Human melanomas and ovarian cancers overexpressing mechanical barrier molecule genes lack immune signatures and have increased patient mortality risk

Extracellular matrix stiffness and tumor-associated macrophage polarization: new fields affecting immune exclusion

In the malignant progression of tumors, there is deposition and cross-linking of collagen, as well as an increase in hyaluronic acid content, which can lead to an increase in extracellular matrix stiffness. Recent research evidence have shown that the extracellular matrix plays an important role in angiogenesis, cell proliferation, migration, immunosuppression, apoptosis, metabolism, and resistance to chemotherapeutic by the alterations toward both secretion and degradation. The clinical importance of tumor-associated macrophage is increasingly recognized, and macrophage polarization plays a central role in a series of tumor immune processes through internal signal cascade, thus regulating tumor progression. Immunotherapy has gradually become a reliable potential treatment strategy for conventional chemotherapy resistance and advanced cancer patients, but the presence of immune exclusion has become a major obstacle to treatment effectiveness, and the reasons for their resistance to these approaches remain uncertain. Currently, there is a lack of exact mechanism on the regulation of extracellular matrix stiffness and tumor-associated macrophage polarization on immune exclusion. An in-depth understanding of the relationship between extracellular matrix stiffness, tumor-associated macrophage polarization, and immune exclusion will help reveal new therapeutic targets and guide the development of clinical treatment methods for advanced cancer patients. This review summarized the different pathways and potential molecular mechanisms of extracellular matrix stiffness and tumor-associated macrophage polarization involved in immune exclusion and provided available strategies to address immune exclusion.

Comparative analysis identifies genetic and molecular factors associated with prognostic clusters of PANoptosis in glioma, kidney and melanoma cancer

The importance of inflammatory cell death, PANoptosis, in cancer is increasingly being recognized. PANoptosis can promote or inhibit tumorigenesis in context-dependent manners, and a computational approach leveraging transcriptomic profiling of genes involved in PANoptosis has shown that patients can be stratified into PANoptosis High and PANoptosis Low clusters that have significant differences in overall survival for low grade glioma (LGG), kidney renal cell carcinoma (KIRC) and skin cutaneous melanoma (SKCM). However, the molecular mechanisms that contribute to differential prognosis between PANoptosis clusters require further elucidation. Therefore, we performed a comprehensive comparison of genetic, genomic, tumor microenvironment, and pathway characteristics between the PANoptosis High and PANoptosis Low clusters to determine the relevance of each component in driving the differential associations with prognosis for LGG, KIRC and SKCM. Across these cancer types, we found that activation of the proliferation pathway was significantly different between PANoptosis High and Low clusters. In LGG and SKCM, we also found that aneuploidy and immune cell densities and activations contributed to differences in PANoptosis clusters. In individual cancers, we identified important roles for barrier gene pathway activation (in SKCM) and the somatic mutation profiles of driver oncogenes as well as hedgehog signaling pathway activation (in LGG). By identifying these genetic and molecular factors, we can possibly improve the prognosis for at risk-stratified patient populations based on the PANoptosis phenotype in LGG, KIRC and SKCM. This not only advances our mechanistic understanding of cancer but will allow for the selection of optimal treatment strategies.

The role of tumor immune microenvironment in chordoma: promising immunotherapy strategies

Chordoma is a rare malignant bone tumor with limited therapeutic options, which is resistant to conventional chemotherapy and radiotherapy, and targeted therapy is also shown with little efficacy. The long-standing delay in researching its mechanisms of occurrence and development has resulted in the dilemma of no effective treatment targets and no available drugs in clinical practice. In recent years, the role of the tumor immune microenvironment in driving tumor growth has become a hot and challenging topic in the field of cancer research. Immunotherapy has shown promising results in the treatment of various tumors. However, the study of the immune microenvironment of chordoma is still in its infancy. In this review, we aim to present a comprehensive reveal of previous exploration on the chordoma immune microenvironment and propose promising immunotherapy strategies for chordoma based on these characteristics.

Cancer immune exclusion: breaking the barricade for a successful immunotherapy

Immunotherapy has changed the course of cancer treatment. The initial steps were made through tumor-specific antibodies that guided the setup of an antitumor immune response. A new and successful generation of antibodies are designed to target immune checkpoint molecules aimed to reinvigorate the antitumor immune response. The cellular counterpart is the adoptive cell therapy, where specific immune cells are expanded or engineered to target cancer cells. In all cases, the key for achieving positive clinical resolutions rests upon the access of immune cells to the tumor. In this review, we focus on how the tumor microenvironment architecture, including stromal cells, immunosuppressive cells and extracellular matrix, protects tumor cells from an immune attack leading to immunotherapy resistance, and on the available strategies to tackle immune evasion.

An estrogen response-related signature predicts response to immunotherapy in melanoma

Background

Estrogen/estrogen receptor signaling influences the tumor microenvironment and affects the efficacy of immunotherapy in some tumors, including melanoma. This study aimed to construct an estrogen response-related gene signature for predicting response to immunotherapy in melanoma.

Methods

RNA sequencing data of 4 immunotherapy-treated melanoma datasets and TCGA melanoma was obtained from open access repository. Differential expression analysis and pathway analysis were performed between immunotherapy responders and non-responders. Using dataset GSE91061 as the training group, a multivariate logistic regression model was built from estrogen response-related differential expression genes to predict the response to immunotherapy. The other 3 datasets of immunotherapy-treated melanoma were used as the validation group. The correlation was also examined between the prediction score from the model and immune cell infiltration estimated by xCell in the immunotherapy-treated and TCGA melanoma cases.

Results

"Hallmark Estrogen Response Late" was significantly downregulated in immunotherapy responders. 11 estrogen response-related genes were significantly differentially expressed between immunotherapy responders and non-responders, and were included in the multivariate logistic regression model. The AUC was 0.888 in the training group and 0.654-0.720 in the validation group. A higher 11-gene signature score was significantly correlated to increased infiltration of CD8+ T cells (rho=0.32, p=0.02). TCGA melanoma with a high signature score showed a significantly higher proportion of immune-enriched/fibrotic and immune-enriched/non-fibrotic microenvironment subtypes (p<0.001)-subtypes with better response to immunotherapy-and significantly better progression-free interval (p=0.021).

Conclusion

In this study, we identified and verified an 11-gene signature that could predict response to immunotherapy in melanoma and was correlated with tumor-infiltrating lymphocytes. Our study suggests targeting estrogen-related pathways may serve as a combination strategy for immunotherapy in melanoma.

Barriers to immune cell infiltration in tumors

Increased immune cell infiltration into tumors is associated with improved patient survival and predicts response to immune therapies. Thus, identification of factors that determine the extent of immune infiltration is crucial, so that methods to intervene on these targets can be developed. T cells enter tumor tissues through the vasculature, and under control of interactions between homing receptors on the T cells and homing receptor ligands (HRLs) expressed by tumor vascular endothelium and tumor cell nests. HRLs are often deficient in tumors, and there also may be active barriers to infiltration. These remain understudied but may be crucial for enhancing immune-mediated cancer control. Multiple intratumoral and systemic therapeutic approaches show promise to enhance T cell infiltration, including both approved therapies and experimental therapies. This review highlights the intracellular and extracellular determinants of immune cell infiltration into tumors, barriers to infiltration, and approaches for intervention to enhance infiltration and response to immune therapies.

CD103 and periplakin are potential biomarkers for response of metastatic melanoma to pembrolizumab

This study was designed to screen for preliminary evidence of predictive markers of melanoma response to PD-1 blockade. We hypothesized that the following immune markers would be positive predictors of response: increased densities of CD103 + CD8 + T cells or Th1 lineage T-bet + T cells, high expression of CXCL9-11 and presence of tertiary lymphoid structures. Conversely, we hypothesized that the high expression of barrier molecules would be a negative predictor of response. Patients with advanced melanoma treated with pembrolizumab were identified, and clinical response as well as overall survival data were collected. Tumor samples were evaluated by multiplex immunofluorescence histology. All statistical analyses were performed in R Studio and Microsoft Excel using the Mann-Whitney U test, chi-square test, Spearman's rank correlation and Kaplan-Meier survival curves. Sixty-five advanced melanoma patients were identified, of whom 46 met inclusion criteria and were included in this study. Increased densities ( P  = 0.04) and proportions ( P  = 0.02) of CD8 + T cells expressing CD103 + were associated with complete response (CR) to pembrolizumab. Improved survival was associated with increased proportions of CD8 + cells expressing CD103 ( P  = 0.0085) as well as decreased density of periplakin + cells ( P  = 0.012) and periplakin + SOX10 + cells ( P  = 0.0012). The density and proportion of CD8 + T cells expressing CD103 + positively correlated with PD-L1 expression, though PD-L1 expression was not significantly correlated with outcomes. This screening study found that increased density and proportion of CD8 + T cells expressing CD103 and decreased density of periplakin were associated with positive outcomes in patients with melanoma metastases treated with pembrolizumab and may warrant further study.

