Genomic Approaches to Understanding Response and Resistance to Immunotherapy

Development of a Bladder Cancer-on-a-Chip Model to Assess Bladder Cancer Cell Invasiveness

We have developed a bladder cancer-on-a-chip model which supports the 3D growth of cells and can be used to assess and quantify bladder cancer cell invasiveness in a physiologically appropriate environment. Three bladder cancer cell lines (T24, J82, and RT4) were resuspended in 50% Matrigel® and grown within a multi-channel organ-on-a-chip system. The ability of live cells to invade across into an adjacent 50% Matrigel®-only channel was assessed over a 2-day period. Cell lines isolated from patients with high-grade bladder cancer (T24 and J82) invaded across into the Matrigel®-only channel at a much higher frequency compared to cells isolated from a patient with low-grade cancer (RT4) (p < 0.001). The T24 and J82 cells also invaded further distances into the Matrigel®-only channel compared to the RT4 cells (p < 0.001). The cell phenotype within the model was maintained as assessed by cell morphology and immunohistochemical analysis of E-cadherin. Treatment with ATN-161, an α5β1 integrin inhibitor and well-known migrastatic drug, caused a dose-dependent decrease in the invasiveness of the J82 cells (p < 0.01). The combined data demonstrate that our bladder cancer-on-a-chip model supports the retention of the bladder cancer cell phenotype and can be used to reproducibly assess and quantify the invasiveness of live bladder cancer cells.

State-Of-The-Art Advancements on Cancer Vaccines and Biomarkers

The origins of cancer vaccines date back to the 1800s. Since then, there have been significant efforts to generate vaccines against solid and hematologic malignancies using a variety of platforms. To date, these efforts have generally been met with minimal success. However, in the era of improved methods and technological advancements, supported by compelling preclinical and clinical data, a wave of renewed interest in the field offers the promise of discovering field-changing paradigms in the management of established and resected disease using cancer vaccines. These include novel approaches to personalized neoantigen vaccine development, as well as innovative immune-modulatory vaccines (IMVs) that facilitate activation of antiregulatory T cells to limit immunosuppression caused by regulatory immune cells. This article will introduce some of the limitations that have affected cancer vaccine development over the past several decades, followed by an introduction to the latest advancements in neoantigen vaccine and IMV therapy, and then conclude with a discussion of some of the newest technologies and progress that are occurring across the cancer vaccine space. Cancer vaccines are among the most promising frontiers for breakthrough innovations and strategies poised to make a measurable impact in the ongoing fight against cancer.

The role of radiotherapy in tumor immunity and the potential of PET/CT in detecting the expression of PD-1/PD-L1

Upregulation of PD-1/PD-L1 allows cancer cells to escape from host immune systems by functionally inactivating T-cell immune surveillance. Clinical blockade strategies have resulted in an increased prevalence of patients with late-stage cancers. However, many cancer patients had limited or no response to current immunotherapeutic strategies. Therefore, how to improve the sensitivity of immunotherapy has become the focus of attention of many scholars. Radiotherapy plays a role in the recruitment of T cells in the tumor microenvironment, increases CD4 + and CD8 + T cells, and increases PD-L1 expression, resulting in the synergistically enhanced antitumor effect of irradiation and PD-L1 blockade. Radiotherapy can cause changes in tumor metabolism, especially glucose metabolism. Tumor glycolysis and tumor immune evasion are interdependent, glycolytic activity enhances PD-L1 expression on tumor cells and thus promotes anti-PD-L1 immunotherapy response. Therefore, the mechanism of radiotherapy affecting tumor immunity may be partly through intervention of tumor glucose metabolism. Furthermore, some authors had found that the uptake of 2'-deoxy-2'-[18F]fluoro-D-glucose(18F-FDG) was correlated with PD-1/PD-L1 expression. Positron emission tomography/computed tomography (PET/CT) is a non-invasive detection method for PD-1/PD-L1 expression and has several potential advantages over immunohistochemical (IHC), PET/CT can dynamically reflect the expression of PD-1/PD-L1 inside the tumor and further guide clinical treatment.

Immune checkpoint inhibitors in cancer: the increased risk of atherosclerotic cardiovascular disease events and progression of coronary artery calcium

BACKGROUND

Immune checkpoint inhibitors (ICIs) have contributed to a significant advancement in the treatment of cancer, leading to improved clinical outcomes in many individuals with advanced disease. Both preclinical and clinical investigations have shown that ICIs are associated with atherosclerosis and other cardiovascular events; however, the exact mechanism underlying this relationship has not been clarified.

METHODS

Patients diagnosed with stages III or IV non-small cell lung cancer (NSCLC) at the Wuhan Union Hospital from March 1, 2020, to April 30, 2022, were included in this retrospective study. Coronary artery calcium (CAC) volume and score were assessed in a subset of patients during non-ECG-gated chest CT scans at baseline and 3, 6, and 12 months after treatment. Propensity score matching (PSM) was performed in a 1:1 ratio to balance the baseline characteristics between the two groups.

RESULTS

Overall, 1458 patients (487 with ICI therapy and 971 without ICI therapy) were enrolled in this cardiovascular cohort study. After PSM, 446 patients were included in each group. During the entire period of follow-up (median follow-up 23.1 months), 24 atherosclerotic cardiovascular disease (ASCVD) events (4.9%) occurred in the ICI group, and 14 ASCVD events (1.4%) in the non-ICI group, before PSM; 24 ASCVD events (5.4%) occurred in the ICI group and 5 ASCVD events (1.1%) in the non-ICI group after PSM. The CAC imaging study group comprised 113 patients with ICI therapy and 133 patients without ICI therapy. After PSM, each group consisted of 75 patients. In the ICI group, the CAC volume/score increased from 93.4 mm3/96.9 (baseline) to 125.1 mm3/132.8 (at 12 months). In the non-ICI group, the CAC volume/score was increased from 70.1 mm3/68.8 (baseline) to 84.4 mm3/87.9 (at 12 months). After PSM, the CAC volume/score was increased from 85.1 mm3/76.4 (baseline) to 111.8 mm3/121.1 (12 months) in the ICI group and was increased from 74.9 mm3/76.8 (baseline) to 109.3 mm3/98.7 (12 months) in the non-ICI group. Both cardiovascular events and CAC progression were increased after the initiation of ICIs.

CONCLUSIONS

Treatment with ICIs was associated with a higher rate of ASCVD events and a noticeable increase in CAC progression.

The impact of pulmonary artery to ascending aorta diameter ratio progression on the prognosis of NSCLC patients treated with immune checkpoint inhibitors

Background

Immunotherapy, represented by immune checkpoint inhibitors (ICIs), is a major breakthrough in cancer treatment. Studies have reported that the use of ICIs is associated with an increase in the pulmonary artery to ascending aorta diameter (PAD/AoD) ratio. However, the impact of PAD/AoD ratio progression on the prognosis of patients is unclear.

Methods

This retrospective cohort study included patients with stage III or IV non-small cell lung cancer (NSCLC) treated with ICIs at the Wuhan Union Hospital between March 1, 2020, and September 1, 2022. The baseline and post-treatment PAD/AoD ratios of patients were evaluated through chest CT scans. The primary outcome of this study was overall survival (OS), while the secondary outcomes included progression-free survival (PFS), objective response rate (ORR) and disease control rate (DCR).

Results

The PAD/AoD ratio increased after the initiation of ICIs (from 0.75 to 0.78; P < 0.001). A total of 441 patients were divided into severe group (n=221) and non-severe group (n=220) according to the median increase of PAD/AoD ratio (1.06). Compared with the non-severe group, the severe group had a lower DCR (87.8% vs. 96.0%, P = 0.005) and ORR (87.5% vs. 96.0%, P = 0.063). Over the entire duration of follow-up (median 22.0 months), 85 (38.5%) patients in the severe group and 30 (7.3%) patients in the non-severe group died. An increased PAD/AoD ratio was associated with shorter PFS (Hazard ratio (HR): 1.48 [95% CI, 1.14 to 1.93]; P = 0.003) and OS (HR: 3.50 [95% CI, 2.30 to 5.30]; P < 0.001). Similar results were obtained across subgroups.

Conclusions

ICI treatment exacerbates an increase in the PAD/AoD ratio in patients with cancer, and greater increase in the PAD/AoD ratio was associated with a worse prognosis. PAD/AoD ratio could be a biomarker to stratify prognosis of NSCLC patients treated with ICIs.

Single cell dynamics of tumor specificity vs bystander activity in CD8+ T cells define the diverse immune landscapes in colorectal cancer

CD8+ T cell activation via immune checkpoint blockade (ICB) is successful in microsatellite instable (MSI) colorectal cancer (CRC) patients. By comparison, the success of immunotherapy against microsatellite stable (MSS) CRC is limited. Little is known about the most critical features of CRC CD8+ T cells that together determine the diverse immune landscapes and contrasting ICB responses. Hence, we pursued a deep single cell mapping of CRC CD8+ T cells on transcriptomic and T cell receptor (TCR) repertoire levels in a diverse patient cohort, with additional surface proteome validation. This revealed that CRC CD8+ T cell dynamics are underscored by complex interactions between interferon-γ signaling, tumor reactivity, TCR repertoire, (predicted) TCR antigen-specificities, and environmental cues like gut microbiome or colon tissue-specific 'self-like' features. MSI CRC CD8+ T cells showed tumor-specific activation reminiscent of canonical 'T cell hot' tumors, whereas the MSS CRC CD8+ T cells exhibited tumor unspecific or bystander-like features. This was accompanied by inflammation reminiscent of 'pseudo-T cell hot' tumors. Consequently, MSI and MSS CRC CD8+ T cells showed overlapping phenotypic features that differed dramatically in their TCR antigen-specificities. Given their high discriminating potential for CD8+ T cell features/specificities, we used the single cell tumor-reactive signaling modules in CD8+ T cells to build a bulk tumor transcriptome classification for CRC patients. This "Immune Subtype Classification" (ISC) successfully distinguished various tumoral immune landscapes that showed prognostic value and predicted immunotherapy responses in CRC patients. Thus, we deliver a unique map of CRC CD8+ T cells that drives a novel tumor immune landscape classification, with relevance for immunotherapy decision-making.

