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The hallmark of Philadelphia chromosome positive (Ph+) leukemia is the BCR/ABL kinase, which is successfully targeted by selective ATP competitors. However, inhibition of BCR/ABL alone is unable to eradicate Ph+ leukemia. The t(9;22) is a reciprocal translocation which encodes not only for the der22 (Philadelphia chromosome) related BCR/ABL, but also for der9 related ABL/BCR fusion proteins, which can be detected in 65% of patients with chronic myeloid leukemia (CML) and 100% of patients with Ph+ acute lymphatic leukemia (ALL). ABL/BCRs are oncogenes able to influence the lineage commitment of hematopoietic progenitors. Aim of this study was to further disclose the role of p96ABL/BCR for the pathogenesis of Ph+ ALL. The co-expression of p96ABL/BCR enhanced the kinase activity and as a consequence, the transformation potential of p185BCR/ABL. Targeting p96ABL/BCR by RNAi inhibited growth of Ph+ ALL cell lines and Ph+ ALL patient-derived long-term cultures (PD-LTCs). Our in vitro and in vivo stem cell studies further revealed a functional hierarchy of p96ABL/BCR and p185BCR/ABL in hematopoietic stem cells. Co-expression of p96ABL/BCR abolished the capacity of p185BCR/ABL to induce a CML-like disease and led to the induction of ALL. Taken together our here presented data reveal an important role of p96ABL/BCR for the pathogenesis of Ph+ ALL.
Anaplastic large cell lymphoma (ALCL) and classical Hodgkin lymphoma (cHL) are lymphomas that contain CD30-expressing tumor cells and have numerous pathological similarities. Whereas ALCL is usually diagnosed at an advanced stage, cHL more frequently presents with localized disease. The aim of the present study was to elucidate the mechanisms underlying the different clinical presentation of ALCL and cHL. Chemokine and chemokine receptor expression were similar in primary ALCL and cHL cases apart from the known overexpression of the chemokines CCL17 and CCL22 in the Hodgkin and Reed-Sternberg (HRS) cells of cHL. Consistent with the overexpression of these chemokines, primary cHL cases encountered a significantly denser T cell microenvironment than ALCL. Additionally to differences in the interaction with their microenvironment, cHL cell lines presented a lower and less efficient intrinsic cell motility than ALCL cell lines, as assessed by time-lapse microscopy in a collagen gel and transwell migration assays. We thus propose that the combination of impaired basal cell motility and differences in the interaction with the microenvironment hamper the dissemination of HRS cells in cHL when compared with the tumor cells of ALCL.
Nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) is an indolent lymphoma, but can transform into diffuse large B cell lymphoma (DLBCL), showing a more aggressive clinical behavior. Little is known about these cases on the molecular level. Therefore, the aim of the present study was to characterize DLBCL transformed from NLPHL (LP-DLBCL) by gene expression profiling (GEP). GEP revealed an inflammatory signature pinpointing to a specific host response. In a coculture model resembling this host response, DEV tumor cells showed an impaired growth behavior. Mechanisms involved in the reduced tumor cell proliferation included a downregulation of MYC and its target genes. Lack of MYC expression was also confirmed in 12/16 LP-DLBCL by immunohistochemistry. Furthermore, CD274/PD-L1 was upregulated in DEV tumor cells after coculture with T cells or monocytes and its expression was validated in 12/19 cases of LP-DLBCL. Thereby, our data provide new insights into the pathogenesis of LP-DLBCL and an explanation for the relatively low tumor cell content. Moreover, the findings suggest that treatment of these patients with immune checkpoint inhibitors may enhance an already ongoing host response in these patients.
