Impact of PD-L1 and PD-1 Expression on the Prognostic Significance of CD8+ Tumor-Infiltrating Lymphocytes in Non-Small Cell Lung Cancer

Boosting immune responses in lung tumor immune microenvironment: A comprehensive review of strategies and adjuvants

The immune system has a substantial impact on the growth and expansion of lung malignancies. Immune cells are encompassed by a stroma comprising an extracellular matrix (ECM) and different cells like stromal cells, which are known as the tumor immune microenvironment (TIME). TME is marked by the presence of immunosuppressive factors, which inhibit the function of immune cells and expand tumor growth. In recent years, numerous strategies and adjuvants have been developed to extend immune responses in the TIME, to improve the efficacy of immunotherapy. In this comprehensive review, we outline the present knowledge of immune evasion mechanisms in lung TIME, explain the biology of immune cells and diverse effectors on these components, and discuss various approaches for overcoming suppressive barriers. We highlight the potential of novel adjuvants, including toll-like receptor (TLR) agonists, cytokines, phytochemicals, nanocarriers, and oncolytic viruses, for enhancing immune responses in the TME. Ultimately, we provide a summary of ongoing clinical trials investigating these strategies and adjuvants in lung cancer patients. This review also provides a broad overview of the current state-of-the-art in boosting immune responses in the TIME and highlights the potential of these approaches for improving outcomes in lung cancer patients.

HIV Associated Lung Cancer: Unique Clinicopathologic Features and Immune Biomarkers Impacting Lung Cancer Screening and Management

OBJECTIVES

Lung cancer contributes significantly to morbidity and mortality in people with HIV (PWH). We study the clinicopathologic characteristics and immune microenvironment in HIV associated lung cancer.

MATERIAL AND METHODS

Clinicopathological characteristics including immunotherapy outcomes were collected for 174 PWH diagnosed with lung cancer. Immunohistochemical staining for PD-L1, CD4, and CD8 was performed.

RESULTS

At diagnosis, patients with HIV associated lung cancer were significantly younger (56.9 vs. 69 years, P < .0001) and more frequently had advanced disease (70% vs. 53%, P = .01). The majority were African American (60% vs. 42%, P < .0001) and were smoking at the time of diagnosis or smoked in the past (98% vs. 86%, P = .0001). Only 10% of HIV associated lung cancer was diagnosed through the screening program. The median CD4+ lymphocyte count was 334 cells/µL, 31% had a CD4 ≤200 cells/µL and 63% of the cohort was virally suppressed. HIV associated non-small-cell lung cancer(NSCLC) was characterized by limited PD-L1 expression compared to the HIV negative cohort, 64% vs. 31% had TPS <1%, and 20% vs. 34% had TPS≥50%, respectively (P = .04). Higher CD8+ TILs were detected in PD-L1-high tumors (P < .0001). 50% of patients achieved disease control in the metastatic setting with the use of immunotherapy, and there were no new safety signals in 19 PWH treated with immunotherapy.

CONCLUSION

Lung cancer in PWH demonstrates unique features highlighting the need for a specialized screening program. Despite low PD-L1 expression, immunotherapy is well tolerated with reasonable disease control. Altered immune system in lung cancer pathogenesis in PWH should be further investigated.

Comprehensively analysis of immunophenotyping signature in triple-negative breast cancer patients based on machine learning

Immunotherapy is a promising strategy for triple-negative breast cancer (TNBC) patients, however, the overall survival (OS) of 5-years is still not satisfactory. Hence, developing more valuable prognostic signature is urgently needed for clinical practice. This study established and verified an effective risk model based on machine learning methods through a series of publicly available datasets. Furthermore, the correlation between risk signature and chemotherapy drug sensitivity were also performed. The findings showed that comprehensive immune typing is highly effective and accurate in assessing prognosis of TNBC patients. Analysis showed that IL18R1, BTN3A1, CD160, CD226, IL12B, GNLY and PDCD1LG2 are key genes that may affect immune typing of TNBC patients. The risk signature plays a robust ability in prognosis prediction compared with other clinicopathological features in TNBC patients. In addition, the effect of our constructed risk model on immunotherapy response was superior to TIDE results. Finally, high-risk groups were more sensitive to MR-1220, GSK2110183 and temsirolimus, indicating that risk characteristics could predict drug sensitivity in TNBC patients to a certain extent. This study proposes an immunophenotype-based risk assessment model that provides a more accurate prognostic assessment tool for patients with TNBC and also predicts new potential compounds by performing machine learning algorithms.

