Expanded clinical and experimental use of SOX11 - using a monoclonal antibody

BACKGROUND

The transcription factor SOX11 is of diagnostic and prognostic importance in mantle cell lymphoma (MCL) and epithelial ovarian cancer (EOC), respectively. Thus, there is an unmet clinical and experimental need for SOX11-targeting assays with low background, high specificity and robust performance in multiple applications, including immunohistochemistry (IHC-P) and flow cytometry, which until now has been lacking.

METHODS

We have developed SOX11-C1, a monoclonal mouse antibody targeting SOX11, and successfully evaluated its performance in western blots (WB), IHC-P, fluorescence microscopy and flow cytometry.

RESULTS

We confirm the importance of SOX11 as a diagnostic antigen in MCL as 100% of tissue micro array (TMA) cases show bright nuclear staining, using the SOX11-C1 antibody in IHC-P. We also show that previous reports of weak SOX11 immunostaining in a fraction of hairy cell leukemias (HCL) are not confirmed using SOX11-C1, which is consistent with the lack of transcription. Thus, high sensitivity and improved specificity are demonstrated using the monoclonal SOX11-C1 antibody. Furthermore, we show for the first time that flow cytometry can be used to separate SOX11 positive and negative cell lines and primary tumors. Of note, SOX11-C1 shows no nonspecific binding to primary B or T cells in blood and thus, can be used for analysis of B and T cell lymphomas from complex clinical samples. Dilution experiments showed that low frequencies of malignant cells (~1%) are detectable above background using SOX11 as a discriminant antigen in flow cytometry.

CONCLUSIONS

The novel monoclonal SOX11-specific antibody offers high sensitivity and improved specificity in IHC-P based detection of MCL and its expanded use in flow cytometry analysis of blood and tissue samples may allow a convenient approach to early diagnosis and follow-up of MCL patients.

Identification of uniquely expressed transcription factors in highly purified B-cell lymphoma samples

Transcription factors (TFs) are critical for B-cell differentiation, affecting gene expression both by repression and transcriptional activation. Still, this information is not used for classification of B-cell lymphomas (BCLs). Traditionally, BCLs are diagnosed based on a phenotypic resemblance to normal B-cells; assessed by immunohistochemistry or flow cytometry, by using a handful of phenotypic markers. In the last decade, diagnostic and prognostic evaluation has been facilitated by global gene expression profiling (GEP), providing a new powerful means for the classification, prediction of survival, and response to treatment of lymphomas. However, most GEP studies have typically been performed on whole tissue samples, containing varying degrees of tumor cell content, which results in uncertainties in data analysis. In this study, global GEP analyses were performed on highly purified, flow-cytometry sorted tumor-cells from eight subgroups of BCLs. This enabled identification of TFs that can be uniquely associated to the tumor cells of chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), hairy cell leukemia (HCL), and mantle cell lymphoma (MCL). The identified transcription factors influence both the global and specific gene expression of the BCLs and have possible implications for diagnosis and treatment.

Identification of molecular targets associated with transformed diffuse large B cell lymphoma using highly purified tumor cells

Follicular lymphoma (FL) frequently transforms into the more aggressive diffuse large B cell lymphoma (DLBCL-tr), but no protein biomarkers have been identified for predictive or early diagnosis. Gene expression analyses have identified genes changing on transformation but have failed to be reproducible in different studies, reflecting the heterogeneity within the tumor tissue and between tumor samples. Gene expression analyses on Affymetrix Human Genome U133 Plus 2.0 arrays were performed, using flow cytometry sorted tumor cells derived from FL and transformed DLBCL. To identify molecular targets associated with the transformation, subsequent immunohistochemistry (IHC) analyses of the corresponding proteins were performed. Using highly purified cells, this study identified 163 genes, which were significantly deregulated during the transformation in a majority of cases. Among the upregulated transcripts, 13 genes were selected for validation using IHC, based on the availability of commercial antibodies, and galectin-3 and NEK2 proteins specifically identify DLBCL-tr, when compared with FL. We demonstrate that by purifying tumor cells through cell sorting, thereby reducing the heterogeneity due to infiltrating cells, it was possible to identify distinct differences between tumor entities rather than variations due to cellular composition. Galectin-3 and NEK2 both identified a subgroup of DLBCL-tr, and the function of these protein markers also suggests a biological role in the transformation process.

The human IgE-encoding transcriptome to assess antibody repertoires and repertoire evolution

Upon encounter with antigen, the B lymphocyte population responds by producing a diverse set of antigen-specific antibodies of various isotypes. The vast size of the responding populations makes it very difficult to study clonal evolution and repertoire composition occurring during these processes in humans. Here, we have explored an approach utilizing the H-EPSILON-encoding transcriptome to investigate aspects of repertoire diversity during the season of antigen exposure. We show through sequencing of randomly picked transcripts that the sizes of patients' repertoires are relatively small. This specific aspect of the transcriptome allows us to construct evolutionary trees pinpointing features of somatic hypermutation as it occurs in humans. Despite the small size of the repertoires, they are highly diverse with respect to VDJ gene usage, suggesting that the H-EPSILON-encoding transcriptome is a faithful mimic of other class-switched isotypes. Importantly, it is possible to use antibody library and selection technologies to define the specificity of clonotypes identified by random sequencing. The small size of the H-EPSILON-encoding transcriptome of peripheral blood B cells, the simple identification of clonally related sets of genes in this population, and the power of library and selection technologies ensure that this approach will allow us to investigate antibody evolution in human B lymphocytes of known specificity. As H-EPSILON repertoires show many of the hallmarks of repertoires encoding other isotypes, we suggest that studies of this type will have an impact on our understanding of human antibody evolution even beyond that occurring in the IgE-producing B cell population.

From Gene Expression Analysis to Tissue Microarrays

Mantle cell lymphoma (MCL) is an aggressive lymphoid malignancy for which better treatment strategies are needed. To identify potential diagnostic and therapeutic targets, a signature consisting of MCL-associated genes was selected based on a comprehensive gene expression analysis of malignant and normal B cells. The corresponding protein epitope signature tags were identified and used to raise monospecific, polyclonal antibodies, which were subsequently analyzed on paraffin-embedded sections of malignant and normal tissue. In this study, we demonstrate that the initial selection strategy of MCL-associated genes successfully allows identification of protein antigens either uniquely expressed or overexpressed in MCL compared with normal lymphoid tissues. We propose that genome-based, affinity proteomics, using protein epitope signature tag-induced antibodies, is an efficient way to rapidly identify a number of disease-associated protein candidates of both previously known and unknown identities.