The mechanisms involved in malignant transformation of mature B and T lymphocytes are still poorly understood. In a previous study, we compared gene expression profiles of the tumor cells of Hodgkin lymphoma (HL) and anaplastic large cell lymphoma (ALCL) to their normal cellular counterparts and found the basic leucine zipper protein ATF-like 3 (BATF3) to be significantly upregulated in the tumor cells of both entities. To assess the oncogenic potential of BATF3 in lymphomagenesis and to dissect the molecular interactions of BATF3 in lymphoma cells, we retrovirally transduced murine mature T and B cells with a BATF3-encoding viral vector and transplanted each population into Rag1-deficient recipients. Intriguingly, BATF3-expressing B lymphocytes readily induced B-cell lymphomas after characteristic latencies, whereas T-cell transplanted animals remained healthy throughout the observation time. Further analyses revealed a germinal center B-cell-like phenotype of most BATF3-initiated lymphomas. In a multiple myeloma cell line, BATF3 inhibited BLIMP1 expression, potentially illuminating an oncogenic action of BATF3 in B-cell lymphomagenesis. In conclusion, BATF3 overexpression induces malignant transformation of mature B cells and might serve as a potential target in B-cell lymphoma treatment.
The hallmark of classical Hodgkin lymphoma (cHL) is the presence of giant, mostly multinucleated Hodgkin-Reed-Sternberg (HRS) cells. Whereas it has recently been shown that giant HRS cells evolve from small Hodgkin cells by incomplete cytokinesis and re-fusion of tethered sister cells, it remains unsolved why this phenomenon particularly takes place in this lymphoma and what the differences between these cell types of variable sizes are. The aim of the present study was to characterize microdissected small and giant HRS cells by gene expression profiling and to assess differences of clonal growth behavior as well as susceptibility toward cytotoxic intervention between these different cell types to provide more insight into their distinct cellular potential. Applying stringent filter criteria, only two differentially expressed genes between small and giant HRS cells, SHFM1 and LDHB, were identified. With looser filter criteria, 13 genes were identified to be differentially overexpressed in small compared to giant HRS cells. These were mainly related to energy metabolism and protein synthesis, further suggesting that small Hodgkin cells resemble the proliferative compartment of cHL. SHFM1, which is known to be involved in the generation of giant cells, was downregulated in giant RS cells at the RNA level. However, reduced mRNA levels of SHFM1, LDHB and HSPA8 did not translate into decreased protein levels in giant HRS cells. In cell culture experiments it was observed that the fraction of small and big HRS cells was adjusted to the basic level several days after enrichment of these populations via cell sorting, indicating that small and big HRS cells can reconstitute the full spectrum of cells usually observed in the culture. However, assessment of clonal growth of HRS cells indicated a significantly reduced potential of big HRS cells to form single cell colonies. Taken together, our findings pinpoint to strong similarities but also some differences between small and big HRS cells.
In contrast to the commonly indolent clinical behavior of nodular lymphocyte predominant Hodgkin lymphoma (NLPHL), T cell/histiocyte rich large B cell lymphoma (THRLBCL) is frequently diagnosed in advanced clinical stages and has a poor prognosis. Besides the different clinical presentations of these lymphoma entities, there are variants of NLPHL with considerable histopathologic overlap compared to THRLBCL. Especially THRLBCL-like NLPHL, a diffuse form of NLPHL, often presents a histopathologic pattern similar to THRLBCL, suggesting a close relationship between both lymphoma entities. To corroborate this hypothesis, we performed gene expression profiling of microdissected tumor cells of NLPHL, THRLBCL-like NLPHL and THRLBCL. In unsupervised analyses, the lymphomas did not cluster according to their entity. Moreover, even in supervised analyses, very few consistently differentially expressed transcripts were found, and for these genes the extent of differential expression was only moderate. Hence, there are no clear and consistent differences in the gene expression of the tumor cells of NLPHL, THRLBCL-like NLPHL and THRLBCL. Based on the gene expression studies, we identified BAT3/BAG6, HIGD1A, and FAT10/UBD as immunohistochemical markers expressed in the tumor cells of all three lymphomas. Characterization of the tumor microenvironment for infiltrating T cells and histiocytes revealed significant differences in the cellular composition between typical NLPHL and THRLBCL cases. However, THRLBCL-like NLPHL presented a histopathologic pattern more related to THRLBCL than NLPHL. In conclusion, NLPHL and THRLBCL may represent a spectrum of the same disease. The different clinical behavior of these lymphomas may be strongly influenced by differences in the lymphoma microenvironment, possibly related to the immune status of the patient at the timepoint of diagnosis.
