Tumor-Associated Disialylated Glycosphingolipid Antigen-Revealing Antibodies Found in Melanoma Patients' Immunoglobulin Repertoire Suggest a Two-Direction Regulation Mechanism Between Immune B Cells and the Tumor

Abstract

There is far less information available about the tumor infiltrating B (TIL-B) cells, than about the tumor infiltrating T cells. We focused on discovering the features and potential role of B lymphocytes in solid tumors. Our project aimed to develop innovative strategies to define cancer membrane structures. We chose two solid tumor types, with variable to considerable B cell infiltration. The strategy we set up with invasive breast carcinoma, showing medullary features, has been introduced and standardized in metastatic melanoma. After detecting B lymphocytes by immunohistochemistry, VH-JH, Vκ-Jκ immunoglobulin rearranged V region genes were amplified by RT-PCR, from TIL-B cDNA. Immunoglobulin variable-region genes of interest were cloned, sequenced, and subjected to a comparative DNA analysis. Single-chain variable (scFv) antibody construction was performed in selected cases to generate a scFv library and to test tumor binding capacity. DNA sequence analysis revealed an overrepresented VH3-1 cluster, represented both in the breast cancer and the melanoma TIL-B immunoglobulin repertoire. We observed that our previously defined anti GD3 ganglioside-binder antibody-variable region genes were present in melanoma as well. Our antibody fragments showed binding potential to disialylated glycosphingolipids (GD3 ganglioside) and their O acetylated forms on melanoma cancer cells. We conclude that our results have a considerable tumor immunological impact, as they reveal the power of TIL-B cells to recognize strong tumor-associated glycosphingolipid structures on melanomas and other solid tumors. As tumor-derived gangliosides affect immune cell functions and reduce the B lymphocytes' antibody production, we suspect an important B lymphocyte and cancer cell crosstalk mechanism. We not only described the isolation and specificity testing of the tumor infiltrating B cells, but also showed the TIL-B cells' highly tumor-associated GD3 ganglioside-revealing potential in melanomas. The present data help to identify new cancer-associated biomarkers that may serve for novel cancer diagnostics. The two-direction regulation mechanism between immune B cells and the tumor could eventually be developed into an innovative cancer treatment strategy.

Smaller size packs a stronger punch - Recent advances in small antibody fragments targeting tumour-associated carbohydrate antigens

“…The presented method can provide means to obtain tumour-specific Abs of human origin. The study provides evidence for a two-way regulation mechanism between TIL-B cells and tumour cells and opens a way to potentially new cancer treatment strategies 88 .…”

CDC25C is a prognostic biomarker and correlated with mitochondrial homeostasis in pancreatic adenocarcinoma

“…Immune infiltration analysis showed that CDC25C overexpression can significantly inhibit the number of naive B cells in the tumor. B cells change the direction of the myeloid response through the humoral immune characteristics and significantly affect tumor progression [ 38 ]. Since the specific mechanism is not clear, the inhibition of naive B cells by CDC25C may partly expound the poor prognosis of PAAD patients with high CDC25C expression.…”

A B‐cell or a key player? The different roles of B‐cells and antibodies in melanoma

“…Based on these user-defined phenotypes, plasmablasts, plasma cells, activated Bcells, germinal centre B-cells, transitional B-cells and memory B-cells have been identified in melanomas (Table 1). Since multiple B-cell subtypes are present in melanoma, this suggests that different B- (Table 1) has, however, hampered consensus in reported studies, and therefore, incomplete B-cell functions in response to melanoma have likely been reported (Amaria et al, 2018;Bosisio et al, 2016;Cabrita et al, 2020;Carpenter et al, 2009;Cipponi et al, 2012;Das et al, 2018;Erdag et al, 2012;Garg et al, 2016;Griss et al, 2019;Harlin et al, 2009;Helmink et al, 2020;Hillen et al, 2008;Kotlan et al, 2019;Ladányi et al, 2011;Martinez-Rodriguez et al, 2014;Messina et al, 2012;Meyer et al, 2012a;Somasundaram et al, 2017); Table 1, Supplementary Table 1. The consistent use of a single marker (usually CD19 or CD20, or the expression of Ig) to identify the presence of B-cells has particularly resulted in inconsistent interpretation, as more information is required to understand whether they have a pro-or anti-tumourigenic role (Table 1; Supplementary Table 1).…”

“…These arrays tend to identify autoantibodies against common native proteins but can be modified to ensure they include targets of interest, such as tumour‐associated antigens and post‐translationally modified (PTM) proteins, which can aberrantly occur in malignantly transformed cells. For example, a classic T‐cell epitope (YMDGTMSQV) formed by PTM of tyrosinase specifically occurs in melanoma (Skipper et al, 1996) and alteration in glycosylation patterns seen in melanoma (Laidler et al, 2005) can increase the number of targets for tumour‐specific antibodies (Kotlan et al, 2019). Studies do not often consider the PTM of proteins, and therefore, there is considerable potential in this approach to identify previously unappreciated targets.…”

“…Markers used to define B-cell subtypes in melanomaBalatoni et al (2018),Bosisio et al (2016), Cabrita et al (2020,Cipponi et al (2012),Erdag et al (2012),Garg et al (2016),Halse et al (2018),Harlin et al (2009),Helmink et al( 2020),Hillen et al (2008),Kotlan et al (2019),Ladányi et al (2011), Martinez-Rodriguez et al (2014), Messina et al (2012), Meyer et al (2012a), Somasundaram et al + CD24 ++ CD38 + + CD10 + CD27 − IgD + Helmink et al (2020) Transitional cell-like Immunohistochemistry CD19 − CD20 + CD138 − CD5 + Griss et al (2019) Circulating memory (nonclass-switched) B-cells Flow cytometry CD19 + CD27 + IgM + Das et al (2018) Memory (non-classswitched) B-cells Mass cytometry CD19 + CD45 + CD27 + IgD + Helmink et al Flow cytometry CD19 + CD20 low/− CD38 high CD 27 + CD3 − CD14 − IgA − IgM − Defalco et al (2018) Plasmablast-like Immunohistochemistry CD19 + CD20 − CD38 + CD138 − Griss et al…”