Elevated TNFRSF4 gene expression is a predictor of poor prognosis in non-M3 acute myeloid leukemia

OX40/OX40 ligand and its role in precision immune oncology

Immune checkpoint inhibitors have changed the treatment landscape for various malignancies; however, their benefit is limited to a subset of patients. The immune machinery includes both mediators of suppression/immune evasion, such as PD-1, PD-L1, CTLA-4, and LAG-3, all of which can be inhibited by specific antibodies, and immune-stimulatory molecules, such as T-cell co-stimulatory receptors that belong to the tumor necrosis factor receptor superfamily (TNFRSF), including OX40 receptor (CD134; TNFRSF4), 4-1BB (CD137; TNFRSF9), and glucocorticoid-induced TNFR-related (GITR) protein (CD357; TNFRSF18). In particular, OX40 and its binding ligand OX40L (CD134L; TNFSF4; CD252) are critical for immunoregulation. When OX40 on activated T cells binds OX40L on antigen-presenting cells, T-cell activation and immune stimulation are initiated via enhanced T-cell survival, proliferation and cytotoxicity, memory T-cell formation, and abrogation of regulatory T cell (Treg) immunosuppressive functions. OX40 agonists are in clinical trials both as monotherapy and in combination with other immunotherapy agents, in particular specific checkpoint inhibitors, for cancer treatment. To date, however, only a minority of patients respond. Transcriptomic profiling reveals that OX40 and OX40L expression vary between and within tumor types, and that only ~ 17% of cancer patients have high OX40 and low OX40L, one of the expression patterns that might be theoretically amenable to OX40 agonist enhancement. Taken together, the data suggest that the OX40/OX40L machinery is a critical part of the immune stimulatory system and that understanding endogenous expression patterns of these molecules and co-existing checkpoints merits further investigation in the context of a precision immunotherapy strategy for cancer therapy.

Aging-related biomarker discovery in the era of immune checkpoint inhibitors for cancer patients

Older patients with cancer, particularly those over 75 years of age, often experience poorer clinical outcomes compared to younger patients. This can be attributed to age-related comorbidities, weakened immune function, and reduced tolerance to treatment-related adverse effects. In the immune checkpoint inhibitors (ICI) era, age has emerged as an influential factor impacting the discovery of predictive biomarkers for ICI treatment. These age-linked changes in the immune system can influence the composition and functionality of tumor-infiltrating immune cells (TIICs) that play a crucial role in the cancer response. Older patients may have lower levels of TIICs infiltration due to age-related immune senescence particularly T cell function, which can limit the effectivity of cancer immunotherapies. Furthermore, age-related immune dysregulation increases the exhaustion of immune cells, characterized by the dysregulation of ICI-related biomarkers and a dampened response to ICI. Our review aims to provide a comprehensive understanding of the mechanisms that contribute to the impact of age on ICI-related biomarkers and ICI response. Understanding these mechanisms will facilitate the development of treatment approaches tailored to elderly individuals with cancer.

FOXD1 expression-based prognostic model for uveal melanoma

FOXD1, a new member of the FOX transcription factor family, serves as a mediator and biomarker for cell reprogramming. But its contribution to prognosis of uveal melanoma (UVM) is unclear. This study demonstrated that FOXD1 might promote tumor growth and invasion, because FOXD1 expression was negatively correlated with overall survival, progression-free survival, and disease-specific survival in UVM patients. This conjecture was verified in cell culture with human uveal melanoma cell line (MUM2B) as model cells. Additionally, the biological mechanisms of FOXD1 based on FOXD1-related genomic spectrum, molecular pathways, tumor microenvironment, and drug treatment sensitivity were examined using The Cancer Genome Atlas (TCGA) database, aiming to reasonably explain why FOXD1 leads to poor prognosis of UVM. On these bases, a novel tumor prognostic model was established using the FOXD1-related immunomodulators TMEM173, TNFRSF4, TNFSF13, and ULBP1, which will enable the stratification of disease seriousness and clinical treatment for patients.

A Ferroptosis-Related lncRNAs Signature Predicts Prognosis of Colon Adenocarcinoma

(1) Ferroptosis is a type of cellular death caused by lipid-dependent iron peroxide, which plays a major role in cancer. Long noncoding RNAs (lncRNAs) are increasingly recognized as key regulating substances in ferroptosis; (2) RNA sequencing expressions and clinical data of 519 patients with colon adenocarcinoma (COAD) were downloaded from The Cancer Genome Atlas (TCGA) database. The expression levels of lncRNAs related to ferroptosis were screened with Pearson correlation analysis. Differential genes were enriched with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. LncRNAs related to ferroptosis were determined with univariate Cox regression and multivariate Cox regression analyses, and patients with COAD were classified into high- and low-risk subgroups according to their median risk score. The prognostic value was further examined, and the association between ferroptosis-related lncRNAs (frlncRNAs) and survival in patients with high and low risks of COAD was validated. A TCGA-COAD data set was used for receiver operating characteristic (ROC) analysis and detrended correspondence analysis (DCA) to assess prediction accuracy. Finally, a nomogram was constructed to predict survival probability; (3) We obtained a model consisting of a five-frlncRNAs signature comprising AP003555.1, AP001469.3, ITGB1-DT, AC129492.1, and AC010973.2 for determining the overall survival (OS) of patients with COAD. The survival analysis and ROC curves showed that the model had good robustness and predictive performance on the TCGA training set; (4) We found that a five-frlncRNAs signature may play a potential role in anti-COAD immunity. Risk characteristics based on frlncRNAs can accurately predict the prognosis and immunotherapy response of patients with COAD.