The immune landscape of solid pediatric tumors

Background

Large immunogenomic analyses have demonstrated the prognostic role of the functional orientation of the tumor microenvironment in adult solid tumors, this variable has been poorly explored in the pediatric counterpart.

Methods

We performed a systematic analysis of public RNAseq data (TARGET) for five pediatric tumor types (408 patients): Wilms tumor (WLM), neuroblastoma (NBL), osteosarcoma (OS), clear cell sarcoma of the kidney (CCSK) and rhabdoid tumor of the kidney (RT). We assessed the performance of the Immunologic Constant of Rejection (ICR), which captures an active Th1/cytotoxic response. We also performed gene set enrichment analysis (ssGSEA) and clustered more than 100 well characterized immune traits to define immune subtypes and compared their outcome.

Results

A higher ICR score was associated with better survival in OS and high risk NBL without MYCN amplification but with poorer survival in WLM. Clustering of immune traits revealed the same five principal modules previously described in adult tumors (TCGA). These modules divided pediatric patients into six immune subtypes (S1-S6) with distinct survival outcomes. The S2 cluster showed the best overall survival, characterized by low enrichment of the wound healing signature, high Th1, and low Th2 infiltration, while the reverse was observed in S4. Upregulation of the WNT/Beta-catenin pathway was associated with unfavorable outcomes and decreased T-cell infiltration in OS.

Conclusions

We demonstrated that extracranial pediatric tumors could be classified according to their immune disposition, unveiling similarities with adults’ tumors. Immunological parameters might be explored to refine diagnostic and prognostic biomarkers and to identify potential immune-responsive tumors.

FOXA1 repression drives lineage plasticity and immune heterogeneity in bladder cancers with squamous differentiation

Cancers arising from the bladder urothelium often exhibit lineage plasticity with regions of urothelial carcinoma adjacent to or admixed with regions of divergent histomorphology, most commonly squamous differentiation. To define the biologic basis for and clinical significance of this morphologic heterogeneity, here we perform integrated genomic analyses of mixed histology bladder cancers with separable regions of urothelial and squamous differentiation. We find that squamous differentiation is a marker of intratumoral genomic and immunologic heterogeneity in patients with bladder cancer and a biomarker of intrinsic immunotherapy resistance. Phylogenetic analysis confirms that in all cases the urothelial and squamous regions are derived from a common shared precursor. Despite the presence of marked genomic heterogeneity between co-existent urothelial and squamous differentiated regions, no recurrent genomic alteration exclusive to the urothelial or squamous morphologies is identified. Rather, lineage plasticity in bladder cancers with squamous differentiation is associated with loss of expression of FOXA1, GATA3, and PPARG, transcription factors critical for maintenance of urothelial cell identity. Of clinical significance, lineage plasticity and PD-L1 expression is coordinately dysregulated via FOXA1, with patients exhibiting morphologic heterogeneity pre-treatment significantly less likely to respond to immune checkpoint inhibitors.

Analysis of prognostic oncogene filaggrin (FLG) wild-type subtype and its implications for immune checkpoint blockade therapy in bladder urothelial carcinoma

BACKGROUND

Bladder urothelial carcinoma (BLCA) is one of the most common urinary tract malignant tumors. Immune checkpoint blockade (ICB) therapy has significantly progressed the treatment of BLCA. This study aimed to investigate the role of specific genetic mutations that may serve as immune biomarkers for ICB therapy in BLCA.

METHODS

Mutation information and expression profiles were acquired from The Cancer Genome Atlas (TCGA) database. Integrated bioinformatics analysis was carried out to explore the subtypes with poor prognosis of BLCA. Functional enrichment analysis was also conducted. The infiltrating immune cells and the prediction of ICB response between different subtypes were explored using the immuCellAI algorithm. Cell Counting Kit-8 (CCK-8) and flow cytometry assays were conducted to explore the effect of filaggrin (FLG) knockdown in BLCA 5637 and T24 cell lines.

RESULTS

An overview of mutation information in BLCA patients was shown. FLG was identified to be strongly associated with the prognosis of BLCA patients and FLG wild-type was associated with poorer outcome. Prognostic FLG wild-type was divided into 2 subtypes (Sub1 and Sub2). Following an investigation of the subtypes, Sub2 of FLG wild-type was found to be associated with poorer outcome in BLCA. The differentially expressed genes (DEGs) between Sub1 and Sub2 were screened out and the DEGs were enriched in malignant tumor proliferation, DNA damage repair, and immune-related pathways. Furthermore, Sub2 of FLG wild-type was associated with infiltrated immune cells, and responded worse to ICB. Sub2 of FLG wild-type may be used as a biomarker to predict the prognosis of BLCA patients receiving ICB. The cellular experiments revealed that knockdown of FLG could suppress BLCA cell proliferation and promote apoptosis.

CONCLUSIONS

FLG is an oncogene that may affect the prognosis of BLCA patients through mutation. Sub2 of FLG wild-type is associated with poor prognosis and can be used to predict ICB response for BLCA treatment. This research provides a new basis and ideas for guiding the clinical application of BLCA immunotherapy.

Targeting the extra domain A of fibronectin for cancer therapy with CAR-T cells

BACKGROUND

One of the main difficulties of adoptive cell therapies with chimeric antigen receptor (CAR)-T cells in solid tumors is the identification of specific target antigens. The tumor microenvironment can present suitable antigens for CAR design, even though they are not expressed by the tumor cells. We have generated a CAR specific for the splice variant extra domain A (EDA) of fibronectin, which is highly expressed in the tumor stroma of many types of tumors but not in healthy tissues.

METHODS

EDA expression was explored in RNA-seq data from different human tumor types and by immunohistochemistry in paraffin-embedded tumor biopsies. Murine and human anti-EDA CAR-T cells were prepared using recombinant retro/lentiviruses, respectively. The functionality of EDA CAR-T cells was measured in vitro in response to antigen stimulation. The antitumor activity of EDA CAR-T cells was measured in vivo in C57BL/6 mice challenged with PM299L-EDA hepatocarcinoma cell line, in 129Sv mice-bearing F9 teratocarcinoma and in NSG mice injected with the human hepatocarcinoma cell line PLC.

RESULTS

EDA CAR-T cells recognized and killed EDA-expressing tumor cell lines in vitro and rejected EDA-expressing tumors in immunocompetent mice. Notably, EDA CAR-T cells showed an antitumor effect in mice injected with EDA-negative tumor cells lines when the tumor stroma or the basement membrane of tumor endothelial cells express EDA. Thus, EDA CAR-T administration delayed tumor growth in immunocompetent 129Sv mice challenged with teratocarcinoma cell line F9. EDA CAR-T treatment exerted an antiangiogenic effect and significantly reduced gene signatures associated with epithelial-mesenchymal transition, collagen synthesis, extracellular matrix organization as well as IL-6-STAT5 and KRAS pathways. Importantly, the human version of EDA CAR, that includes the human 41BB and CD3ζ endodomains, exerted strong antitumor activity in NSG mice challenged with the human hepatocarcinoma cell line PLC, which expresses EDA in the tumor stroma and the endothelial vasculature. EDA CAR-T cells exhibited a tropism for EDA-expressing tumor tissue and no toxicity was observed in tumor bearing or in healthy mice.

CONCLUSIONS

These results suggest that targeting the tumor-specific fibronectin splice variant EDA with CAR-T cells is feasible and offers a therapeutic option that is applicable to different types of cancer.

Proteomic analysis reveals key differences between squamous cell carcinomas and adenocarcinomas across multiple tissues

Squamous cell carcinoma (SCC) and adenocarcinoma (AC) are two main histological subtypes of solid cancer; however, SCCs are derived from different organs with similar morphologies, and it is challenging to distinguish the origin of metastatic SCCs. Here we report a deep proteomic analysis of 333 SCCs of 17 organs and 69 ACs of 7 organs. Proteomic comparison between SCCs and ACs identifies distinguishable pivotal pathways and molecules in those pathways play consistent adverse or opposite prognostic roles in ACs and SCCs. A comparison between common and rare SCCs highlights lipid metabolism may reinforce the malignancy of rare SCCs. Proteomic clusters reveal anatomical features, and kinase-transcription factor networks indicate differential SCC characteristics, while immune subtyping reveals diverse tumor microenvironments across and within diagnoses and identified potential druggable targets. Furthermore, tumor-specific proteins provide candidates with differentially diagnostic values. This proteomics architecture represents a public resource for researchers seeking a better understanding of SCCs and ACs.

