Cell-of-origin classification using the Hans and Lymph2Cx algorithms in primary cutaneous large B-cell lymphomas

Primary cutaneous diffuse large B-cell lymphoma, leg type (PCDLBCL-LT) and primary cutaneous follicle center lymphoma with a diffuse population of large cells (PCFCL-LC) are both primary cutaneous B-cell lymphomas with large-cell morphology (CLBCL) but with different clinical characteristics and behavior. In systemic diffuse large B-cell lymphoma, not otherwise specified (DLBCL-NOS), gene-expression profiling (GEP) revealed two molecular subgroups based on their cell-of-origin (COO) with prognostic significance: the germinal center B-cell-like (GCB) subtype and the activated B-cell-like (ABC) subtype. This study investigated whether COO classification is a useful tool for classification of CLBCL. For this retrospective study, 51 patients with PCDLBCL-LT and 15 patients with PCFCL-LC were analyzed for their COO according to the immunohistochemistry-based Hans algorithm and the NanoString GEP-based Lymph2Cx algorithm. In PCFCL-LC, all cases (100%) classified as GCB by both Hans and Lymph2Cx. In contrast, COO classification in PCDLBCL-LT was heterogeneous. Using Hans, 75% of the PCDLBCL-LT patients classified as non-GCB and 25% as GCB, while Lymph2Cx classified only 18% as ABC, 43% as unclassified/intermediate, and 39% as GCB. These COO subgroups did not differ in the expression of BCL2 and IgM, mutations in MYD88 and/or CD79B, loss of CDKN2A, or survival. In conclusion, PCFCL-LC uniformly classified as GCB, while PCDLBCL-LT classified along the COO spectrum of DLBCL-NOS using the Hans and Lymph2Cx algorithms. In contrast to DLBCL-NOS, the clinical relevance of COO classification in CLBCL using these algorithms has limitations and cannot be used as an alternative for the current multiparameter approach in differentiation of PCDLBCL-LT and PCFCL-LC.

Comprehensive profiling of mRNA splicing indicates that GC content signals altered cassette exon inclusion in Ewing sarcoma

ABSTRACT Ewing sarcoma (EwS) is a small round blue cell tumor and is the second most frequent pediatric bone cancer. 85% of EwS tumors express the fusion oncoprotein EWS-FLI1, the product of a t(11;22) reciprocal translocation. Prior work has indicated that transcription regulation alone does not fully describe the oncogenic capacity of EWS-FLI1, nor does it provide an effective means to stratify patient tumors. Research using EwS cell lines and patient samples has suggested that EWS-FLI1 also disrupts mRNA biogenesis. In this work we both describe the underlying characteristics of mRNA that are aberrantly spliced in EwS tumor samples as well as catalogue mRNA splicing events across other pediatric tumor types. Here, we also use short- and long-read sequencing to identify cis-factors that contribute to splicing profiles we observe in Ewing sarcoma. Our analysis suggests that GC content upstream of cassette exons is a defining factor of mRNA splicing in EwS. We also describe specific splicing events that discriminate EwS tumor samples from the assumed cell of origin, human mesenchymal stem cells derived from bone marrow (hMSC-BM). Finally, we identify specific splicing factors PCBP2, RBMX, and SRSF9 by motif enrichment and confirm findings from tumor samples in EwS cell lines.

Clonotype pattern in T-cell lymphomas map the cell of origin to immature lymphoid precursors

Mature T-cell lymphomas (TCLs) are rare, clinically heterogeneous hematologic cancers of high medical need. TCLs have inferior prognosis which is attributed to poor understanding of their pathogenesis. Based on phenotypic similarities between normal and neoplastic lymphocytes it has been assumed that TCLs develop in the periphery, directly from various subtypes of normal T-cells. To address the debated question of the cell of origin in TCLs we analyzed to identify the highly variable complementarity determining regions (CDR3) regions of T-cell receptor (TCR) to trace the clonal history of the T-cells. We have collected previously published whole genome -exome, and -transcriptome sequencing data from 574 TCL patients. TCR clonotypes were identified by de novo assembly of CDR3 regions of TCR γ, β and α. We have found that the vast majority of TCLs are clonotypically oligoclonal, although the pattern oligoclonality varied. Anaplastic large cell lymphoma was most diverse comprising multiple clonotypes of TCRγ, β and α whereas adult T-cell lymphoma/leukemia and peripheral T-cell lymphomas often showed monoclonality for TCRγ and β but had diverse TCRα clonotypes. These patterns of rearrangements indicated that TCLs are initiated at the level of the lymphoid precursor. In keeping with this hypothesis, TCR rearrangements in TCLs resembled the pattern seen in the human thymus showing biased usage of V and J segments of high combinatorial probability resulting in recurrent, "public" CDR3 sequences shared across unrelated patients and different clinical TCL entities. Clonotypically diverse initiating cells may seed target tissues being responsible for disease relapses after therapy.

