Prognostic Impact of Memory CD8(+) T Cells on Immunotherapy in Human Cancers: A Systematic Review and Meta-Analysis

Immunomethylomic profiles of long-term head and neck squamous cell carcinoma survivors on immune checkpoint inhibitors

Aim: This study addresses the challenge of predicting the response of head and neck squamous cell carcinoma (HNSCC) patients to immunotherapy. Methods: Using DNA methylation cytometry, we analyzed the immune profiles of six HNSCC patients who showed a positive response to immunotherapy over a year without disease progression. Results: There was an initial increase in CD8 T memory cells and natural killer cells during the first four cycles of immunotherapy, which then returned to baseline levels after a year. Baseline CD8 T cell levels were lower in HNSCC immunotherapy responders but became similar to those in healthy subjects after immunotherapy. Conclusion: These findings suggest that monitoring fluctuations in immune profiles could potentially identify biomarkers for immunotherapy response in HNSCC patients.

Biomarkers for Immune Checkpoint Inhibitors in Renal Cell Carcinoma

Immune checkpoint inhibitor (ICI) therapy has revolutionized renal cell carcinoma treatment. Patients previously thought to be palliative now occasionally achieve complete cures from ICI. However, since immunotherapies stimulate the immune system to induce anti-tumor immunity, they often lead to adverse autoimmunity. Furthermore, some patients receive no benefit from ICI, thereby unnecessarily risking adverse events. In many tumor types, PD-L1 expression levels, immune infiltration, and tumor mutation burden predict the response to ICI and help inform clinical decision making to better target ICI to patients most likely to experience benefits. Unfortunately, renal cell carcinoma is an outlier, as these biomarkers fail to discriminate between positive and negative responses to ICI therapy. Emerging biomarkers such as gene expression profiles and the loss of pro-angiogenic proteins VHL and PBRM-1 show promise for identifying renal cell carcinoma cases likely to respond to ICI. This review provides an overview of the mechanistic underpinnings of different biomarkers and describes the theoretical rationale for their use. We discuss the effectiveness of each biomarker in renal cell carcinoma and other cancer types, and we introduce novel biomarkers that have demonstrated some promise in clinical trials.

MXRA8 is an immune-relative prognostic biomarker associated with metastasis and CD8+ T cell infiltration in colorectal cancer

Background

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths worldwide. Tumor metastasis and CD8⁺ T cell infiltration play a crucial role in CRC patient survival. It is important to determine the etiology and mechanism of the malignant progression of CRC to develop more effective treatment strategies.

Methods

We conducted weighted gene co-expression network analysis (WGCNA) to explore vital modules of tumor metastasis and CD8⁺ T cell infiltration, then with hub gene selection and survival analysis. Multi-omics analysis is used to explore the expression pattern, immunity, and prognostic effect of MXRA8. The molecular and immune characteristics of MXRA8 are analyzed in independent cohorts, clinical specimens, and in vitro.

Results

MXRA8 expression was strongly correlated with tumor malignancy, metastasis, recurrence, and immunosuppressive microenvironment. Furthermore, MXRA8 expression predicts poor prognosis and is an independent prognostic factor for OS in CRC.

Conclusion

MXRA8 may be a potential immunotherapeutic and prognostic biomarker for CRC.

A pan-cancer and single-cell sequencing analysis of CD161, a promising onco-immunological biomarker in tumor microenvironment and immunotherapy

Background

CD161 has been linked to the appearance and development of various cancers.

Methods

The mutation map and the variation of CNVs and SNVs of CD161 were displayed according to cBioportal and GSCALite. We also evaluated the pathway enrichment and drug sensitivity of CD161 according to GSCALite. We performed a single-cell sequencing analysis of cancer cells and T cells in melanoma. The cell communication patterns related to CD161 were further explored. Multiplex immunofluorescence staining of tissue microarrays was used to detect the association between CD161 expression and macrophages and T cells.

