Innate Lymphoid Cells in the Malignant Melanoma Microenvironment

The role of innate lymphoid cells (ILCs) in cancer progression has been uncovered in recent years. ILCs are classified as Type 1, Type 2, and Type 3 ILCs, which are characterized by the transcription factors necessary for their development and the cytokines and chemokines they produce. ILCs are a highly heterogeneous cell population, showing both anti– and protumoral properties and capable of adapting their phenotypes and functions depending on the signals they receive from their surrounding environment. ILCs are considered the innate counterparts of the adaptive immune cells during physiological and pathological processes, including cancer, and as such, ILC subsets reflect different types of T cells. In cancer, each ILC subset plays a crucial role, not only in innate immunity but also as regulators of the tumor microenvironment. ILCs’ interplay with other immune and stromal cells in the metastatic microenvironment further dictates and influences this dichotomy, further strengthening the seed-and-soil theory and supporting the formation of more suitable and organ-specific metastatic environments. Here, we review the present knowledge on the different ILC subsets, focusing on their interplay with components of the tumor environment during the development of primary melanoma as well as on metastatic progression to organs, such as the liver or lung.This research was funded by University of Basque Country, grant number GIU17/66

An E2F7-Dependent Transcriptional Program Modulates DNA Damage Repair And Genomic Stability

Corrigendum published on 03 July 2019 Nucleic Acids Research 47 (14) : 7716–7717 (2019) https://doi.org/10.1093/nar/gkz587The cellular response to DNA damage is essential for maintaining the integrity of the genome. Recent evidence has identified E2F7 as a key player in DNA damage-dependent transcriptional regulation of cell-cycle genes. However, the contribution of E2F7 to cellular responses upon genotoxic damage is still poorly defined. Here we show that E2F7 represses the expression of genes involved in the maintenance of genomic stability, both throughout the cell cycle and upon induction of DNA lesions that interfere with replication fork progression. Knockdown of E2F7 leads to a reduction in 53BP1 and FANCD2 foci and to fewer chromosomal aberrations following treatment with agents that cause interstrand crosslink (ICL) lesions but not upon ionizing radiation. Accordingly, E2F7-depleted cells exhibit enhanced cell-cycle re-entry and clonogenic survival after exposure to ICL-inducing agents. We further report that expression and functional activity of E2F7 are p53-independent in this context. Using a cell-based assay, we show that E2F7 restricts homologous recombination through the transcriptional repression of RAD51. Finally, we present evidence that downregulation of E2F7 confers an increased resistance to chemotherapy in recombination-deficient cells. Taken together, our results reveal an E2F7-dependent transcriptional program that contributes to the regulation of DNA repair and genomic integrity.This work was supported by grants from the Spanish Ministry [SAF2012-33551 and SAF2015-67562-R, co-financed by FEDER funds, and SAF2014-57791-REDC], the Basque Government [IT634-13 and KK-2015/89], and the University of the Basque Country UPV/EHU [UFI11/20] to AMZ; and grants from the Spanish Ministry [SAF2015-69920-R], and Worldwide Cancer Research [15-0278] to MM. JM was recipient of a Basque Government fellowship for graduate studies and JVR is recipient of a UPV/EHU fellowship for graduate studies. M.A.F. was supported by a young investigator grant from MINECO [SAF2014-60442-JIN; co-financed by FEDER funds]. Funding for open access charge: Spanish Ministry [SAF2015-67562-R, co-financed by FEDER funds]; Basque Government [IT634-13]

Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study

Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contains information about the general status of the organism and therefore represents a valuable source for biomarkers. Thus, we aimed to define serological biomarkers that could be used along with clinical and histopathological features of the disease to predict metastatic events on the early-stage population of patients. We previously demonstrated that in stage II melanoma patients, serum levels of dermcidin (DCD) were associated with metastatic progression. Based on the relevance of the immune response on the cancer progression and the recent association of DCD with local and systemic immune response against cancer cells, serum DCD was analyzed in a new cohort of patients along with interleukin 4 (IL-4), IL-6, IL-10, IL-17A, interferon gamma (IFN-gamma), transforming growth factor-beta (TGF- beta), and granulocyte-macrophage colony-stimulating factor (GM-CSF). We initially recruited 448 melanoma patients, 323 of whom were diagnosed as stages I-II according to AJCC. Levels of selected cytokines were determined by ELISA and Luminex, and obtained data were analyzed employing machine learning and Kaplan-Meier techniques to define an algorithm capable of accurately classifying early-stage melanoma patients with a high and low risk of developing metastasis. The results show that in early-stage melanoma patients, serum levels of the cytokines IL-4, GM-CSF, and DCD together with the Breslow thickness are those that best predict melanoma metastasis. Moreover, resulting algorithm represents a new tool to discriminate subjects with good prognosis from those with high risk for a future metastasis.We are grateful to the Basque Biobank for providing the serum samples. We are also most grateful to Drs Arantza Arrieta and Natalia Maruri (Cruces University Hospital) for their technical support with the serum marker detection. This work was supported by grants from the Basque Government (KK2016-036 and KK2017-041 to MDB), UPV/EHU (GIU17/066 to MDB), H2020-ESCEL JTI (15/01 to MDB), and MINECO (PCIN-2015-241 to MDB

Pirin is a prognostic marker of human melanoma that dampens the proliferation of malignant cells by downregulating JARID1B/KDM5B expression

