Precision cancer medicine (PCM) to support the treatment of solid tumors requires minimally invasive diagnostics. Here, we describe the development of fine‐needle aspiration biopsy‐based (FNA) molecular cytology which will be increasingly important in diagnostics and adaptive treatment. We provide support for FNA‐based molecular cytology having a significant potential to replace core needle biopsy (CNB) as a patient‐friendly potent technique for tumor sampling for various tumor types. This is not only because CNB is a more traumatic procedure and may be associated with more complications compared to FNA‐based sampling, but also due to the recently developed molecular methods used with FNA. Recent studies show that image‐guided FNA in combination with ultrasensitive molecular methods also offers opportunities for characterization of the tumor microenvironment which can aid therapeutic decisions. Here we provide arguments for an increased implementation of molecular FNA‐based sampling as a patient‐friendly diagnostic method, which may, due to its repeatability, facilitate regular sampling that is needed during different treatment lines, to provide tumor information, supporting treatment decisions, shortening lead times in healthcare, and benefit healthcare economics.

Univariable Cox regressions, disease-specific survival.

Test for proportional hazards.

BACKGROUND:Improved molecular diagnosis is needed in prostate cancer (PC). Fine needle aspiration (FNA) is a minimally invasive biopsy technique, less traumatic compared to core needle biopsy, and could be useful for diagnosis of PC. Molecular biomarkers (BMs) in FNA-samples can be assessed for prediction, eg of immunotherapy efficacy before treatment as well as at treatment decision time points during disease progression.METHODS:In the present pilot study, the expression levels of 151 BM proteins were analysed by proximity extension assay in FNA-samples from 16 patients, including benign prostate lesions (n = 3) and cancers (n = 13). An ensemble data analysis strategy was applied using several machine learning models.RESULTS:Twelve potentially predictive BM proteins correlating with International Society of Urological Pathology grade groups were identified, among them vimentin, tissue factor pathway inhibitor 2, and integrin beta-5. The validity of the results was supported by network analysis that showed functional associations between most of the identified putative BMs. We also showed that multiple immune checkpoint targets can be assessed (eg PD-L1, CD137, and Galectin-9), which may support the selection of immunotherapy in advanced PC. Results are promising but need further validation in a larger cohort.CONCLUSIONS:Our pilot study represents a "proof of concept" and shows that multiplex profiling of potential diagnostic and predictive BM proteins is feasible on tumour material obtained by FNA sampling of prostate cancer. Moreover, our results demonstrate that an ensemble data analysis strategy may facilitate the identification of BM signatures in pilot studies when the patient cohort is limited.

Steps of Cox regression analyses to final models.

<p>Correlation between standard clinicopathological and genome instability parameters.</p>

Examples of different genome instability profiles.

<p>Analysis of deviance comparing models with and without genome instability parameters.</p>

Multivariable Cox regressions including the standard proliferation variable.

Test for proportional hazards.

Kaplan Meier curves of clinicopathological and image cytometric data.

BACKGROUND:Increasing evidence suggests that platelets play a central role in cancer progression, with altered storage and selective release from platelets of specific tumor-promoting proteins as a major mechanism. Fluorescence-based super-resolution microscopy (SRM) can resolve nanoscale spatial distribution patterns of such proteins, and how they are altered in platelets upon different activations. Analysing such alterations by SRM thus represents a promising, minimally invasive strategy for platelet-based diagnosis and monitoring of cancer progression. However, broader applicability beyond specialized research labs will require objective, more automated imaging procedures. Moreover, for statistically significant analyses many SRM platelet images are needed, of several different platelet proteins. Such proteins, showing alterations in their distributions upon cancer progression additionally need to be identified.RESULTS:A fast, streamlined and objective procedure for SRM platelet image acquisition, analysis and classification was developed to overcome these limitations. By stimulated emission depletion SRM we imaged nanoscale patterns of six different platelet proteins; four different SNAREs (soluble N-ethylmaleimide factor attachment protein receptors) mediating protein secretion by membrane fusion of storage granules, and two angiogenesis regulating proteins, representing cargo proteins within these granules coupled to tumor progression. By a streamlined procedure, we recorded about 100 SRM images of platelets, for each of these six proteins, and for five different categories of platelets; incubated with cancer cells (MCF-7, MDA-MB-231, EFO-21), non-cancer cells (MCF-10A), or no cells at all. From these images, structural similarity and protein cluster parameters were determined, and probability functions of these parameters were generated for the different platelet categories. By comparing these probability functions between the categories, we could identify nanoscale alterations in the protein distributions, allowing us to classify the platelets into their correct categories, if they were co-incubated with cancer cells, non-cancer cells, or no cells at all.CONCLUSIONS:The fast, streamlined and objective acquisition and analysis procedure established in this work confirms the role of SNAREs and angiogenesis-regulating proteins in platelet-mediated cancer progression, provides additional fundamental knowledge on the interplay between tumor cells and platelets, and represent an important step towards using tumor-platelet interactions and redistribution of nanoscale protein patterns in platelets as a basis for cancer diagnostics.