Role of ALOX5 in non-small cell lung cancer: A potential therapeutic target associated with immune cell infiltration

OBJECTIVES

The efficacy of immunotherapy for lung cancer is closely related to immune cell infiltration. Arachidonic acid 5-lipoxygenase (ALOX5) can activate inflammatory responses and trigger various cell death patterns; however, the relevance of ALOX5 to immune cell infiltration in lung cancer is unclear. The expression of ALOX5 in non-small cell lung cancer (NSCLC) is analyzed using an online database to explore the correlation between ALOX5 and immune cell infiltration in NSCLC and its relationship with prognosis.

METHODS

Differences in ALOX5 expression in NSCLC and normal lung tissues were analyzed by online databases such as TIMER, GEPIA and HPA; the UALCAN database was used to reveal the relationship between ALOX5 and clinical features; Kaplan-Meier database was applied to explore the prognostic value of ALOX5; GeneMANIA and String Website was used to explore genes and proteins associated with ALOX5 expression, respectively; the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to analyze ALOX5 differential genes which were picked up through the TCGA database; GSEA software was applied to predict the signal pathways that ALOX5 may be involved in; and the TIMER database was used to analyze the effect of ALOX5 expression on the level of immune cell infiltration.

RESULTS

Compared with the normal lung tissues, the ALOX5 expression was low in NSCLC tissues (P<0.05), and which affected the prognosis of lung cancer patients. The expression level of ALOX5 was related to clinical features such as sex, age, metastasis, and pathological staging in NSCLC patients (all P<0.05). The gene interaction network analysis found that the genes interacting with ALOX5 mainly included the genes related to lipid oxidation and pro-inflammatory mediators such as coactosin like protein 1 (COTL1), leukotriene C4 synthase (LTC4S), and prostaglandin endoperoxide synthase 2 (PTGS2), and the protein-protein interaction analysis results were consistent. GO and KEGG analysis found that ALOX5 was involved in the biological process of activation of immune cell function and was involved in immune response function pathways. The GSEA analysis showed that ALOX5 may activate immune responses and mediate immune-related prognosis by affecting the cytokine-cytokine receptor interactions, natural killer-mediated cytotoxicity, and T cell receptor signaling pathways. The ALOX5 mRNA expressions in lung adenocarcinoma and lung squamous cell carcinoma were positively correlated with the tumor infiltration immune cells (B cells, CD8+ T cells, CD4+ T cells, etc.) (all P<0.05), and the ALOX5 mRNA expression was positively correlated with the expression of classic T cell immune checkpoint inhibitor genes (P<0.001).

CONCLUSIONS

The ALOX5 gene expression in NSCLC is significantly downregulated, and which can affect NSCLC prognosis and immune cell infiltration levels. ALOX5 gene may be a potential biomarker of NSCLC prognosis associated with immune cell infiltration.

Functional status and spatial interaction of T cell subsets driven by specific tumor microenvironment correlate with recurrence of non-small cell lung cancer

Background

The anti-tumoral or pro-tumoral roles of CD4+ and CD8+ T cells typify the complexity of T cell subsets function in cancer. In the non-small cell lung cancer (NSCLC), the density and topology of distinct T cell phenotypes at the tumor center (TC) versus the invasive margin (IM) are largely unknown. Here, we investigated T cell subsets density and distribution within TC and IM regions in NSCLC and its impact on the prognosis.