Single-cell chromatin accessibility landscape in kidney identifies additional cell-of-origin in heterogenous papillary renal cell carcinoma

Papillary renal cell carcinoma (pRCC) is the most heterogenous renal cell carcinoma. Patient survival varies and no effective therapies for advanced pRCC exist. Histological and molecular characterization studies have highlighted the heterogeneity of pRCC tumours. Recent studies identified the proximal tubule (PT) cell as a cell-of-origin for pRCC. However, it remains elusive whether other pRCC subtypes have different cell-of-origin. Here, by obtaining genome-wide chromatin accessibility profiles of normal human kidney cells using single-cell transposase-accessible chromatin-sequencing and comparing the profiles with pRCC samples, we discover that besides PT cells, pRCC can also originate from kidney collecting duct principal cells. We show pRCCs with different cell-of-origin exhibit different molecular characteristics and clinical behaviors. Further, metabolic reprogramming appears to mediate the progression of pRCC to the advanced state. Here, our results suggest that determining cell-of-origin and monitoring origin-dependent metabolism could potentially be useful for early diagnosis and treatment of pRCC.

The Pathologic and Genetic Characteristics of Extranodal NK/T-Cell Lymphoma

Extranodal NK/T-cell lymphoma is a neoplasm of NK cells or cytotoxic T cells presenting in extranodal sites, most often in the nasal cavity. The typical immunophenotypes are cCD3+, sCD3−, CD4−, CD5−, CD8−, CD16−, and CD56+ with the expression of cytotoxic molecules. Tumor subsets express NK cell receptors, CD95/CD95L, CD30, MYC, and PDL1. Virtually all the tumor cells harbor the EBV genome, which plays a key role in lymphomagenesis as an epigenetic driver. EBV-encoded oncoproteins modulate the host-cell epigenetic machinery, reprogramming the viral and host epigenomes using host epigenetic modifiers. NGS analysis revealed the mutational landscape of ENKTL, predominantly involving the JAK–STAT pathway, epigenetic modifications, the RNA helicase family, the RAS/MAP kinase pathway, and tumor suppressors, which indicate an important role of these pathways and this group of genes in the lymphomagenesis of ENKTL. Recently, three molecular subtypes were proposed, the tumor-suppressor/immune-modulator (TSIM), MGA-BRDT (MB), and HDAC9-EP300-ARID1A (HEA) subtypes, and they are well-correlated with the cell of origin, EBV pattern, genomic alterations, and clinical outcomes. A future investigation into the function and interaction of discovered genes would be very helpful for better understanding the molecular pathogenesis of ENKTL and establishing better treatment strategies.

Cell Type of Pancreatic Ductal Adenocarcinoma Origin: Implications for Prognosis and Clinical Outcomes

<b><i>Background:</i></b> Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease that has no effective early detection method or treatment to date. <b><i>Summary:</i></b> The normal cell type that initiates PDAC, or its cellular origin, is still unknown. To investigate the contribution of distinct normal epithelial cell types to PDAC tumorigenesis, genetically engineered mouse models were used to show that both acinar and ductal cells are capable of giving rise to PDAC. These studies indicated that genetic mutations and pancreatic injury interact differently with each cellular origin to affect their predilection and process for forming PDAC. In this review, we summarize recent findings using various genetically engineered mouse models in the identification and characterization of the PDAC cell of origin. We also discuss potential implications for cellular origin on tumor development, PDAC transcriptional subtype, and disease prognosis of patients. <b><i>Key Message:</i></b> Although it is clear that both ductal and acinar cells have the potential to form PDAC, whether cellular origin can indeed influence patient prognosis and whether knowledge of cellular origin will aid in the diagnosis or treatment of patients in the future will need further study.

