Implications of the tumor immune microenvironment for staging and therapeutics

Targeting the lung tumor stroma: harnessing nanoparticles for effective therapeutic interventions

Lung cancer remains an influential global health concern, necessitating the development of innovative therapeutic strategies. The tumor stroma, which is known as tumor microenvironment (TME) has a central impact on tumor expansion and treatment resistance. The stroma of lung tumors consists of numerous cells and molecules that shape an environment for tumor expansion. This environment not only protects tumoral cells against immune system attacks but also enables tumor stroma to attenuate the action of antitumor drugs. This stroma consists of stromal cells like cancer-associated fibroblasts (CAFs), suppressive immune cells, and cytotoxic immune cells. Additionally, the presence of stem cells, endothelial cells and pericytes can facilitate tumor volume expansion. Nanoparticles are hopeful tools for targeted drug delivery because of their extraordinary properties and their capacity to devastate biological obstacles. This review article provides a comprehensive overview of contemporary advancements in targeting the lung tumor stroma using nanoparticles. Various nanoparticle-based approaches, including passive and active targeting, and stimuli-responsive systems, highlighting their potential to improve drug delivery efficiency. Additionally, the role of nanotechnology in modulating the tumor stroma by targeting key components such as immune cells, extracellular matrix (ECM), hypoxia, and suppressive elements in the lung tumor stroma.

Spatial Heterogeneity of Immune Regulators Drives Dynamic Changes in Local Immune Responses, Affecting Disease Outcomes in Pancreatic Cancer

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is considered a low-immunogenic (LI) tumor with a "cold" tumor microenvironment and is mostly unresponsive to immune checkpoint blockade therapies. In this study, we decipher the impact of intratumoral heterogeneity of immune determinants on antitumor responses.

EXPERIMENTAL DESIGN

We performed spatial proteomic and transcriptomic analyses and multiplex immunofluorescence on multiple tumor regions, including tumor center (TC) and invasive front (IF), from 220 patients with PDAC, classified according to their transcriptomic immune signaling into high-immunogenic PDAC (HI-PDAC, n = 54) and LI PDAC (LI-PDAC, n = 166). Spatial compartments (tumor: pancytokeratin+/CD45- and leukocytes: pancytokeratin-/CD45+) were defined by fluorescence imaging.

RESULTS

HI-PDAC exhibited higher densities of cytotoxic T lymphocytes with upregulation of T-cell priming-associated immune determinants, including CD40, ITGAM, glucocorticoid-induced TNF-related receptor, CXCL10, granzyme B, IFNG, and HLA-DR, which were significantly more prominent at the IF than at the TC. In contrast, LI-PDAC exhibited immune-evasive tumor microenvironments with downregulation of immune determinants and a negative gradient from TC to IF. Patients with HI-PDAC had significantly better outcomes but showed more frequently exhausted immune phenotypes.

CONCLUSIONS

Our results indicate strategic differences in the regulation of immune determinants, leading to different levels of effectiveness of antitumor responses between HI and LI tumors and dynamic spatial changes, which affect the evolution of immune evasion and patient outcomes. This finding supports the coevolution of tumor and immune cells and may help define therapeutic vulnerabilities to improve antitumor immunity and harness the responsiveness to immune checkpoint inhibitors in patients with PDAC.

Overall survival prediction of gastric cancer using the gene signature of CT-detected extramural venous invasion combined with M2 macrophages infiltration

BACKGROUND

CT-detected Extramural venous invasion (EMVI) is known as an independent risk factor for distant metastasis in patients with advanced gastric cancer (GC). However, the molecular basis is not clear. In colorectal cancer, M2 macrophages plays a vital role in determining EMVI. This study aimed to investigate the relationship between CT-detected EMVI and the M2 macrophages as well as prognosis predictionusing a radiogenomic approach.

METHOD

We utilized EMVI-related genes (from mRNA sequencing of 13 GC samples correlated with EMVI score by spearman analysis, P < 0.01) to overlap the co-expression genes of WGCNA module and M2 macrophages related genes (from mRNA data of 371 GC patients in TCGA database), generating a total of 136 genes. An EMVI-M2-prognosis-related hub gene signature was constructed by COX and least absolute shrinkage and selection operator (LASSO) analysis from a training cohort TCGA database (n = 371) and validated it in a validation cohort from GEO database (n = 357). High- and low-risk groups were divided by hub gene (EGFLAM and GNG11) signature-derived risk scores. We assessed its predictive ability through Kaplan-Meier (K-M) curve and COX analysis. Furthermore, we utilized ESTIMATE to detect tumor mutation burden (TMB) and evaluate sensitivity to immune checkpoint inhibitors (ICIs). Expression of hub genes was tested using western blotting and immunohistochemistry (IHC) analysis.