Methods

We performed multiplex immunofluorescence using a tissue microarray of samples from 99 patients with locally advanced NSCLC to elucidate the distributions of tumor cell, T cell subpopulations (CD4/conventional CD4/regulatory CD4/CD8/cytotoxic CD8/pre-dysfunctional CD8/dysfunctional CD8), microvessel density (MVD), cancer-associated fibroblasts (CAFs) and hypoxia-inducible factor-1α (HIF-1α) in TC and IM tissues. Cell-to-cell nearest neighbor distances and interactions were analyzed using the phenoptrreports R package. Cox regression was used to evaluate the associations between T cell subsets density and proximity to tumor cells and recurrence-free survival (RFS). Correlations between different cell subsets were examined by Spearman's or Kruskal-Wallis tests.

Results

In the locally advanced NSCLC, the proportion of tumor cells and CAFs in IM is lower than in the TC, while MVD, CD4+, and CD8+ T lymphocytes were increased, and tumor cells were closer to T lymphocytes and their subsets. The density and proximity of CD4+ and CD8+ T cells in the TC and IM regions were not associated with RFS, but in the IM area, increased density of dysfunctional CD8 and closer regulatory CD4 to tumor cells were independent risk factors for recurrence (HR were 3.536 and 2.884, respectively), and were positively correlated with HIF-1α+CD8 (r = 0.41, P = 0.000) and CAFs (P = 0.017), respectively.s.

Conclusions

In locally advanced NSCLC, the functional status of T cells in the IM region is closely related to recurrence. The density of dysfunctional CD8 and the proximity of regulatory CD4 to tumor cells were independent risk factors for recurrence, and are positively correlated with the hypoxia response of CD8+ T cells and CAFs. Targeting hypoxia or CAFs is expected to further sensitize therapy.

Nanoparticles overcome adaptive immune resistance and enhance immunotherapy via targeting tumor microenvironment in lung cancer

Lung cancer is one of the common malignant cancers worldwide. Immune checkpoint inhibitor (ICI) therapy has improved survival of lung cancer patients. However, ICI therapy leads to adaptive immune resistance and displays resistance to PD-1/PD-L1 blockade in lung cancer, leading to less immune response of lung cancer patients. Tumor microenvironment (TME) is an integral tumor microenvironment, which is involved in immunotherapy resistance. Nanomedicine has been used to enhance the immunotherapy in lung cancer. In this review article, we described the association between TME and immunotherapy in lung cancer. We also highlighted the importance of TME in immunotherapy in lung cancer. Moreover, we discussed how nanoparticles are involved in regulation of TME to improve the efficacy of immunotherapy, including Nanomedicine SGT-53, AZD1080, Nanomodulator NRF2, Cisplatin nanoparticles, Au@PG, DPAICP@ME, SPIO NP@M-P, NBTXR3 nanoparticles, ARAC nanoparticles, Nano-DOX, MS NPs, Nab-paclitaxel, GNPs-hPD-L1 siRNA. Furthermore, we concluded that targeting TME by nanoparticles could be helpful to overcome resistance to PD-1/PD-L1 blockade in lung cancer.

Downregulation of T-cell cytotoxic marker IL18R1 promotes cancer proliferation and migration and is associated with dismal prognosis and immunity in lung squamous cell carcinoma

Immunotherapy can improve the survival of patients with advanced lung squamous cell carcinoma (LUSC). T cytotoxic cells are one of the main members of the immune microenvironment. Herein, we aimed to identify the roles of T-cell cytotoxic markers interleukin 18 (IL18) receptor 1 (IL18R1) in the LUSC progression using bioinformatics, clinical tissue specimen, and cell experiment. We assessed the association between the IL18R1 expression and immune infiltration and IL18R1-related competing RNA network. The IL18R1 expression was downregulated in the LUSC tissues. The IL18R1 expression downregulation was associated with diagnosis and short overall survival and disease-specific survival, and it was also an independent risk factor for dismal survival time in LUSC. IL18R1-related nomograms predicted the survival time of patients with LUSC. IL18R1 overexpression inhibited the proliferation, migration, and invasion of LUSC cells. The IL18R1 expression was significantly associated with the microenvironment (stromal, immune, and estimate scores), immune cells (such as the T cells, cytotoxic cells, CD8 T cells), and immune cell markers (such as the CD8A, PD-1, and CTLA4) in LUSC. AC091563.1 and RBPMS-AS1 downregulation was positively associated with the IL18R1 expression, negatively associated with the miR-128-3p expression, and associated with short disease-specific survival and progression in LUSC. In conclusion, IL18R1 was significantly downregulated and associated with the prognosis and immune microenvironment. IL18R1 overexpression inhibits the growth and migration of cancer cells in LUSC. Furthermore, AC091563.1 and RBPMS-AS1 might compete with IL18R1 to bind miR-128-3p for participating in LUSC progression. These results showed that IL18R1 is a biomarker for evaluating the prognosis of patients with LUSC.