Squamous cell carcinomas are an aggressive cancer type which can occur in multiple organ systems. Here, the authors analyse the proteome of SCC cancers from 17 organs and show commonly dysregulated proteins independent of location.

Genomic and immunological profiles of small-cell lung cancer between East Asians and Caucasian

The characterization of immunological and genomic differences in small-cell lung cancer (SCLC) between East Asian (EA) and Caucasian patients can reveal important clinical therapies for EA patients with SCLC. By sequencing and analyzing a molecular and immunological dataset of 98-SCLC patients of EA ancestry, immunogenicity, including DNA damage repair alterations and tumor mutation burden (TMB), was found to be significantly higher in the EA cohort than in the Caucasian cohort. The epithelial-mesenchymal transition (EMT) was the signaling signature with the predominant frequency of mutations across all patients in the EA cohort. Analysis of tumor-infiltrated immune cells revealed that resting lymphocytes were significantly enriched in the EA cohort. Compound-targeting analysis showed that topoisomerase inhibitors might be capable of targeting TP53 and RB1 comutations in EA SCLC patients. EA SCLC patients who harbored COL6A6 mutations had poor survival, while Caucasian SCLC patients with OTOF, ANKRD30B, and TECPR2 mutations were identified to have a shorter survival.

Identification of Potential Core Genes Between Primary and Metastatic Malignant Melanoma and Analysis of Their Immune Correlation

Purpose

To identify the potential differential genes between primary and metastatic melanoma, screen out immune-related genes in core genes and analyze their immune correlation, thus searching for the early diagnostic biomarkers of cutaneous malignant melanoma (CMM) and the targets of curbing metastasis.

Materials and Methods

We analyzed two microarray datasets (GSE8401 and GSE46517) derived from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between primary and metastatic melanoma were screened out using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to identify the functions and pathways of DEGs. We analyzed protein–protein interaction of these DEGs based on the Search Tool for the Retrieval of Interacting Genes database and showed by Cytoscape software. In addition, the online Gene Expression Profiling Interactive Analysis tool (GEPIA) was used to analyze the prognostic value of hub genes expressed in metastatic melanoma patients. Immune-related genes in hub genes were screened and further analyzed.

Results

A total of 178 upregulated DEGs and 4 downregulated DEGs were identified. 23 terms and 4 pathways were confirmed related to metastatic melanoma. Ten hub genes with a high degree of connectivity were found. Overexpression of three hub genes (DSG1, FLG, PKP1) (P<0.01) was associated with metastasis and poor prognosis of CMM. Among them, the patients with overexpression of PKP1 suffered shorter survival. In addition, 2 immune-related genes (EGFR and CDH1) in hub genes were screened out and both of them were related to anti-tumor immunity, although their expression level did not affect the overall survival of CMM patients significantly.

Conclusion

Our study suggests that DSG1, FLG and PKP1 were overexpressed in metastatic melanoma compared with primary melanoma, and overexpression of these three genes was an unfavorable prognostic factor ifor CMM patients, which may indicate that they are associated with promoting metastasis of malignant melanoma. EGFR and CDH1 play a crucial role in anti-tumor immunity for CMM. Further research is needed to explore the value of these genes in the inhibition of metastasis and treatment of CMM.

Identification of Keratinocyte Differentiation-Involved Genes for Metastatic Melanoma by Gene Expression Profiles

Background

Melanoma is the deadliest type of skin cancer. Until now, its pathological mechanisms, particularly the mechanism of metastasis, remain largely unknown. Our study on the identification of genes in association with metastasis for melanoma provides a novel understanding of melanoma.

Methods

From the Gene Expression Omnibus (GEO) database, the gene expression microarray datasets GSE46517, GSE7553, and GSE8401 were downloaded. We made use of R aiming at analyzing the differentially expressed genes (DEGs) between metastatic and nonmetastatic melanoma. R was also used in differentially expressed miRNA (DEM) data mining from GSE18509, GSE19387, GSE24996, GSE34460, GSE35579, GSE36236, and GSE54492 datasets referring to Li's study. Based on the DEG and DEM data, we performed functional enrichment analysis through the application of the DAVID database. Furthermore, we constructed the protein-protein interaction (PPI) network and established functional modules by making use of the STRING database. Through making use of Cytoscape, the PPI results were visualized. We predicted the targets of the DEMs through applying TargetScan, miRanda, and PITA databases and identified the overlapping genes between DEGs and predicted targets, followed by the construction of DEM-DEG pair network. The expressions of these keratinocyte differentiation-involved genes in Module 1 were identified based on the data from TCGA.

Results

239 DEGs were screened out in all 3 datasets, which were inclusive of 21 positively regulated genes and 218 negatively regulated genes. Based on these 239 DEGs, we finished constructing the PPI network which was formed from 225 nodes and 846 edges. We finished establishing 3 functional modules. And we analyzed 92 overlapping genes and 26 miRNA, including 11 upregulated genes targeted by 11 negatively regulated DEMs and 81 downregulated genes targeted by 15 positively regulated DEMs. As proof of the differential expression of metastasis-associated genes, eleven keratinocyte differentiation-involved genes, including LOR, EVPL, SPRR1A, FLG, SPRR1B, SPRR2B, TGM1, DSP, CSTA, CDSN, and IVL in Module 1, were obviously downregulated in metastatic melanoma tissue in comparison with primary melanoma tissue based on the data from TCGA.

Conclusion

239 melanoma metastasis-associated genes and 26 differentially expressed miRNA were identified in our study. The keratinocyte differentiation-involved genes may take part in melanoma metastasis, providing a latent molecular mechanism for this disease.

Improving the therapeutic index in adoptive cell therapy: key factors that impact efficacy

The therapeutic index (TI) is a quantitative assessment of a drug safety proportional to its effectiveness. The estimation is intuitive when the engagement of the product with its target is dependent on stable chemistry and predictable pharmacokinetics as is the case for small molecules or antibodies. But for therapeutics with complex biodistribution and context-dependent potency such as adoptive cell therapy (ACT) products, TI estimations need to consider a broader array of factors. These include product-dependent variability such as functional fitness, unpredictable pharmacokinetics due to non-specific trapping, sequestration and extravasation into normal tissues and variable rates of in vivo expansion. In the case of solid malignancies, additional modifiers dependent on individual tumor immune biology may affect pharmacodynamics, including differential trafficking to benign compared with cancer tissue, hampered engagement with target cells, immune suppression and cellular dysfunction due to unfavorable metabolic conditions. Here, we propose a patient-specific assessment of factors affecting on-tumor from off-tumor activity in disparate immunologic environments that impact ACT’s clinical efficacy and may favorably balance the TI. for ACT products.

Pulmonary Neuroendocrine Neoplasms Overexpressing Epithelial-Mesenchymal Transition Mechanical Barriers Genes Lack Immune-Suppressive Response and Present an Increased Risk of Metastasis

Typical carcinoids (TC), atypical carcinoids (AC), large cell neuroendocrine carcinomas (LCNEC), and small cell lung carcinomas (SCLC) encompass a bimodal spectrum of metastatic tumors with morphological, histological and histogenesis differences, The hierarchical structure reveals high cohesiveness between neoplastic cells by mechanical desmosomes barrier assembly in carcinoid tumors and LCNEC, while SCLC does not present an organoid arrangement in morphology, the neoplastic cells are less cohesive. However, the molecular mechanisms that lead to PNENs metastasis remain largely unknown and require further study. In this work, epithelial to mesenchymal transition (EMT) transcription factors were evaluated using a set of twenty-four patients with surgically resected PNENs, including carcinomas. Twelve EMT transcription factors (BMP1, BMP7, CALD1, CDH1, COL3A1, COL5A2, EGFR, ERBB3, PLEK2, SNAI2, STEAP1, and TCF4) proved to be highly expressed among carcinomas and downregulated in carcinoid tumors, whereas upregulation of BMP1, CDH2, KRT14 and downregulation of CAV2, DSC2, IL1RN occurred in both histological subtypes. These EMT transcription factors identified were involved in proliferative signals, epithelium desmosomes assembly, and cell motility sequential steps that support PNENs invasion and metastasis in localized surgically resected primary tumor. We used a two-stage design where we first examined the candidate EMT transcription factors using a whole-genome screen, and subsequently, confirmed EMT-like changes by transmission electron microscopy and then, the EMT-related genes that were differentially expressed among PNENs subtypes were predicted through a Metascape analysis by in silico approach. A high expression of these EMT transcription factors was significantly associated with lymph node and distant metastasis. The sequential steps for invasion and metastasis were completed by an inverse association between functional barrier created by PD-L1 immunosuppressive molecule and EMT transcriptional factors. Our study implicates upregulation of EMT transcription factors to high proliferation rates, mechanical molecular barriers disassembly and increased cancer cell motility, as a critical molecular event leading to metastasis risk in PNENs thus emerging as a promising tool to select and customize therapy.