RESULTS

The overall survival (OS) was significantly reduced in the high-risk group (Training/Validation: AUC = 0.701/0.620; P < 0.001/0.003). Furthermore, the risk score was identified as an independent predictor of OS in multivariate COX regression analyses (Training/Validation: HR = 1.909/1.928; 95% CI: 1.225-2.974/1.308-2.844). The low-risk group exhibited significantly higher TMB levels (P = 1.6e- 07) and greater sensitivity to ICIs. Significant higher expression of hub-genes was identified on multiple GC cell lines and original samples. Hub-genes knockdown in gastric cancer cell lines inhibited their proliferation, metastatic and invasive capacity to varying degrees. In vivo experiments indicate that EGFLAM, as one of the hub genes, its high expression can serve as a biomarker for low response to immunotherapy.

CONCLUSION

Our study demonstrated EMVI-M2 gene signature could effectively predict the prognosis of GC tissue, reflecting the relationship between EMVI and M2 macrophages.

RARB associated with MSI, affects progression and prognosis of gastric cancer

Microsatellite instability (MSI) has been widely acknowledged as an important factor regulating tumor intrinsic biological behavior and affecting the survival of gastric cancer patients. Here, we firstly identified the RARB as a gene associated with MSI gastric cancer. RARB was downregulated in human gastric cancer tissues compared to paired paracancerous tissues, Knockdown of RARB accelerated the proliferation, invasion and migration of cancer cells in vitro. Mechanismly, RARB knockdown promoted epithelial-mesenchymal transition (EMT) process of gastric cancer. However, RARBLow patients exhibited better survival compared to RARBHigh patients. Further study revealed that RARB expression was inversely correlated with MSI status and immune infiltrates in vivo. Thus, RARB may be a potential target for the treatment of gastric cancer.

Utility of neutrophil-to-lymphocyte ratio as an indicator of tumor immune status in non-small cell lung cancer

BACKGROUND

Neutrophil-to-lymphocyte ratio (NLR) has been reported as a prognostic biomarker in non-small cell lung cancer (NSCLC); however, the underlying biological rationale remains unclear. The present study aimed to explore the potential utility of NLR as a surrogate biomarker for immune response to cancer and to elucidate the underlying mechanism.

METHODS

This retrospective study included the medical records of 120 patients with NSCLC who underwent surgery at the study institution in 2012. NLR in peripheral blood was determined from blood test within 30 days before surgery. Tumor immune status was evaluated using immunohistochemical staining to identify CD3+, CD8+ and FOXP3+ tumor-infiltrating lymphocytes (TILs), and the relationship of NLR, with clinicopathologic characteristics including 5-year overall survival (OS), and the tumor immune status was investigated. The median values of NLR and TIL count were used as cutoff points.

RESULTS

The 5-year OS was significantly better in patients with low NLR (<2.2) than in those with high NLR (≥2.2) (70.1% vs. 56.8%, P = 0.042) and in patients with high CD3+ TIL count (≥242) than in those with low CD3+ TIL count (<242) (70% vs. 56.8%, P = 0.019). Additionally, the CD3+ TIL count was negatively correlated with preoperative NLR (P = 0.005).

CONCLUSION

NLR might potentially reflect the immune status of tumor microenvironment, explaining its impact on prognosis of patients with NSCLC.

Moderate physical activity during neoadjuvant chemotherapy in breast cancer patients: effect on cancer-related inflammation and pathological complete response-the Neo-Runner study

BACKGROUND

Physical activity (PA) reduces the risk of developing breast cancer (BC) and mortality rate in BC patients starting PA after diagnosis. Immunomodulation is considered responsible for these effects. However, limited data exist on the immunomodulation induced by moderate PA (mPA) during neoadjuvant chemotherapy (NACT). We have investigated the longitudinal change of cytokines during NACT alone or combined with mPA.

MATERIALS AND METHODS

Twenty-three cytokines were analyzed in BC patients at consecutive timepoints: at baseline (T0), before starting mPA (T1), before surgery (T2), and after surgery (T3). mPA consisted of 3-weekly brisk-walking sessions for 9-10 consecutive weeks.