SP142 evaluation contributes to the prediction of immune checkpoint inhibitor efficacy in non-small cell lung cancer with high PD-L1 expression assessed by 22C3

Background

It remains unclear whether assessing programmed death-ligand 1 (PD-L1) expression by SP142 plus 22C3 adds value for predicting the response to immunotherapy in non-small cell lung cancer (NSCLC).

Methods

This retrospective multicenter study included patients with advanced NSCLC treated with immune-checkpoint inhibitors. We constructed tissue microarrays (TMAs) and performed immunohistochemical staining with 22C3 and SP142 assays. We denoted the PD-L1 tumor proportion score (TPS) obtained from clinical medical records based on 22C3 staining as "22C3 (C)" and that obtained with 22C3 staining using our TMA as "22C3 (TMA)". SP142 staining was evaluated in both tumor cells and immune cells. We assessed the concordance between each PD-L1 assessment method and analyzed the objective response rate (ORR), progression-free survival (PFS) and overall survival (OS) based on the PD-L1 expression level determined using the 22C3 and SP142 assays.

Results

In total, 288 patients were included. Among those with 22C3 (TMA) ≥50%, 60% of patients showed SP142 TC3 or IC3; among patients with 22C3 (C) <1%, 9% and 18% exhibited 22C3 (TMA) ≥1% and SP142 TC1/2/3 or IC1/2/3, respectively. Among patients with 22C3 (C) ≥50% treated with immune-checkpoint inhibitor monotherapy, the SP142 TC1/2/3 or IC1/2/3 group showed significantly better ORR, PFS and OS than the SP142 TC0 and IC0 group (54% vs. 29%, P=0.040, median =11.0 vs. 3.2 months, P=0.002, median =27.9 vs. 12.6 months, P=0.030, respectively). Multivariate analysis revealed that SP142 TC0 and IC0 was an independent unfavorable prognostic factor for PFS and OS in patients with 22C3 (C) ≥50% treated with immune-checkpoint inhibitor monotherapy. For those with 22C3 (C) ≥50% and SP142 TC0 and IC0, immune-checkpoint inhibitor concurrent with chemotherapy tended to result in a longer PFS and OS than immune-checkpoint inhibitor monotherapy (median =13.7 vs. 2.3 months, P=0.054, median = not estimable vs. 12.0 months, P=0.064, respectively).

Conclusions

SP142 evaluation contributes to the prediction of immune-checkpoint inhibitor efficacy in NSCLC with high PD-L1 expression assessed by 22C3.

Potential impact of WTAP and YTHDF2 on tumor immunity in lung adenocarcinoma

WTAP and N6-methyladenosine (m6A) reader proteins (YTHDF2) are N6-methyladenosine (m6A) methyltransferase and m6A reading proteins, respectively. In recent years, the tumor immune environment has received more and more attention in the progress and treatment of cancer. The aim of this study was to investigate the relationship between N6-methyladenosine (m6A) methyltransferase (WTAP)/YTHDF2 and the immunological characteristics of lung adenocarcinoma (LUAD). Based on the expression of WTAP and YTHDF2 in the cancer genome atlas (TCGA) and gene expression omnibus (GEO) database, LUAD patients were divided into 2 clusters by coherently clustering method, and performed gene set enrichment analysis (GSEA) to identify the functional differences. Immunoinvasion analysis was performed using ESTIMATE, CIBERSORT, and single-sample GSEA (ssGSEA), and expression of immune checkpoint inhibitors (ICIs) targets was assessed, while tumor mutation burden (TMB) was calculated in tumor samples. Weighted gene co-expression network analysis (WGCNA) was used to identify the genes related to both WTAP/YTHDF2 expression and immunity. The immunological characteristics between the 2 clusters were externally verified based on GSE39582. The expression of WTAP was higher in cluster 1 and YTHDF2 was lower, but it was opposite in cluster 2. Cluster 1 had stronger immune infiltration, more ICIs target expression, more TMB. In addition, WGCNA identified 22 genes associated with WTAP/YTHDF2 expression and immune score, including TIM3 (HAVCR2) and CD86. WTAP and YTHDF2 influence immune contexture and may be novel prognostic and druggable targets associated with the immune system of LUAD.