TMT-Based Quantitative Proteomic Analysis Reveals the Effect of Bone Marrow Derived Mesenchymal Stem Cell on Hair Follicle Regeneration

Hair loss (HL) is a common chronic problem of poorly defined etiology. Herein, we explored the functionality of bone marrow-derived mesenchymal stem cell (BMSC) and conditioned medium (MSC-CM) as regulators of hair follicle proliferation and regeneration, and the mechanistic basis for such activity. BMSC were cultured and identified in vitro through the induction of multilineage differentiation and the use of a CCK-8 kit. The dorsal skin of mice was then injected with BMSC and MSC-CM, and the impact of these injections on hair cycle transition and hair follicle stem cell (HFSC) proliferation was then evaluated via hematoxylin and eosin (H&E) staining and immunofluorescent (IF) staining. We then conducted a tandem mass tags (TMT)-based quantitative proteomic analysis of control mice and mice treated with BMSC or MSC-CM to identify differentially expressed proteins (DEPs) associated with these treatments. Parallel reaction monitoring (PRM) was utilized as a means of verifying our proteomic analysis results. Herein, we found that BMSC and MSC-CM injection resulted in the transition of telogen hair follicles to anagen hair follicles, and we observed the enhanced proliferation of HFSCs positive for Krt15 and Sox9. Our TMT analyses identified 1,060 and 770 DEPs (fold change＞1.2 or＜0.83 and p ＜ 0.05) when comparing the BMSC vs. control and MSC-CM vs. control groups, respectively. Subsequent PRM validation of 14 selected DEPs confirmed these findings, and led to the identification of Stmn1, Ncapd2, Krt25, and Ctps1 as hub DEPs in a protein-protein interaction network. Together, these data suggest that BMSC and MSC-CM treatment can promote the proliferation of HFSCs, thereby facilitating hair follicle regeneration. Our proteomics analyses further indicate that Krt25, Cpm, Stmn1, and Mb may play central roles in hair follicle transition in this context and may represent viable clinical targets for the treatment of HL.

Molecular characteristics and tumorigenicity of ascites-derived tumor cells: mitochondrial oxidative phosphorylation as a novel therapy target in ovarian cancer

Ovarian cancer disseminates primarily intraperitoneally. Detached tumor cell aggregates (spheroids) from the primary tumor are regarded as ‘metastatic units’ that exhibit a low sensitivity to classical chemotherapy, probably due to their unique molecular characteristics. We have analyzed the cellular composition of ascites from OvCa patients, using flow cytometry, and studied their behavior in vitro and in vivo. We conclude that ascites‐derived cultured cells from OvCa patients give rise to two subpopulations: adherent cells and non‐adherent cells. Here, we found that the AD population includes mainly CD90⁺ cells with highly proliferative rates in vitro but no tumorigenic potential in vivo, whereas the NAD population contains principally tumor cell spheroids (EpCAM⁺/CD24⁺) with low proliferative potential in vitro. Enriched tumor cell spheroids from the ascites of high‐grade serous OvCA patients, obtained using cell strainers, were highly tumorigenic in vivo and their metastatic spread pattern precisely resembled the tumor dissemination pattern found in the corresponding patients. Comparative transcriptome analyses from ascites‐derived tumor cell spheroids (n = 10) versus tumor samples from different metastatic sites (n = 30) revealed upregulation of genes involved in chemoresistance (TGM1, HSPAs, MT1s), cell adhesion and cell‐barrier integrity (PKP3, CLDNs, PPL), and the oxidative phosphorylation process. Mitochondrial markers (mass and membrane potential) showed a reduced mitochondrial function in tumoroids from tumor tissue compared with ascites‐derived tumor spheroids in flow cytometry analysis. Interestingly, response to OXPHOS inhibition by metformin and IACS010759 in tumor spheroids correlated with the extent of mitochondrial membrane potential measured by fluorescence‐activated cell sorting. Our data contribute to a better understanding of the biology of ovarian cancer spheroids and identify the OXPHOS pathway as new potential treatment option in advanced ovarian cancer.

Ancestry-associated transcriptomic profiles of breast cancer in patients of African, Arab, and European ancestry

Breast cancer largely dominates the global cancer burden statistics; however, there are striking disparities in mortality rates across countries. While socioeconomic factors contribute to population-based differences in mortality, they do not fully explain disparity among women of African ancestry (AA) and Arab ancestry (ArA) compared to women of European ancestry (EA). In this study, we sought to identify molecular differences that could provide insight into the biology of ancestry-associated disparities in clinical outcomes. We applied a unique approach that combines the use of curated survival data from The Cancer Genome Atlas (TCGA) Pan-Cancer clinical data resource, improved single-nucleotide polymorphism-based inferred ancestry assignment, and a novel breast cancer subtype classification to interrogate the TCGA and a local Arab breast cancer dataset. We observed an enrichment of BasalMyo tumors in AA patients (38 vs 16.5% in EA, p = 1.30E - 10), associated with a significant worse overall (hazard ratio (HR) = 2.39, p = 0.02) and disease-specific survival (HR = 2.57, p = 0.03). Gene set enrichment analysis of BasalMyo AA and EA samples revealed differences in the abundance of T-regulatory and T-helper type 2 cells, and enrichment of cancer-related pathways with prognostic implications (AA: PI3K-Akt-mTOR and ErbB signaling; EA: EGF, estrogen-dependent and DNA repair signaling). Strikingly, AMPK signaling was associated with opposing prognostic connotation (AA: 10-year HR = 2.79, EA: 10-year HR = 0.34). Analysis of ArA patients suggests enrichment of BasalMyo tumors with a trend for differential enrichment of T-regulatory cells and AMPK signaling. Together, our findings suggest that the disparity in the clinical outcome of AA breast cancer patients is likely related to differences in cancer-related and microenvironmental features.

Next Generation Imaging Techniques to Define Immune Topographies in Solid Tumors

In recent years, cancer immunotherapy experienced remarkable developments and it is nowadays considered a promising therapeutic frontier against many types of cancer, especially hematological malignancies. However, in most types of solid tumors, immunotherapy efficacy is modest, partly because of the limited accessibility of lymphocytes to the tumor core. This immune exclusion is mediated by a variety of physical, functional and dynamic barriers, which play a role in shaping the immune infiltrate in the tumor microenvironment. At present there is no unified and integrated understanding about the role played by different postulated models of immune exclusion in human solid tumors. Systematically mapping immune landscapes or "topographies" in cancers of different histology is of pivotal importance to characterize spatial and temporal distribution of lymphocytes in the tumor microenvironment, providing insights into mechanisms of immune exclusion. Spatially mapping immune cells also provides quantitative information, which could be informative in clinical settings, for example for the discovery of new biomarkers that could guide the design of patient-specific immunotherapies. In this review, we aim to summarize current standard and next generation approaches to define Cancer Immune Topographies based on published studies and propose future perspectives.

Hypoxia and the phenomenon of immune exclusion

Over the last few years, cancer immunotherapy experienced tremendous developments and it is nowadays considered a promising strategy against many types of cancer. However, the exclusion of lymphocytes from the tumor nest is a common phenomenon that limits the efficiency of immunotherapy in solid tumors. Despite several mechanisms proposed during the years to explain the immune excluded phenotype, at present, there is no integrated understanding about the role played by different models of immune exclusion in human cancers. Hypoxia is a hallmark of most solid tumors and, being a multifaceted and complex condition, shapes in a unique way the tumor microenvironment, affecting gene transcription and chromatin remodeling. In this review, we speculate about an upstream role for hypoxia as a common biological determinant of immune exclusion in solid tumors. We also discuss the current state of ex vivo and in vivo imaging of hypoxic determinants in relation to T cell distribution that could mechanisms of immune exclusion and discover functional-morphological tumor features that could support clinical monitoring.

Identification of lncRNA-mRNA Regulatory Module to Explore the Pathogenesis and Prognosis of Melanoma

Skin cutaneous melanoma (SKCM) is an aggressive form of skin cancer that results in high mortality rate worldwide. It is vital to discover effective prognostic biomarkers and therapeutic targets for the treatment of melanoma. Long non-coding RNA (lncRNA) has been verified to play an essential role in the regulation of gene expression in diseases and tumors. Therefore, it is significant to explore the function of lncRNAs in the development and progression of SKCM. In this paper, a set of differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were first screened out using 471 cutaneous melanoma samples and 813 normal skin samples. Gene Ontology and KEGG pathway enrichment analysis were performed to obtain the significant function annotations and pathways of DEmRNAs. We also ran survival analysis on both DElncRNAs and DEmRNAs to identify prognostic-related lncRNAs and mRNAs. Next, a set of hub genes derived from protein-protein interaction (PPI) network analysis and lncRNA target genes screened from starbase-ENCORI database were integrated to construct a lncRNA-mRNA regulatory module, which includes 6 lncRNAs 4 target mRNAs. We further checked the capacity of these lncRNA and mRNA in the diagnosis of melanoma, and found that single lncRNA can effectively distinguish tumor and normal tissue. Moreover, we ran CMap analysis to select a list of small molecule drugs for SKCM, such as EGFR inhibitor AG-490, growth factor receptor inhibitor GW-441756 and apoptosis stimulant betulinic-acid, which have shown therapeutic effect in the treatment of melanoma.