Results

A high CD161 level was related to neoantigens expression, pathway enrichment, and drug sensitivity. In addition, single-cell sequencing analysis showed that CD161 was mainly expressed in T cells, M1 and M2 Macrophages, neoplastic, microglial cells, neurons, and cancer cells in many tumor types. Further study on pseudotime trajectories and functional annotation of CD161 proved the critical role of CD161 in tumor progression and T cell immunity in melanoma. Multiplex immunofluorescence revealed that CD161 is closely correlated with the immune infiltration of T cells and macrophages in multiple cancers. In addition, high CD161 expression predicted a favorable immunotherapy response.

Conclusion

CD161 is involved in the immune infiltration of T cells and macrophages and might be a promising target for tumor immunotherapy.

Exponential Slope from Absolute Lymphocyte Counts during Radio-Chemotherapy Can Predict an Aggressive Course of Cervical Cancer

This study aimed to investigate whether the exponential slope α from absolute lymphocyte counts during concurrent radio−chemotherapy (CRT) is associated with aggressive and non-aggressive courses of cervical cancer. We analyzed 362 patients with stage IB−IVB cervical cancer treated with CRT in two groups: 323 patients without mRNA data (cohort 1) and 39 with mRNA data (cohort 2) from plasma exosomes. We calculated the α of each patient; 69 patients who died of cancer in cohort 1 were divided into 44 who died within 30 months (aggressive group), and 25 who died after more than 30 months (non-aggressive group). The median follow-up periods of cohorts 1 and 2 were 63 and 28 months, respectively. The log2 fold change (log2FC) between read counts of mRNAs before treatment and after the second week of CRT was calculated. Multivariate analyses from cohort 1 showed that neutrophil-to-lymphocyte ratio (NLR) ≥ 2.43 and α < 0.08 were statistically significant predictors of disease-specific survival (DSS) in the aggressive group (DSS-A), whereas α ≥ 0.08 was the only significant predictor of DSS in the non-aggressive group (DSS-NA). The 2.5-year DSS-A and 8-year DSS-NA rates of patients with α ≥ 0.08 and α < 0.08 were 86.7% and 73%, and 78.5% and 94.8% in the high-NLR group, respectively. In cohort 2, patients with both NLR < 2.7 and α ≥ 0.07 had a higher 2.5-year DSS rate than did those with either NLR ≥ 2.72 or α < 0.07. E2F8 and STX6 significantly correlated with ɑ and survival. The 2.5-year DSS rates in patients with E2F8 + STX6 (log2FC) < 0.2429 and ≥0.2429 were 100% and 77.2%, respectively. The exponential slope α can potentially distinguish between aggressive and non-aggressive courses in cervical cancer patients.

Imaging Effector Memory T-Cells Predicts Response to PD1-Chemotherapy Combinations in Colon Cancer

Often, patients fail to respond to immune checkpoint inhibitor (ICI) treatment despite favourable biomarker status. Numerous chemotherapeutic agents have been shown to promote tumour immunogenicity when used in conjunction with ICIs; however, little is known about whether such combination therapies lead to a lasting immune response. Given the potential toxicity of ICI–chemotherapy combinations, identification of biomarkers that accurately predict how individuals respond to specific treatment combinations and whether these responses will be long lasting is of paramount importance. In this study, we explored [18F]AlF-NOTA-KCNA3P, a peptide radiopharmaceutical that targets the Kv1.3 potassium channel overexpressed on T-effector memory (TEM) cells as a PET imaging biomarker for lasting immunological memory response. The first-line colon cancer chemotherapies oxaliplatin and 5-fluorouracil were assessed in a syngeneic colon cancer model, either as monotherapies or in combination with PD1, comparing radiopharmaceutical uptake to memory-associated immune cells in the tumour. [18F]AlF-NOTA-KCNA3P reliably separated tumours with immunological memory responses from non-responding tumours and could be used to measure Kv1.3-expressing TEM cells responsible for durable immunological memory response to combination therapy in vivo.

