OBJECTIVE: Although immune checkpoint inhibitors (ICPi) for salivary gland cancer (SGC) have been investigated in clinical trials, details of the tumor immune microenvironment (TIME) remain unclear. This research aimed to elucidate the TIME of SGC and its relationship with tumor mutation burden (TMB) and to explore the rationale for the applicability of ICPi.
METHODS: We selected five pathological types, namely adenoid cystic carcinoma (ACC); adenocarcinoma, not otherwise specified (ANOS); salivary duct carcinoma (SDC); and low/high-grade mucoepidermoid carcinoma (MEClow/high). We investigated the TIME and TMB of each pathological type. TIME was evaluated by multiplexed fluorescent immunohistochemistry. TMB was measured by next-generation sequencing.
RESULTS: ACC and MEChigh showed the lowest and highest infiltration of immune effector and suppressor cells in both tumor and stroma. ANOS, SDC, and MEClow showed modest infiltration of immune effector cells in tumors. Correlation analysis showed a positive correlation between CD3+CD8+ T cells in tumor and TMB (r = 0.647). CD3+CD8+ T cells in tumors showed a positive correlation with programmed cell death-ligand 1 expression in tumor cells (r = 0.513) and a weak positive correlation with CD3+CD4+Foxp3+ cells in tumors (r = 0.399). However, no correlation was observed between CD3+CD8+ T cells and CD204+ cells in tumors (r = -0.049).
CONCLUSIONS: The TIME of ACC was the so-called immune desert type, which may explain the mechanisms of the poor response to ICPi in previous clinical trials. On the other hand, MEChigh was the immune-inflamed type, and this may support the rationale of ICPi for this pathological subtype.

BACKGROUND: Tumor mutation burden (TMB) and VHL mutation play a crucial role in the management of patients with clear cell renal cell carcinoma (ccRCC), such as guiding adjuvant chemotherapy and improving clinical outcomes. However, the time-consuming and expensive high-throughput sequencing methods severely limit their clinical applicability. Predicting intratumoral heterogeneity poses significant challenges in biology and clinical settings. Our aimed to develop a self-supervised attention-based multiple instance learning (SSL-ABMIL) model to predict TMB and VHL mutation status from hematoxylin and eosin-stained histopathological images.
METHODS: We obtained whole slide images (WSIs) and somatic mutation data of 350 ccRCC patients from The Cancer Genome Atlas for developing SSL-ABMIL model. In parallel, 163 ccRCC patients from Clinical Proteomic Tumor Analysis Consortium cohort was used as independent external validation set. We systematically compared three different models (Wang-ABMIL, Ciga-ABMIL, and ImageNet-MIL) for their ability to predict TMB and VHL alterations.
RESULTS: We first identified two groups of populations with high- and low-TMB (cut-off point = 0.9). In two independent cohorts, the Wang-ABMIL model achieved the highest performance with decent generalization performance (AUROC = 0.83 ± 0.02 and 0.8 ± 0.04 in predicting TMB and VHL, respectively). Attention heatmaps revealed that the Wang-ABMIL model paid the highest attention to tumor regions in high-TMB patients, while in VHL mutation prediction, non-tumor regions were also assigned high attention, particularly the stromal regions infiltrated by lymphocytes.
CONCLUSIONS: Our results indicated that SSL-ABMIL can effectively extract histological features for predicting TMB and VHL mutation, demonstrating promising results in linking tumor morphology and molecular biology.