Trop2: Jack of All Trades, Master of None

Trophoblast cell surface antigen 2 (Trop2) is a widely expressed glycoprotein and an epithelial cell adhesion molecule (EpCAM) family member. Although initially identified as a transmembrane protein, other subcellular localizations and processed forms were described. Its congenital mutations cause a gelatinous drop-like corneal dystrophy, a disease characterized by loss of barrier function in corneal epithelial cells. Trop2 is considered a stem cell marker and its expression associates with regenerative capacity in various tissues. Trop2 overexpression was described in tumors of different origins; however, functional studies revealed both oncogenic and tumor suppressor roles. Nevertheless, therapeutic potential of Trop2 was recognized and clinical studies with drug-antibody conjugates have been initiated in various cancer types. One of these agents, sacituzumab govitecan, has been recently granted an accelerated approval for therapy of metastatic triple-negative breast cancer. In this article, we review the current knowledge about the yet controversial function of Trop2 in homeostasis and pathology.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

DeepSurvNet: deep survival convolutional network for brain cancer survival rate classification based on histopathological images

Histopathological whole slide images of haematoxylin and eosin (H&E)-stained biopsies contain valuable information with relation to cancer disease and its clinical outcomes. Still, there are no highly accurate automated methods to correlate histolopathological images with brain cancer patients' survival, which can help in scheduling patients therapeutic treatment and allocate time for preclinical studies to guide personalized treatments. We now propose a new classifier, namely, DeepSurvNet powered by deep convolutional neural networks, to accurately classify in 4 classes brain cancer patients' survival rate based on histopathological images (class I, 0-6 months; class II, 6-12 months; class III, 12-24 months; and class IV, >24 months survival after diagnosis). After training and testing of DeepSurvNet model on a public brain cancer dataset, The Cancer Genome Atlas, we have generalized it using independent testing on unseen samples. Using DeepSurvNet, we obtained precisions of 0.99 and 0.8 in the testing phases on the mentioned datasets, respectively, which shows DeepSurvNet is a reliable classifier for brain cancer patients' survival rate classification based on histopathological images. Finally, analysis of the frequency of mutations revealed differences in terms of frequency and type of genes associated to each class, supporting the idea of a different genetic fingerprint associated to patient survival. We conclude that DeepSurvNet constitutes a new artificial intelligence tool to assess the survival rate in brain cancer. Graphical abstract A DCNN model was generated to accurately predict survival rates of brain cancer patients (classified in 4 different classes) accurately. After training the model using images from H&E stained tissue biopsies from The Cancer Genome Atlas database (TCGA, left), the model can predict for each patient, based on a histological image (top right), its survival class accurately (bottom right).

High-risk Stage III colon cancer patients identified by a novel five-gene mutational signature are characterized by upregulation of IL-23A and gut bacterial translocation of the tumor microenvironment

The heterogeneities of colorectal cancer (CRC) lead to staging inadequately of patients' prognosis. Here, we performed a prognostic analysis based on the tumor mutational profile and explored the characteristics of the high-risk tumors. We sequenced 338 colorectal carcinomas as the training dataset, constructed a novel five-gene (SMAD4, MUC16, COL6A3, FLG and LRP1B) prognostic signature, and validated it in an independent dataset from The Cancer Genome Atlas (TCGA). Kaplan-Meier and Cox regression analyses confirmed that the five-gene signature is an independent predictor of recurrence and prognosis in patients with Stage III colon cancer. The mutant signature translated to an increased risk of death (hazard ratio = 2.45, 95% confidence interval = 1.15-5.22, p = 0.016 in our dataset; hazard ratio = 4.78, 95% confidence interval = 1.33-17.16, p = 0.008 in TCGA dataset). RNA and bacterial 16S rRNA sequencing of high-risk tumors indicated that mutations of the five-gene signature may lead to intestinal barrier integrity, translocation of gut bacteria and deregulation of immune response and extracellular related genes. The high-risk tumors overexpressed IL23A and IL1RN genes and enriched with cancer-related bacteria (Bacteroides fragilis,Peptostreptococcus, Parvimonas, Alloprevotella and Gemella) compared to the low-risk tumors. The signature identified the high-risk group characterized by gut bacterial translocation and upregulation of interleukins of the tumor microenvironment, which was worth further researching.

Oncogenic states dictate the prognostic and predictive connotations of intratumoral immune response

BACKGROUND

An immune active cancer phenotype typified by a T helper 1 (Th-1) immune response has been associated with increased responsiveness to immunotherapy and favorable prognosis in some but not all cancer types. The reason of this differential prognostic connotation remains unknown.

METHODS

To explore the contextual prognostic value of cancer immune phenotypes, we applied a multimodal pan-cancer analysis among 31 different histologies (9282 patients), encompassing immune and oncogenic transcriptomic analysis, mutational and neoantigen load and copy number variations.

RESULTS

We demonstrated that the favorable prognostic connotation conferred by the presence of a Th-1 immune response was abolished in tumors displaying specific tumor-cell intrinsic attributes such as high transforming growth factor-beta (TGF-β) signaling and low proliferation capacity. This observation was independent of mutation rate. We validated this observation in the context of immune checkpoint inhibition. WNT-β catenin, barrier molecules, Notch, hedgehog, mismatch repair, telomerase activity and AMPK signaling were the pathways most coherently associated with an immune silent phenotype together with mutations of driver genes including IDH1/2, FOXA2, HDAC3, PSIP1, MAP3K1, KRAS, NRAS, EGFR, FGFR3, WNT5A and IRF7.

CONCLUSIONS

This is the first systematic study demonstrating that the prognostic and predictive role of a bona fide favorable intratumoral immune response is dependent on the disposition of specific oncogenic pathways. This information could be used to refine stratification algorithms and prioritize hierarchically relevant targets for combination therapies.

The Biology of Immune-Active Cancers and Their Regulatory Mechanisms

The development of cancer results from the evolutionary balance between the proliferating aptitude of cancer cells and the response of the host's tissues. Some cancers are characterized by genetic instability dependent upon impaired DNA repair mechanisms that lead to the chaotic disruption of multiple cellular functions often in excess of the cancer survival needs and may exert broad effects on surrounding tissues, some beneficial and some detrimental to cancer growth. Among them, inflammatory processes that accompany wound healing may initiate a reaction of the host against the neo-formation. This is possibly triggered by the release by dying cancer cells of molecules known as Damage-Associated Molecular Patterns (DAMPs) following a process termed Immunogenic Cell Death (ICD) that initiates an immune response through innate and adaptive mechanisms. Indeed, analysis of large cancer data sets has shown that ICD is strictly associated with the activation of other immune effector or immune-regulatory pathways. Here, we will describe how immune activation and compensatory immune-regulatory mechanisms balance anti-cancer immune surveillance and the roles that innate and adaptive immunity play including the weight that neo-epitopes may exert as initiators and sculptors of high-affinity memory and effector immune responses against cancer. We will discuss the evolutionary basis for the existence of immune checkpoints and how several theories raised to explain cancer resistance to immunotherapy represent a facet of a similar evolutionary phenomenon that we described in the Theory of Everything. We will show how the biology of immunogenicity and counterbalancing immune regulation is widespread across cancers independent of their ontogenesis while subtle idiosyncratic differences are discernible among them. Finally, we will suggest that overcoming immune resistance implies distinct approaches relevant to the immune context of individual cancers.

The Barrier Molecules Junction Plakoglobin, Filaggrin, and Dystonin Play Roles in Melanoma Growth and Angiogenesis

OBJECTIVE

To understand role of barrier molecules in melanomas.

BACKGROUND

We have reported poor patient survival and low immune infiltration of melanomas that overexpress a set of genes that include filaggrin (FLG), dystonin (DST), junction plakoglobin (JUP), and plakophilin-3 (PKP3), and are involved in cell-cell adhesions. We hypothesized that these associations are causal, either by interfering with immune cell infiltration or by enhancing melanoma cell growth.

METHODS

FLG and DST were knocked out by CRISPR/Cas9 in human DM93 and murine B16-F1 melanoma cells. PKP3 and JUP were overexpressed in murine B16-AAD and human VMM39 melanoma cells by lentiviral transduction. These cell lines were evaluated in vitro for cell proliferation and in vivo for tumor burden, immune composition, cytokine expression, and vascularity.