Background: Definite diagnosis and therapeutic management of cholangiocarcinoma (CCA) remains a challenge. The aim of the current study was to investigate feasibility and potential impact on clinical management of targeted sequencing of intraductal biopsies.
Methods: Intraductal biopsies with suspicious findings from 16 patients with CCA in later clinical course were analyzed with targeted sequencing including tumor and control benign tissue (n = 55 samples). A CCA-specific sequencing panel containing 41 genes was designed and a dual strand targeted enrichment was applied.
Results: Sequencing was successfully performed for all samples. In total, 79 mutations were identified and a mean of 1.7 mutations per tumor sample (range 0–4) as well as 2.3 per biopsy (0–6) were detected and potentially therapeutically relevant genes were identified in 6/16 cases. In 14/18 (78%) biopsies with dysplasia or inconclusive findings at least one mutation was detected. The majority of mutations were found in both surgical specimen and biopsy (68%), while 28% were only present in biopsies in contrast to 4% being only present in the surgical tumor specimen.
Conclusion: Targeted sequencing from intraductal biopsies is feasible and potentially improves the diagnostic yield. A profound genetic heterogeneity in biliary dysplasia needs to be considered in clinical management and warrants further investigation.
Translational impact: The current study is the first to demonstrate the feasibility of sequencing of intraductal biopsies which holds the potential to impact diagnostic and therapeutical management of patients with biliary dysplasia and neoplasia.
Background The differential diagnosis between follicular thyroid adenoma and minimal invasive follicular thyroid carcinoma is often difficult for several reasons. One major aspect is the lack of typical cytological criteria in well differentiated specimens. New marker molecules, shown by poly- or monoclonal antibodies proved helpful. Methods We performed global gene expression analysis of 12 follicular thyroid tumours (4 follicular adenomas, 4 minimal invasive follicular carcinomas and 4 widely invasive follicular carcinomas), followed by immunohistochemical staining of 149 cases. The specificity of the antibody was validated by western blot analysis Results In gene expression analysis QPRT was detected as differently expressed between follicular thyroid adenoma and follicular thyroid carcinoma. QPRT protein could be detected by immunohistochemistry in 65% of follicular thyroid carcinomas including minimal invasive variant and only 22% of follicular adenomas. Conclusion Consequently, QPRT is a potential new marker for the immunohistochemical screening of follicular thyroid nodules.