Current prostate cancer risk classifications rely on clinicopathological parameters resulting in uncertainties for prognostication. To improve individual risk stratification, we examined the predictive value of selected proteins with respect to tumor heterogeneity and genomic instability. We assessed the degree of genomic instability in 50 radical prostatectomy specimens by DNA-Image-Cytometry and evaluated protein expression in related 199 tissue-microarray (TMA) cores. Immunohistochemical data of SATB1, SPIN1, TPM4, VIME and TBB5 were correlated with the degree of genomic instability, established clinical risk factors and overall survival. Genomic instability was associated with a GS ≥ 7 (p = 0.001) and worse overall survival (p = 0.008). A positive SATB1 expression was associated with a GS ≤ 6 (p = 0.040), genomic stability (p = 0.027), and was a predictor for increased overall survival (p = 0.023). High expression of SPIN1 was also associated with longer overall survival (p = 0.048) and lower preoperative PSA-values (p = 0.047). The combination of SATB1 expression, genomic instability, and GS lead to a novel Prostate Cancer Prediction Score (PCP-Score) which outperforms the current D'Amico et al. stratification for predicting overall survival. Low SATB1 expression, genomic instability and GS ≥ 7 were identified as markers for poor prognosis. Their combination overcomes current clinical risk stratification regimes.

Background: Many carcinomas have recurrent chromosomal aneuploidies specific to the tissue of tumor origin. The reason for this specificity is not completely understood. Methods: In this study, we looked at the frequency of chromosomal arm gains and losses in different cancer types from the The Cancer Genome Atlas (TCGA) and compared them to the mean gene expression of each chromosome arm in corresponding normal tissues of origin from the Genotype-Tissue Expression (GTEx) database, in addition to the distribution of tissue-specific oncogenes and tumor suppressors on different chromosome arms. Results: This analysis revealed a complex picture of factors driving tumor karyotype evolution in which some recurrent chromosomal copy number reflect the chromosome arm-wide gene expression levels of the their normal tissue of tumor origin. Conclusions: We conclude that the cancer type-specific distribution of chromosomal arm gains and losses is potentially "hardwiring" gene expression levels characteristic of the normal tissue of tumor origin, in addition to broadly modulating the expression of tissue-specific tumor driver genes.

The role of Tetraploidization (TPZ) in tumor progression is not clearly described as an important link from one benign tumor to a more malign tumor. In this report we will intertwine the TPZ in a chain starting with diploid and during a lot of replicative stress parameters and hypoxia under increasing genomic instability losing genetic material and move down to aneuploids tumors. To arrange this connection between DNA (DI) entities we separated all tetraploid tumors in two subgroups (1.8 ≥ DI<2.0) and to (2.0 ≥ DI<2.2), and furthermore, two aneuploid groups divided in (1.2 ≥ DI<1.4) and (1.4 ≥ DI<1.8). This rather simple higher level of resolution has opened a new way to a deeper understanding of ploidy alterations during tumor progression. In total 1253 breast cancer patients divided in five decades were included from age <40 years and up to ≥ 70s. Two connected decades (50 ≥ age<70 years) were included in mammography screening interfering with the data and improved the results. The whole data of DNA- indices in each of the four DI intervals were included within (1.2 ≥ DI<2.2). Furthermore, the genomic instability was analyzed by three increasing levels of Stemline-Scatter Index (SSI): SSI<6, SSI<15 and SSI ≤ 60 rel. units which drives the genomic instability towards higher degree of malignancy.