OBJECTIVE: The purpose of this study is to compare genetic mutations, tumor mutation burden (TMB), and the effects of molecular targeted drugs and immune checkpoint inhibitors (ICIs) in head and neck mucosal melanoma (HNMUM) with those in skin melanoma (SKM) and ocular melanoma (OM).
METHODS: Data were analyzed for 72 consecutive patients with HNMUM, including 366 with SKM and 31 with OM, registered at the Japan National Cancer Center, Center for Cancer Genomics and Advanced Therapeutics (C-CAT) between June 2019 and October 2023. Genetic alterations and TMB were determined by FoundationOne CDx next-generation sequencing.
RESULTS: The top 10 mutations in HNMUM were RAD21 (47.2%), NBN (45.8%), MYC (40.3%), LYN (31.9%), NRAS (29.1%), IRF4 (23.6%), DAXX (22.2%), KIT (22.2%), NOTCH3 (20.8%), and DDR1 (19.4%), with 16.6 ± 0.8 (mean ± SEM) mutations/individual. In SKM, BRAF (p = 0.04) mutation was associated with a significantly better prognosis. The TMB values were 5.7 ± 2.1 (mean ± SEM) in HNMUM, 4.1 ± 0.2 in SKM, and 3.4 ± 0.9 in OM, with no significant differences among the three groups. The median survival time for patients with distant metastases was 803 (95% confidence interval: 539-NA) days for HNMUM, 1413 (831-2172) days for SKM, and 1138 (438-NA) days for OM.
CONCLUSIONS: The top 10 mutations in HNMUM are closer to those in OM than those in SKM. There was no significant difference in TMB values or survival rates with regard to the therapeutic effect of ICIs among the diseases, which suggests that current treatment of HNMUM with ICIs is appropriate.
METHODS: 3 Laryngoscope, 2024.

UNASSIGNED: A minority of patients with MSS tumors present a high tumor mutation burden (TMB) without underlying MMR defects.
UNASSIGNED: Publicly available genomic series were assessed for identification of patients with MSS gastric gastroesophageal junction, and esophageal adenocarcinomas and a high TMB, defined as more than 10 mutations per Mb. These were compared with MSS cancers and a low TMB for genetic alterations and for survival outcomes.
UNASSIGNED: Patients with MSS cancers with high TMB in the MSK series were older but did not differ in other clinicopathologic parameters compared with MSS patients with low TMB. Mutations in tumor suppressors TP53 and APC and oncogenes KRAS and ERBB4 as well as amplifications of ERBB2 were more prevalent in the high TMB group of MSS cancers. Mutations in DDR associated genes, in epigenetic modifiers and in genes associated with immune response were more prevalent in the hIgh TMB group patients. However, high TMB was not associated with an improved survival in MSS gastric/gastroesophageal junction/esophageal adenocarcinomas (Log Rank p = 0.5).
UNASSIGNED: MSS Gastric/gastroesophageal junction/esophageal adenocarcinomas with TMB above 10 mutations per Mb possess a genomic landscape with increased alteration frequencies in common gastroesophageal cancer genes and pathways.

Low-expression antigens, especially neoantigens, pose a significant challenge in immunotherapy for low immunogenicity pancreatic cancer. Increasing the tumor mutation burden is crucial to enhance the expression of tumor antigens and improve tumor immunogenicity. However, the incomplete intervention in DNA stability hampers effective elevation of the tumor mutation burden, thus reducing the probability of neoantigen. To address this issue, we have developed a novel nano-regulator that intervenes in the DNA stability of tumor cells, thereby enhancing tumor mutations. This nano-regulator comprises metal-organic frameworks (MOFs) encapsulating DNA damage agent doxorubicin and DNA damage repair inhibitor siRNA-ATR, enabling simultaneous induction of DNA mutations and inhibition of their repair. Importantly, this regulator, named as MOFDOX&siATR, can modulate the tumor gene expression profile, induce the production of neoantigens of Atp8b1, and enhance the immunogenicity of pancreatic cancer. The characteristics of DNA stability intervention by MOFDOX&siATR hold promise for augmenting the immune response in low immunogenic tumors, making it a potential nanomedicine for the treatment of pancreatic cancer.