RESULTS

Ninety-two patients were assessed: 21 patients refused mPA (untrained) and 71 agreed (trained). At T1, NACT induced significant up-regulation of interleukin (IL)-5, IL-6, IL-15, chemokine ligand (CCL)-2, interferon-γ, and C-X-C motif ligand (CXCL)-10 and reduction of expression of IL-13 and CCL-22. At T2, NACT and mPA induced up-regulation of IL-21, CCL-2, and tumor necrosis factor-α and reduction of expression of IL-8, IL-15, vascular endothelial growth factor, and soluble interleukin 6 receptor. Only CXCL-10 increased in untrained patients. A cytokine score (CS) was created to analyze, all together, the changes between T1 and T2. At T2 the CS decreased in trained and increased in untrained patients. We clustered the patients using cytokines and predictive factors and identified two clusters. The cluster A, encompassing 90% of trained patients, showed more pathological complete response (pCR) compared to the cluster B: 78% versus 22%, respectively.

CONCLUSIONS

mPA interacts with NACT inducing CS reduction in trained patients not observed in untrained patients, suggesting a reduction of inflammation, notwithstanding chemotherapy. This effect may contribute to the higher rate of pCR observed in the cluster A, including most trained patients.

Comprehensive analysis of single-cell RNA and bulk RNA sequencing based on M2 tumor-associated macrophage and angiogenesis-related genes to assess prognosis and therapeutic response in lung adenocarcinoma

M2 tumor-associated macrophage (M2 TAM), a crucial component of the tumor microenvironment, has a significant impact on tumor invasion and metastasis in the form of angiogenesis for lung adenocarcinoma (LUAD). In this study, both single-cell RNA and bulk RNA sequencing data were analyzed to identify 12 M2 TAM and angiogenesis-related genes (OLR1, CTSL, HLA-DPB1, NUPR1, ALOX5, DOCK4, CSF2RB, PTPN6, TNFSF12, HNRNPA2B1, NCL, and BIRC2). These genes were used to construct a prognostic signature, which was subsequently validated using an external cohort. Moreover, the immune profile analysis indicated that the low-risk group exhibited a distinct immune cell infiltration and relatively active status. Importantly, the prognostic signature was closely associated with PD-1, CTLA4, tumor mutation burden, and anti-cancer drug sensitivity. In summary, this study proposes a new prognostic signature for patients with LUAD based on M2 TAM and angiogenesis-related genes. The signature forecasts the prognosis of LUAD by an independent manner, reveals the potential molecular mechanisms involved in tumor immune-related functions, and offers appropriate clinical strategies for the treatment of patients with LUAD.

Distinctive Phenotypic and Microenvironmental Characteristics of Neuroendocrine Carcinoma and Adenocarcinoma Components in Gastric Mixed Adenoneuroendocrine Carcinoma

This study aimed to conduct an in-depth examination of gene expression and microenvironmental profiles of gastric neuroendocrine carcinoma (NEC) and mixed adeno-NEC (MANEC). Tissue microarrays from 55 patients with gastric MANEC (N = 32) or NEC (N = 23) were analyzed using digital spatial profiling (GeoMx DSP, NanoString Technologies). Representative regions of interest were selected from the adenocarcinoma (ADC) portion (ADC-MANEC) and the NEC portion (NEC-MANEC) of the MANEC cores, and pure NEC (pNEC) cores. All regions of interest were separated into epithelial components and stromal components using the masking procedure in the GeoMx platform, followed by transcriptome analysis. Comparison of gene expression between ADC-MANEC and NEC-MANEC/pNEC identified several differentially expressed genes in the epithelial (including PEG10, MAP1B, STMN3, and AKT3) and stromal (FN1, COL1A1, SPARC, and BGN) components. Gene set enrichment analysis revealed that pathways related to the E2F target and G2M checkpoint were more enriched in NEC-MANEC and pNEC than in ADC-MANEC. Deconvolution analysis showed that the microenvironmental profile varied according to histologic differentiation. In ADC-MANEC, intraepithelial infiltrating immune cells were relatively more numerous, whereas fibroblasts in the stroma were more abundant in NEC-MANEC and pNEC. This study confirmed the distinct expression profile of each histologic component of MANEC according to its tumor vs stromal compartment using the DSP platform. Although each component of MANEC shares the same genetic origin, distinctive phenotypes should not be overlooked when managing patients with MANEC. This study provides a useful validation data set for future studies.