Explore the impact of hypoxia-related genes (HRGs) in Cutaneous melanoma

BACKGROUND

Cutaneous melanoma (CM) has an overall poor prognosis due to a high rate of metastasis. This study aimed to explore the role of hypoxia-related genes (HRGs) in CM.

METHODS

We first used on-negative matrix factorization consensus clustering (NMF) to cluster CM samples and preliminarily analyzed the relationship of HRGs to CM prognosis and immune cell infiltration. Subsequently, we identified prognostic-related hub genes by univariate COX regression analysis and the least absolute shrinkage and selection operator (LASSO) and constructed a prognostic model. Finally, we calculated a risk score for patients with CM and investigated the relationship between the risk score and potential surrogate markers of response to immune checkpoint inhibitors (ICIs), such as TMB, IPS values, and TIDE scores.

RESULTS

Through NMF clustering, we identified high expression of HRGs as a risk factor for the prognosis of CM patients, and at the same time, increased expression of HRGs also indicated a poorer immune microenvironment. Subsequently, we identified eight gene signatures (FBP1, NDRG1, GPI, IER3, B4GALNT2, BGN, PKP1, and EDN2) by LASSO regression analysis and constructed a prognostic model.

CONCLUSION

Our study identifies the prognostic significance of hypoxia-related genes in melanoma and shows a novel eight-gene signature to predict the potential efficacy of ICIs.

Identification of sterile a-motif domain-containing 9-like as a potential biomarker in patients with cutaneous melanoma

Skin cutaneous melanoma (SKCM) is one of the most aggressive malignancies, accounting for approximately 75% of skin cancer-related fatalities annually. Sterile a-motif domain-containing 9-like (SAMD9L) has been found to regulate cell proliferation and suppress the neoplastic phenotype, but its specific role in SKCM remains unknown. To investigate the cancer-associated immunology of SKCM and the role of SAMD9L in tumor progression, we conducted an integrative bioinformatics analysis that revealed elevated expression levels of SAMD9L in SKCM. ROC curves and survival analyses confirmed the considerable diagnostic and prognostic abilities of SAMD9L. Moreover, a real-world cohort of 35 SKCM patients from the First Affiliated Hospital of Soochow University showed that higher expression levels of SAMD9L were associated with better prognosis. We performed validation experiments, including cell culture, generation of lentiviral-transfected SKCM cell lines, cell proliferation assay, and transwell assay, which demonstrated that down-regulation of SAMD9L significantly promoted proliferation and migration capacities of SKCM cells. Additionally, SAMD9L expression was found to be strongly linked to immune infiltration. Our results revealed a positive correlation between SAMD9L and XAF1 expression, suggesting that SAMD9L may serve as a prospective prognostic indicator of SKCM with co-expressed XAF1 gene. In summary, our findings indicate that SAMD9L may serve as a promising prognostic and therapeutic biomarker and play a critical role in tumor-immune interactions in SKCM.

H4-methylation regulators mediated epitranscriptome patterns and tumor microenvironment infiltration characterization in hepatocellular carcinoma

Epigenetic modifications are involved in the remodeling of the tumor microenvironment (TME) and the regulation of immune response. Nonetheless, the role of histone H4 methylation (H4M) modification in the TME and immune regulation of hepatocellular carcinoma (HCC) is unknown. As a result, the purpose of this research is to discover H4M-mediated modification patterns and their effects on TME and immunologic characteristics in HCC. A total of 2305 samples were enrolled from 13 different cohorts. With the help of consensus clustering analysis, three distinct H4M modification patterns were identified. The cell-infiltrating characteristics of TME under these three patterns were highly consistent with their enriched biological processes and clinical outcome. The H4Mscore was then created using principal component analysis algorithm to quantify the H4M modification pattern of each individual tumor and was systematically correlated with representative tumor characteristics. We found that analyzing H4M modification patterns within individual tumors could predict TME infiltration, homologous recombination deficiency (HRD), intratumor heterogeneity, proliferation activity, mRNA stemness index, and prognosis. The group with a low H4Mscore had an inflamed TME phenotype and a better immunotherapy response, as well as a better survival outcome. The prognostic value of H4Mscore was validated in three internal cohorts and five external cohorts, respectively. In external immunotherapy cohorts, the low H4Mscore was also linked to an enhanced response to anti-PD-1/L1 and anti-CTLA4 immunotherapy and a better prognosis. This study revealed that H4M modification played an important role in forming TME diversity and complexity. Evaluating the H4M modification pattern of individual tumors could help us learn more about TME and develop more effective immunotherapy strategies.

Manipulation of PD-L1 Endosomal Trafficking Promotes Anticancer Immunity

The aberrant regulation of PD-L1 in tumor cells remains poorly understood. Here, the authors systematically investigate the endosomal trafficking of plasma membrane PD-L1 in tumor cells. They show that plasma membrane PD-L1 is continuously internalized, and then trafficked from early endosomes to multivesicular bodies/late endosomes, recycling endosomes, lysosomes, and/or extracellular vesicles (EVs). This constitutive endocytic trafficking of PD-L1 is Rab5- and clathrin-dependent. Triazine compound 6J1 blocks the endosomal trafficking of PD-L1 and induces its accumulation in endocytic vesicles by activating Rab5. 6J1 also promotes exosomal PD-L1 secretion by activating Rab27. Together, these effects result in a decrease in the membrane level of PD-L1 in 6J1-treated tumor cells and enables tumor cells to be more susceptible to the tumor-killing activity of T cells in vitro. 6J1 also increases tumor-infiltrating cytotoxic T cells and promotes chemokines secretion in the tumor microenvironment. Rab27 knockdown abolishes 6J1-induced PD-L1 secretion in EVs and revokes the exhausted tumor-infiltrating T cells in tumors, thereby improving the anticancer efficacy of 6J1. Furthermore, a combination of 6J1 and an anti-PD-1 antibody significantly improves the anticancer immune response. Therefore, manipulating PD-L1 endosomal trafficking provides a promising means to promote an anticancer immune response in addition to the immune checkpoint-blocking antibody therapy.

Identification of tumor mutation burden-associated molecular and clinical features in cancer by analyzing multi-omics data

Background

Tumor mutation burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in cancer. Systematic identification of molecular features correlated with TMB is significant, although such investigation remains insufficient.

Methods

We analyzed associations of somatic mutations, pathways, protein expression, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), competing endogenous RNA (ceRNA) antitumor immune signatures, and clinical features with TMB in various cancers using multi-omics datasets from The Cancer Genome Atlas (TCGA) program and datasets for cancer cohorts receiving the immune checkpoint blockade therapy.

Results

Among the 32 TCGA cancer types, melanoma harbored the highest percentage of high-TMB (≥ 10/Mb) cancers (49.4%), followed by lung adenocarcinoma (36.9%) and lung squamous cell carcinoma (28.1%). Three hundred seventy-six genes had significant correlations of their mutations with increased TMB in various cancers, including 11 genes (ARID1A, ARID1B, BRIP1, NOTCH2, NOTCH4, EPHA5, ROS1, FAT1, SPEN, NSD1,and PTPRT) with the characteristic of their mutations associated with a favorable response to immunotherapy. Based on the mutation profiles in three genes (ROS1, SPEN, and PTPRT), we defined the TMB prognostic score that could predict cancer survival prognosis in the immunotherapy setting but not in the non-immunotherapy setting. It suggests that the TMB prognostic score's ability to predict cancer prognosis is associated with the positive correlation between immunotherapy response and TMB. Nine cancer-associated pathways correlated positively with TMB in various cancers, including nucleotide excision repair, DNA replication, homologous recombination, base excision repair, mismatch repair, cell cycle, spliceosome, proteasome, and RNA degradation. In contrast, seven pathways correlated inversely with TMB in multiple cancers, including Wnt, Hedgehog, PI3K-AKT, MAPK, neurotrophin, axon guidance, and pathways in cancer. High-TMB cancers displayed higher levels of antitumor immune signatures and PD-L1 expression than low-TMB cancers in diverse cancers. The association between TMB and survival prognosis was positive in bladder, gastric, and endometrial cancers and negative in liver and head and neck cancers. TMB also showed significant associations with age, gender, height, weight, smoking, and race in certain cohorts.

Conclusions

The molecular and clinical features significantly associated with TMB could be valuable predictors for TMB and immunotherapy response and therefore have potential clinical values for cancer management.

Immunological classification of hepatitis B virus-positive hepatocellular carcinoma by transcriptome analysis

BACKGROUND

Hepatitis B virus (HBV) infection is a major factor responsible for HBV+ hepatocellular carcinoma (HCC).

AIM

An immunological classification of HBV+ HCC may provide both biological insights and clinical implications for this disease.

METHODS

Based on the enrichment of 23 immune signatures, we identified two immune-specific subtypes (Imm-H and Imm-L) of HBV+ HCC by unsupervised clustering. We showed that this subtyping method was reproducible and predictable by analyzing three different datasets.

RESULTS

Compared to Imm-L, Imm-H displayed stronger immunity, more stromal components, lower tumor purity, lower stemness and intratumor heterogeneity, lower-level copy number alterations, higher global methylation level, and better overall and disease-free survival prognosis. Besides immune-related pathways, stromal pathways (ECM receptor interaction, focal adhesion, and regulation of actin cytoskeleton) and neuro-related pathways (neuroactive ligand-receptor interaction, and prion diseases) were more highly enriched in Imm-H than in Imm-L. We identified nine proteins differentially expressed between Imm-H and Imm-L, of which MYH11, PDCD4, Dvl3, and Syk were upregulated in Imm-H, while PCNA, Acetyl-a-Tubulin-Lys40, ER-α_pS118, Cyclin E2, and β-Catenin were upregulated in Imm-L.

CONCLUSION

Our data suggest that “hot” tumors have a better prognosis than “cold” tumors in HBV+ HCC and that “hot” tumors respond better to immunotherapy.