BACKGROUND:PITX2 DNA methylation has been shown to predict outcomes in high-risk breast cancer patients after anthracycline-based chemotherapy. To determine its prognostic versus predictive value, the impact of PITX2 DNA methylation on outcomes was studied in an untreated cohort vs. an anthracycline-treated triple-negative breast cancer (TNBC) cohort.MATERIAL AND METHODS:The percent DNA methylation ratio (PMR) of paired-like homeodomain transcription factor 2 (PITX2) was determined by a validated methylation-specific real-time PCR test. Patient samples of routinely collected archived formalin-fixed paraffin-embedded (FFPE) tissue and clinical data from 144 TNBC patients of 2 independent cohorts (i.e., 66 untreated patients and 78 patients treated with anthracycline-based chemotherapy) were analyzed.RESULTS:The risk of 5- and 10-year overall survival (OS) increased continuously with rising PITX2 DNA methylation in the anthracycline-treated population, but it increased only slightly during 10-year follow-up time in the untreated patient population. PITX2 DNA methylation with a PMR cutoff of 2 did not show significance for poor vs. good outcomes (OS) in the untreated patient cohort (HR = 1.55; p = 0.259). In contrast, the PITX2 PMR cutoff of 2 identified patients with poor (PMR >2) vs. good (PMR ≤2) outcomes (OS) with statistical significance in the anthracycline-treated cohort (HR = 3.96; p = 0.011). The results in the subgroup of patients who did receive anthracyclines only (no taxanes) confirmed this finding (HR = 5.71; p = 0.014).CONCLUSION:In this hypothesis-generating study PITX2 DNA methylation demonstrated predominantly predictive value in anthracycline treatment in TNBC patients. The risk of poor outcome (OS) correlates with increasing PITX2 DNA methylation.

Introduction/Background* Routine blood markers provide poor diagnostic capacity for ovarian cancer. Ultrasound examination using the criteria developed by International Ovarian Tumor Analysis group is the most sensitive and specific diagnostic method, but in up to 20% of cases evaluation is inconclusive (Sladkevicius et al. 2020; Valentin et al. 2011). We pioneered platelet proteome analysis and identified platelet biomarkers of ovarian cancer (Lomnytska et al. 2018). Methodology The purpose of the study is to identify diagnostic marker panel on platelet microvesicles in blood plasma for non-invasive differential diagnostics of benign adnexal lesions, borderline tumours and ovarian cancer. The expression of platelet protein biomarkers on platelet microvesicles in patients with benign and malignant adnexal lesions was analysed using flow cytometry. Identified biomarker panels were analysed together with the gynaecologic ultrasound criteria. Result(s)* Analysis comprised 39 patients with benign adnexal lesions (n=10), borderline (n=10), ovarian cancer stage I-II (n=8) and stage III-IV (n=11). Using flow cytometry analysis of platelet microvesicles in platelet-poor blood plasma, we detected our previously identified by proteome analysis of platelets markers ACTN4, CRKL, ERP29, GELS, PHB and SRC (Lomnytska et al., 2018). Expression of P-selectin positive platelet microvesicles was 2-fold higher in ovarian cancer (p<0.05). Increased expression of our identified markers on P-selectin positive platelet microvesicles was observed in ovarian cancer (figure 1). Conclusion* Identified platelet biomarkers (Lomnytska et al. 2018) are detectable on platelet microvesicles in blood plasma with increased expression in ovarian cancer. Further analysis of microvesicles in relation to ultrasound evaluation has the potential to improve ovarian cancer diagnostics.