Immunotherapy targeting inhibitory checkpoints: The role of NK and other innate lymphoid cells

Monoclonal antibodies that target specific ligand-receptor signaling pathways and act as immune checkpoint inhibitors have been designed to remove the brakes in T cells and restore strong and long-term antitumor-immunity. Of note, many of these inhibitory receptors are also expressed by Innate Lymphoid Cells (ILCs), suggesting that also blockade of inhibitory pathways in innate lymphocytes has a role in the response to the treatment with checkpoint inhibitors. ILCs comprise cytotoxic NK cells and "helper" subsets and are important cellular components in the tumor microenvironment. In addition to killing tumor cells, ILCs release inflammatory cytokines, thus contributing to shape adaptive cell activation in the context of immunotherapy. Therefore, ILCs play both a direct and indirect role in the response to checkpoint blockade. Understanding the impact of ILC-mediated response on the treatment outcome would contribute to enhance immunotherapy efficacy, as still numerous patients resist or relapse.

Immunophenotyping of pulmonary sarcomatoid carcinoma

Background

Previous studies have suggested that patients with pulmonary sarcomatoid carcinoma (PSC)may benefit from immune checkpoint inhibitors (ICIs); however, relevant data are lacking. This study aimed to establish the immunophenotype of PSC by assessing PD-L1 and CD8+ T-cell infiltration.

Methods

A retrospective analysis of pathologically confirmed PSC cases from two centers was performed from January 2009 to May 2021. According to the infiltration of CD8+ T cells in different spatial regions, patients were classified into three types: immune-inflamed, immune-excluded, and immune desert. PD-L1 staining was also performed on the intratumoral region and the tumor proportion score (TPS) was used for scoring. Combined with CD8+ T-cell infiltration and PD-L1 expression in the intratumoral region, immunophenotyping can be divided into four types: type I (PD-L1+/CD8+, adaptive immune resistance), type II (PD-L1-/CD8-, immunologic ignorance), type III (PD-L1+/CD8-, intrinsic induction), and type IV (PD-L1-/CD8+, tolerance). Finally, correlation analysis was performed on the immunophenotype, clinicopathological characteristics, and outcomes of the patients.

Results

A total of 32 patients with PSC were included in the final analysis. Of these patients, 65.6% (21/32), 15.6% (5/32), and 18.8% (6/32) were classified as immune-inflamed, immune-excluded, and immune-desert, respectively. Notably, the immune-inflamed type is predominantly observed in pleomorphic carcinomas (PC, 66.7%). Moreover, among these participants, 19 (59.4%) were classified as PD-L1 positive according to the TPS score. In particular, 11 (34.4%) patients had PD-L1 TPS scores >50%. Next, we immunophenotyped patients with PSC based on CD8+ T cell infiltration and tumor cell PD-L1 expression (types I–IV). Type I (PD-L1+/CD8+, adaptive immune resistance) was the most prevalent subtype, accounting for 46.9% (15/32), followed by type II (PD-L1-/CD8-, immunological ignorance) (21.9%), type IV (PD-L1-/CD8+, tolerance) (18.7%), and type III (PD-L1+/CD8-, intrinsic induction) (12.5%). Finally, we performed a survival analysis and found that neither immunophenotype was a predictor of prognosis in patients with PSC. Multivariate analysis showed that pneumonectomy increased the risk of death by four times compared with lobectomy (RR: 4.1; 95% CI:1.3-12.4, P=0.014).