Obeticholic acid and 5β-cholanic acid 3 exhibit anti-tumor effects on liver cancer through CXCL16/CXCR6 pathway

Hepatocellular carcinoma (HCC) is the most common type of liver malignancy with a high incidence and mortality rate. Previous in vitro and in vivo studies have confirmed that liver sinusoidal endothelial cells (LSEC) secrete CXCL16, which acts as a messenger to increase the hepatic accumulation of CXCR6⁺ natural killer T (NKT) cells and exert potent antitumor effects. However, evidence for this process in humans is lacking and its clinical significance is still unclear. In this study, by dissecting the human HCC single-cell RNA-seq data, we verified this process through cellphoneDB. NKT cells in patients with high expression of CXCL16 exhibited a higher activation state and produced more interferon-γ (IFN-γ) compared with those with low expression. We next investigated the signaling pathways between activated (CD69 high) and unactivated NKT cells (CD69 low) using NKT cell-developmental trajectories and functional enrichment analyses. In vivo experiments, we found that farnesoid X receptor agonist (obeticholic acid) combined with the takeda G protein coupled receptor 5 antagonist (5β-cholanic acid 3) exhibited significant tumor suppressive effects in the orthotopic liver tumor model and this result may be related to the CXCL16/CXCR6 axis. In conclusion, our study provides the basis and potential strategies for HCC immunotherapy based on NKT cells.

Construction and experimental validation of a B cell senescence-related gene signature to evaluate prognosis and immunotherapeutic sensitivity in bladder cancer

Senescent B cells exhibit reduced antibody production and enhanced proinflammatory cytokine and chemokine secretion, exerting non-negligible functions in antitumor immunity. This study aims to clarify the prognosis value of B cell senescence-related genes in bladder cancer (BLCA). Twelve B cell senescence-related genes were identified based on previous studies and the single-cell RNA sequencing of a BLCA sample from Gene Expression Omnibus (GEO). The Cancer Genome Atlas BLCA cohort was used as the training dataset. Three cohorts from GEO, 35 clinical samples from the local hospital, and in vitro cell experiments were used for validation. The unsupervised clustering based on the 12 genes was associated with the prognosis and the tumor immunity. Through least absolute shrinkage and selection operator regression and random forest algorithm, G protein subunit gamma 11 (GNG11) and inhibitor of DNA binding 1 (ID1) of the 12 genes were determined as significant prognosis predictors and then included in the multivariate Cox regression model. The model was a reliable and robust prognosis biomarker across multiple large-scale cohorts (pooled HR = 1.76, 95% CI = 1.41-2.20). The tight association between the model and BLCA malignant degree was demonstrated in the local cohort (P < 0.01). The model could also predict the immunotherapeutic sensitivity, which was confirmed by the tumor immune dysfunction and exclusion algorithm (P < 0.0001) and IMvigor210 cohort (P < 0.0001). At last, in vitro cell experiments in IM-9 and GM12878 B cells indicated that GNG11 and ID1 were involved in the cellular aging process. Collectively, a B cell senescence-related gene signature was constructed to evaluate the prognosis and immunotherapeutic response in BLCA, providing novel insights into the biological mechanisms.

MAST: a hybrid Multi-Agent Spatio-Temporal model of tumor microenvironment informed using a data-driven approach

Motivation

Recently, several computational modeling approaches, such as agent-based models, have been applied to study the interaction dynamics between immune and tumor cells in human cancer. However, each tumor is characterized by a specific and unique tumor microenvironment, emphasizing the need for specialized and personalized studies of each cancer scenario.

Results

We present MAST, a hybrid Multi-Agent Spatio-Temporal model which can be informed using a data-driven approach to simulate unique tumor subtypes and tumor-immune dynamics starting from high-throughput sequencing data. It captures essential components of the tumor microenvironment by coupling a discrete agent-based model with a continuous partial differential equations-based model.The application to real data of human colorectal cancer tissue investigating the spatio-temporal evolution and emergent properties of four simulated human colorectal cancer subtypes, along with their agreement with current biological knowledge of tumors and clinical outcome endpoints in a patient cohort, endorse the validity of our approach.

Availability and implementation

MAST, implemented in Python language, is freely available with an open-source license through GitLab (https://gitlab.com/sysbiobig/mast), and a Docker image is provided to ease its deployment. The submitted software version and test data are available in Zenodo at https://dx.doi.org/10.5281/zenodo.7267745.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

SP140 inhibits STAT1 signaling, induces IFN-γ in tumor-associated macrophages, and is a predictive biomarker of immunotherapy response

BACKGROUND

Understanding the role and potential therapeutic targeting of tumor-associated macrophages (TAMs) is crucial to developing new biomarkers and therapeutic strategies for cancer immunotherapies. The epigenetic reader SP140 has emerged as a master regulator of macrophage transcriptional programs; however, its role in the signaling of TAMs and response to immunotherapy has not been investigated.

METHODS

We evaluated the correlation between SP140 expression in head and neck squamous cell carcinoma (HNSCC) TAMs and clinical outcomes. We also used complementary bioinformatics and experimental approaches to study the association of SP140 expression with tumor mutation burden, patient survival, immunogenic signature of tumors, and signaling of TAMs. SP140 overexpression or knockdown was implemented to identify the role of SP140 in downstream signaling and production of inflammatory cytokine and chemokines. Chromatin immunoprecipitation and analysis of assay of transposase accessible chromatin sequencing data were used to demonstrate the direct binding of SP140 on the promoters of STAT1. Finally, correlation of SP140 with immune cell infiltrates and response to immune-checkpoint blockade in independent cohorts of HNSCC, metastatic melanoma, and melanoma was assessed.

RESULTS

We found that SP140 is highly expressed in TAMs across many cancer types, including HNSCCs. Interestingly, higher expression of SP140 in the tumors was associated with higher tumor mutation burden, improved survival, and a favorable response to immunotherapy. Tumors with high SP140 expression showed enrichment of inflammatory response and interferon-gamma (IFN-γ) pathways in both pan-cancer analysis and HNSCC-specific analysis. Mechanistically, SP140 negatively regulates transcription and phosphorylation of STAT1 and induces IFN-γ signaling. Activating SP140 in macrophages and TAMs induced the proinflammatory macrophage phenotype, increased the antitumor activity of macrophages, and increased the production of IFN-γ and antitumor cytokines and chemokines including interleukin-12 and CXCL10. SP140 expression provided higher sensitivity and specificity to predict antiprogrammed cell death protein 1 immunotherapy response compared with programmed death-ligand 1 in HNSCCs and lung cancer. In metastatic melanoma, higher levels of SP140 were associated with a durable response to immunotherapy, higher immune score estimates, high infiltrations of CD8+ T cells, and inflammatory TAMs.

CONCLUSIONS

Our findings suggest that SP140 could serve as both a therapeutic target and a biomarker to identify immunotherapy responders.

Bioinformatics analysis identifies PSMB8 as a key gene in the cutaneous malignant melanoma tumor microenvironment

Background

Cutaneous tumors are commonly seen in clinical practice, and malignant melanoma (MM) is the leading cause of cutaneous tumor-induced death. The tumor microenvironment (TME), a critical part of tumorigenesis, has been a research hotspot in recent years. However, the effects of the MM microenvironment components remain elusive. This study aimed to analyze the various components in the TME of MM to identify factors affecting the tumorigenesis, progression, and metastasis of MM and the survival of MM patients. We also aimed to identify biomarkers related to TME rehabilitation to provide a new direction for MM treatment.

Methods

We used bioinformatics to analyze the RNA-seq and somatic mutation data of 473 MM patients from The Cancer Genome Atlas database. Firstly, the patients' immunity and stroma were separately scored by the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) method. According to the median score, the participants were split into high- and low-score groups. Then, Gene Set Enrichment Analysis (GSEA) was performed, showing that high-expression genes were highly abundant in biological and metabolic activities associated with the immune system.

Results

Differentially expressed genes (DEGs) and differentially mutated genes (DMGs) were identified and intersected to obtain the key immune-related genes PSMB8, FAM216B, DYSF, and FAM131C. PSMB8 was finally selected as the preferred immune-related prognostic marker; it was positively associated with overall survival and therefore considered a protective gene for MM patients. The GSEA analysis showed that PSMB8 with high expression had greater gene abundance in biological and metabolic processes related to immune system. In addition, CIBERSORT analysis showed an association between the proportion of tumor-infiltrating immune cells and PSMB8 expression.

Conclusions

Our results suggest that PSMB8 might be associated with tumorigenesis and MM progression and could serve as a biomarker for the TME rehabilitation of MM. Our findings provide a new perspective and direction for the treatment of MM.

A novel prognostic model for cutaneous melanoma based on an immune-related gene signature and clinical variables

Abundant evidence has indicated that the prognosis of cutaneous melanoma (CM) patients is highly complicated by the tumour immune microenvironment. We retrieved the clinical data and gene expression data of CM patients in The Cancer Genome Atlas (TCGA) database for modelling and validation analysis. Based on single-sample gene set enrichment analysis (ssGSEA) and consensus clustering analysis, CM patients were classified into three immune level groups, and the differences in the tumour immune microenvironment and clinical characteristics were evaluated. Seven immune-related CM prognostic molecules, including three mRNAs (SUCO, BTN3A1 and TBC1D2), three lncRNAs (HLA-DQB1-AS1, C9orf139 and C22orf34) and one miRNA (hsa-miR-17-5p), were screened by differential expression analysis, ceRNA network analysis, LASSO Cox regression analysis and univariate Cox regression analysis. Their biological functions were mainly concentrated in the phospholipid metabolic process, transcription regulator complex, protein serine/threonine kinase activity and MAPK signalling pathway. We established a novel prognostic model for CM integrating clinical variables and immune molecules that showed promising predictive performance demonstrated by receiver operating characteristic curves (AUC ≥ 0.74), providing a scientific basis for predicting the prognosis and improving the clinical outcomes of CM patients.

Identification of fatty acid metabolism-related molecular subtype biomarkers and their correlation with immune checkpoints in cutaneous melanoma

PURPOSE

Fatty acid metabolism (FAM) affects the immune phenotype in a metabolically dynamic tumor microenvironment (TME), but the use of FAM-related genes (FAMGs) to predict the prognosis and immunotherapy response of cutaneous melanoma (CM) patients has not been investigated. In this study, we aimed to construct FAM molecular subtypes and identify key prognostic biomarkers in CM.