UNASSIGNED: Tumor mutation burden (TMB) remains a promising but ambiguous predictive biomarker for the efficacy of immune checkpoint inhibitors (ICIs). We investigated the predictive value of TMB in patients with advanced non-small cell lung cancer (NSCLC) treated by ICI-containing therapies under strictly matched clinical settings.
UNASSIGNED: PubMed, Embase, Cochrane Central, ClinicalTrials.gov, and bioRxiv databases were searched till October 16, 2021. All randomized controlled trials (RCTs) that compared patients with high TMB (TMB-H) and low TMB (TMB-L) and provided hazard ratio (HR) and corresponding 95% confidence interval (CI) in advanced NSCLC patients receiving ICIs were included, and mirror-based meta-analysis was performed (Part1). Bayesian network meta-analysis was conducted to investigate the efficacy of distinct first-line regimens in TMB-H and TMB-L groups (Part2). Public cohorts were used for validation and further exploration (Part3).
UNASSIGNED: Twelve RCTs (n=5527) and 5 public cohorts (n=573) were included. In Part1, TMB-H patients generally exhibited a more significant progression-free survival (PFS) benefit from ICI-containing therapies compared to TMB-L patients (HR=0.58, 95% CI: 0.49-0.67, P < 0.0001). In Part2, anti-PD-1 plus chemotherapy ranked best for PFS in both TMB-H and TMB-L groups. Anti-PD-L1 plus anti-CTLA-4 therapies indicated better PFS and overall survival (OS) benefit than single ICI and chemotherapy in the TMB-H group, but ranked worst in the TMB-L group. Finally, TMB was validated to be an independent predictive biomarker from programmed cell death-ligand 1 (PD-L1) expression in Part3, which could further distinguish beneficiaries of ICI-containing therapies with PD-L1 < 50%.
UNASSIGNED: TMB-H could be a predictive biomarker independent of PD-L1 expression to identify beneficiaries of ICI-containing therapy in advanced NSCLC patients.

Data on prevalence of programmed death ligand-1 (PD-L1) expression and its correlation with tumor biomarkers in Chinese patients with muscle-invasive urothelial bladder cancer (MIUBC) are scarce. We investigated the prevalence of PD-L1 expression, PD-L1 expression in tumor cells (TC) and immune cells (IC), and its correlation with tumor biomarkers (CD8+ T cells and tumor mutation burden [TMB]) in Chinese patients with newly diagnosed MIUBC (NCT03433924). Of 248 patients enrolled, 229 with PD-L1 data available were analysed. High PD-L1 expression (≥ 25% of TC or IC with PD-L1 expression) was observed in 120 (52.4%) patients. 59 cases showed positive staining in ≥ 25% of TC, and 82 cases had positive staining in ≥ 25% of IC. High expression of CD8+ T cell and TMB (> 10 mutations/megabase) was observed in 44.5% and 54.1% patients, respectively. A positive correlation was observed between percentage of TC with membrane PD-L1 positivity and CD8+ T cells (0.34; P < 0.001) and between IC with membrane PD-L1 positivity and CD8+ T cells (0.44; P < 0.001). There is high prevalence of PD-L1 expression in Chinese patients with MIUBC, suggesting that a sizable subset of patients could benefit from immunotherapy. The correlation of PD-L1 expression with tumor biomarkers provide clues for mechanisms underlying the effects of biomarkers for predicting efficacy.

BACKGROUND: Human cytomegalovirus (HCMV) is a herpesvirus that can infect various cell types and modulate host gene expression and immune response. It has been associated with the pathogenesis of various cancers, but its molecular mechanisms remain elusive.
METHODS: We comprehensively analyzed the expression of HCMV pathway genes across 26 cancer types using the Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases. We also used bioinformatics tools to study immune invasion and tumor microenvironment in pan-cancer. Cox regression and machine learning were used to analyze prognostic genes and their relationship with drug sensitivity.
RESULTS: We found that HCMV pathway genes are widely expressed in various cancers. Immune infiltration and the tumor microenvironment revealed that HCMV is involved in complex immune processes. We obtained prognostic genes for 25 cancers and significantly found 23 key genes in the HCMV pathway, which are significantly enriched in cellular chemotaxis and synaptic function and may be involved in disease progression. Notably, CaM family genes were up-regulated and AC family genes were down-regulated in most tumors. These hub genes correlate with sensitivity or resistance to various drugs, suggesting their potential as therapeutic targets.
CONCLUSIONS: Our study has revealed the role of the HCMV pathway in various cancers and provided insights into its molecular mechanism and therapeutic significance. It is worth noting that the key genes of the HCMV pathway may open up new doors for cancer prevention and treatment.