Immunophenotypic characteristics of Diffuse Large Bcell Lymphoma

Introduction: Immunohistochemistry (IHC) is essential in the diagnostic workup of Diffuse Large B cell lymphoma (DLBCL). Determination of biological heterogenicity of Diffuse Large B-cell Lymphoma (DLBCL) is critical to institute precise treatment and predict prognosis. IHC confirms B cell phenotypes, reflects molecular subtype based on cell of origin and determines other immunophenotypic characteristics. Methods and Material: All cases of DLBCL diagnosed in 2020 (Jan-Dec) in histopathology department of Evercare Hospital Dhaka were included in this study. Histopathological sections were stained with CD20, CD3, CD5, CD30, BCL2, BCL6, CD10, MUM1, MYC, Ki67 and other markers. Hans algorithm was applied to classify DLBCL cases into germinal center B-cell (GCB) or Non-GCB. Results: Out of 64 DLBCL cases, 21 (24%) of DLBCL were GCB, while 76% (43 cases) were non-GCB subtypes. 30% cases of DLBCL showed double expression for MYC and BCL2. Fewer cases were immunoreactive for CD5 and CD30. Conclusion: This first study at Dhaka with wide range of antibody to characterize the Immunophenotypic features of DLBCL. The main finding of this study is the identification of non-germinal center B-cell (non-GCB) as the major immunophenotype of DLBCL. This may be an enabler for further studies to observe the clinical outcome of different subtypes of GCB and Non-GCB. Bioresearch Commu. 8(1): 1049-1052, 2022 (January)

Crosstalk with keratinocytes causes GNAQ oncogene specificity in melanoma

Different melanoma subtypes exhibit specific and non-overlapping sets of oncogene and tumor suppressor mutations, despite a common cell of origin in melanocytes. For example, activation of the Gαq/11 signaling pathway is a characteristic initiating event in primary melanomas that arise in the dermis, uveal tract or central nervous system. It is rare in melanomas arising in the epidermis. The mechanism for this specificity is unknown. Here, we present evidence that in the mouse, crosstalk with the epidermal microenvironment actively impairs the survival of melanocytes expressing the GNAQQ209L oncogene. We found that GNAQQ209L, in combination with signaling from the interfollicular epidermis (IFE), stimulates dendrite extension, leads to actin cytoskeleton disorganization, inhibits proliferation and promotes apoptosis in melanocytes. The effect was reversible and paracrine. In contrast, the epidermal environment increased the survival of wildtype and BrafV600E expressing melanocytes. Hence, our studies reveal the flip side of Gaq/11 signaling, which was hitherto unsuspected. In the future, the identification of the epidermal signals that restrain the GNAQQ209L oncogene could suggest novel therapies for GNAQ and GNA11 mutant melanomas.

Tracing and Targeting the Origins of Childhood Cancer

Despite the success of treating childhood cancers with cytotoxic agents, novel therapeutic strategies are required to achieve the next leap in cure rates. A promising avenue may be to target the origin of childhood cancers. Here, we review recent advances in tracing the origins of pediatric tumors. Cancer-to-normal cell comparisons by single-cell mRNA sequencing reveal the fetal state of cancer cells, as well as their cell of origin. Recent phylogenetic analyses have uncovered large tissue-resident precursor clones to childhood cancers, which already possess key genomic alterations leading to tumor formation. Both the transcriptional fetalness and genomic status of the premalignant tissue bed provide further avenues for targeted therapy. Overall, these advances begin to describe the precise origins of pediatric tumors and pave the way for novel methods in detecting, treating, and perhaps even preventing childhood cancers. Expected final online publication date for the Annual Review of Cancer Biology, Volume 6 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Cancer Type Classification in Liquid Biopsies Based on Sparse Mutational Profiles Enabled through Data Augmentation and Integration

Identifying the cell of origin of cancer is important to guide treatment decisions. Machine learning approaches have been proposed to classify the cell of origin based on somatic mutation profiles from solid biopsies. However, solid biopsies can cause complications and certain tumors are not accessible. Liquid biopsies are promising alternatives but their somatic mutation profile is sparse and current machine learning models fail to perform in this setting. We propose an improved method to deal with sparsity in liquid biopsy data. Firstly, data augmentation is performed on sparse data to enhance model robustness. Secondly, we employ data integration to merge information from: (i) SNV density; (ii) SNVs in driver genes and (iii) trinucleotide motifs. Our adapted method achieves an average accuracy of 0.88 and 0.65 on data where only 70% and 2% of SNVs are retained, compared to 0.83 and 0.41 with the original model, respectively. The method and results presented here open the way for application of machine learning in the detection of the cell of origin of cancer from liquid biopsy data.