METHODS

We used a CM dataset in The Cancer Genome Atlas (TCGA) to construct FAM molecular subtypes. We performed Kaplan-Meier (K-M) analysis, gene set enrichment analysis (GSEA), and TME analysis to assess differences in the prognosis and immune phenotype between subtypes. We used weighted gene co-expression network analysis (WGCNA) to identify key biomarkers that regulate tumor metabolism and immunity between the subtypes. We compared overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS) between CM patients with high or low biomarker expression. We applied univariable and multivariable Cox analyses to verify the independent prognostic value of the FAM biomarkers. We used GSEA and TME analysis to investigate the immune-related regulation mechanism of the FAM subtype biomarker. We evaluated the immune checkpoint inhibition (ICI) response and chemotherapy sensitivity between CM patients with high or low biomarker expression. We performed real-time fluorescent quantitative PCR (qRT-PCR) and semi-quantitative analysis of the immunohistochemical (IHC) data from the Human Protein Atlas to evaluate the mRNA and protein expression levels of the FAM biomarkers in CM.

RESULTS

We identified 2 FAM molecular subtypes (cluster 1 and cluster 2). K-M analysis showed that cluster 2 had better OS and PFS than cluster 1 did. GSEA showed that, compared with cluster 1, cluster 2 had significantly upregulated immune response pathways. The TME analysis indicated that immune cell subpopulations and immune functions were highly enriched in cluster 2 as compared with cluster 1. WGCNA identified 6 hub genes (ACSL5, ALOX5AP, CD1D, CD74, IL4I1, and TBXAS1) as FAM biomarkers. CM patients with high expression levels of the six biomarkers had better OS, PFS, and DSS than those with low expression levels of the biomarkers. The Cox regression analyses verified that the 6 FAM biomarkers can be independent prognostic factors for CM patients. The single-gene GSEA showed that the high expression levels of the 6 genes were mainly enriched in T-cell antigen presentation, the PD-1 signaling pathway, and tumor escape. The TME analysis confirmed that the FAM subtype biomarkers were not only related to immune infiltration but also highly correlated with immune checkpoints such as PD-1, PD-L1, and CTLA-4. TIDE scores confirmed that patients with high expression levels of the 6 biomarkers had worse immunotherapy responses. The 6 genes conveyed significant sensitivity to some chemotherapy drugs. qRT-PCR and IHC analyses verified the expression levels of the 6 biomarkers in CM cells.

CONCLUSION

Our FAM subtypes verify that different FAM reprogramming affects the function and phenotype of infiltrating immune cells in the CM TME. The FAM molecular subtype biomarkers can be independent predictors of prognosis and immunotherapy response in CM patients.

Identifying tumor immunity-associated molecular features in liver hepatocellular carcinoma by multi-omics analysis

Background: Although current immunotherapies have achieved some successes for hepatocellular carcinoma (HCC) patients, their benefits are limited for most HCC patients. Therefore, the identification of biomarkers for promoting immunotherapeutic responses in HCC is urgently needed.

Methods: Using the TCGA HCC cohort, we investigated correlations of various molecular features with antitumor immune signatures (CD8⁺ T cell infiltration and cytolytic activity) and an immunosuppressive signature (PD-L1 expression) in HCC. These molecular features included mRNAs, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), proteins, and pathways.

Results: We found that the mutations of several oncogenes and tumor suppressor genes significantly correlated with reduced antitumor immune signatures, including TTN, CTNNB1, RB1, ZFHX4, and TP53. It indicates that these genes’ mutations may inhibit antitumor immune responses in HCC. Four proteins (Syk, Lck, STAT5, and Caspase-7) had significant positive expression correlations with CD8⁺ T cell enrichment, cytolytic activity, and PD-L1 expression in HCC. It suggests that these proteins’ expression could be useful biomarkers for the response to immune checkpoint inhibitors Similiarly, we identified other types of biomarkers potentially useful for predicting the response to ICIs, including miRNAs (hsa-miR-511-5p, 150-3p, 342-3p, 181a-3p, 625-5p, 4772-3p, 155-3p, 142-5p, 142-3p, 155-5p, 625-3p, 1976, 7702), many lncRNAs, and pathways (apoptosis, cytokine-cytokine receptor interaction, Jak-STAT signaling, MAPK signaling, PI3K-AKT signaling, HIF-1 signaling, ECM receptor interaction, focal adhesion, and estrogen signaling). Further, tumor mutation burden showed no significant correlation with antitumor immunity, while tumor aneuploidy levels showed a significant negative correlation with antitumor immunity.

Conclusion: The molecular features significantly associated with HCC immunity could be predictive biomarkers for immunotherapeutic responses in HCC patients. They could also be potential intervention targets for boosting antitumor immunity and immunotherapeutic responses in HCC.

Construction and validation of a gene signature related to bladder urothelial carcinoma based on immune gene analysis

BACKGROUND

This study developed a gene signature associated with a malignant and common tumor of the urinary system, the Bladder Urothelial Carcinoma (BLCA).

METHODS

The Cancer Genome Atlas (TCGA) database was searched to obtain 414 BLCA samples and the expression spectra of 19 normal samples. Single-sample Gene Set Enrichment Analysis (ssGSEA) was conducted to determine the enrichment levels in the BLCA samples of the 29 immune genes. Unsupervised hierarchical clustering, gene set enrichment analysis (GSEA), single-factor Cox analysis, least absolute shrinkage and selection operator (LASSO) regression models, and GEO queues were used to determine the BLCA immune gene subtype, analyze the biological pathway differences between immune gene subtypes, determine the characteristic genes of BLCA associated with prognosis, identify the BLCA-related genes, and verify the gene signature, respectively.

RESULTS

We identified two immune gene subtypes (immunity_L and immunity_H). The latter was significantly related to receptors, JAK STAT signaling pathways, leukocyte interleukin 6 generation, and cell membrane signal receptor complexes. Four characteristic genes (RBP1, OAS1, LRP1, and AGER) were identified and constituted the gene signature. Significant survival advantages, higher mutation frequency, and superior immunotherapy were observed in the low-risk group patients. The gene signature had good predictive ability. The results of the validation group were consistent with TCGA queue results.

CONCLUSIONS

We constructed a 4-gene signature that helps monitor BLCA occurrence and prognosis, providing an important basis for developing personalized BLCA immunotherapy.

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Background: Glioma is the most prevalent malignant intracranial tumor. Many studies have shown that angiogenesis plays a crucial role in glioma tumorigenesis, metastasis, and prognosis. In this study, we conducted a comprehensive analysis of angiogenesis-related genes (ARGs) in glioma.

Methods: RNA-sequencing data of glioma patients were obtained from TCGA and CGGA databases. Via consensus clustering analysis, ARGs in the sequencing data were distinctly classified into two subgroups. We performed univariate Cox regression analysis to determine prognostic differentially expressed ARGs and least absolute shrinkage and selection operator Cox regression to construct a 14-ARG risk signature. The CIBERSORT algorithm was used to explore immune cell infiltration, and the ESTIMATE algorithm was applied to calculate immune and stromal scores.

Results: We found that the 14-ARG signature reflected the infiltration characteristics of different immune cells in the tumor immune microenvironment. Additionally, total tumor mutational burden increased significantly in the high-risk group. We combined the 14-ARG signature with patient clinicopathological data to construct a nomogram for predicting 1-, 3-, and 5-year overall survival with good accuracy. The predictive value of the prognostic model was verified in the CGGA cohort. SPP1 was a potential biomarker of glioma risk and was involved in the proliferation, invasion, and angiogenesis of glioma cells.

Conclusion: In conclusion, we established and validated a novel ARG risk signature that independently predicted the clinical outcomes of glioma patients and was associated with the tumor immune microenvironment.

Emerging immune-based technologies for high-grade gliomas

INTRODUCTION

The selection of a tailored and successful strategy for high-grade gliomas (HGGs) treatment is still a concern. The abundance of aberrant mutations within the heterogenic genetic landscape of glioblastoma strongly influences cell expansion, proliferation, and therapeutic resistance. Identification of immune evasion pathways opens the way to novel immune-based strategies. This review intends to explore the emerging immunotherapies for HGGs. The immunosuppressive mechanisms related to the tumor microenvironment and future perspectives to overcome glioma immunity barriers are also debated.

AREAS COVERED

An extensive literature review was performed on the PubMed/Medline and ClinicalTrials.gov databases. Only highly relevant articles in English and published in the last 20 years were selected. Data about immunotherapies coming from preclinical and clinical trials were summarized.

EXPERT OPINION

The overall level of evidence about the efficacy and safety of immunotherapies for HGGs is noteworthy. Monoclonal antibodies have been approved as second-line treatment, while peptide vaccines, viral gene strategies, and adoptive technologies proved to boost a vivid antitumor immunization. Malignant brain tumor-treating fields are ever-changing in the upcoming years. Constant refinements and development of new routes of drug administration will permit to design of novel immune-based treatment algorithms thus improving the overall survival.

PTEN-PI3K pathway alterations in advanced prostate cancer and clinical implications

BACKGROUND

Despite significant advances in molecular characterization and therapeutic targeting of advanced prostate cancer, it remains the second most common cause of cancer death in men in the United States. The PI3K (Phosphatidylinositol 3-kinase)/AKT (AKT serine/threonine kinase)/mTOR (mammalian target of rapamycin) signaling pathway is commonly altered in prostate cancer, most frequently through loss of the PTEN (Phosphatase and Tensin Homolog) tumor suppressor, and is critical for cancer cell proliferation, migration, and survival.

METHODS

This study summarizes signaling through the PTEN/PI3K pathway, alterations in pathway components commonly seen in advanced prostate cancer, and results of clinical trials of pathway inhibitors reported to date with a focus on more recently reported studies. It also reviews rationale for combination approaches currently under study, including with taxanes, immune checkpoint inhibitors and poly (ADP-ribose) polymerase inhibitors, and discusses future directions in biomarker testing and therapeutic targeting of this pathway.

RESULTS

Clinical trials studying pharmacologic inhibitors of PI3K, AKT or mTOR kinases have demonstrated modest activity of specific agents, with several trials of pathway inhibitors currently in progress. A key challenge is the importance of PI3K/AKT/mTOR signaling in noncancerous tissues, leading to predictable but often severe toxicities at therapeutic doses.

RESULTS

Further advances in selective pharmacologic inhibition of the PI3K/AKT/mTOR pathway in tumors, development of rational combinations, and appropriate biomarker selection to identify the appropriate tumor- and patient-specific vulnerabilities will be required to optimize clinical benefit from therapeutic targeting of this pathway.