Increased Multiplexity in Optical Tissue Clearing-Based Three-Dimensional Immunofluorescence Microscopy of the Tumor Microenvironment by Light-Emitting Diode Photobleaching

Optical tissue clearing and three-dimensional (3D) immunofluorescence (IF) microscopy is transforming imaging of the complex tumor microenvironment (TME). However, current 3D IF microscopy has restricted multiplexity; only 3 or 4 cellular and noncellular TME components can be localized in cleared tumor tissue. Here we report a light-emitting diode (LED) photobleaching method and its application for 3D multiplexed optical mapping of the TME. We built a high-power LED light irradiation device and temperature-controlled chamber for completely bleaching fluorescent signals throughout optically cleared tumor tissues without compromise of tissue and protein antigen integrity. With newly developed tissue mounting and selected region-tracking methods, we established a cyclic workflow involving IF staining, tissue clearing, 3D confocal microscopy, and LED photobleaching. By registering microscope channel images generated through 3 work cycles, we produced 8-plex image data from individual 400 μm-thick tumor macrosections that visualize various vascular, immune, and cancer cells in the same TME at tissue-wide and cellular levels in 3D. Our method was also validated for quantitative 3D spatial analysis of cellular remodeling in the TME after immunotherapy. These results demonstrate that our LED photobleaching system and its workflow offer a novel approach to increase the multiplexing power of 3D IF microscopy for studying tumor heterogeneity and response to therapy.

Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer

Since US Food and Drug Administration approval of programmed death ligand 1 (PD-L1) as the first companion diagnostic for immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, many patients have experienced increased overall survival. To improve selection of ICI responders versus nonresponders, microsatellite instability/mismatch repair deficiency (MSI/MMR) and tumor mutation burden (TMB) came into play. Clinical data show PD-L1, MSI/MMR, and TMB are independent predictive immunotherapy biomarkers. Harmonization of testing methodologies, optimization of assay design, and results analysis are ongoing. Future algorithms to determine immunotherapy eligibility might involve complementary use of current and novel biomarkers. Artificial intelligence could facilitate algorithm implementation to convert complex genetic data into recommendations for specific ICIs.

Identification of EGR4 as a prospective target for inhibiting tumor cell proliferation and a novel biomarker in colorectal cancer

EGR4 (Early Growth Response 4) is a member of the EGR family, involving in tumorigenesis. However, the function and action mechanism of EGR4 in the pathogenesis of colorectal cancer (CRC) remain unclear. To address this, we assessed the prognosis of CRC based on EGR4 using the Kaplan-Meier plotter tool and tissue microarray. The abundance of immunoinfiltration was evaluated through ssGSEA, TISIDB, and TIMER. In vitro experiments involving knockdown or overexpression of EGR4 were performed, and RNA-sequencing was conducted to explore potential mechanisms. Furthermore, we used oxaliplatin and 5-fluorouracil to validate the impact of EGR4 on chemo-resistance. Pan-cancer analysis and tissue microarray showed that EGR4 was highly expressed in CRC and significantly correlated with an unfavorable prognosis. Moreover, EGR4 expression was associated with immunoinfiltration and cancer-associated fibroblasts in the CRC microenvironment. Functional enrichment demonstrated that high-expressional EGR4 were involved in chromatin and nucleosome assembly. Additionally, EGR4 promoted the proliferation of CRC cells. Mechanistically, EGR4 upregulated TNFα to activate the NF-κB signaling pathway, and its knockdown reduced p65 nuclear translocation. Importantly, combining shEGR4 with oxaliplatin and 5-fluorouracil significantly inhibited CRC proliferation. Taken together, these findings provide new insights into the potential prognosis and therapeutic targets of EGR4 in CRC.

Entinostat, nivolumab and ipilimumab for women with advanced HER2-negative breast cancer: a phase Ib trial

We report the results of 24 women, 50% (N = 12) with hormone receptor-positive breast cancer and 50% (N = 12) with advanced triple-negative breast cancer, treated with entinostat + nivolumab + ipilimumab from the dose escalation (N = 6) and expansion cohort (N = 18) of ETCTN-9844 ( NCT02453620 ). The primary endpoint was safety. Secondary endpoints were overall response rate, clinical benefit rate, progression-free survival and change in tumor CD8:FoxP3 ratio. There were no dose-limiting toxicities. Among evaluable participants (N = 20), the overall response rate was 25% (N = 5), with 40% (N = 4) in triple-negative breast cancer and 10% (N = 1) in hormone receptor-positive breast cancer. The clinical benefit rate was 40% (N = 8), and progression-free survival at 6 months was 50%. Exploratory analyses revealed that changes in myeloid cells may contribute to responses; however, no correlation was noted between changes in CD8:FoxP3 ratio, PD-L1 status and tumor mutational burden and response. These findings support further investigation of this treatment in a phase II trial.

