcome of patients.