Interleukin 20 receptor subunit beta (IL20RB) predicts poor prognosis and regulates immune cell infiltration in clear cell renal cell carcinoma

BACKGROUND AND OBJECTIVE

Emerging evidence has proven the robust role of tumor mutation burden (TMB) and immune cell infiltration (ICI) in cancer immunotherapy. However, the precise effect of TMB and ICI on clear cell renal cell carcinoma (ccRCC) remains elusive and merits further investigation. Therefore, we aim to identify the TMB-related genes in predicting prognosis and to explore the potential mechanisms of the identified Interleukin 20 receptor subunit beta (IL20RB) in ICI in ccRCC.

METHOD

The relative information of patients with ccRCC was obtained from The Cancer Genome Atlas database (TCGA). Immune-related genes were downloaded from the Immunology Database and Analysis Portal database. Cox regression analysis was used to identify prognosis-related immune genes for ccRCC. The relationship of IL20RB expression levels with clinicopathological parameters was analyzed using the "limma" and "survival" packages. Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC) databases were used as external validation. Quantitative Real-time PCR (qRT-PCR) and western blots were used to validate the expression levels of IL20RB in tumor cells. Cell counting kit-8 (CCK-8) assay and colony formation assay were used to examine the effect of IL20RB on the viability of ccRCC cells. Gene set enrichment analysis (GSEA) was introduced for the analysis of IL20RB-related signaling pathways. Tumor Immune Estimation Resource (TIMER) and Tumor and Immune System Interaction Database (TISIDB) were utilized to determine the correlation of IL20RB expression levels with tumor-infiltrating immune cells (TIICs).

RESULTS

IL20RB was significantly overexpressed in different ccRCC tissues and cells. High IL20RB expression in ccRCC patients was associated with short overall survival, high tumor grade, and advanced TNM stage. After knockdown of IL20RB with small interfering RNA (siRNA) technology, ccRCC cells' proliferation was significantly attenuated. Moreover, overexpression of IL20RB could increase the infiltration level of several immune cells, especially T follicular helper cells (Tfh), and overexpressed Tfh cells were correlated with poor prognosis in ccRCC.

CONCLUSIONS

IL20RB may function as an immune-associated therapeutic target for it determines cancer progression and regulates immune cell infiltration in ccRCC.

A Radiomics-Based Machine Learning Model for Prediction of Tumor Mutational Burden in Lower-Grade Gliomas

Simple Summary

Lower-grade glioma (LGG) is a kind of center nervous system neoplasm that arises from the glial cells. Lower-grade glioma patients have a median survival time in the range of 1.5–8 years based on the tumor genotypes. In term of epidemiology, most of the lower-grade glioma patients are diagnosed at young adult of age, which led to an early age of death. For exact diagnosis and effective treatment, a pathological result from biopsy sample is required. However, it is long turnaround time. In this study, using pre-operative magnetic resonance images, we developed a non-invasive model to classify tumor mutational burden (TMB), a prognostic factor of treatment response in lower-grade glioma patients, with an accuracy of 0.7936. To our knowledge, our study represents the best model for classification of TMB in LGG patients at present.

Abstract

Glioma is a Center Nervous System (CNS) neoplasm that arises from the glial cells. In a new scheme category of the World Health Organization 2016, lower-grade gliomas (LGGs) are grade II and III gliomas. Following the discovery of suppression of negative immune regulation, immunotherapy is a promising effective treatment method for lower-grade glioma patients. However, the therapy is not effective for all types of LGGs, and tumor mutational burden (TMB) has been shown to be a potential biomarker for the susceptibility and prognosis of immunotherapy in lower-grade glioma patients. Hence, predicting TMB benefits brain cancer patients. In this study, we investigated the correlation between MRI (magnetic resonance imaging)-based radiomic features and TMB in LGG by applying machine learning methods. Six machine learning classifiers were examined on the features extracted from the genetic algorithm. Subsequently, a light gradient boosting machine (LightGBM) succeeded in selecting 11 radiomics signatures for TMB classification. Our LightGBM model resulted in high accuracy of 0.7936, and reached a balance between sensitivity and specificity, achieving 0.76 and 0.8107, respectively. To our knowledge, our study represents the best model for classification of TMB in LGG patients at present.

Three Prognostic Biomarkers Correlate with Immune Checkpoint Blockade Response in Bladder Urothelial Carcinoma

Aim

We aim to develop a signature that could accurately predict prognosis and evaluate the response to immune checkpoint blockade (ICB) in bladder urothelial carcinoma (BLCA).

Methods

Based on comprehensive analysis of public database, we identified prognosis-related hub genes and investigated their predictive values for the ICB response in BLCA.

Results

Among 69 common DEGs, three genes (AURKA, BIRC5, and CKS1B) were associated with poor prognosis, and which were related to histological subtypes, TP53 mutation status, and the C2 (IFN-gamma dominant) subtype. Three genes and their related risk model can effectively predict the response of immunotherapy. Their related drugs were identified through analysis of drug bank database.

Conclusions

Three genes could predict prognosis and evaluate the response to ICB in BLCA.

Novel immune subtypes identification of HER2-positive breast cancer based on immunogenomic landscape

HER2 positive BC is heterogeneous. But few studies discussed the classification of HER2-positive BC based on immune-related signatures. Using three publicly BC genomics datasets, we classified HER2 positive BC based on 33 immune-related signatures and used unsupervised machine learning methods to predict and perform the classification. We grouped three HER2-positive BC subtypes that we called Immune-High (IM-H), Immune-Medium (IM-M), and Immune-Low (IM-L), and manifested this categorization was predictable, duplicable and reliable by analyzing another dataset. Compared to other subtypes, IM-H had a higher immune cell infiltration level and stronger anti-tumor immune activities, as well as better clinical survival outcome. Besides these signatures, there were some cancer-related pathways which were hyperactivated in IM-H, including cytokine-cytokine receptor interactions, antigen processing and presentation pathways, natural killer cell-mediated cytotoxicity, Th1 and Th2 cell differentiation, chemokine signaling pathway, Th17 cell differentiation, B and T cell receptor signaling, NF-kappa B signaling, PD-L1 expression and PD-1 checkpoint pathway in cancer, TNF signaling, IL-17 signaling, NOD-like receptor signaling and Toll-like receptor signaling. By contrast, IM-L showed depressed immune-related signatures and enhanced activation of lycosylphosphatidylinositol-anchor biosynthesis and mismatch repair. Moreover, we discovered a gene co-expression network focused on eight transcription factor genes (EOMES, TBX21, GFI1, IRF4, POU2AF1, CIITA, FOXP3 and TOX) and one tumor suppress gene (PRF1), which were closely related with tumor immune. We identified three HER2-positive BC subtypes based on immune-related signatures, which had potential clinical implications and promoted the optimal stratification of HER2-positive BC responsive to immunotherapy.

FLG Is a Potential Biomarker of Prognosis and Immunotherapy in Skin Cutaneous Melanoma

Background

Skin cutaneous melanoma is one of most aggressive type of cancers worldwide. Therefore, the identification of SKCM biomarkers is of great importance. FLG gene is one of the genes that encode proteins involved in epidermal formation. This was the first time to study the role of FLG in the prognosis and immune infiltrates of skin cutaneous melanoma.

Methods

We downloaded the somatic mutation data of 471 SKCM patients from the Cancer Genome Atlas (TCGA) database and analyzed the mutation profiles with "MafTools" package. The expression of FLG and the overall survival in SKCM were analyzed by GEPIA. Additionally, univariate and multivariate Cox analyses were used to compare several clinical features with survival rates. We used TIMER to investigate FLG expression and collection of immune infiltration levels in SKCM, as well as cumulative survival in SKCM. Meanwhile, we also used CIBERSORT to investigate the association between FLG and cancer immune infiltration. In addition, gene set enrichment analysis (GSEA) was performed using the TCGA dataset. Furthermore, data from GEO and HPA was used to validate the results.

Results

Single nucleotide polymorphism (SNP) happened more frequently than insertion or deletion, and C > T was the most common of SNV in SKCM. We selected the first 15 mutated genes by analyzing 471 melanoma samples, and the prognosis analysis showed that only the high expression of mutated FLG gene was significantly correlated with the poor prognosis of SKCM. Multivariate Cox analysis showed that age, the worse tumor status, less lymph node metastasis, and FLG expression were independent factors for prognosis. Specifically, lower infiltration levels of B cell, CD8+ T cells, neutrophils, and dendritic cells correlated with poor survival outcomes in SKCM. GSEA revealed that FLG is closely related to cancer pathways and epidermal cell proliferation. In addition, the previous conclusions can be verified from external data from GEO and HPA.

Conclusion

The discovery of mutant gene FLG as a biomarker of SKCM helps elucidate how changes in the immune environment promote the occurrence of cutaneous melanoma. Further analysis suggested that FLG might be a new predictor of SKCM prognosis.

Identification and validation of a tumor mutation burden-related signature combined with immune microenvironment infiltration in adrenocortical carcinoma

Tumor mutation burden (TMB), an emerging molecular determinant, is accompanied by microsatellite instability and immune infiltrates in various malignancies. However, whether TMB is related to the prognosis or immune responsiveness of adrenocortical carcinoma (ACC) remains to be elucidated. This paper aims to investigate the impact of TMB on the prognosis and immune microenvironment infiltration in ACC. The somatic mutation data, gene expression profile, and corresponding clinicopathological information were retrieved from TCGA. The mutation landscape was summarized and visualized with the waterfall diagram. The ACC patients were divided into low and high TMB groups based on the median TMB value and differentially expressed genes (DEGs) between the two groups were identified. Diverse functional analyses were conducted to determine the functionality of the DEGs. The immune cell infiltration signatures were evaluated based on multiple algorithms. Eventually, a TMB Prognostic Signature (TMBPS) was established and its predictive accuracy for ACC was evaluated. Single nucleotide polymorphism and C > T were found to be more common than other missense mutations. In addition, lower TMB levels indicated improved survival outcomes and were correlated with younger age and earlier clinical stage. Functional analysis suggested that DEGs were primarily related to the cell cycle, DNA replication, and cancer progression. Additionally, significant differences in infiltration levels of activated CD4+ T cells, naive B cells, and activated NK cells were observed in two TMB groups. We also found that patients with higher TMBPS showed worse survival outcomes, which was validated in the Gene Expression Omnibus database. Our study systematically analyzed the mutation and identified a TMBPS combined with immune microenvironment infiltration in ACC. It is expected that this paper can promote the development of ACC treatment strategies.