UNASSIGNED: To investigate the correlation between programmed death ligand 1(PD-L1), tumor mutation burden (TMB) and the short-term efficacy and clinical characteristics of anti-PD-1 immune checkpoint inhibitor combination chemotherapy in NSCLC patients. The efficacy of the prediction model was evaluated.
UNASSIGNED: A total of 220 NSCLC patients receiving first-line treatment with anti-PD-1 immune checkpoint inhibitor combined with chemotherapy were retrospectively collected. The primary endpoint was short-term efficacy ORR. The correlation between short-term efficacy, PD-L1, TMB, and clinical characteristics using χ2 test or t-test was evaluated. Screen the independent prognostic factors using univariate and multivariate logistic regression analyses, and construct a nomogram prediction model using the \"rms\" package in R software. Using receiver operating characteristic (ROC) curve analysis to evaluate the independent Prognostic factors and the prediction model. Using decision curve analysis (DCA) to verify the superiority of the prediction model.
UNASSIGNED: The mean values of PD-L1, TMB, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, and albumin were the highest in the ORR group, PD-L1 expression and TMB correlated with epidermal growth factor receptor expression. Multivariate analyses showed that PD-L1, TMB, and neutrophil were independent prognostic factors for ORR. The area under the ROC curve (AUC) values of the ROC constructed based on these three indicators were 0.7104, 0.7139, and 0.7131, respectively. The AUC value under the ROC of the nomogram model was 0.813. The DCA of the model showed that all three indicators used together to build the prediction model of the net return were higher than those of the single indicator prediction model.
UNASSIGNED: PD-L1, TMB, and neutrophils are independent prognostic factors for short-term efficacy. The nomogram prediction model constructed using these three indicators can further improve predictive efficacy of ICIs in patients with NSCLC.

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in the treatment of gastric cancer (GC). The application of tumor mutational burden (TMB) in predicting immunotherapy efficacy in GC patients is limited and controversial, emphasizing the importance of optimizing TMB-based patient selection. By combining TMB and major histocompatibility complex (MHC) related hub genes, we established a novel TM-Score. This score showed superior performance for immunotherapeutic selection (AUC = 0.808) compared to TMB, MSI status, and EBV status. Additionally, it predicted the prognosis of GC patients. Subsequently, a machine learning model adjusted by the TM-Score further improved the accuracy of survival prediction (AUC > 0.8). Meanwhile, we found that GC patients with low TM-Score had a higher mutation frequency, higher expression of HLA genes and immune checkpoint genes, and higher infiltration of CD8+ T cells, CD4+ helper T cells, and M1 macrophages. This suggests that TM-Score is significantly associated with tumor immunogenicity and tumor immune environment. Notably, based on the RNA-seq and scRNA-seq, it was found that AKAP5, a key component gene of TM-Score, is involved in anti-tumor immunity by promoting the infiltration of CD4+ T cells, NK cells, and myeloid cells. Additionally, siAKAP5 significantly reduced MHC-II mRNA expression in the GC cell line. In addition, our immunohistochemistry assays confirmed a positive correlation between AKAP5 and human leukocyte antigen (HLA) expression. Furthermore, AKAP5 levels were higher in patients with longer survival and those who responded to immunotherapy in GC, indicating its potential value in predicting prognosis and immunotherapy outcomes. In conclusion, TM-Score, as an optimization of TMB, is a more precise biomarker for predicting the immunotherapy efficacy of the GC population. Additionally, AKAP5 shows promise as a therapeutic target for GC.