RESULTS

Immune infiltrates were not altered by these genes. FLG/DST knockout reduced proliferation of human DM93 melanoma in vitro, and decreased B16-F1 tumor burden in vivo. Overexpression of JUP, but not PKP3, in B16-AAD significantly increased tumor burden, increased VEGF-A, reduced IL-33, and enhanced vascularity.

CONCLUSIONS

FLG and DST support melanoma cell growth in vitro and in vivo. Growth effects of JUP were only evident in vivo, and may be mediated, in part, by enhancing angiogenesis. In addition, growth-promoting effects of FLG and DST in vitro suggest that these genes may also support melanoma cell proliferation through angiogenesis-independent pathways. These findings identify FLG, DST, and JUP as novel therapeutic targets whose down-regulation may provide clinical benefit to patients with melanoma.

Status of Immune Oncology: Challenges and Opportunities

This volume is intended to review the methods used to identify biomarkers predictive of cancer responsiveness to immunotherapy. The successful development of clinically actionable biomarkers depends upon three features: (a) their biological role with respect to malignant transformation and tumor progression; (b) the ability to detect them with robust, reliable, and clinically applicable assays; and (c) their prognostic or predictive value, as validated in clinical trials.Identifying biomarkers that have predictive value for patient selection based on the likelihood of benefiting from anticancer immunotherapy is a lengthy and complex process. To date, few predictive biomarkers for anticancer immunotherapy have been robustly analytically and clinically validated (i.e., PD-L1 expression as measured by IHC assays and microsatellite instability (MSI)/dMMR as measured by PCR or IHC, respectively).This introductory chapter to this book focuses on scientific and technical aspects relevant to the identification and validation of predictive biomarkers for immunotherapy. We emphasize that methods should address both the biology of the tumor and the tumor microenvironment. Moreover, the identification of biomarkers requires highly sensitive, multiplexed, comprehensive techniques, especially for application in clinical care. Thus, in this chapter, we will define the outstanding questions related to the immune biology of cancer as a base for development of the biomarkers and assays using diverse methodologies. These biomarkers will likely be identified through research that integrates conventional immunological approaches along with high-throughput genomic and proteomic screening and the host immune response of individual patients that relates to individual tumor biology and immune drugs' mechanism of action.Checkpoint inhibitor therapy (CIT) is by now an accepted modality of cancer treatment. However, immune resistance is common, and most patients do not benefit from the treatment. The reasons for resistance are diverse, and approaches to circumvent it need to consider genetic, biologic, and environmental factors that affect anticancer immune response. Here, we propose to systematically address fundamental concepts based on the premise that malignant cells orchestrate their surroundings by interacting with innate and adaptive immune sensors. This principle applies to most cancers and governs their evolution in the immune-competent host. Understanding the basic requirement(s) for this evolutionary process will guide biomarker discovery and validation and ultimately guide to effective therapeutic choices. This volume will also discuss novel biomarker approaches aimed at informing an effective assay development from a mechanistic point of view, as well as the clinical implementation (i.e., patient enrichment) for immune therapies.

Multi-omics analysis of tumor mutational burden combined with prognostic assessment in epithelial ovarian cancer based on TCGA database

Background: Tumor mutation burden (TMB) is considered as a novel biomarker of response to immunotherapy and correlated with survival outcomes in various malignancies. Here, TMB-related genes (TRGs) expression signatures were constructed to investigate the association between TMB and prognosis in epithelial ovarian cancer (EOC), and the potential mechanism in immunoregulation was also explored. Methods: Based on somatic mutation data of 436 EOC samples from The Cancer Genome Atlas database, we examined the relationship between TMB level and overall survival (OS), as well as disease-free survival (DFS). Next, the TRGs signatures were constructed and validated. Differential abundance of immune cell infiltration, expression levels of immunomodulators and functional enrichment in high- and low-risk groups were also analyzed. Results: Higher TMB level revealed better OS and DFS, and correlated with earlier clinical stages in EOCs (P = 2.796e-04). The OS-related prognostic model constructed based on seven TRGs (B3GALT1, LIN7B, ANGPT2, D2HGDH, TAF13, PFDN4 and DNAJC19) significantly stratified EOC patients into high- and low-risk groups (P < 0.001). The AUC values of the seven-gene prognostic signature at 1 year, 3 years, and 5 years were 0.703, 0.758 and 0.777. While the DFS-related prognostic model was constructed based on the 4 TRGs (LPIN3, PXYLP1, IGSF23 and B3GALT1), with AUCs of 0.617, 0.756, and 0.731, respectively. Functional analysis indicated that immune-related pathways were enriched in low-risk groups. When considering the infiltration patterns of immune cells, we found higher proportions of follicular helper T (Tfh) cell and M1 macrophage, while lower infiltration of M0 macrophage in low-risk groups (P < 0.05). Accordingly, TMB levels of low-risk patients were significantly higher both in OS and DFS model (P < 0.01). Conclusions: Our TRGs-based models are reliable predictive tools for OS and DFS. High TMB may confer with an immunogenic microenvironment and predict favorable outcomes in EOCs.

The Paradox of Cancer Immune Exclusion: Immune Oncology Next Frontier

Checkpoint inhibitor therapy (CIT) has revolutionized cancer treatment but it has also reached a standstill when an absent dialog between cancer and immune cells makes it irrelevant. This occurs with high prevalence in the context of "immune silent" and, even perhaps, "immune-excluded" tumors. The latter are characterized by T cells restricted to the periphery of cancer nests. Since in either case T cells do not come in direct contact with most cancer cells, CIT rests immaterial. Adoptive cell therapy (ACT), may also be affected by limited access to antigen-bearing cancer cells. While lack of immunogenicity intuitively explains the immune silent phenotype, immune exclusion is perplexing. The presence of T cells at the periphery suggests that chemo-attraction recruits them and an immunogenic stimulus promotes their persistence. However, what stops the T cells from infiltrating the tumors' nests and reaching the germinal center (GC)? Possibly, a concentric gradient of increased chemo-repulsion or decreased chemo-attraction demarcates an abrupt "do not trespass" warning. Various hypotheses suggest physical or functional barriers but no definitive consensus exists over the weight that each plays in human cancers. On one hand, it could be hypothesized that the intrinsic biology of cancer cells may degenerate from a "cancer stem cell" (CSC)-like phenotype in the GC toward a progressively more immunogenic phenotype prone to immunogenic cell death (ICD) at the periphery. On the other hand, the intrinsic biology of the cancer cells may not change but it is the disorderly architecture of the tumor microenvironment (TME) that alters in a centripetal direction cancer cell metabolism, both directly and indirectly, the function of surrounding stromal cells. In this chapter, we examine whether the paradoxical exclusion of T cells from tumors may serve as a model to understand the requirements for tumor immune infiltration and, correspondingly, we put forth strategies to restore the dialog between immune cells and cancer to enhance the effectiveness of immune oncology (IO) approaches.

Systems analysis of barrier molecule and ARNT-related gene expression regulation in melanoma

Background: We have identified, in melanomas, a set of genes encoding proteins that mediate mechanical barrier function in normal skin (barrier molecule genes, BMGs) and whose overexpression is associated with decreased immune signatures and shorter patient survival. The most overexpressed of these, filaggrin (FLG), is expressed on chromosome 1q21.3, which also encodes genes of the epidermal differentiation complex (EDC). EDC genes may be regulated by the transcription factors (TFs) AHR and ARNT. We hypothesized that ARNT-related genes would be expressed concordantly with BMG and EDC genes, inversely associated with immune signatures, and enhanced by 1q21.3 copy gain. Methods: Gene expression data from human melanomas in the Cancer Genome Atlas (TCGA), and a validation GEO dataset were evaluated, with copy number profiles from TCGA. Expression of Th1 immune genes and BMG/EDCs at 1q21.3 was visualized using clustered copy number and mRNA profiles. Associations of clusters and 1q21.3 copy number with patient survival and mRNA expression were assessed using Kaplan Meier curves, log-rank tests, and Wilcoxon rank sum tests. Results: BMGs are concordantly expressed with EDC genes. Clustering divided tumors into 4 categories: (1) Immune^HI, (2) BMG/EDC^HI, (3) ARNT^HI, (4) Mixed. Both ARNT^HI and BMG/EDC^HI tumors had low immune signatures and significantly shortened survival. KLF4 and FOXF2 are putative TFs that may regulate these genes. Conclusions: ARNT^HI tumors may represent another subset of tumors, in addition to BMG/EDC^HI tumors, with barriers to immune infiltrates, likely with different mechanisms. These genes have prognostic significance and may be relevant targets for future therapy.