OIP5 Is a Novel Prognostic Biomarker in Clear Cell Renal Cell Cancer Correlating With Immune Infiltrates

Opa interacting protein 5 (OIP5), overexpressed in some types of human cancers, has been reported to be associated with the carcinogenesis of human cancer. However, its contribution to cancer immunity remains unknown. Furthermore, the relationship between OIP5 and cancer immunity remains uncertain. In our research, we explored the different expression of OIP5 between 539 ccRCC and 72 normal renal tissues base on TCGA data set. We analyzed the associations between OIP5 expression with ccRCC progression and survival. Next, we compared immune cell profiles in cancer tissues and normal tissues in the Cancer Genome Atlas (TCGA) ccRCC cohort. We found that the level of immune cell infiltration was correlated with the copy number of OIP5 gene in ccRCC. The effect of OIP5 on immune activity was verified by Gene Set Enrichment Analysis of RNA-seq data from 32 ccRCC cell lines in the public database. Moreover, a pathway enrichment analysis of 49 OIP5-associated immunomodulators demonstrated the involvement of the T cell receptor signaling pathway, the JAK-STAT signaling pathway, the NF-kappa B signaling pathway and the primary immunodeficiency pathway. In addition, using OIP5-associated immunomodulators, we constructed multiple-gene risk prediction signatures using the Cox regression model. Our results provided insights into the role of OIP5 in tumor immunity and revealed that OIP5 may be a potential immunotherapeutic target for ccRCC. Designated immune signature is a promising prognostic biomarker in ccRCC.

CD1B is a Potential Prognostic Biomarker Associated with Tumor Mutation Burden and Promotes Antitumor Immunity in Lung Adenocarcinoma

Purpose

Tumor mutation burden (TMB) and tumor-infiltrating lymphocytes (TILs) have been well recognized as molecular determinants of immunotherapy responsiveness. In this study, we aimed to construct a TMB prognostic model and explore biomarkers that have predictive potential for prognosis and therapeutic effect in lung adenocarcinoma (LUAD).

Patients and Methods

The TCGA, GEO and Immport databases were used to analyze the mutation profiles and immune infiltration of LUAD. TMB scores were calculated and differential analysis was conducted to identify TMB-related genes. Then, Cox regression model and survival analysis were applied to identify the prognostic genes and construct a TMB prognostic model. The expression and prognostic value of CD1B were further verified by immunohistochemistry (IHC) in 92 patient tissue samples. GSEA was performed to analyze the signaling pathways associated with CD1B expression.

Results

High-TMB samples exhibited higher infiltration of CD8+ T cells, CD4+ memory T cells, and M1 macrophages. A total of 397 TMB-related differentially expressed genes were identified, of which 47 were immune-related genes. Cox regression analyses determined 3 hub TMB-related immune genes (CD1B, SCGB3A1, and VEGFD) with prognostic effects, and a TMB prognostic model was constructed. The model demonstrated robust predictive ability in both the training (TCGA) and testing (GEO) datasets. Notably, CD1B was identified as an independent prognostic factor. IHC of clinical samples showed that low expression of CD1B was related to poor overall survival and advanced pathological stages. In addition, there was a strong positive correlation between CD1B and most immune checkpoint molecules, including PD-L1. CD1B expression was associated with immune cell infiltration and immune activation in LUAD.

Conclusion

Our study constructed a TMB prognostic model that effectively predicted the prognosis of LUAD patients. CD1B expression is correlated with better prognosis and promotes antitumor immunity in LUAD, which may serve as a potential prognostic biomarker and immune-related therapeutic target for LUAD.

CMTM6 as a master regulator of PD-L1

Immune checkpoint proteins, such as programmed cell death receptor 1 (PD-1) and its ligand (PD-L1), play critical roles in the pathology of chronic inflammatory pathological conditions, particularly cancer. In addition, the activation of PD-1/PD-L1 pathway is involved in mediating resistance to certain anti-cancer chemo- and immuno-therapeutics. Unfortunately, targeting the PD-1/PD-L1 pathway by the available anti-PD-1/PD-L1 drugs can benefit only a small proportion of cancer patients. Thus, studying the factors that regulate the expression of these immune checkpoint proteins is of central importance in this context. Recent investigations have identified CMTM6 and, to a lesser extent, CMTM4, as master regulators of PD-L1 expression in various cancer cells. Understanding the mechanisms by which such proteins upregulate the expression of PD-L1 in tumor cells, and determining the potential regulators of CMTM6 expression in different types of cancers will accelerate the development of new therapeutic targets and/or lead to the enhancement of the currently available PD-1/PD-L1 blockade therapies.

The clinical and prognostic significance of CMTM6/PD-L1 in oncology

The recent discovery of CMTM6 and to a lesser extent CMTM4, two members of the chemokine-like factor (CKLF)-like MARVEL transmembrane domain-containing family, as master positive regulators of PD-L1 expression, the primary ligand of programmed cell death 1 (PD-1), on tumor and immune cells has opened new horizons for investigating the role of CMTM6/CMTM4 in different aspects of oncology including their clinical and prognostic values in different cancer types. The absence of a specific review article addressing the available results about the clinical and prognostic roles of CMTM6 alone and/or in combination with PD-L1 in cancer has encouraged us to write this paper.

Abundant expression of ferroptosis-related SAT1 is related to unfavorable outcome and immune cell infiltration in low-grade glioma

Background

Low-grade glioma (LGG) is susceptible to ferroptosis, which is involved in TMZ resistance. Ferroptosis induction can enhance the sensitivity to TMZ and synergistically kill glioma cells. T cell-promoted tumor ferroptosis is a vital anti-tumor mechanism of immune checkpoint inhibitors. The SAT1 activation is closely related to ferroptosis upon ROS induction due to the upregulation of arachidonate 15-lipoxygenase (ALOX15) expression.

Methods

The expression of SAT1 in pan-cancer and corresponding normal tissue from the TCGA data portal was primarily explored. The landscape of SAT1 and immune cell infiltration and their corresponding gene marker sets in different tissues were further explored. Additionally, we evaluated the relationships between SAT1 and the clinicopathologic parameters of LGG, and the disease-specific survival (DSS), progression-free interval (PFI), and overall survival (OS) were also assessed using KM survival curves and multivariate analysis in LGG. Meanwhile, the Gene Set Enrichment Analysis (GSEA) was also implemented to determine the potential effect of the SAT1 gene in LGG. Furthermore, the predictive power of SAT1 was validated using an independent LGG cohort from the Chinese Glioma Genome Atlas (CGGA) data.

Results

In general, the expression of SAT1 is different between most tumors and their adjacent normal tissues. The results demonstrated that SAT1 expression is positively associated with TMB in LGG, BRCA, and THYM. The results displayed that the expression level of SAT1 is obviously correlated with the level of infiltrating macrophages and CD8 + T cells, and the levels of most immune gene sets were associated with the SAT1 expression in LGG. Interestingly, univariate and multivariate models significantly indicated that the OS and PFI of patients with LGG with high SAT1 levels were poorer than those with low SAT1 expression in the TCGA LGG cohort. GSEA showed that SAT1 was involved in immune regulation and multiple signaling pathways. Finally, our analysis demonstrated that SAT1 was closely associated with IDH mutation, 1p19q codeletion, chemoradiotherapy resistance and disease recurrence.

Conclusions

Abundant expression of SAT1 was related to poor disease prognosis and abundant immune cell infiltration in LGG.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09313-w.

Identification of SCN7A as the key gene associated with tumor mutation burden in gastric cancer

Objective

Previous studies have shown that tumor mutation burden (TMB) in cancer is associated with prognosis. The purpose of this study is to identify TMB related genes in gastric cancer (GC) and to explore their prognostic value.

Methods

In our research, weighted gene coexpression network analysis (WGCNA) algorithm was used to cluster the most relevant TMB modules in the Cancer Genome Atlas (TCGA) database. Limma package was used to screen the differentially expressed genes, and the intersection was identified as hub genes. We used gene expression profiling interactive analysis (GEPIA) and survival algorithm to analyze the clinical characteristics and prognosis of hub genes in tumor and normal tissue samples of TCGA and Gene Expression Omnibus cohort respectively. We also used CIBERSORT algorithm to calculate the proportion of 22 tumor immune cells in the high and low expression subgroups of hub genes. In addition, we used gene set enrichment analysis (GSEA) to predict the biological function of hub genes. P < 0.05 was considered statistically significant.

Results

In the TCGA cohort, TMB was significantly correlated with the clinical features of GC (P < 0.05). Through WGCNA and differential gene analysis, we identified SCN7A as the hub gene (P < 0.05, |log2fc|> 1, and mm > 0.8). We found that the expression of SCN7A in tumor tissues was lower than that in normal tissues, and its expression level was also related to overall survival rate and tumor stage. GSEA analysis showed that SCN7A low expression group was enriched with "DNA replication", "base extension repair" and "proteasome" gene sets in GC. In addition, we found that there were significant differences in the infiltration degree of 7 kinds of immune cells between the two groups.

Conclusion

TMB can indicate the prognosis of gastric cancer. SCN7A is a hub gene associated with TMB, and its low expression is associated with better prognosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02112-4.

Systematic evaluation of the prognostic and immunological role of PDLIM2 across 33 cancer types

The protein PDLIM2 regulates the stability of various transcription factors and is required for polarized cell migration. However, the clinical relevance and immune infiltration of PDLIM2 in cancer are not well-understood. We utilized The Cancer Genome Atlas and Genotype-Tissue Expression database to characterize alterations in PDLIM2 in pan-cancer. TIMER was used to explore PDLIM2 expression and immune infiltration levels. We assessed the correlation between PDLIM2 expression and immune-associated gene expression, immune score, tumor mutation burden, and DNA microsatellite instability. PDLIM2 significantly affected the prognosis of various cancers. Increased expression of PDLIM2 was significantly correlated with the tumor grade in seven types of tumors. The expression level of PDLIM2 was positively correlated with immune infiltrates, including B cells, CD8+ T cells, CD4+ T cells, neutrophils, macrophages, and dendritic cells in bladder urothelial, kidney renal papillary cell, and colon adenocarcinoma. High expression levels of PDLIM2 tended to be associated with higher immune and stromal scores. PDLIM2 expression was associated with the tumor mutation burden in 12 cancer types and microsatellite instability in 5 cancer types. PDLIM2 levels were strongly correlated with diverse immune-related genes. PDLIM2 can act as a prognostic-related therapeutic target and is correlated with immune infiltrates in pan-cancer.

