Anderle, N. | Search bioRxiv

bioRxiv2022

Protein profiling of breast carcinomas reveals expression of immune-suppressive factors and signatures relevant to patient outcome

BackgroundIn cancerous tissue, a complex interplay of tumour cells with different cell types from the tumour microenvironment is causing modulations in signalling processes. By directly assessing expression of a multitude of proteins and protein variants, extensive information on signalling pathways, their activation status and the effect of the immunological landscape can be obtained providing viable information for treatment response. MethodsProtein extracted from archived breast cancer tissue from patients without adjuvant therapy was subjected to high-throughput Western blotting using the DigiWest technology. Expression of 150 proteins and protein variants covering cell cycle control, apoptosis, Jak/Stat, MAPK-, Pi3K/Akt-, Wnt-, and, autophagic signalling as well as general tumour markers was monitored in a cohort of 84 patient samples. The degree of immune cell infiltration was investigated and set against treatment outcome by integrating patient specific follow-up data. ResultsCharacterization of the tumour microenvironment by monitoring CD8, CD11c, CD16 and CD68 expression revealed a strong correlation of event-free patient survival with immune cell infiltration. Furthermore, the presence of tumour infiltrating lymphocytes was linked to a pronounced activation of the Jak/Stat signalling pathway and apoptotic processes. Elevated phosphorylation of peroxisome proliferator-activated receptor gamma (PPAR{gamma}, pS112) in non-immune infiltrated tumour tissue suggests a novel immune evasion mechanism in breast cancer characterized by increased PPAR{gamma} activation. ConclusionMultiplexed immune cell marker assessment and protein profiling of tumour tissue provides functional signalling data facilitating breast cancer patient stratification.

cancer biology↗

bioRxiv2021

A platform of patient-derived microtumors identifies treatment response and therapeutic vulnerabilities of ovarian cancer

BackgroundIn light of the frequent development of therapeutic resistance in cancer treatment, there is a strong need for personalized model systems representing patient tumor heterogeneity, while enabling parallel drug testing and identification of appropriate treatment responses in individual patients. Using ovarian cancer as a prime example of a heterogeneous tumor disease with complex microenvironment and high recurrence rates, we developed a 3D preclinical ovarian cancer model comprised of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs) for identification of treatment vulnerabilities and validation of anti-cancer drug efficacy using immunohistochemistry, immune cell phenotyping, functional assays and protein profiling analyses. MethodsPDM and TILs were isolated from fresh primary ovarian cancer tissue specimen using mechanical disruption and limited enzymatic digestion and were subsequently cultured in suspension in defined media in the absence of serum. The heterogeneous cellular composition of isolated PDM as well as autologous TILs was analyzed by FFPE immunohistochemistry and multi-color flow cytometry, respectively. For in-depth protein profiling of PDM we established Reverse Phase Protein Array (RPPA) analyses of >110 total and phospho-proteins. Treatment efficacy in response to chemotherapeutics as well as immunotherapeutic compounds was assessed in PDM and PDM-TIL co-cultures using a functional viability assay in microplate format. ResultsThe enzymatic digestion of primary ovarian cancer tissue and suspension culture in defined serum-free media allowed fast and efficient recovery of patient-derived microtumors (PDM). Immunohistochemical analyses demonstrated histopathological comparability of ovarian cancer PDM with corresponding patient tumor tissue. Reverse Phase Protein Array (RPPA)-based analyses of >110 total and phospho-proteins enabled the identification of patient-specific sensitivities to standard, platinum-based therapy and thereby the prediction of potential treatment-responders. Finally, combining PDM and autologous TILs for individual efficacy testing of immune checkpoint inhibitor treatment demonstrated the potential for patient-specific enhancement of cytotoxic TIL activity by this therapeutic approach. Conclusion3D patient-derived ovarian cancer microtumors represent a preclinical, ex vivo tumor model that reflects intertumoral heterogeneity and represent the cellular complexity of individual patient tumors. Combining protein pathway analysis and anti-cancer drug efficacy testing of PDM enables drug mode-of-action analyses and therapeutic sensitivity prediction within a clinically relevant time frame after surgery. Follow-up studies in larger cohorts are currently under way to further evaluate the applicability of this platform to support clinical decision-making and personalizing cancer treatment.

cancer biology↗