Integration of protein interaction and gene co-expression information for identification of melanoma candidate genes

Cutaneous melanoma is an aggressive form of skin cancer that causes death worldwide. Although much has been learned about the molecular basis of melanoma genesis and progression, there is also increasing appreciation for the continuing discovery of melanoma genes to improve the genetic understanding of this malignancy. In the present study, melanoma candidate genes were identified by analysis of the common network from cancer type-specific RNA-Seq co-expression data and protein-protein interaction profiles. Then, an integrated network containing the known melanoma-related genes represented as seed genes and the putative genes represented as linker genes was generated using the subnetwork extraction algorithm. According to the network topology property of the putative genes, we selected seven key genes (CREB1, XPO1, SP3, TNFRSF1B, CD40LG, UBR1, and ZNF484) as candidate genes of melanoma. Subsequent analysis showed that six of these genes are melanoma-associated genes and one (ZNF484) is a cancer-associated gene on the basis of the existing literature. A signature comprising these seven key genes was developed and an overall survival analysis of 461 cutaneous melanoma cases was carried out. This seven-gene signature can accurately determine the risk profile for cutaneous melanoma tumors (log-rank P=3.27E-05) and be validated on an independent clinical cohort (log-rank P=0.028). The presented seven genes might serve as candidates for studying the molecular mechanisms and help improve the prognostic risk assessment, which have clinical implications for melanoma patients.

Patterns of immune-cell infiltration in murine models of melanoma: roles of antigen and tissue site in creating inflamed tumors

Immune-cell infiltration is associated with improved survival in melanoma. Human melanoma metastases may be grouped into immunotypes representing patterns of immune-cell infiltration: A (sparse), B (perivascular cuffing), and C (diffuse). Immunotypes have not been defined for murine melanomas, but may provide opportunities to understand mechanism-driving immunotype differences. We performed immunohistochemistry with immune-cell enumeration, immunotyping, and vascular density scoring in genetically engineered (Braf/Pten and Braf/Pten/β-catenin) and transplantable (B16-F1, B16-OVA, and B16-AAD) murine melanomas. The transplantable tumors were grown in subcutaneous (s.c.) or intraperitoneal (i.p.) locations. Braf/Pten and Braf/Pten/β-catenin tumors had low immune-cell densities, defining them as Immunotype A, as did B16-F1 tumors. B16-OVA (s.c. and i.p.) and B16-AAD s.c. tumors were Immunotype B, while B16-AAD i.p. tumors were primarily Immunotype C. Interestingly, the i.p. location was characterized by higher immune-cell counts in B16-OVA tumors, with counts that trended higher for B16-F1 and B16-AAD. The i.p. location was also characterized by higher vascularity in B16-F1 and B16-AAD tumors. These findings demonstrate that spontaneously mutated neoantigens in B16 melanomas were insufficient to induce robust intratumoral immune-cell infiltrates, but instead were Immunotype A tumors. The addition of model neoantigens (OVA or AAD) to B16 enhanced infiltration, but this most often resulted in Immunotype B. We find that tumor location may be an important element in enabling Immunotype C tumors. In aggregate, these data suggest important roles both for the antigen type and for the tumor location in defining immunotypes.

Toward a comprehensive view of cancer immune responsiveness: a synopsis from the SITC workshop

Tumor immunology has changed the landscape of cancer treatment. Yet, not all patients benefit as cancer immune responsiveness (CIR) remains a limitation in a considerable proportion of cases. The multifactorial determinants of CIR include the genetic makeup of the patient, the genomic instability central to cancer development, the evolutionary emergence of cancer phenotypes under the influence of immune editing, and external modifiers such as demographics, environment, treatment potency, co-morbidities and cancer-independent alterations including immune homeostasis and polymorphisms in the major and minor histocompatibility molecules, cytokines, and chemokines. Based on the premise that cancer is fundamentally a disorder of the genes arising within a cell biologic process, whose deviations from normality determine the rules of engagement with the host's response, the Society for Immunotherapy of Cancer (SITC) convened a task force of experts from various disciplines including, immunology, oncology, biophysics, structural biology, molecular and cellular biology, genetics, and bioinformatics to address the complexity of CIR from a holistic view. The task force was launched by a workshop held in San Francisco on May 14-15, 2018 aimed at two preeminent goals: 1) to identify the fundamental questions related to CIR and 2) to create an interactive community of experts that could guide scientific and research priorities by forming a logical progression supported by multiple perspectives to uncover mechanisms of CIR. This workshop was a first step toward a second meeting where the focus would be to address the actionability of some of the questions identified by working groups. In this event, five working groups aimed at defining a path to test hypotheses according to their relevance to human cancer and identifying experimental models closest to human biology, which include: 1) Germline-Genetic, 2) Somatic-Genetic and 3) Genomic-Transcriptional contributions to CIR, 4) Determinant(s) of Immunogenic Cell Death that modulate CIR, and 5) Experimental Models that best represent CIR and its conversion to an immune responsive state. This manuscript summarizes the contributions from each group and should be considered as a first milestone in the path toward a more contemporary understanding of CIR. We appreciate that this effort is far from comprehensive and that other relevant aspects related to CIR such as the microbiome, the individual's recombined T cell and B cell receptors, and the metabolic status of cancer and immune cells were not fully included. These and other important factors will be included in future activities of the taskforce. The taskforce will focus on prioritization and specific actionable approach to answer the identified questions and implementing the collaborations in the follow-up workshop, which will be held in Houston on September 4-5, 2019.

PKP3 interactions with MAPK-JNK-ERK1/2-mTOR pathway regulates autophagy and invasion in ovarian cancer

Armadillo-related proteins function in both signal transduction and cell adhesion, it also plays a central role in tumorigenesis. Plakophilin 3 (PKP3) is a member of the armadillo protein family. PKP3 has demonstrated a role in melanoma, breast cancer, gastric cancer, and other kind of cancers; however its role in ovarian cancer was not fully understood. In this study we explored the function and mechanisms of PKP3 in ovarian cancer. An elevated level of PKP3 was found in ovarian cancer tissues compared with normal tissues. PKP3 also modulate cellular proliferation and invasion in ovarian cancer. The ability of cellular proliferation, formation, and invasion was significantly decreased after the silencing of PKP3 in SKOV3 cells. While an over-expression of PKP3 in A2780 cells up-regulates the ability of cellular proliferation, formation, and invasion. As for the mechanism of PKP3, mTOR pathway was activated to regulate autophagy according to the interaction of PKP3 with the upstream of MAPK pathway. The result of this study support PKP3 as the oncogene candidate and a potential target for the treatment of ovarian cancer.

Comparative molecular characterization of typical and exceptional responders in glioblastoma

Glioblastoma (GBM) is the most common and the deadliest type of primary brain tumor, with a median survival time of only 15 months despite aggressive treatment. Although most patients have an extremely poor prognosis, a relatively small number of patients survive far beyond the median survival time. Investigation of these exceptional responders has sparked a great deal of interest and is becoming an important focus in the field of cancer research. To investigate the molecular differences between typical and exceptional responders in GBM, comparative analyses of somatic mutations, copy number, methylation, and gene expression datasets from The Cancer Genome Atlas were performed, and the results of these analyses were integrated via gene ontology and pathway analyses to assess the functional significance of the differential aberrations. Less severe copy number loss of CDKN2A, lower expression of CXCL8, and FLG mutations are all associated with an exceptional response. Typical responders are characterized by upregulation of NF-κB signaling and of pro-inflammatory cytokines, while exceptional responders are characterized by upregulation of Alzheimer's and Parkinson's disease pathways as well as of genes involved in synaptic transmission. The upregulated pathways and processes in typical responders are consistently associated with more aggressive tumor phenotypes, while those in the exceptional responders suggest a retained ability in tumor cells to undergo cell death in response to treatment. With the upcoming launch of the National Cancer Institute's Exceptional Responders Initiative, similar studies with much larger sample sizes will likely become possible, hopefully providing even more insight into the molecular differences between typical and exceptional responders.

Immune oncology, immune responsiveness and the theory of everything

Anti-cancer immunotherapy is encountering its own checkpoint. Responses are dramatic and long lasting but occur in a subset of tumors and are largely dependent upon the pre-existing immune contexture of individual cancers. Available data suggest that three landscapes best define the cancer microenvironment: immune-active, immune-deserted and immune-excluded. This trichotomy is observable across most solid tumors (although the frequency of each landscape varies depending on tumor tissue of origin) and is associated with cancer prognosis and response to checkpoint inhibitor therapy (CIT). Various gene signatures (e.g. Immunological Constant of Rejection - ICR and Tumor Inflammation Signature - TIS) that delineate these landscapes have been described by different groups. In an effort to explain the mechanisms of cancer immune responsiveness or resistance to CIT, several models have been proposed that are loosely associated with the three landscapes. Here, we propose a strategy to integrate compelling data from various paradigms into a “Theory of Everything”. Founded upon this unified theory, we also propose the creation of a task force led by the Society for Immunotherapy of Cancer (SITC) aimed at systematically addressing salient questions relevant to cancer immune responsiveness and immune evasion. This multidisciplinary effort will encompass aspects of genetics, tumor cell biology, and immunology that are pertinent to the understanding of this multifaceted problem.