Immunotherapy in HER2-Positive Breast Cancer: A Systematic Review

Introduction

The clinical outcome of HER2-positive breast cancer patients changed with the use of anti-Her therapies, though it still remains an aggressive and fatal disease. Implementation of immune checkpoint inhibitors in HER2-positive Breast cancer is a concept supported by the reported biological and preclinical data.

Methods

We conducted a systematic review of the current literature involving immune checkpoint inhibitors alone or in combination with targeted therapies or chemotherapy finalized or running in HER2-positive breast cancer.

Results

Twelve clinical trials and 2 case reports were identified in our study.

Conclusion

The reported clinical trials highlight that checkpoint inhibition seems to be promising in metastatic, neoadjuvant, and adjuvant settings of HER2-positive breast cancer.

Identification of Breast Cancer Immune Subtypes by Analyzing Bulk Tumor and Single Cell Transcriptomes

Background: The histological and molecular classification of breast cancer (BC) is being used in the clinical management of this disease. However, subtyping of BC based on the tumor immune microenvironment (TIME) remains insufficiently explored, although such investigation may provide new insights into intratumor heterogeneity in BC and potential clinical implications for BC immunotherapy.

Methods: Based on the enrichment scores of 28 immune cell types, we performed clustering analysis of transcriptomic data to identify immune-specific subtypes of BC using six different datasets, including five bulk tumor datasets and one single-cell dataset. We further analyzed the molecular and clinical features of these subtypes.

Results: Consistently in the six datasets, we identified three BC subtypes: BC-ImH, BC-ImM, and BC-ImL, which had high, medium, and low immune signature scores, respectively. BC-ImH displayed a significantly better survival prognosis than BC-ImL. Triple-negative BC (TNBC) and human epidermal growth factor receptor-2-positive (HER2+) BC were likely to have the highest proportion in BC-ImH and the lowest proportion in BC-ImL. In contrast, hormone receptor-positive (HR+) BC had the highest proportion in BC-ImL and the lowest proportion in BC-ImH. Furthermore, BC-ImH had the highest tumor mutation burden (TMB) and predicted neoantigens, while BC-ImL had the highest somatic copy number alteration (SCNA) scores. It is consistent with that TMB and SCNA correlate positively and negatively with anti-tumor immune response, respectively. TP53 had the highest mutation rate in BC-ImH and the lowest mutation rate in BC-ImL, supporting that TP53 mutations promote anti-tumor immune response in BC. In contrast, PIK3CA displayed the highest mutation rate in BC-ImM, while GATA3 had the highest mutation rate in BC-ImL. Besides immune pathways, many oncogenic pathways were upregulated in BC-ImH, including ErbB, MAPK, VEGF, and Wnt signaling pathways; the activities of these pathways correlated positively with immune signature scores in BC.

Conclusions: The tumors with the strong immune response (“hot” tumors) have better clinical outcomes than the tumors with the weak immune response (“cold” tumors) in BC. TNBC and HER2+ BC are more immunogenic, while HR + BC is less immunogenic. Certain HER2+ or HR + BC patients could be propitious to immunotherapy in addition to TNBC.

Prognostic value of tumor mutation burden and the relationship between tumor mutation burden and immune infiltration in HER2+ breast cancer: a gene expression-based study

BACKGROUND

Whether tumor mutation burden (TMB) correlated with improved survival outcomes or promotion of immunotherapies remained controversy in various malignancies. We aimed to explore the prognostic value of TMB and the relationship between TMB and immune infiltration in human epidermal growth factor receptor 2-positive (HER2+) breast cancer (BC).

METHODS

We downloaded somatic mutation data and clinical information for 216 HER2+ BC patients from the The Cancer Genome Atlas (TCGA) and cBioPortal databases. Patients were divided into high- and low-TMB groups through TMB calculation. Cox regression analysis was used to establish an immune- and mutant-related risk model based on 5-hub genes. The relationship between 5-hub genes mutants and the level of immune infiltration, as well as the relationship between the risk model and the immune microenvironment were analyzed by "TIMER" database.

RESULTS

TMB was negatively correlated with overall survival (OS) and disease-free survival (DFS), and high TMB may inhibit immune infiltration in HER2+ BC. Furthermore, risk score classified effectively patients into low- and high-risk groups in training and validation cohorts. The infiltration of CD4⁺ T cells and NK cells and the levels of immune checkpoint pathway genes were lower in the high-risk group, which indicated a poor prognosis.

CONCLUSIONS

Higher TMB correlated with poor survival outcomes and might inhibit the immune infiltrates in HER2+ BC. The 5-hub TMB-related signature conferred lower immune cells infiltration which deserved further validation.

Classification of lung adenocarcinoma based on stemness scores in bulk and single cell transcriptomes

•

This study explores tumor stemness based on both bulk tumor and single cell transcriptome datasets.

•

High-stemness tumors are less responsive to immunotherapy and targeted therapy compared with low-stemness tumors.

•

Many high-stemness cells are at the beginning of the cell evolution trajectory, while most low-stemness cells are in the terminal or later phase.

•

The correlations of tumor stemness with intratumor heterogeneity and tumor immunity were in the opposite direction between bulk tumors and single cells.

Tumor stemness is associated with tumor progression and therapy resistance. The recent advances in sequencing, genomics, and computational technologies have facilitated investigation into the tumor stemness cell-like characteristics. We identified subtypes of lung adenocarcinoma (LUAD) in bulk tumors or single cells based on the enrichment scores of 12 stemness signatures by clustering analysis of their transcriptomic profiles. Three stemness subtypes of LUAD were identified: St-H, St-M, and St-L, having high, medium, and low stemness signatures, respectively, consistently in six different datasets. Among the three subtypes, St-H was the most enriched in epithelial-mesenchymal transition, invasion, and metastasis signaling, genomically instable, irresponsive to immunotherapies and targeted therapies, and hence had the worst prognosis. We observed that intratumor heterogeneity was significantly higher in high-stemness than in low-stemness bulk tumors, but significantly lower in high-stemness than in low-stemness single cancer cells. Moreover, tumor immunity was stronger in high-stemness than in low-stemness cancer cells, but weaker in high-stemness than in low-stemness bulk tumors. These differences between bulk tumors and single cancer cells could be attributed to the non-tumor cells in bulk tumors that confounded the results of correlation analysis. Furthermore, pseudotime analysis showed that many St-H cells were at the beginning of the cell evolution trajectory, compared to most St-L cells in the terminal or later phase, suggesting that many low-stemness cells are originated from high-stemness cells. The stemness-based classification of LUAD may provide novel insights into the tumor biology as well as precise clinical management of this disease.

Current Perspectives on the Immunosuppressive Niche and Role of Fibrosis in Hepatocellular Carcinoma and the Development of Antitumor Immunity

Immune checkpoint inhibitors have become the mainstay of treatment for hepatocellular carcinoma (HCC). However, they are ineffective in some cases. Previous studies have reported that genetic alterations in oncogenic pathways such as Wnt/β-catenin are the important triggers in HCC for primary refractoriness. T-cell exhaustion has been reported in various tumors and is likely to play a prominent role in the emergence of HCC due to chronic inflammation and cirrhosis-associated immune dysfunction. Immunosuppressive cells including regulatory T-cells and tumor-associated macrophages infiltrating the tumor are associated with hyperprogressive disease in the early stages of immune checkpoint inhibitor treatment. In addition, stellate cells and tumor-associated fibroblasts create an abundant desmoplastic environment by producing extracellular matrix. This strongly contributes to epithelial to mesenchymal transition via signaling activities including transforming growth factor beta, Wnt/β-catenin, and Hippo pathway. The abundant desmoplastic environment has been demonstrated in pancreatic ductal adenocarcinoma and cholangiocarcinoma to suppress cytotoxic T-cell infiltration, PD-L1 expression, and neoantigen expression, resulting in a highly immunosuppressive niche. It is possible that a similar immunosuppressive environment is created in HCC with advanced fibrosis in the background liver. Although sufficient understanding is required for the establishment of immune therapies of HCC, further investigations are still required in this field.

Prediction performance of twelve tumor mutation burden panels in melanoma and non-small cell lung cancer

As a potential biomarker to predict the response to immunotherapy, tumor mutation burden (TMB) which can be estimated by the cancer gene panel (CGP) has received considerable attention. However, it is not clear which CGP is better in predicting the efficacy of immunotherapy. To evaluate the twelve CGPs, we compared them on 13 datasets of melanoma and non-small cell lung cancer (NSCLC) from the perspective of gene composition, reliability of measuring TMB and prediction performance of patient treatment benefits. The larger CGPs generally performed better, but their proportions of driver genes and function densities were smaller. The CGPs performed differently on melanoma and NSCLC patients treated with two blockades. Moreover, their ability to classify and predict patients with or without long-term clinical benefits was similar but not good enough, so it is necessary to explore a higher-performance biomarker.

Nanoparticle-Based RNAi Therapeutics Targeting Cancer Stem Cells: Update and Prospective

Cancer stem cells (CSCs) are characterized by intrinsic self-renewal and tumorigenic properties, and play important roles in tumor initiation, progression, and resistance to diverse forms of anticancer therapy. Accordingly, targeting signaling pathways that are critical for CSC maintenance and biofunctions, including the Wnt, Notch, Hippo, and Hedgehog signaling cascades, remains a promising therapeutic strategy in multiple cancer types. Furthermore, advances in various cancer omics approaches have largely increased our knowledge of the molecular basis of CSCs, and provided numerous novel targets for anticancer therapy. However, the majority of recently identified targets remain ‘undruggable’ through small-molecule agents, whereas the implications of exogenous RNA interference (RNAi, including siRNA and miRNA) may make it possible to translate our knowledge into therapeutics in a timely manner. With the recent advances of nanomedicine, in vivo delivery of RNAi using elaborate nanoparticles can potently overcome the intrinsic limitations of RNAi alone, as it is rapidly degraded and has unpredictable off-target side effects. Herein, we present an update on the development of RNAi-delivering nanoplatforms in CSC-targeted anticancer therapy and discuss their potential implications in clinical trials.