An On-Treatment Decreased Trend of Serum IL-6 and IL-8 as Predictive Markers Quickly Reflects Short-Term Efficacy of PD-1 Blockade Immunochemotherapy in Patients with Advanced Gastric Cancer

Objective

Immunotherapy has proven effective in treating advanced gastric cancer (AGC), yet its benefits are limited to a subset of patients. Our aim is to swiftly identify prognostic biomarkers using cytokines to improve the precision of clinical guidance and decision-making for PD-1 inhibitor-based cancer immunotherapy in AGC.

Materials and Methods

The retrospective study compared 36 patients with AGC who received combined anti-PD-1 immunotherapy and chemotherapy (immunochemotherapy) with a control group of 20 patients who received chemotherapy alone. The concentrations of TNF-α, IL-1β, IL-2R, IL-6, IL-8, IL-10, and IL-17 in the serum were assessed using chemiluminescence immunoassay at three distinct time intervals following the commencement of immunochemotherapy.

Results

When compared to controls, patients undergoing immunochemotherapy demonstrated a generalized rise in cytokine levels after the start of treatment. However, patients who benefited from immunochemotherapy showed a decrease in IL-6 or IL-8 concentrations throughout treatment (with varied trends observed for IL-1β, IL-2R, IL-10, IL-17, and TNF-α) was evident in patients benefiting from immunochemotherapy but not in those who did not benefit. Among these markers, the combination of IL-6, IL-8, and CEA showed optimal predictive performance for short-term efficacy of immunochemotherapy in AGC patients.

Conclusion

Reductions in IL-6/IL-8 levels observed during immunochemotherapy correlated with increased responsiveness to treatment effectiveness. These easily accessible blood-based biomarkers are predictive and rapid and may play a crucial role in identifying individuals likely to derive benefits from PD-1 blockade immunotherapy.

Clinicopathological significance of microsatellite instability and immune escape mechanism in patients with gastric solid-type poorly differentiated adenocarcinoma

BACKGROUND

In gastric solid-type poorly differentiated adenocarcinoma (PDA), the role of microsatellite instability and immune escape mechanism remains unclear. The current study aimed to elucidate the clinical significance of mismatch repair (MMR) status, genome profile, C-X-C motif chemokine receptor 2 (CXCR2) expression, and myeloid-derived suppressor cell (MDSC) infiltration in solid-type PDA.

METHODS

In total, 102 primary solid-type PDA cases were retrieved, and classified into 46 deficient-MMR (dMMR) and 56 proficient-MMR (pMMR) cases based on immunohistochemistry (IHC) and polymerase chain reaction-based molecular testing results. The mRNA expression profiles (NanoString nCounter Assay) of stage-matched dMMR (n = 6) and pMMR (n = 6) cases were examined. The CXCR2 expression and MDSC infiltration (CD11b- and CD33-positive cells) were investigated via IHC in all solid-type PDA cases.

RESULTS

mRNA analysis revealed several differentially expressed genes and differences in biological behavior between the dMMR (n = 46) and pMMR (n = 56) groups. In the multivariate analysis, the dMMR status was significantly associated with a longer disease-free survival (hazard ratio = 5.152, p = 0.002) and overall survival (OS) (hazard ratio = 5.050, p = 0.005). CXCR2-high expression was significantly correlated with a shorter OS in the dMMR group (p = 0.018). A high infiltration of CD11b- and CD33-positive cells was significantly correlated with a shorter OS in the pMMR group (p = 0.022, 0.016, respectively).

CONCLUSIONS

dMMR status can be a useful prognostic predictor, and CXCR2 and MDSCs can be novel therapeutic targets in patients with solid-type PDA.

Principles of risk assessment in colon cancer: immunity is key

In clinical practice, the administration of adjuvant chemotherapy (ACT) following tumor surgical resection raises a critical dilemma for stage II colon cancer (CC) patients. The prognostic features used to identify high-risk CC patients rely on the pathological assessment of tumor cells. Currently, these factors are considered for stratifying patients who may benefit from ACT at early CC stages. However, the extent to which these factors predict clinical outcomes (i.e. recurrence, survival) remains highly controversial, also uncertainty persists regarding patients' response to treatment, necessitating further investigation. Therefore, an imperious need is to explore novel biomarkers that can reliably stratify patients at risk, to optimize adjuvant treatment decisions. Recently, we evaluated the prognostic and predictive value of Immunoscore (IS), an immune digital-pathology assay, in stage II CC patients. IS emerged as the sole significant parameter for predicting disease-free survival (DFS) in high-risk patients. Moreover, IS effectively stratified patients who would benefit most from ACT based on their risk of recurrence, thus predicting their outcomes. Notably, our findings revealed that digital IS outperformed the visual quantitative assessment of the immune response conducted by expert pathologists. The latest edition of the WHO classification for digestive tumor has introduced the evaluation of the immune response, as assessed by IS, as desirable and essential diagnostic criterion. This supports the revision of current cancer guidelines and strongly recommends the implementation of IS into clinical practice as a patient stratification tool, to guide CC treatment decisions. This approach may provide appropriate personalized therapeutic decisions that could critically impact early-stage CC patient care.