Conclusion

Patients with PSC are characterized by immune-inflamed type and type I (PD-L1+/CD8+, adaptive immune resistance), explaining the intrinsic reasons for their high response rate to immunotherapy.

Comparing T Cell Subsets in Broncho-Alveolar Lavage (BAL) and Peripheral Blood in Patients with Advanced Lung Cancer

Background: Lung cancer (LC) tissue for immunological characterization is often scarce. We explored and compared T cell characteristics between broncho-alveolar lavage from tumor affected (t-BAL) and contralateral lung (cl-BAL), with matched peripheral blood (PB). Methods: BAL and PB were collected during bronchoscopy for diagnostic and/or therapeutic purposes in patients with monolateral primary lesion. Results: Of 33 patients undergoing BAL and PB sampling, 21 had histologically-confirmed LC. Most cases were locally-advanced or metastatic non-small cell LC. T cell characteristics were not significantly different in t-BAL vs. cl-BAL. Compared to PB, CD8 T cells in BAL presented features of immune activation and exhaustion (high PD-1, low IFN-g production). Accordingly, regulatory CD4 T cells were also higher in BAL vs. PB. When dichotomizing T cell density in t-BAL in high and low, we found that PD-L1 expression in LC was associated with T cell density in t-BAL. T-BAL with high T cell density had higher %IFN-g+CD8 T cells and lower %T-regs. Conclusion: In BAL from advanced LC patients, T cells present features of exhaustion. T cells in t-BAL could be the best surrogate of tumor-infiltrating T cell, and future studies should evaluate T cell phenotype and density as potential biomarkers for cancer immunotherapy outcome.

Comparison of three validated PD-L1 immunohistochemical assays in urothelial carcinoma of the bladder: interchangeability and issues related to patient selection

Different programmed cell death-ligand 1 (PD-L1) assays and scoring algorithms are being used in the evaluation of PD-L1 expression for the selection of patients for immunotherapy in specific settings of advanced urothelial carcinoma (UC). In this paper, we sought to investigate three approved assays (Ventana SP142 and SP263, and Dako 22C3) in UC with emphasis on implications for patient selection for atezolizumab/pembrolizumab as the first line of treatment. Tumors from 124 patients with invasive UC of the bladder were analyzed using tissue microarrays (TMA). Serial sections were stained with SP263 and SP142 on Ventana Benchmark Ultra and with 22C3 on Dako Autostainer Link 48. Stains were evaluated independently by two observers and scored using the combined positive score (CPS) and tumor infiltrating immune cells (IC) algorithms. Differences in proportions (DP), overall percent agreement (OPA), positive percent agreement (PPA), negative percent agreement (NPA), and Cohen κ were calculated for all comparable cases. Good overall concordance in analytic performance was observed for 22C3 and SP263 with both scoring algorithms; specifically, the highest OPA was observed between 22C3 and SP263 (89.6%) when using CPS. On the other hand, SP142 consistently showed lower positivity rates with high differences in proportions (DP) compared with 22C3 and SP263 with both CPS and IC, and with a low PPA, especially when using the CPS algorithm. In conclusion, 22C3 and SP263 assays show comparable analytical performance while SP142 shows divergent staining results, with important implications for the selection of patients for both pembrolizumab and atezolizumab.

A digital assay for programmed death-ligand 1 (22C3) quantification combined with immune cell recognition algorithms in non-small cell lung cancer

