Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLC

New insights into immune cells in cancer immunotherapy: from epigenetic modification, metabolic modulation to cell communication

Cancer is one of the leading causes of death worldwide, and more effective ways of attacking cancer are being sought. Cancer immunotherapy is a new and effective therapeutic method after surgery, radiotherapy, chemotherapy, and targeted therapy. Cancer immunotherapy aims to kill tumor cells by stimulating or rebuilding the body's immune system, with specific efficiency and high safety. However, only few tumor patients respond to immunotherapy and due to the complex and variable characters of cancer immune escape, the behavior and regulatory mechanisms of immune cells need to be deeply explored from more dimensions. Epigenetic modifications, metabolic modulation, and cell-to-cell communication are key factors in immune cell adaptation and response to the complex tumor microenvironment. They collectively determine the state and function of immune cells through modulating gene expression, changing in energy and nutrient demands. In addition, immune cells engage in complex communication networks with other immune components, which are mediated by exosomes, cytokines, and chemokines, and are pivotal in shaping the tumor progression and therapeutic response. Understanding the interactions and combined effects of such multidimensions mechanisms in immune cell modulation is important for revealing the mechanisms of immunotherapy failure and developing new therapeutic targets and strategies.

Predictive value of PD-L1 and TMB for short-term efficacy prognosis in non-small cell lung cancer and construction of prediction models

Objective

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.

Methods

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.

Results

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.

Conclusion

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.

Impacts of tumor microenvironment during neoadjuvant chemotherapy in patients with esophageal squamous cell carcinoma

With the advent of immune checkpoint inhibitors (ICIs), a better understanding of tumor microenvironment (TME) is becoming crucial in managing esophageal squamous cell carcinoma (ESCC) patients. We investigated the survival impact of TME status and changes in patients with ESCC who underwent neoadjuvant chemotherapy (NAC) followed by surgery (n = 264). We examined immunohistochemical status (CD4+, CD8+, CD20+, Foxp3+, HLA class-1+, CD204+, and programmed death ligand-1 [PD-L1+]) on 264 pre-NAC and 204 paired post-NAC specimens. Patients were classified by their pre- and post-NAC immune cell status and their changes following NAC. Our findings showed that pre-NAC TME status was not significantly associated with survival outcomes. In contrast, post-NAC TME status, such as low level of T cells, CD4+ T cells, and high PD-L1 combined positive score (CPS), were significantly associated with poor overall survival (OS). Notably, TME changes through NAC exerted significant survival impacts; patients with consistently low levels of T cells, low levels of CD4+ T cells, or high levels of PD-L1 (CPS) had very poor OS (3-year OS: 35.5%, 40.2%, and 33.3%, respectively). Tumor microenvironment changes of consistently low T cells, low CD4+ T cells, and high PD-L1 were independent predictors of poor OS in multivariate Cox hazards analyses, while factors indicating post-NAC status (T cells, CD4+, and PD-L1 [CPS]) alone were not. Therefore, we suggest that the consistently low T/high PD-L1 group could benefit from additional therapies, such as ICIs, and the importance of stratification by the TME, which has recently been recognized.

Biomarkers of immunotherapy for non-small cell lung cancer

Immunotherapy is revolutionizing the treatment of non-small cell lung cancer by targeting immune checkpoint proteins, including programmed death-1, programmed death ligand 1 and cytotoxic T-lymphocyte-associated antigen 4. Several immune checkpoint inhibitors, including programmed death ligand 1 inhibitors, programmed death-1 inhibitors and cytotoxic T-lymphocyte-associated antigen 4 inhibitors, were approved for the treatment of patients with advanced non-small cell lung cancer. Programmed death ligand 1 expression is currently the only predictive biomarker for immune checkpoint inhibitors to guide the treatment strategy in these patients. However, programmed death ligand 1 expression is not a perfect biomarker for predicting the efficacy of immunotherapy. Therefore, various biomarkers such as tumour mutation burden, tumour microenvironment, gut microbiome and T-cell receptor repertoire have been proposed to predict the efficacy of immunotherapy more accurately. Additionally, combining different biomarkers may provide a more accurate prediction of response to immunotherapy. This article reports the review of the latest evidence of the predictive marker of immunotherapy in patients with advanced non-small cell lung cancer.

Roles of tissue-resident immune cells in immunotherapy of non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most common and lethal type of lung cancer, with limited treatment options and poor prognosis. Immunotherapy offers hope for improving the survival and quality of life of NSCLC patients, but its efficacy depends on the tumor immune microenvironment (TME). Tissue-resident immune cells are a subset of immune cells that reside in various tissues and organs, and play an important role in fighting tumors. In NSCLC, tissue-resident immune cells are heterogeneous in their distribution, phenotype, and function, and can either promote or inhibit tumor progression and response to immunotherapy. In this review, we summarize the current understanding on the characteristics, interactions, and roles of tissue-resident immune cells in NSCLC. We also discuss the potential applications of tissue-resident immune cells in NSCLC immunotherapy, including immune checkpoint inhibitors (ICIs), other immunomodulatory agents, and personalized cell-based therapies. We highlight the challenges and opportunities for developing targeted therapies for tissue-resident immune cells and optimizing existing immunotherapeutic approaches for NSCLC patients. We propose that tissue-resident immune cells are a key determinant of NSCLC outcome and immunotherapy response, and warrant further investigation in future research.