Abstract Background: Published data on the basis of a research-use-only PITX2 methylation assay using fresh-frozen tissue showed that the PITX2 DNA methylation may be a predictive marker for response to (neo) adjuvant anthracycline-based chemotherapy in breast cancer patients, including high-risk lymph node positive, estrogen receptor-positive, HER2-negative breast cancer and triple-negative breast cancer (TNBC). A retrospective study showed that high-risk ER-positive patients with a high PITX2 methylation ratio (PMR>12) had a poor outcome after anthracycline-based chemotherapy [HR 2,28; 95%-Cl 1,49 - 3,49; p<0.001, median DFS 71 months] compared to patients with low PITX2 methylation ratios [PMR≤12, median DFS 105 months]. Nevertheless, the question regarding the prognostic versus predictive value of PITX2 methylation for anthracycline therapy remained unanswered so far. Within an exploratory study using archived tissue specimen, this question was addressed by comparing the impact of PITX2 methylation on outcome in an untreated versus treated TNBC population. Methods: Patient samples and clinical data from 144 TNBC patients of 2 cohorts were analyzed: 1) 66 untreated patients from the Karolinska Institute in Sweden (primary diagnosis 1971-1976) and 2) 78 patients treated with anthracycline-based chemotherapy from the Comprehensive Cancer Center TUM in Germany (primary diagnosis 1996 to 2014). The main eligibility criteria were as follows: ER-negative, PR-negative, HER2-negative breast cancer (TNBC); no endocrine therapy; untreated collective: no further therapy besides surgery and radiation therapy; treated collective: surgery followed by anthracycline based chemotherapy. Samples were assessed for PITX2 methylation using a CE marked PITX2 RGQ PCR Test. The study was designed to determine the PITX2 PMR cut-off value in the untreated population (n=66, prognostic value) and to subsequently determine if this cut-off provides statistical significance in the treated population (n=78, prognostic & predictive value) as well. If no statistically significant cut-off value can be determined in the untreated population, cut-off determination was performed in the treated population and the cut-off was applied in the untreated population. The primary clinical endpoint for all cut-offs was 10-years DFS, secondary clinical endpoints were DFS censored at 5-years and OS censored at 5- and 10-years. Results: The untreated TNBC study population demonstrated a higher event rate at 10-years DFS/OS compared to the anthracycline-treated population [36 DFS/28 OS events vs 28 DFS/14 OS events]. Anthracycline treatment improved significantly overall survival [HR=0.42; p=0.008]. Risk recurrence increased continuously over 5 year and 10 years DFS/OS with increasing PITX2 DNA methylation in the anthracycline-treated population but not in the untreated patients over 5 years DFS/OS and only marginally over 10 years DFS/OS. PITX2 methylation identifies at the cut-off of PMR 2 a patient population with poor vs good overall survival with statistical significance [HR=3.96, p=0.011] in the treated patient cohort but did not identify patients with poor vs good outcome in the untreated patient cohort [HR=1.55, p=0.259]. Summary: In this hypothesis generating study DNA-methylation of PITX2 identifies with high statistical significance anthracycline-treated patients with poor vs good survival. Recurrence risk increases with increasing PITX2 DNA-methylation. PITX2 DNA-methylation shows no prognostic, but significant predictive value for anthracycline treatment in TNBC patients in this study. To confirm conclusively the predictive value of PITX2 DNA-methylation, the results warrant a confirmatory study with tumor specimens from a prospective trial of anthracycline-treated patients vs. anthracycline-free treated patients. Citation Format: Marion Kiechle, Gabriele Schricker, Rudolf Napieralski, Michaela Aubele, Gert Auer, Kurt Ulm, Jonathan Perkins, Stefan Paepke, Moritz Hamann, Olaf G. Wilhelm. PITX2 DNA methylation: A prognostic/predictive biomarker for anthracycline-based chemotherapy [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-08-65.