Quantitative performance assessment of Ultivue multiplex panels in formalin-fixed, paraffin-embedded human and murine tumor specimens

We present a rigorous validation strategy to evaluate the performance of Ultivue multiplex immunofluorescence panels. We have quantified the accuracy and precision of four different multiplex panels (three human and one mouse) in tumor specimens with varying levels of T cell density. Our results show that Ultivue panels are typically accurate wherein the relative difference in cell proportion between a multiplex image and a 1-plex image is less than 20% for a given biomarker. Ultivue panels exhibited relatively high intra-run precision (CV ≤ 25%) and relatively low inter-run precision (CV >> 25%) which can be remedied by using local intensity thresholding to gate biomarker positivity. We also evaluated the reproducibility of cell-cell distance estimates measured from multiplex images which show high intra- and inter-run precision. We introduce a new metric, multiplex labeling efficiency, which can be used to benchmark the overall fidelity of the multiplex data across multiple batch runs. Taken together our results provide a comprehensive characterization of Ultivue panels and offer practical guidelines for analyzing multiplex images.

Identification of macrophage-related genes correlated with prognosis and immunotherapy efficacy in non-small cell lung cancer

Background

Malignant tumours, particularly non-small cell lung cancer (NSCLC), pose a significant threat to human health due to their prevalence and lethality. Treatment methods for NSCLC vary greatly among individuals, making it crucial to identify predictive markers. Moreover, during tumour initiation and progression, tumour cells can release signaling molecules to induce polarization of macrophages towards a more tumour friendly M2 phenotype, which can promote tumour growth, metastasis, and drug resistance.

Methods

We employed a comprehensive approach, combining bulk RNA-seq and single-cell sequencing analysis.

Results

In our study, we used bulk RNA-seq and single-cell sequencing methods to analyze differential cells in NSCLC and adjacent tissues, searching for relevant marker genes that can predict prognosis and drug efficacy. We scrutinized biological phenomena such as macrophage-related gene methylation, copy number variation, and alternative splicing. Additionally, we utilized a co-culture technique of immune and tumour cells to explore the role of these genes in macrophage polarization. Our findings revealed distinct differences in macrophages between cancerous and adjacent tissues. We identified ANP32A, CCL20, ERAP2, MYD88, TMEM126B, TUBB6, and ZNF655 as macrophage-related genes that correlate with NSCLC patient prognosis and immunotherapy efficacy. Notably, ERAP2, TUBB6, CCL20, and TMEM126B can induce macrophage M0 to M2 polarization, promoting tumour proliferation.

Conclusion

These findings significantly contribute to our understanding of the NSCLC tumour immune microenvironment. They pave the way for further research into the potential of these genes as targets for regulating tumour occurrence and development.

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.

CATD: a reproducible pipeline for selecting cell-type deconvolution methods across tissues

Motivation

Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the selection of appropriate methods. Additionally, the growing accessibility of single-cell RNA sequencing datasets, often accompanied by bulk expression from related samples enable the benchmark of existing methods.

Results

In this study, we conduct a comprehensive assessment of 31 methods, utilizing single-cell RNA-sequencing data from diverse human and mouse tissues. Employing various simulation scenarios, we reveal the efficacy of regression-based deconvolution methods, highlighting their sensitivity to reference choices. We investigate the impact of bulk-reference differences, incorporating variables such as sample, study and technology. We provide validation using a gold standard dataset from mononuclear cells and suggest a consensus prediction of proportions when ground truth is not available. We validated the consensus method on data from the stomach and studied its spillover effect. Importantly, we propose the use of the critical assessment of transcriptomic deconvolution (CATD) pipeline which encompasses functionalities for generating references and pseudo-bulks and running implemented deconvolution methods. CATD streamlines simultaneous deconvolution of numerous bulk samples, providing a practical solution for speeding up the evaluation of newly developed methods.

Availability and implementation

https://github.com/Papatheodorou-Group/CATD_snakemake.