Development and Characterization of a Luciferase Labeled, Syngeneic Murine Model of Ovarian Cancer

Despite advances in surgery and targeted therapies, the prognosis for women with high-grade serous ovarian cancer remains poor. Moreover, unlike other cancers, immunotherapy has minimally impacted outcomes in patients with ovarian cancer. Progress in this regard has been hindered by the lack of relevant syngeneic ovarian cancer models to study tumor immunity and evaluate immunotherapies. To address this problem, we developed a luciferase labeled murine model of high-grade serous ovarian cancer, STOSE.M1 luc. We defined its growth characteristics, immune cell repertoire, and response to anti PD-L1 immunotherapy. As with human ovarian cancer, we demonstrated that this model is poorly sensitive to immune checkpoint modulators. By developing the STOSE.M1 luc model, it will be possible to probe the mechanisms underlying resistance to immunotherapies and evaluate new therapeutic approaches to treat ovarian cancer.

A Differentiation-Related Gene Prognostic Index Contributes to Prognosis and Immunotherapy Evaluation in Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common gastrointestinal tumor with a poor prognosis, which is associated with poor differentiation of tumor cells. However, the potential value of cell differentiation-related molecules in predicting the benefit and prognosis of immune checkpoint inhibitors (ICI) therapy remains unknown. Herein, to investigate the differentiation trajectory of HCC cells and their clinical significance, a differentiation-related gene prognostic index (DRGPI) based on HCC differentiation-related genes (HDRGs) was constructed to elucidate the immune characteristics and therapeutic benefits of ICI in the HCC subgroup defined by DRGPI. Single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from four HCC samples were integrated for bioinformatics analysis. Then, PON1, ADH4, SQSTM1, HSP90AA1, and STMN1 were screened out to construct a DRGPI. More intriguingly, RT-qPCR validation of the expression of these genes yielded consistent results with the TCGA database. Next, the risk scoring (RS) constructed based on DRGPI suggested that the overall survival (OS) of the DRGPI-high patients was significantly worse than that of the DRGPI-low patients. A nomogram was constructed based on DRGPI-RS and clinical characteristics, which showed strong predictive performance and high accuracy. The comprehensive results indicated that a low DRGPI score was associated with low TP53 mutation rates, high CD8 T cell infiltration, and more benefit from ICI therapy. Homoplastically, the high DRGPI score reflected the opposite results. Taken together, our study highlights the significance of HCC cell differentiation in predicting prognosis, indicating immune characteristics, and understanding the therapeutic benefits of ICI, and suggests that DRGPI is a valuable prognostic biomarker for HCC.

PD-L1 siRNA-hyaluronic acid conjugate for dual-targeted cancer immunotherapy

"Foreignization" of tumor cells via delivery of a non-self foreign antigen (Ag) into tumors is an appealing strategy to initiate anti-tumor immunity that can facilitate tumor rejection by pre-existing foreign-Ag-reactive T cells. However, the immune-suppressive factors in the tumor microenvironment (TME) limit the durable and potent immune response of these cells against tumor antigens, stressing the need for improved tumor-foreignization strategies. Here, we demonstrate that blockade of programmed cell death ligand 1 (PD-L1) on both tumor cells and dendritic cells (DCs) can markedly potentiate the induction of tumor-reactive T cells, thereby strengthening the anti-tumor immunity ignited by tumor-foreignization. Specifically, we developed a polymeric nanoconjugate (PEG-HA-OVA/PPLs), consisting of siPD-L1-based polyplexes, PEGylated hyaluronic acid as the CD44-targeting moiety, and ovalbumin (OVA) as a model foreign antigen. Notably, PEG-HA-OVA/PPLs were simultaneously delivered into CD44^high tumor cells and CD44^high DCs, leading to efficient cross-presentation of OVA and downregulation of PD-L1 in both cell types. Importantly, the nanoconjugate not only allowed OVA-specific T cells to vigorously reject the foreignized tumor cells but also reprogrammed the TME to elicit robust T-cell responses specific to the endogenous tumor Ags, eventually generating long-lasting protective immunity. Thus, our combination strategy represents an innovative approach for the induction of potent tumor immunity via a two-step consecutive immune boost against exogenous and endogenous tumor Ags.