Immunogenic chemotherapy: great potential for improving response rates

The activation of anti-tumor immunity is critical in treating cancers. Recent studies indicate that several chemotherapy agents can stimulate anti-tumor immunity by inducing immunogenic cell death and durably eradicate tumors. This suggests that immunogenic chemotherapy holds great potential for improving response rates. However, chemotherapy in practice has only had limited success in inducing long-term survival or cure of cancers when used either alone or in combination with immunotherapy. We think that this is because the importance of dose, schedule, and tumor model dependence of chemotherapy-activated anti-tumor immunity is under-appreciated. Here, we review immune modulation function of representative chemotherapy agents and propose a model of immunogenic chemotherapy-induced long-lasting responses that rely on synergetic interaction between killing tumor cells and inducing anti-tumor immunity. We comb through several chemotherapy treatment schedules, and identify the needs for chemotherapy dose and schedule optimization and combination therapy with immunotherapy when chemotherapy dosage or immune responsiveness is too low. We further review tumor cell intrinsic factors that affect the optimal chemotherapy dose and schedule. Lastly, we review the biomarkers indicating responsiveness to chemotherapy and/or immunotherapy treatments. A deep understanding of how chemotherapy activates anti-tumor immunity and how to monitor its responsiveness can lead to the development of more effective chemotherapy or chemo-immunotherapy, thereby improving the efficacy of cancer treatment.

Association between pretreatment C-reactive protein level and survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

BACKGROUND

Current evidence suggests that C-reactive protein (CRP) levels may affect cancer prognosis. However, the effect of CRP has not been validated in immunotherapy recipients with non-small cell lung cancer (NSCLC). Therefore, we performed a meta-analysis to explore the prognostic value of CRP level in patients with NSCLC treated with immune checkpoint inhibitors.

METHODS

PubMed, Web of Science, Embase, and Scopus databases were systematically retrieved for eligible publications, and hazard ratios (HRs) with corresponding 95% confidence intervals (95%CIs) were extracted and merged to evaluate the correlation between pretreatment CRP levels and overall survival (OS) and progression-free survival (PFS). Subgroup and sensitivity analyses were conducted to confirm these findings.

RESULTS

Thirty-five cohorts consisting of 4698 patients were included in the primary analysis. Pooled results demonstrated that a higher pretreatment CRP level is associated with worse OS and PFS (OS: HR = 1.13, 95 %CI:1.09-1.18; PFS: HR = 1.16, 95 %CI:1.10-1.22). These findings remained robust after further statistical analyses.

CONCLUSION

Pretreatment CRP level could be a promising biomarker for NSCLC immunotherapy. However, prospective studies are required to validate these findings.

It's high-time to re-evaluate the value of induced-chemotherapy for reinforcing immunotherapy in colorectal cancer

Immunotherapy has made significant advances in the treatment of colorectal cancer (CRC), revolutionizing the therapeutic landscape and highlighting the indispensable role of the tumor immune microenvironment. However, some CRCs have shown poor response to immunotherapy, prompting investigation into the underlying reasons. It has been discovered that certain chemotherapeutic agents possess immune-stimulatory properties, including the induction of immunogenic cell death (ICD), the generation and processing of non-mutated neoantigens (NM-neoAgs), and the B cell follicle-driven T cell response. Based on these findings, the concept of inducing chemotherapy has been introduced, and the combination of inducing chemotherapy and immunotherapy has become a standard treatment option for certain cancers. Clinical trials have confirmed the feasibility and safety of this approach in CRC, offering a promising method for improving the efficacy of immunotherapy. Nevertheless, there are still many challenges and difficulties ahead, and further research is required to optimize its use.

Application of radiomics-based multiomics combinations in the tumor microenvironment and cancer prognosis

The advent of immunotherapy, a groundbreaking advancement in cancer treatment, has given rise to the prominence of the tumor microenvironment (TME) as a critical area of research. The clinical implications of an improved understanding of the TME are significant and far-reaching. Radiomics has been increasingly utilized in the comprehensive assessment of the TME and cancer prognosis. Similarly, the advancement of pathomics, which is based on pathological images, can offer additional insights into the panoramic view and microscopic information of tumors. The combination of pathomics and radiomics has revolutionized the concept of a "digital biopsy". As genomics and transcriptomics continue to evolve, integrating radiomics with genomic and transcriptomic datasets can offer further insights into tumor and microenvironment heterogeneity and establish correlations with biological significance. Therefore, the synergistic analysis of digital image features (radiomics, pathomics) and genetic phenotypes (genomics) can comprehensively decode and characterize the heterogeneity of the TME as well as predict cancer prognosis. This review presents a comprehensive summary of the research on important radiomics biomarkers for predicting the TME, emphasizing the interplay between radiomics, genomics, transcriptomics, and pathomics, as well as the application of multiomics in decoding the TME and predicting cancer prognosis. Finally, we discuss the challenges and opportunities in multiomics research. In conclusion, this review highlights the crucial role of radiomics and multiomics associations in the assessment of the TME and cancer prognosis. The combined analysis of radiomics, pathomics, genomics, and transcriptomics is a promising research direction with substantial research significance and value for comprehensive TME evaluation and cancer prognosis assessment.

Immune checkpoint inhibitors in the treatment of oesophageal squamous cell carcinoma: where are we and where are we going?

Oesophageal squamous cell carcinoma (ESCC) is a kind of malignant tumour with high invasiveness and a poor prognosis. Immunotherapy, especially immune checkpoint inhibitors (ICIs), is a rapidly growing therapeutic method that activates and enhances anti-tumour immunity to treat patients with malignancy. Several clinical trials have confirmed the efficacy of ICIs in the treatment of ESCC. ICIs have been approved for the treatment of patients with ESCC. However, only a subset of patients can obtain excellent benefits from ICI therapy. In recent years, there has been a growing interest in exploring predictive biomarkers of immunotherapy response. In this review, we highlighted the predictive biomarkers for the prognosis of ESCC patients treated with ICIs and pointed out the existing problems and the direction of future research in this field.