Expression of the immune checkpoint modulator OX40 indicates poor survival in acute myeloid leukemia

Despite therapeutic advances, mortality of Acute Myeloid Leukemia (AML) is still high. Currently, the determination of prognosis which guides treatment decisions mainly relies on genetic markers. Besides molecular mechanisms, the ability of malignant cells to evade immune surveillance influences the disease outcome and, among others, the expression of checkpoints modulators contributes to this. In AML, functional expression of the checkpoint molecule OX40 was reported, but the prognostic relevance of OX40 and its ligand OX40L axis has so far not been investigated. Here we described expression and prognostic relevance of the checkpoint modulators OX40 and OX40L, analyzed on primary AML cells obtained from 92 therapy naïve patients. Substantial expression of OX40 and OX40L on AML blasts was detected in 29% and 32% of the investigated subjects, respectively, without correlation between the expression of the receptor and its ligand. Whereas OX40L expression was not associated with different survival, patients with high expression levels of the receptor (OX40^high) on AML blasts survived significantly shorter than OX40^low patients (p = 0.009, HR 0.46, 95% CI 0.24–0.86), which identifies OX40 as novel prognostic marker and a potential therapeutic target in AML patients.

An immune-related lncRNA pairs signature to identify the prognosis and predict the immune landscape of laryngeal squamous cell carcinoma

Background

Laryngeal squamous cell carcinoma (LSCC) is the most common squamous cell carcinoma. Though significant effort has been focused on molecular pathogenesis, development, and recurrence of LSCC, little is known about its relationship with the immune-related long non-coding RNA (lncRNA) pairs.

Methods

After obtaining the transcriptome profiling data sets and the corresponding clinical characteristics of LSCC patients and normal samples from The Cancer Genome Atlas (TCGA) database, a series of bioinformatic analysis was conducted to select the differently expressed immune-related lncRNAs and build a signature of immune-related lncRNA pairs. Then, the effectiveness of the signature was validated.

Results

A total of 111 LSCC patients and 12 normal samples’ transcriptome profiling data sets were retrieved from TCGA. 301 differently expressed immune-related lncRNAs were identified and 35,225 lncRNA pairs were established. After univariate Cox analysis, LASSO regression and multivariate Cox analysis, 7 lncRNA pairs were eventually selected to construct a signature. The riskscore was computed using the following formula: Riskscore = 0.95 × (AL133330.1|AC132872.3) + (-1.23)  × (LINC01094|LINC02154) + 0.65 × (LINC02575|AC122685.1) + (-1.15)  × (MIR9-3HG|LINC01748) + 1.45 × (AC092687.3|SNHG12) + (-0.87)  × (AC090204.1|AL158166.1) + 0.64 × (LINC01063|Z82243.1). Patients were classified into the high-risk group (> 1.366) and the low-risk group (< 1.366) according to the cutoff value (1.366), which is based on the 5-year riskscore ROC curve. The survival analysis showed that the low-risk group had a better prognosis (P < 0.001). The riskscore was better than other clinical characteristics in prognostic prediction and the area under the curves (AUCs) for the 1-, 3-, and 5-year survivals were 0.796, 0.946, and 0.895, respectively. Combining age, gender, grade, stage, and riskscore, a nomograph was developed to predict survival probability in LSCC patients. Then, the riskscore was confirmed to be related with the content of tumor-infiltration immune cells and the model could serve as a potential predictor for chemosensitivity.

Conclusion

We successfully established a more stable signature of 7 immune-related lncRNA pairs, which has demonstrated a better prognostic ability for LSCC patients and may assist clinicians to precisely prescribe chemo drugs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09524-1.

Comparison of Laboratory Methods for the Clinical Follow Up of Checkpoint Blockade Therapies in Leukemia: Current Status and Challenges Ahead

The development of immune checkpoint inhibitors, the monoclonal antibodies that modulate the interaction between immune checkpoint molecules or their ligands on the immune cells or tumor tissue has revolutionized cancer treatment. While there are various studies proving their efficacy in hematological malignancies, there is also a body of accumulating evidence indicating that immune checkpoint inhibitors' clinical benefits are limited in such diseases. In addition, due to their regulatory nature that balances the immune responses, blockade of immune checkpoints may lead to toxic side effects and autoimmune responses, and even primary or acquired resistance mechanisms may restrict their success. Thus, the need for laboratory biomarkers to identify and monitor patient populations who are more likely respond to this type of therapy and the management of side effects seem critical. However, guidelines regarding the use of immune checkpoint inhibitors in hematological cancers and during follow-up are limited while there is no consensus on the laboratory parameters to be investigated for safety and efficacy of the treatment. This review aims to provide an insight into recent information on predictive and prognostic value of biomarkers and laboratory tests for the clinical follow up of hematological malignancies, with an emphasis on leukemia.

