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Multivariable Survival Models.

Figure S1. Selected images of different sTILs amounts, illustration of applied scoring method and images of IHC stainings. Figure S2. TLS in MIBC Figure S3. Subtyping of the CCC-EMN cohort and the TCGA-Cohort according to the MDACC-subtyping gene signature Figure S4. TCGA-Basal tumors (n=142). CIBERSORT and Mutational Burden. Figure S5. TCGA Luminal tumors (n=243). CIBERSORT and Mutational Burden. Figure S6. Distribution of tumor mutational burden (TMB; based on total single nucleotide variants) and neoantigens among different cut-offs of stromal TILs. Figure S7. TCGA - Antigen presenting cell signature (AGPS) and combined adjuvant platinum-containing chemotherapy cohort.

Supplementary Table from Epigenetic Therapies in Ovarian Cancer Alter Repetitive Element Expression in a TP53-Dependent Manner

(A) Clinico-pathological cohort data and molecular genetic features of the mapping bladder (Case ID4). (B) Clinico-pathological cohort data of the tissue microarray cohort of papillary high grade carcinomas and CIS.

(A) Unsupervised hierarchical clustering of tumor subtyping protein markers determined by semiquantitative immunohistochemistry (CK5, CK14, CD44, CK20, GATA3, FOXA1, UPKII) reveals a basal and luminal cluster. (B) HER2/neu protein expression (left panel) and ERBB2/CEN17-ratio in the WBHM samples. HER2/neu protein expression and its genetically detected ERBB2-gene locus amplification co-occur in CIS, pT1 carcinomas and MIBCs. (C) Distribution of "Normal-like", "Transforming-like" and "Invasive-like" cluster assignments in the WBHM scheme illustrates "Invasive-like" lesions surrounded by "Transforming-like" lesions. CIS = Carcinoma in situ; DYS = Dysplasia; UPUMP/HYP = urothelial proliferation of unknown malignant potential/ hyperplasia (abbreviated as "HYP" in graphs); IRS = Immunoreactive score; MIBC = Muscle-invasive bladder cancer; pT1 = Stroma invasive bladder cancer; U = Tumor associated urothelium.

Epithelial ovarian carcinomas are particularly deadly due to intratumoral heterogeneity, resistance to standard-of-care therapies, and poor response to alternative treatments such as immunotherapy. Targeting the ovarian carcinoma epigenome with DNA methyltransferase inhibitors (DNMTi) or histone deacetylase inhibitors (HDACi) increases immune signaling and recruits CD8+ T cells and natural killer cells to fight ovarian carcinoma in murine models. This increased immune activity is caused by increased transcription of repetitive elements (RE) that form double-stranded RNA (dsRNA) and trigger an IFN response. To understand which REs are affected by epigenetic therapies in ovarian carcinoma, we assessed the effect of DNMTi and HDACi on ovarian carcinoma cell lines and patient samples. Subfamily-level (TEtranscripts) and individual locus-level (Telescope) analysis of REs showed that DNMTi treatment upregulated more REs than HDACi treatment. Upregulated REs were predominantly LTR and SINE subfamilies, and SINEs exhibited the greatest loss of DNA methylation upon DNMTi treatment. Cell lines with TP53 mutations exhibited significantly fewer upregulated REs with epigenetic therapy than wild-type TP53 cell lines. This observation was validated using isogenic cell lines; the TP53-mutant cell line had significantly higher baseline expression of REs but upregulated fewer upon epigenetic treatment. In addition, p53 activation increased expression of REs in wild-type but not mutant cell lines. These data give a comprehensive, genome-wide picture of RE chromatin and transcription-related changes in ovarian carcinoma after epigenetic treatment and implicate p53 in RE transcriptional regulation.Significance:This study identifies the repetitive element targets of epigenetic therapies in ovarian carcinoma and indicates a role for p53 in this process.See interview with Katherine B. Chiappinelli, PhD, recipient of the 2022 Cancer Research Early Career Award: https://vimeo.com/720726570

Reference sequences, gene lists and gene expression distribution of utilized NanoString-assays.