PD-L1 (22C3) checkpoint inhibitor therapy represents a mainstay of modern cancer immunotherapy for non-small cell lung cancer (NSCLC). In vitro diagnostic (IVD) PD-L1 antibody staining is widely used to predict clinical intervention efficacy. However, pathologist interpretation of this assay is cumbersome and variable, resulting in poor positive predictive value concerning patient therapy response. To address this, we developed a digital assay (DA) termed Tissue Insight (TI) 22C3 NSCLC, for the quantification of PD-L1 in NSCLC tissues, including digital recognition of macrophages and lymphocytes. We completed clinical validation of this digital image analysis solution in 66 NSCLC patient samples, followed by concordance studies (comparison of PD-L1 manual and digital scores) in an additional 99 patient samples. We then combined this DA with three distinct immune cell recognition algorithms for detecting tissue macrophages, alveolar macrophages, and lymphocytes to aid in sample interpretation. Our PD-L1 (22C3) DA was successfully validated and had a scoring agreement (digital to manual) higher than the inter-pathologist scoring. Furthermore, the number of algorithm-identified immune cells showed significant correlation when compared with those identified by immunohistochemistry in serial sections stained by double immunofluorescence. Here, we demonstrated that TI 22C3 NSCLC DA yields comparable results to pathologist interpretation while eliminating the intra- and inter-pathologist variability associated with manual scoring while providing characterization of the immune microenvironment, which can aid in clinical treatment decisions.

Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification

Background

High immune infiltration is associated with favourable prognosis in patients with non-small-cell lung cancer (NSCLC), but an automated workflow for characterizing immune infiltration, with high validity and reliability, remains to be developed.

Methods

We performed a multicentre retrospective study of patients with completely resected NSCLC. We developed an image analysis workflow for automatically evaluating the density of CD3⁺ and CD8⁺ T-cells in the tumour regions on immunohistochemistry (IHC)-stained whole-slide images (WSIs), and proposed an immune scoring system “I-score” based on the automated assessed cell density.

Results

A discovery cohort (n = 145) and a validation cohort (n = 180) were used to assess the prognostic value of the I-score for disease-free survival (DFS). The I-score (two-category) was an independent prognostic factor after adjusting for other clinicopathologic factors. Compared with a low I-score (two-category), a high I-score was associated with significantly superior DFS in the discovery cohort (adjusted hazard ratio [HR], 0.54; 95% confidence interval [CI] 0.33–0.86; P = 0.010) and validation cohort (adjusted HR, 0.57; 95% CI 0.36–0.92; P = 0.022). The I-score improved the prognostic stratification when integrating it into the Cox proportional hazard regression models with other risk factors (discovery cohort, C-index 0.742 vs. 0.728; validation cohort, C-index 0.695 vs. 0.685).

Conclusion

This automated workflow and immune scoring system would advance the clinical application of immune microenvironment evaluation and support the clinical decision making for patients with resected NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03458-9.

A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts Tumor Immune Profiles in Non-Small Cell Lung Cancer: A Retrospective Multicohort Study

Background

The tumor immune microenvironment (TIME) phenotypes have been reported to mainly impact the efficacy of immunotherapy. Given the increasing use of immunotherapy in cancers, knowing an individual's TIME phenotypes could be helpful in screening patients who are more likely to respond to immunotherapy. Our study intended to establish, validate, and apply a machine learning model to predict TIME profiles in non-small cell lung cancer (NSCLC) by using 18F-FDG PET/CT radiomics and clinical characteristics.

Methods

The RNA-seq data of 1145 NSCLC patients from The Cancer Genome Atlas (TCGA) cohort were analyzed. Then, 221 NSCLC patients from Daping Hospital (DPH) cohort received18F-FDG PET/CT scans before treatment and CD8 expression of the tumor samples were tested. The Artificial Intelligence Kit software was used to extract radiomic features of PET/CT images and develop a radiomics signature. The models were established by radiomics, clinical features, and radiomics-clinical combination, respectively, the performance of which was calculated by receiver operating curves (ROCs) and compared by DeLong test. Moreover, based on radiomics score (Rad-score) and clinical features, a nomogram was established. Finally, we applied the combined model to evaluate TIME phenotypes of NSCLC patients in The Cancer Imaging Archive (TCIA) cohort (n = 39).

Results

TCGA data showed CD8 expression could represent the TIME profiles in NSCLC. In DPH cohort, PET/CT radiomics model outperformed CT model (AUC: 0.907 vs. 0.861, P = 0.0314) to predict CD8 expression. Further, PET/CT radiomics-clinical combined model (AUC = 0.932) outperformed PET/CT radiomics model (AUC = 0.907, P = 0.0326) or clinical model (AUC = 0.868, P = 0.0036) to predict CD8 expression. In the TCIA cohort, the predicted CD8-high group had significantly higher immune scores and more activated immune pathways than the predicted CD8-low group (P = 0.0421).