Transcriptional profile and immune infiltration in colorectal cancer reveal the significance of inducible T-cell costimulator as a crucial immune checkpoint molecule

BACKGROUND

Emergence of novel immuno-therapeutics has shown promising improvement in the clinical outcome of colorectal cancer (CRC).

OBJECTIVE

To identify robust immune checkpoints based on expression and immune infiltration profiles of clinical CRC samples.

METHODS

One dataset from The Cancer Genome Atlas database and two from Gene Expression Omnibus were independently employed for the analysis. Genes associated with overall survival were identified, and distribution of each immune checkpoint with respect to different clinical features was determined to explore key immune checkpoints. Multiple staining methods were used to verify the correlation between key immune checkpoint ICOS and clinical pathological features. Differentially expressed mRNA and long non-coding RNA (lncRNA) were then detected for gene set enrichment analysis and gene set variation analysis to investigate the differentially enriched biological processes between low- and high-expression groups. Significant immune-related mRNAs and lncRNA were subjected to competing endogenous RNA (ceRNA) network analysis. Correlation of inducible T-cell costimulator (ICOS) and top 10 genes in ceRNA network were further considered for validation.

RESULTS

ICOS was identified from 14 immune checkpoints as the most highly correlated gene with survival and clinical features in CRC. The expression of ICOS protein in the poorly differentiated group was lower than that in the moderately differentiated group, and the expression in different pathological stages was significant. In addition, the expressions of ICOS were negatively correlated with Ki67. A conspicuous number of immune-related pathways were enriched in differentially expressed genes in the ICOS high- and low-expression groups. Integration with immune infiltration data revealed a multitude of differentially expressed immune-related genes enriched for ceRNA network. Furthermore, expression of top 10 genes investigated from ceRNA network showed high correlation with ICOS.

CONCLUSION

ICOS might serve as a robust immune checkpoint for prognosis with several genes being potential targets of ICOS-directed immunotherapy in CRC.

An immune-related gene prognostic prediction risk model for neoadjuvant chemoradiotherapy in rectal cancer using artificial intelligence

Background

This study aimed to establish and validate a prognostic model based on immune-related genes (IRGPM) for predicting disease-free survival (DFS) in patients with locally advanced rectal cancer (LARC) undergoing neoadjuvant chemoradiotherapy, and to elucidate the immune profiles associated with different prognostic outcomes.

Methods

Transcriptomic and clinical data were sourced from the Gene Expression Omnibus (GEO) database and the West China Hospital database. We focused on genes from the RNA immune-oncology panel. The elastic net approach was employed to pinpoint immune-related genes significantly impacting DFS. We developed the IRGPM for rectal cancer using the random forest technique. Based on the IRGPM, we calculated prognostic risk scores to categorize patients into high-risk and low-risk groups. Comparative analysis of immune characteristics between these groups was conducted.

Results

In this study, 407 LARC samples were analyzed. The elastic net identified a signature of 20 immune-related genes, forming the basis of the IRGPM. Kaplan-Meier survival analysis revealed a lower 5-year DFS in the high-risk group compared to the low-risk group. The receiver operating characteristic (ROC) curve affirmed the model's robust predictive capability. Validation of the model was performed in the GSE190826 cohort and our institution's cohort. Gene expression differences between high-risk and low-risk groups predominantly related to cytokine-cytokine receptor interactions. Notably, the low-risk group exhibited higher immune scores. Further analysis indicated a greater presence of activated B cells, activated CD8 T cells, central memory CD8 T cells, macrophages, T follicular helper cells, and type 2 helper cells in the low-risk group. Additionally, immune checkpoint analysis revealed elevated PDCD1 expression in the low-risk group.

Conclusions

The IRGPM, developed through random forest and elastic net methodologies, demonstrates potential in distinguishing DFS among LARC patients receiving standard treatment. Notably, the low-risk group, as defined by the IRGPM, showed enhanced activation of adaptive immune responses within the tumor microenvironment.

Research progress of exosomes in drug resistance of breast cancer

Since breast cancer is a heterogeneous disease, there are currently a variety of treatment methods available, including chemotherapy, endocrine therapy, molecular targeted therapy, immunotherapy, radiation therapy, etc. Breast cancer recurrence and metastasis, despite many treatment modalities, constitute a considerable threat to patients' survival time and pose a clinical challenge that is difficult to tackle precisely. Exosomes have a very special and crucial role in the treatment of drug resistance in breast cancer as a carrier of intercellular communication in the tumor microenvironment. Exosomes and breast cancer treatment resistance have been linked in a growing number of clinical investigations in recent years. This paper covers the status of research on exosomes in the treatment of breast cancer drug resistance and offers theoretical guidance for investigating new strategies to treat breast cancer drug resistance.