Prognosis in young patients with breast cancer is generally poor, yet considerable differences in clinical outcomes between individual patients exist. To understand the genetic basis of the disparate clinical courses, tumors were collected from 34 younger women, 17 with good and 17 with poor outcomes, as determined by disease-specific survival during a follow-up period of 17 years. The clinicopathologic parameters of the tumors were complemented with DNA image cytometry profiles, enumeration of copy numbers of eight breast cancer genes by multicolor fluorescence in situ hybridization, and targeted sequence analysis of 563 cancer genes. Both groups included diploid and aneuploid tumors. The degree of intratumor heterogeneity was significantly higher in aneuploid versus diploid cases, and so were gains of the oncogenes MYC and ZNF217. Significantly more copy number alterations were observed in the group with poor outcome. Almost all tumors in the group with long survival were classified as luminal A, whereas triple-negative tumors predominantly occurred in the short survival group. Mutations in PIK3CA were more common in the group with good outcome, whereas TP53 mutations were more frequent in patients with poor outcomes. This study shows that TP53 mutations and the extent of genomic imbalances are associated with poor outcome in younger breast cancer patients and thus emphasize the central role of genomic instability vis-a-vis tumor aggressiveness.

Abstract We previously studied synchronous ductal carcinomas in situ (DCIS) and invasive ductal carcinomas (IDC) using our novel approach of multiplex interphase Fluorescence in situ Hybridization (miFISH) that allows simultaneous enumeration of copy numbers of up to 20 gene loci per single cell, providing new insights into tumor clonality and intratumor heterogeneity (ITH). A high degree of chromosomal instability was present in DCIS, and we frequently observed a direct clonal evolution from DCIS to IDC. We now ask whether this degree of instability is also present in even earlier potential precursor lesions like atypical ductal hyperplasias (ADH). We are therefore conducting a retrospective study analyzing ADH lesions from patients without synchronous DCIS or IDC (pure ADH) and from patients with ADH adjacent to higher-grade lesions. Using our miFISH assay, we simultaneously assess copy number changes of six oncogenes (COX2 (1q), PIK3CA (3q), MET (7q), MYC (8q), CCND1 (11q), HER2 (17q), ZNF217 (20q)) and six tumor suppressor genes (FHIT (3p), DBC2 (8p), RB1 (13q), CDH1 (16q), TP53 (17q), NF2 (22q), typical for breast tumorigenesis. So far, we have analyzed fifteen pure ADH and five ADH with synchronous DCIS or IDC. The miFISH analysis showed that the majority of all pure ADH displayed a stable diploid genome without any copy number changes observed for the genes tested while only 3/15 (20%) showed changes, namely (i) a COX2 and HER2 gain in a diploid genome, (ii) a CDH1and MET loss in a tetraploid genome and (iii) a COX2 gain in a diploid genome. In the group of ADH with adjacent higher-grade lesions (n=5), all DCIS and IDC lesions analyzed displayed breast cancer specific copy number changes corroborating our previous results. Of note, two of the ADH lesions adjacent to these aberrant DCIS or IDC lesions had normal diploid genomes. Of the remaining three synchronous ADH lesions, one showed a complex gain and loss pattern similar to its adjacent DCIS, the second one was characterized by a simple COX2 gain which was maintained in the adjacent DCIS in addition to a DBC2 loss and MYC gain. The third ADH displayed a tetraploid clone without any gains or losses, while the adjacent IDC revealed a complex gain and loss pattern in its tetraploid genome. Our preliminary data indicate that the majority of pure ADH does not harbor copy number changes. However, there is a small subset of pure ADH revealing gain and loss patterns typical for DCIS and IDC often involving COX2 gain indicating it as an early event. Of note, ADH lesions adjacent to DCIS or IDC tend to display similar changes as their adjacent higher-grade lesions suggesting them as direct precursor lesions. We are currently analyzing more ADH samples and plan to add material from an ADH patient cohort with long-term follow-up to explore whether miFISH can stratify ADH patients into different risk groups. Citation Format: Kiara Whitaker, Jausheng Tzeng, Daniela Hirsch, Irianna Torres, Steven Brower, Gert Auer, Miguel Sanchez, Thomas Ried, Kerstin Heselmeyer-Haddad. miFISH single cell analysis as a potential tool to stratify the progression risk in patients with Atypical Ductal Hyperplasia (ADH) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2498.