The heterogeneity of tumor-infiltrating CD8+ T cells in metastatic melanoma distorts their quantification: how to manage heterogeneity?

CD8 T-cell infiltration of metastatic melanoma may be a useful biomarker for prediction of prognosis and response to therapy. The heterogeneous distribution of CD8 T cells within a single tumor, and across different tumors within a single patient, may complicate quantification of infiltration. However, the impact of heterogeneity has not been quantified sufficiently. To address this, we have assessed intratumoral heterogeneity of CD8 T-cell counts, as well as intertumoral heterogeneity for synchronous and metachronous metastases. In a tissue microarray containing 189 melanoma metastases from 147 patients, the density of CD8 T cells per sample was determined by immunohistochemistry. The mean density and coefficient of variation were calculated for each tumor and the rates of discordant values were determined. CD8 counts varied widely among different core samples of the same tumors (average coefficient of variation=0.77, 95% confidence interval: 0.70-0.85), with discordance occurring in 40% of tumors. CD8 densities were similar among pairs of simultaneous tumors; however, significant changes in CD8 densities were observed among 35 pairs of metachronous tumors. CD8 T-cell density is not well represented by a single 1 mm diameter sample. Differences in CD8 T-cell counts, observed in clinical trials, from pretreatment to post-treatment specimens may be explained by the spatial and temporal heterogeneity of CD8 distribution, especially if the assessed samples are small (i.e. 1 mm). A sufficiently large biopsy of one of several synchronous tumors may be representative of CD8 T-cell infiltration of a patient's disease.

Overexpression of adhesion molecules and barrier molecules is associated with differential infiltration of immune cells in non-small cell lung cancer

Immunotherapy is emerging as a promising option for lung cancer treatment. Various endothelial adhesion molecules, such as integrin and selectin, as well as various cellular barrier molecules such as desmosome and tight junctions, regulate T-cell infiltration in the tumor microenvironment. However, little is known regarding how these molecules affect immune cells in patients with lung cancer. We demonstrated for the first time that overexpression of endothelial adhesion molecules and cellular barrier molecule genes was linked to differential infiltration of particular immune cells in non-small cell lung cancer. Overexpression of endothelial adhesion molecule genes is associated with significantly lower infiltration of activated CD4 and CD8 T-cells, but higher infiltration of activated B-cells and regulatory T-cells. In contrast, overexpression of desmosome genes was correlated with significantly higher infiltration of activated CD4 and CD8 T-cells, but lower infiltration of activated B-cells and regulatory T-cells in lung adenocarcinoma. This inverse relation of immune cells aligns with previous studies of tumor-infiltrating B-cells inhibiting T-cell activation. Although overexpression of endothelial adhesion molecule or cellular barrier molecule genes alone was not predictive of overall survival in our sample, these genetic signatures may serve as biomarkers of immune exclusion, or resistance to T-cell mediated immunotherapy.

Cancer immune resistance: can theories converge?

Immune oncology (IO) is challenged to expand its usefulness to a broader range of cancers. A second generation of IO agents acting beyond the realm of Checkpoint Inhibitor Therapy (CIT) is sought with the intent of turning immune-resistant cancers into appealing IO targets. The published literature proposes a profusion of models to explain cancer immune resistance to CIT that largely outnumber the immune landscapes and corresponding resistance mechanisms. In spite of the complex and contradicting models suggested to explain refractoriness to CIT, the identification of prevailing mechanisms and their targeting may not be as daunting as it at first appears. Here, we suggest that cancer cells go through a conserved evolutionary bottleneck facing a Two-Option Choice to evade recognition by the immune competent host: they can either adopt a clean oncogenic process devoid of immunogenic stimuli (immune-silent tumors) or display an entropic biology prone to immune recognition (immune-active tumors) but resilient to rejection thanks to the recruitment of compensatory immune suppressive processes. Strategies aimed at enhancing the effectiveness of CIT will be different according to the immune landscape targeted.

The MAPK hypothesis: immune-regulatory effects of MAPK-pathway genetic dysregulations and implications for breast cancer immunotherapy

With the advent of checkpoint inhibition, immunotherapy has revolutionized the clinical management of several cancers, but has demonstrated limited efficacy in mammary carcinoma. Transcriptomic profiling of cancer samples defined distinct immunophenotypic categories characterized by different prognostic and predictive connotations. In breast cancer, genomic alterations leading to the dysregulation of mitogen-activated protein kinase (MAPK) pathways have been linked to an immune-silent phenotype associated with poor outcome and treatment resistance. These aberrations include mutations of MAP3K1 and MAP2K4, amplification of KRAS, BRAF, and RAF1, and truncations of NF1. Anticancer therapies targeting MAPK signaling by BRAF and MEK inhibitors have demonstrated clear immunologic effects. These off-target properties could be exploited to convert the immune-silent tumor phenotype into an immune-active one. Preclinical evidence supports that MAPK-pathway inhibition can dramatically increase the efficacy of immunotherapy. In this review, we provide a detailed overview of the immunomodulatory impact of MAPK-pathway blockade through BRAF and MEK inhibitions. While BRAF inhibition might be relevant in melanoma only, MEK inhibition is potentially applicable to a wide range of tumors. Context-dependent similarities and differences of MAPK modulation will be dissected, in light of the complexity of the MAPK pathways. Therapeutic strategies combining the favorable effects of MAPK-oriented interventions on the tumor microenvironment while maintaining T-cell function will be presented. Finally, we will discuss recent studies highlighting the rationale for the implementation of MAPK-interference approaches in combination with checkpoint inhibitors and immune agonists in breast cancer.

Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab

The mechanisms by which immune checkpoint blockade modulates tumor evolution during therapy are unclear. We assessed genomic changes in tumors from 68 patients with advanced melanoma, who progressed on ipilimumab or were ipilimumab-naive, before and after nivolumab initiation (CA209-038 study). Tumors were analyzed by whole-exome, transcriptome, and/or T cell receptor (TCR) sequencing. In responding patients, mutation and neoantigen load were reduced from baseline, and analysis of intratumoral heterogeneity during therapy demonstrated differential clonal evolution within tumors and putative selection against neoantigenic mutations on-therapy. Transcriptome analyses before and during nivolumab therapy revealed increases in distinct immune cell subsets, activation of specific transcriptional networks, and upregulation of immune checkpoint genes that were more pronounced in patients with response. Temporal changes in intratumoral TCR repertoire revealed expansion of T cell clones in the setting of neoantigen loss. Comprehensive genomic profiling data in this study provide insight into nivolumab's mechanism of action.

Genome-wide analysis of DNA Methylation profiles on sheep ovaries associated with prolificacy using whole-genome Bisulfite sequencing

Background

Ovulation rate and litter size are important reproductive traits in sheep with high economic value. Recent work has revealed a potential link between DNA methylation and prolificacy. However, a genome-wide study that sought to identify potential DNA methylation sites involved in sheep prolificacy indicated that it is still unknown. Here, we aimed to investigate the genome-wide DNA methylation profiles of Hu sheep ovaries by comparing a high-prolificacy group (HP, litter size of three for at least 2 consecutive lambings) and low prolificacy group (LP, litter size of one for at least 2 consecutive lambings) using deep whole-genome bisulfite sequencing (WGBS).

Results

First, our results demonstrated lower expression levels of DNA methyltransferase (DNMT) genes in the ovaries of the HP group than that in the ovaries of the LP group. Both groups showed similar proportions of methylation at CpG sites but different proportions at non-CpG sites. Subsequently, we identified 70,899 differential methylated regions (DMRs) of CG, 16 DMRs of CHG, 356 DMRs of CHH and 12,832 DMR-related genes(DMGs). Gene Ontology (GO) analyses revealed that some DMGs were involved in regulating female gonad development and ovarian follicle development. Finally, we found that 10 DMGs, including BMP7, BMPR1B, CTNNB1, FST, FSHR, LHCGR, TGFB2 and TGFB3, are more likely to be involved in prolificacy of Hu sheep, as assessed by correlation analysis and listed in detail.

Conclusions

This study revealed the global DNA methylation pattern of sheep ovaries associated with high and low prolificacy groups, which may contribute to a better understanding of the epigenetic regulation of sheep reproductive capacity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4068-9) contains supplementary material, which is available to authorized users.

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