In gastric cancer (GC), there are four molecular subclasses that indicate whether patients respond to chemotherapy or immunotherapy, according to the TCGA. In clinical practice, however, not every patient undergoes molecular testing. Many laboratories have used well-implemented in situ techniques (IHC and EBER-ISH) to determine the subclasses in their cohorts. Although multiple stains are used, we show that a staining approach is unable to correctly discriminate all subclasses. As an alternative, we trained an ensemble convolutional neuronal network using bagging that can predict the molecular subclass directly from hematoxylin–eosin histology. We also identified patients with predicted intra-tumoral heterogeneity or with features from multiple subclasses, which challenges the postulated TCGA-based decision tree for GC subtyping. In the future, deep learning may enable targeted testing for molecular subtypes and targeted therapy for a broader group of GC patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Zur genomweiten Genexpressionsanalyse werden Microarray-Experimente verwendet. Ziel dieser Arbeit ist es, Methoden zur Präprozessierung von Microarrays der Firma Affymetrix zu evaluieren und die VSN-Methode für Experimente mit weniger als 1000 Zellen zu verbessern. Bei dieser Technologie wird die Expression jedes Gens durch mehrere Probessets gemessen. Jedes Probeset besteht aus einem Perfect-Match (PM) und einem dazugehörigen Mismatch (MM). Der Expressionswert pro Gen wird durch ein vierstufiges Verfahren aus den einzelnen Probe-Werten berechnet: Hintergrundkorrektur, Normalisierung, PM-Adjustierung und Aggregation. Für jeden dieser Schritte existieren mehrere Algorithmen. Dazu dienten die im affy-Paket des Bioconductor implementierten Methoden MAS5, RMA, VSN und die Methode sRMA von Cope et al. [Cope et al., 2006] in Kombination mit der Methode VSN von Huber et al. [Huber et al., 2002]. Den ersten Teil dieser Arbeit bildet die Reanalyse der Datensätze von Küppers et al. [Küppers et al., 2003] und Piccaluga et al. [Piccaluga et al., 2007] mit der VSN-Methode. Dabei konnte gezeigt werden, dass die VSN-Methode gegenüber Klein et al. [Klein et al., 2001] Vorteile zeigt. Bei beiden Datensätzen wurden zusätzliche Gene gefunden, die für die Pathogenese der jeweiligen Tumorarten wichtig sein können. Einige der zusätzlich gefunden Gene wurden durch andere wissenschaftliche Arbeiten bestätigt. Die Gene, die bisher in keinem Zusammenhang mit der untersuchten Tumorart stehen, sind eine Möglichkeit für die weitere Forschung. Vor allem der Zytokine/Zytokine Signalweg wurde bei beiden Reanalysen als überrepräsentiert erkannt. Da für einige Microarray-Experimente die Anzahl der Zellen und damit die Menge an mRNA nur begrenzt zur Verfügung stehen, müssen die Laborarbeit und die statistischen Analysen angepasst werden. Hierzu werden fünf Methoden für die Präprozessierung untersucht, um zu evaluieren, welche Methode geeignet ist, derartige Expressionsdaten zu verrechnen. Auf Basis eines Testdatensatzes der bereits zur Etablierung des Laborprozesses diente werden Expressionswerte durch empirische Verteilung, Gammaverteilung und ein linear gemischtes Modell simuliert. Die Simulation lässt sich in vier Schritte einteilen: Wahl der Verteilung, Simulation der Expressionsmatrix, Simulation der differentiellen Expression, Sortierung der Probes innerhalb des Probesets. Anschließend werden die fünf Präprozessierungsmethoden mit diesen simulierten Expressionsdaten auf ihre Sensitivität und Spezifität untersucht. Während sich bei den empirisch und gammaverteilt simulierten Expressionsdaten kein eindeutiges Ergebnis abzeichnet, hat sVSN bei den Daten aus dem linear gemischten Modell die größte Sensitivität und die größte Spezifität. Der in dieser Arbeit entwickelte sVSN-Algorithmus wurde zum ersten Mal angewendet und bewertet. Abschließend wird ein Teildatensatz von Brune et al. verwendet und hinsichtlich der fünf Präprozessierungsmethoden untersucht. Die Ergebnisse der sVSN-Methode wird im Detail weiter verfolgt. Die zusätzlich gefunden Gene können durch bereits veröffentlichte Arbeiten bestätigt werden. Letztendlich zeigt sich, dass neuere statistische Methoden (wie das im Rahmen dieser Arbeit entwickelte sVSN) bei der Analyse von Affymetrix Microarrays einen Vorteil bringen. Die sVSN und sRMA Methoden zeigen Vorteile, da die Probes nach der Normalisierung gewichtet werden, bevor diese aggregiert werden. Die MAS5-Methode schneidet am schlechtesten ab und sollte bei geringen Zellmengen nicht eingesetzt werden. Für die Analyse mit geringer Menge an mRNA müssen weitere Untersuchungen vorgenommen werden, um eine geeignete statistische Methode für die Analyse der Expressionsdaten zu finden.