Originally considered to act as a transcriptional co‑factor, Pirin has recently been reported to play a role in tumorigenesis and the malignant progression of many tumors. Here, we have analyzed the diagnostic and prognostic value of Pirin expression in the early stages of melanoma, and its role in the biology of melanocytic cells. Pirin expression was analyzed in a total of 314 melanoma biopsies, correlating this feature with the patient’s clinical course. Moreover, PIR downregulated primary melanocytes were analyzed by RNA sequencing, and the data obtained were validated in human melanoma cell lines overexpressing PIR by functional assays. The immunohistochemistry multivariate analysis revealed that early melanomas with stronger Pirin expression were more than twice as likely to develop metastases during the follow‑up. Transcriptome analysis of PIR downregulated melanocytes showed a dampening of genes involved in the G1/S transition, cell proliferation, and cell migration. In addition, an in silico approach predicted that JARID1B as a potential transcriptional regulator that lies between PIR and its downstream modulated genes, which was corroborated by co‑transfection experiments and functional analysis. Together, the data obtained indicated that Pirin could be a useful marker for the metastatic progression of melanoma and that it participates in the proliferation of melanoma cells by regulating the slow‑cycling JARID1B gene.This project was supported by grants from the Basque Government (KK2017-041 and KK2020-00069 to M.D.B.), the UPV/EHU (GIU17/066 to M.D.B.), H2020-ESCEL JTI (15/01 to M.D.B.) and MINECO (PCIN-2015-241 to M.D.B.). CP holds a predoctoral fellowship from the Basque Government. Part of this project is under European patent No. EP3051291 (EP14796149.4): “Method for diagnosis and prognosis of cutaneous melanoma”, Univer- sity of the Basque Country (UPV/EHU). The authors acknowledge the technical support SGIker resources at the UPV/EHU for the computational calculations, which were carried out in the Arina Informatics Cluster. The authors are grateful to the Basque Biobank for providing the biopsy samples and in particular, to María Jesús Fernández and Arantza Perez Dobaran for their technical support with the immunohistochemistry

RKIP Regulates Differentiation-Related Features in Melanocytic Cells

Raf Kinase Inhibitor Protein (RKIP) has been extensively reported as an inhibitor of keysignaling pathways involved in the aggressive tumor phenotype and shows decreased expressionin several types of cancers. However, little is known about RKIP in melanoma or regarding its functionin normal cells. We examined the role of RKIP in both primary melanocytes and malignant melanomacells and evaluated its diagnostic and prognostic value. IHC analysis revealed a significantly higherexpression of RKIP in nevi compared with early-stage (stage I–II, AJCC 8th) melanoma biopsies.Proliferation, wound healing, and collagen-coated transwell assays uncovered the implication ofRKIP on the motility but not on the proliferative capacity of melanoma cells as RKIP protein levelswere inversely correlated with the migration capacity of both primary and metastatic melanoma cellsbut did not alter other parameters. As shown by RNA sequencing, endogenous RKIP knockdownin primary melanocytes triggered the deregulation of cellular differentiation-related processes,including genes (i.e., ZEB1, THY-1) closely related to the EMT. Interestingly, NANOG was identifiedas a putative transcriptional regulator of many of the deregulated genes, and RKIP was able todecrease the activation of the NANOG promoter. As a whole, our data support the utility of RKIPas a diagnostic marker for early-stage melanomas. In addition, these findings indicate its participationin the maintenance of a differentiated state of melanocytic cells by modulating genes intimately linkedto the cellular motility and explain the progressive decrease of RKIP often described in tumors.This project was supported by grants from the Basque Government (KK2016-036 and KK2017-041 toM.D.B.), UPV/EHU (GIU17/066 to M.D.B.), H2020-ESCEL JTI (15/01 to M.D.B.) and MINECO (PCIN-2015-241 toM.D.B.). CP holds a predoctoral fellowship from the Basque Governmen

Serum markers improve current prediction of metastasis development in early‐stage melanoma patients: a machine learning‐based study

Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contains information about the general status of the organism and therefore represents a valuable source for biomarkers. Thus, we aimed to define serological biomarkers that could be used along with clinical and histopathological features of the disease to predict metastatic events on the early-stage population of patients. We previously demonstrated that in stage II melanoma patients, serum levels of dermcidin (DCD) were associated with metastatic progression. Based on the relevance of the immune response on the cancer progression and the recent association of DCD with local and systemic immune response against cancer cells, serum DCD was analyzed in a new cohort of patients along with interleukin 4 (IL-4), IL-6, IL-10, IL-17A, interferon gamma (IFN-gamma), transforming growth factor-beta (TGF- beta), and granulocyte-macrophage colony-stimulating factor (GM-CSF). We initially recruited 448 melanoma patients, 323 of whom were diagnosed as stages I-II according to AJCC. Levels of selected cytokines were determined by ELISA and Luminex, and obtained data were analyzed employing machine learning and Kaplan-Meier techniques to define an algorithm capable of accurately classifying early-stage melanoma patients with a high and low risk of developing metastasis. The results show that in early-stage melanoma patients, serum levels of the cytokines IL-4, GM-CSF, and DCD together with the Breslow thickness are those that best predict melanoma metastasis. Moreover, resulting algorithm represents a new tool to discriminate subjects with good prognosis from those with high risk for a future metastasis.We are grateful to the Basque Biobank for providing the serum samples. We are also most grateful to Drs Arantza Arrieta and Natalia Maruri (Cruces University Hospital) for their technical support with the serum marker detection. This work was supported by grants from the Basque Government (KK2016-036 and KK2017-041 to MDB), UPV/EHU (GIU17/066 to MDB), H2020-ESCEL JTI (15/01 to MDB), and MINECO (PCIN-2015-241 to MDB