(A)Overview of genes belonging to gene clusters (PanCancer Progression Panel). (B) Most differentially expressed signaling pathways and genes between lesion cluster A and C. (C) Most differentially expressed signaling pathways and genes between lesion cluster A and C.

Comparison of RNAseq and Nanostring-based subtyping in MIBCs from the CCC-EMN cohort with available RNAseq data. The 22 pairs of MIBC/CIS and the WBHM specimen were chosen from this pool of tumors. Subtyping is based on the 21 genes containing MDACC panel (Supplementary Table 2). RNAseq data were generated from FFPE tissues using QuantSeq kits (Lexogen) using 500 ng input RNA. The QuantSeq libraries were sequenced on an Illumina Hiseq platform and generated data were further processed according to the GRCh38, and further normalized. Inter-gene correlations range from 0.78-0.97 (Spearman rank correlations). Comparison of subtype assignment based on average linkage unsupervised hierarchical clustering shows a 100% overlap with no discordant classifications occurring, thus indicating that Nanostring is suitable for subtyping bladder cancer samples compared to RNAseq.

(A) Unsupervised hierarchical clustering reveals three lesion clusters (lesion cluster A-C) designated below the heat map. Histological classifications are shown above the heatmap and gene cluster families A*-D* are depicted on the left-sided cluster. Distribution of the lesion types in each cluster A-C are illustrated as pie diagrams below the heatmap. (B) Gene families from gene clusters C* and D* are mainly expressed in lesion clusters A/B in tumor associated urothelium, non-invasive urothelial lesions and CIS, while gene family A* is upregulated in CIS and pT1/MIBC samples. P-values were derived by nonparametric Kruskal-Wallis tests and are depicted above the graphs. P-values of single group comparisons derived by nonparametric Mann-Whitney tests are depicted in Suppl. Table 5. (C) Distribution of lesion cluster assignments (A-C) in the WBHM scheme. (D) Boxplots depicting differential expression of ERBB2, ERBB3, EGFR, STAT3 and CADM1 (STAT3-regulator) in luminal and basal tumors from the TCGA bladder cancer cohort. CIS = Carcinoma in situ; DYS = Dysplasia; UPUMP/HYP = urothelial proliferation of unknown malignant potential/ hyperplasia (abbreviated as "HYP" in graphs); MIBC = Muscle-invasive bladder cancer; pT1 = Stroma invasive bladder cancer; U = Tumor associated urothelium.

Supplementary Figure from Epigenetic Therapies in Ovarian Cancer Alter Repetitive Element Expression in a TP53-Dependent Manner

Supplementary Data from Epigenetic Therapies in Ovarian Cancer Alter Repetitive Element Expression in a TP53-Dependent Manner

Basal and luminal subtypes of invasive bladder tumors have significant prognostic and predictive impacts for patients. However, it remains unclear whether tumor subtype commitment occurs in noninvasive urothelial lesions or in carcinoma in situ (CIS) and which gene pathways are important for bladder tumor progression. To understand the timing of this commitment, we used gene expression and protein analysis to create a global overview of 36 separate tissues excised from a whole bladder encompassing urothelium, noninvasive urothelial lesions, CIS, and invasive carcinomas. Additionally investigated were matched CIS, noninvasive urothelial lesions, and muscle-invasive bladder cancers (MIBC) from 22 patients. The final stage of subtype commitment to either a luminal or basal MIBC occurred at the CIS transition. For all tissues combined, hierarchical clustering of subtype gene expression revealed three subtypes: “luminal,” “basal,” and a “luminal p53-/extracellular matrix (ECM)-like” phenotype of ECM-related genes enriched in tumor-associated urothelium, noninvasive urothelial lesions, and CIS, but rarely invasive, carcinomas. A separate cohort of normal urothelium from noncancer patients showed significantly lower expression of ECM-related genes compared with tumor-associated urothelium, noninvasive urothelial lesions, and CIS. A PanCancer Progression Panel of 681 genes unveiled pathways specific for the luminal p53-/ECM-like cluster, for example, ECM remodeling, angiogenesis, epithelial-to-mesenchymal transition, cellular discohesion, cell motility involved in tumor progression, and cell proliferation and oncogenic ERBB2/ERBB3 signaling for invasive carcinomas. In conclusion, this study provides insights into bladder cancer subtype commitment and associated signaling pathways, which could help predict therapy response and enhance our understanding of therapy resistance.Significance:This study demonstrates that CIS is the stage of commitment for determining MIBC tumor subtype, which is relevant for patient prognosis and therapy response.