The role of circadian genes in the pathogenesis of colorectal cancer

Colorectal cancer (CRC) is the third most frequent cancer in human beings and is also the major cause of death among the other gastrointestinal cancers. The exact mechanisms of CRC development in most patients remains unclear. So far, several genetically, environmental and epigenetically risk factors have been identified for CRC development. The circadian rhythm is a 24-h rhythm that drives several biologic processes. The circadian system is guided by a central pacemaker which is located in the suprachiasmatic nucleus (SCN) in the hypothalamus. Circadian rhythm is regulated by circadian clock genes, cytokines and hormones like melatonin. Disruptions in biological rhythms are known to be strongly associated with several diseases, including cancer. The role of the different circadian genes has been verified in various cancers, however, the pathways of different circadian genes in the pathogenesis of CRC are less investigated. Identification of the details of the pathways in CRC helps researchers to explore new therapies for the malignancy.

Immune Checkpoints OX40 and OX40L in Small-Cell Lung Cancer: Predict Prognosis and Modulate Immune Microenvironment

Background

OX40 and OX40 ligand (OX40L), as essential immune checkpoint (IC) modulators, are highly correlated with cancer immunity regulation as well as tumor microenvironment (TME). Immunotherapy showed outstanding advantages in small-cell lung cancer (SCLC) therapy. However, functions and clinical significance of OX40 and OX40L in SCLC were not clear yet.

Materials and Methods

SCLC samples of 143 patients were collected for immunohistochemistry (IHC) or whole-exome sequencing (WES). We comprehensively explored the expression and mutation of OX40/OX40L in SCLC, and systematically linked OX40/OX40L with TME.

Results

The expression of OX40/OX40L on tumor cells and tumor-infiltrating lymphocytes (TILs) was found in the IHC cohort and verified in other cohorts with SCLC tissues and cell lines. The results showed co-expression patterns among OX40/OX40L, other ICs, and T-cell markers. The WES data suggested that OX40/OX40L mutation is rare in SCLC (<5%). Patients with positive OX40 protein expression on TILs showed substantially higher recurrence-free survival than those with negative expression (p=0.009). The external dataset also indicated that high OX40/OX40L expression was correlated with better prognosis [overall survival: OX40, p<0.001; OX40L, p=0.019]. Importantly, activation of immunity and high infiltration of CD4(+) and CD8(+) T cells were observed in the high OX40/OX40L expression group.

Conclusions

Collectively, this work highlighted the significance of OX40 and OX40L in prognosis and TME cell infiltration characterization of SCLC. Evaluating the OX40/OX40L-expression levels of individual patients with SCLC might contribute to guiding more precise therapy.

The landscape of gene co-expression modules correlating with prognostic genetic abnormalities in AML

Background

The heterogenous cytogenetic and molecular variations were harbored by AML patients, some of which are related with AML pathogenesis and clinical outcomes. We aimed to uncover the intrinsic expression profiles correlating with prognostic genetic abnormalities by WGCNA.

Methods

We downloaded the clinical and expression dataset from BeatAML, TCGA and GEO database. Using R (version 4.0.2) and ‘WGCNA’ package, the co-expression modules correlating with the ELN2017 prognostic markers were identified (R² ≥ 0.4, p < 0.01). ORA detected the enriched pathways for the key co-expression modules. The patients in TCGA cohort were randomly assigned into the training set (50%) and testing set (50%). The LASSO penalized regression analysis was employed to build the prediction model, fitting OS to the expression level of hub genes by ‘glmnet’ package. Then the testing and 2 independent validation sets (GSE12417 and GSE37642) were used to validate the diagnostic utility and accuracy of the model.

Results

A total of 37 gene co-expression modules and 973 hub genes were identified for the BeatAML cohort. We found that 3 modules were significantly correlated with genetic markers (the ‘lightyellow’ module for NPM1 mutation, the ‘saddlebrown’ module for RUNX1 mutation, the ‘lightgreen’ module for TP53 mutation). ORA revealed that the ‘lightyellow’ module was mainly enriched in DNA-binding transcription factor activity and activation of HOX genes. The ‘saddlebrown’ module was enriched in immune response process. And the ‘lightgreen’ module was predominantly enriched in mitosis cell cycle process. The LASSO- regression analysis identified 6 genes (NFKB2, NEK9, HOXA7, APRC5L, FAM30A and LOC105371592) with non-zero coefficients. The risk score generated from the 6-gene model, was associated with ELN2017 risk stratification, relapsed disease, and prior MDS history. The 5-year AUC for the model was 0.822 and 0.824 in the training and testing sets, respectively. Moreover, the diagnostic utility of the model was robust when it was employed in 2 validation sets (5-year AUC 0.743–0.79).

Conclusions

We established the co-expression network signature correlated with the ELN2017 recommended prognostic genetic abnormalities in AML. The 6-gene prediction model for AML survival was developed and validated by multiple datasets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02914-2.