Conclusion

Our study indicates that 18F-FDG PET/CT radiomics-clinical combined model could be a clinically practical method to non-invasively detect the tumor immune status in NSCLCs.

Distinct immune gene programs associated with host tumor immunity, neoadjuvant chemotherapy and chemoimmunotherapy in resectable NSCLC

PURPOSE

Our understanding of the immunopathology of resectable NSCLC is still limited. Here, we explore immune programs that inform of tumor immunity and response to neoadjuvant chemotherapy and chemoimmunotherapy in localized NSCLC.

EXPERIMENTAL DESIGN

Targeted immune gene sequencing using the HTG Precision Immuno-Oncology panel was performed in localized NSCLCs from three cohorts based on treatment: naïve (n=190), neoadjuvant chemotherapy (n=38) and neoadjuvant chemoimmunotherapy (n=21). Tumor immune microenvironment (TIME) phenotypes based on the location of CD8+ T cells (inflamed, cold, excluded), tumoral PD-L1 expression (&lt;1% and {greater than or equal to}1%), and tumor infiltrating lymphocytes (TILs). Immune programs and signatures were statistically analyzed based on tumoral PD-L1 expression, immune phenotypes, pathological response and were cross-compared across the three cohorts.

RESULTS

PD-L1 positive tumors exhibited increased signature scores for various lymphoid and myeloid cell subsets (p&lt;0.05). TIME phenotypes exhibited disparate frequencies by stage, PD-L1 expression, and mutational burden. Inflamed and PD-L1+/TILs+ NSCLCs displayed overall significantly heightened levels of immune signatures, with the excluded group representing an intermediate state. A cytotoxic T cell signature was associated with favorable survival in neoadjuvant chemotherapy-treated NSCLCs (p&lt;0.05). Pathological response to chemoimmunotherapy was positively associated with higher expression of genes involved in immune activation, chemotaxis, as well as T and NK cells (p&lt;0.05 for all). Among the three cohorts, chemoimmunotherapy-treated NSCLCs exhibited highest scores for various immune cell subsets including T effector and B cells (p&lt;0.05).

CONCLUSIONS

Our findings highlight immune gene programs that may underlie host tumor immunity and response to neoadjuvant chemotherapy and chemoimmunotherapy in resectable NSCLC.

Polymorphonuclear Myeloid-Derived Suppressor Cells Are Abundant in Peripheral Blood of Cancer Patients and Suppress Natural Killer Cell Anti-Tumor Activity

Tumor microenvironment (TME) includes a wide variety of cell types and soluble factors capable of suppressing immune-responses. While the role of NK cells in TME has been analyzed, limited information is available on the presence and the effect of polymorphonuclear (PMN) myeloid-derived suppressor cells, (MDSC). Among the immunomodulatory cells present in TME, MDSC are potentially efficient in counteracting the anti-tumor activity of several effector cells. We show that PMN-MDSC are present in high numbers in the PB of patients with primary or metastatic lung tumor. Their frequency correlated with the overall survival of patients. In addition, it inversely correlated with low frequencies of NK cells both in the PB and in tumor lesions. Moreover, such NK cells displayed an impaired anti-tumor activity, even those isolated from PB. The compromised function of NK cells was consequent to their interaction with PMN-MDSC. Indeed, we show that the expression of major activating NK receptors, the NK cytolytic activity and the cytokine production were inhibited upon co-culture with PMN-MDSC through both cell-to-cell contact and soluble factors. In this context, we show that exosomes derived from PMN-MDSC are responsible of a significant immunosuppressive effect on NK cell-mediated anti-tumor activity. Our data may provide a novel useful tool to implement the tumor immunoscore. Indeed, the detection of PMN-MDSC in the PB may be of prognostic value, providing clues on the presence and extension of both adult and pediatric tumors and information on the efficacy not only of immune response but also of immunotherapy and, possibly, on the clinical outcome.