Identification of Survival and Therapeutic Response-Related Ferroptosis Regulators in Bladder Cancer through Data Mining and Experimental Validation

Simple Summary

Based on machine learning methods, we constructed a prognostic signature to calculate the survival probability of BLCA and to further investigate the underlying mechanism of the ferroptosis-related signature. We found that the signature was not only correlated with the prognostic value but was also associated with the tumor microenvironment (TME), tumor mutation burden (TMB) and the curative outcomes of both immunotherapy and chemotherapy. Furthermore, we proved the reliability of the signature in some external datasets and built a risk score evaluation nomogram for clinical use.

Abstract

Ferroptosis has been reported to regulate tumorigenesis, metastasis, drug resistance and the immune response. However, the potential roles of ferroptosis regulators in the advancement of bladder cancer remain to be explored. We systematically evaluated the multidimensional alteration landscape of ferroptosis regulators in bladder cancer and checked if their expression correlated with the ferroptosis index. We used least absolute shrinkage and selection operator regression to form a signature consisting of seven ferroptosis regulator. We confirmed the signature’s prognostic and predictive accuracy with five independent datasets. A nomogram was built to predict the overall survival and risk of death of patients. The relative expression of the genes involved in the signature was also clarified by real-time quantitative PCR. We found the risk score was related to tumor progression and antitumor immunity-related pathways. Moreover, there existed negative association between the relative antitumor immune cell infiltration level and the risk score, and higher tumor mutation burden was found in the group of lower risk score. We used The Tumor Immune Dysfunction and Exclusion database and IMvigor210 cohort having immunotherapy efficacy results to confirm the prediction function of the risk score. Furthermore, the ferroptosis regulator signature could also reflect the chemotherapy sensitivity of bladder cancer.

Checkpoint Inhibition in Bladder Cancer: Clinical Expectations, Current Evidence, and Proposal of Future Strategies Based on a Tumor-Specific Immunobiological Approach

Simple Summary

In contrast with other strategies, immunotherapy is a treatment aimed at empowering the patient’s immune system in order to increase immunity and the response against cancer. Recently, a new class of drugs, immune checkpoint inhibitors, has shown potential in increasing treatment chances for patients with bladder cancers, improving their survival. However, predicting the response to immune checkpoint inhibition is important, since only a group of patients develop a good response. Biomarkers to predict the response to checkpoint inhibition must identify tumors’ and patients’ specific profiles. This study reviews the current knowledge on this most relevant clinical topic, focusing on bladder cancer, going from basic science to ongoing clinical trials and available clinical evidence. Finally, a critical analysis of published data is provided, and an original panel of biomarkers, able to select the right patients for treatments, based on patient-specific immune profiling, is proposed.

Abstract

In contrast with other strategies, immunotherapy is the only treatment aimed at empowering the immune system to increase the response against tumor growth. Immunotherapy has a role in the treatment of bladder cancer (BC) due to these tumors’ high tumor mutational burden (TMB) and mostly prominent immune infiltrate. The therapy or combination has to be adjusted to the tumor’s immunobiology. Recently, a new class of immunotherapeutic agents, immune checkpoint inhibitors (ICI), has shown potential in increasing treatment chances for patients with genitourinary cancers, improving their oncological outcomes. The clinical efficacy of ICI has been shown in both the first-line treatment of cisplatin-ineligible patients, with programmed death ligand 1 (PD-L1)-positive tumors (atezolizumab, pembrolizumab), and in second-line settings, for progression after platinum-based chemotherapy (atezolizumab, pembrolizumab, and nivolumab for FDA and EMA; durvalumab and avelumab for FDA alone). Predicting the response to ICI is important since only a subset of patients undergoing ICI therapy develop a concrete and lasting response. Most of the patients require a different therapy or therapy combination to achieve tumor control. The cancer immunity cycle provides a conceptual framework to assist therapy selection. Biomarkers to predict response to ICI must identify where the cancer immunity cycle is disrupted. We reviewed the current knowledge on ICI treatment in BC, going from basic science to current data and available clinical evidence. Secondly, a critical analysis of published data is provided, and an original panel of biomarkers able to predict response to ICI treatment, based on tumor-specific immune profiling, is proposed.

Pan-cancer analyses reveal that increased Hedgehog activity correlates with tumor immunosuppression and resistance to immune checkpoint inhibitors

Background

Immune checkpoint inhibitors (ICIs) have shown numerous clinical benefits in multiple cancer types, but good predictive biomarkers are severely lacking. Although increasing evidence has linked Hedgehog (Hh) signaling pathway with tumor development, a systematic investigation for its potential as a biomarker remains elusive.

Methods

We collected and analyzed the transcriptional data and clinical outcomes of diverse cancers from the Cancer Genome Atlas and four published ICI datasets. Hh activity was estimated by conducting a single‐sample gene‐set enrichment analysis (ssGSEA) for the Hh‐related genes and calculating the ssGSEA score in each tumor sample.

Results

Our findings suggest that tumors with high Hh activity displayed multiple immunosuppressive characteristics, including lack of anti‐tumor response pathways, downregulation of immune effectors, enrichment of immunosuppressive cells and chemokines, and activation of immunosuppressive signaling. Notably, patients in the non‐response group had enriched Hh activity and showed worse overall survival (OS; pooled HR = 1.50, 95% CI = 1.02–2.21, p = 0.039). In the subgroup of high programmed cell death ligand 1 (PD‐L1) expression, patients who harbored high Hh activity displayed a dramatically lower response rate to ICIs and a strikingly worse OS (pooled HR = 2.89, 95% CI = 1.53–5.49, p < 0.001).

Conclusion

Increased Hh activity correlates with tumor immunosuppression across diverse cancers. Hh activity is not only a predictive biomarker for resistance to ICIs but can also better predict clinical outcomes in combination with PD‐L1 expression.

Development and Validation of Tumor Immunogenicity Based Gene Signature for Skin Cancer Risk Stratification

Melanoma is one of the most aggressive types of skin cancer, with significant heterogeneity in overall survival. Currently, tumor-node-metastasis (TNM) staging is insufficient to provide accurate survival prediction and appropriate treatment decision making for several types of tumors, such as those in melanoma patients. Therefore, the identification of more reliable prognosis biomarkers is urgently essential. Recent studies have shown that low immune cells infiltration is significantly associated with unfavorable clinical outcome in melanoma patients. Here we constructed a prognostic-related gene signature for melanoma risk stratification by quantifying the levels of several cancer hallmarks and identify the Wnt/β-catenin activation pathway as a primary risk factor for low tumor immunity. A series of bioinformatics and statistical methods were combined and applied to construct a Wnt-immune-related prognosis gene signature. With this gene signature, we computed risk scores for individual patients that can predict overall survival. To evaluate the robustness of the result, we validated the signature in multiple independent GEO datasets. Finally, an overall survival-related nomogram was established based on the gene signature and clinicopathological features. The Wnt-immune-related prognostic risk score could better predict overall survival compared with standard clinicopathological features. Our results provide a comprehensive map of the oncogene-immune-related gene signature that can serve as valuable biomarkers for better clinical decision making.

Molecular markers of systemic therapy response in urothelial carcinoma

Identification of reliable molecular biomarkers that can complement clinical practice represents a fascinating challenge in any cancer field. Urothelial carcinoma is a very heterogeneous disease and responses to systemic therapies, and outcomes after radical cystectomy are difficult to predict. Advances in molecular biology such as next generation sequencing and whole genome or transcriptomic analysis provide promising platforms to achieve a full understanding of the biology behind the disease and can identify emerging predictive biomarkers. Moreover, the ability to categorize patients' risk of recurrence after curative treatment, or even predict benefit from a conventional or targeted therapies, represents a compelling challenge that may reshape both selection for tailored treatment and disease monitoring. Progress has been made but currently no molecular biomarkers are used in the clinical setting to predict response to systemic agents in either neoadjuvant or adjuvant settings highlighting a relevant unmet need. Here, we aim to present the emerging role of molecular biomarkers in predicting response to systemic agents in urothelial carcinoma.

A heat-shocked melanoma cell lysate vaccine enhances tumor infiltration by prototypic effector T cells inhibiting tumor growth

BACKGROUND

Immune checkpoint blocker (ICB) therapy has shown survival benefits for some patients with cancer. Nevertheless, many individuals remain refractory or acquire resistance to treatment, motivating the exploration of complementary immunotherapies. Accordingly, cancer vaccines offer an attractive alternative. Optimal delivery of multiple tumor-associated antigens combined with potent adjuvants seems to be crucial for vaccine effectiveness.

METHODS

Here, a prototype for a generic melanoma vaccine, named TRIMELVax, was tested using B16F10 mouse melanoma model. This vaccine is made of heat shock-treated tumor cell lysates combined with the Concholepas concholepas hemocyanin as adjuvant.

RESULTS

While B16F10 lysate provides appropriate melanoma-associated antigens, both a generic human melanoma cell lysate and hemocyanin adjuvant contributes with danger signals promoting conventional dendritic type 1 cells (cDC1), activation, phagocytosis and effective antigen cross-presentation. TRIMELVax inhibited tumor growth and increased mice survival, inducing cellular and humoral immune responses. Furthermore, this vaccine generated an increased frequency of intratumor cDC1s but not conventional type 2 dendritic cells (cDC2s). Augmented infiltration of CD3⁺, CD4⁺ and CD8⁺ T cells was also observed, compared with anti-programmed cell death protein 1 (PD-1) monotherapy, while TRIMELVax/anti-PD-1 combination generated higher tumor infiltration of CD4⁺ T cells. Moreover, TRIMELVax promoted an augmented proportion of PD-1^lo CD8⁺ T cells in tumors, a phenotype associated with prototypic effector cells required for tumor growth control, preventing dysfunctional T-cell accumulation.

CONCLUSIONS

The therapeutic vaccine TRIMELVax efficiently controls the weakly immunogenic and aggressive B16F10 melanoma tumor growth, prolonging tumor-bearing mice survival even in the absence of ICB. The strong immunogenicity shown by TRIMELVax encourages clinical studies in patients with melanoma.