Pairwise group P-values of analyses with multiple group comparisons tested by non-parametric Kruskal-Wallis tests.

Genes and proteins used for calculation of gene- and protein-expression scores (luminal-ness/basal-ness/ECM/EMT/signature scores).

Methylene blue (MB) is a dye used for histology with clinical importance and intercalates into nucleic acids. After MB staining of formalin fixed paraffin embedded (FFPE) muscle invasive bladder cancer (MIBC) and normal urothelium, specific regions could be microdissected. It is not known if MB influences RNA used for gene expression studies. Therefore, we analyzed MIBC using five different RNA isolation methods comparing patient matched FFPE and fresh frozen (FF) tissues pre-stained with or without MB. We demonstrate a positive impact of MB on RNA integrity with FF tissues using real time PCR with no interference of its chemical properties. FFPE tissues showed no improvement of RNA integrity, which we propose is due to formalin induced nucleotide crosslinks. Using direct multiplex RNA hybridization the best genes for normalization of MIBC and control tissues were identified from 34 reference genes. In addition, 5SrRNA and 5.8SrRNA were distinctive reference genes detecting

The value of programmed cell death ligand-1 (PD-L1) to predict durable responses to immune checkpoint inhibitors (ICIs) in metastatic urothelial carcinoma (mUC) is inconsistent. We hypothesize that the use of archived primary tumor material (PRIM) for PD-L1 testing in clinical trials not properly reflecting the metastatic disease status (MET) contributes to this clinical issue.To analyze the predictive and prognostic value of PD-L1, spatial immunephenotypes, and major histocompatibility complex class I (MHC-I) determined in patient-matched PRIM/MET.PD-L1, spatial immunephenotypes, and MHC-I were examined in 154 mUC patients with at least one available pretreatment MET (138 patient-matched PRIM/MET pairs).PD-L1, spatial immunephenotype, and MHC-I status of (patient-matched PRIM and) pretreatment MET were correlated with chemotherapy and ICI response and outcomes.Discordance rates in patient-matched PRIM/MET were 25/30%, 36%, and 49% for PD-L1 (CPS10/IC5%), immunephenotypes, and MHC-I (loss vs preserved), respectively. Correlations with chemotherapy and ICI responses were observed for immunephenotypes and MHC-I status determined in MET (not for PD-L1 alone), but not in PRIM. In case of ICIs, patients with cytotoxic tumor immune microenvironment (TIME) showed durable responses with disease control rates of 90% and a hazard ratio for disease progression/death of 0.05 (95% confidence interval: 0.01-0.65) versus patients with immunedepleted MET (disease control rate 29%). MET MHC-I status added an incremental value to predict durable ICI responses. Limitations include the partly retrospective design and the lack of MET multisampling on individual patient level.The TIME is subject to substantial dynamics during metastatic evolution. MET immunephenotypes and MHC-I statuses show promising potential to predict chemotherapy and durable ICI responses, while the PRIM TIME does not. Thus, future clinical trials should rather rely on pretreatment MET biopsies reflecting the current immunological disease state than on PRIM.Prediction of chemotherapy and responses to immune checkpoint inhibitors might be possible using representative pretreatment metastatic biopsies.