A recurrence-predictive model based on eight genes and tumor mutational burden/microsatellite instability status in Stage II/III colorectal cancer

BACKGROUND

Although adjuvant chemotherapy (ACT) is widely used to treat patients with Stage II/III colorectal cancer (CRC), administering ACT to specific patients remains a challenge. The decision to ACT requires an accurate assessment of recurrence risk and absolute treatment benefit. However, the traditional TNM staging system does not accurately assess a patient's individual risk of recurrence.

METHODS

To identify recurrence risk-related genetic factors for Stage II/III CRC patients after radical surgery, we conducted an analysis of whole-exome sequencing of 47 patients with Stage II/III CRC who underwent radical surgery at five institutions. Patients were grouped into non-recurrence group (NR, n = 24, recurrence-free survival [RFS] > 5 years) and recurrence group (R, n = 23, RFS <2 years). The TCGA-COAD/READ cohort was employed as the validation dataset.

RESULTS

A recurrence-predictive model (G8plus score) based on eight gene (CUL9, PCDHA12, HECTD3, DCX, SMARCA2, FAM193A, AATK, and SORCS2) mutations and tumor mutation burden/microsatellite instability (TMB/MSI) status was constructed, with 97.87% accuracy in our data and 100% negative predictive value in the TCGA-COAD/READ cohort. For the TCGA-COAD/READ cohort, the G8plus-high group had better RFS (HR = 0.22, p = 0.024); the G8plus-high tumors had significantly more infiltrated immune cell types, higher tertiary lymphoid structure signature scores, and higher immunological signature scores. The G8plus score was also a predict biomarker for immunotherapeutic in advanced CRC in the PUCH cohort.

CONCLUSIONS

In conclusion, the G8plus score is a powerful biomarker for predicting the risk of recurrence in patients with stage II/III CRC. It can be used to stratify patients who benefit from ACT and immunotherapy.

Characterization of candidate factors associated with the metastasis and progression of high-grade serous ovarian cancer

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is the biggest cause of gynecological cancer-related mortality because of its extremely metastatic nature. This study aimed to explore and evaluate the characteristics of candidate factors associated with the metastasis and progression of HGSOC.

METHODS

Transcriptomic data of HGSOC patients' samples collected from primary tumors and matched omental metastatic tumors were obtained from three independent studies in the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were selected to evaluate the effects on the prognosis and progression of ovarian cancer using data from The Cancer Genome Atlas (TCGA) database. Hub genes' immune landscapes were estimated by the Tumor Immune Estimation Resource (TIMER) database. Finally, using 25 HGSOC patients' cancer tissues and 10 normal fallopian tube tissues, immunohistochemistry (IHC) was performed to quantify the expression levels of hub genes associated with International Federation of Gynecology and Obstetrics (FIGO) stages.

RESULTS

Fourteen DEGs, ADIPOQ , ALPK2 , BARX1 , CD37 , CNR2 , COL5A3 , FABP4 , FAP , GPR68 , ITGBL1 , MOXD1 , PODNL1 , SFRP2 , and TRAF3IP3 , were upregulated in metastatic tumors in every database while CADPS , GATA4 , STAR , and TSPAN8 were downregulated. ALPK2 , FAP , SFRP2 , GATA4 , STAR , and TSPAN8 were selected as hub genes significantly associated with survival and recurrence. All hub genes were correlated with tumor microenvironment infiltration, especially cancer-associated fibroblasts and natural killer (NK) cells. Furthermore, the expression of FAP and SFRP2 was positively correlated with the International Federation of Gynecology and Obstetrics (FIGO) stage, and their increased protein expression levels in metastatic samples compared with primary tumor samples and normal tissues were confirmed by IHC ( P = 0.0002 and P = 0.0001, respectively).

CONCLUSIONS

This study describes screening for DEGs in HGSOC primary tumors and matched metastasis tumors using integrated bioinformatics analyses. We identified six hub genes that were correlated with the progression of HGSOC, particularly FAP and SFRP2 , which might provide effective targets to predict prognosis and provide novel insights into individual therapeutic strategies for HGSOC.

Increased multiplexity in optical tissue clearing-based 3D immunofluorescence microscopy of the tumor microenvironment by LED photobleaching

Optical tissue clearing and three-dimensional (3D) immunofluorescence (IF) microscopy have been transforming imaging of the complex tumor microenvironment (TME). However, current 3D IF microscopy has restricted multiplexity; only three or four cellular and non-cellular TME components can be localized in a cleared tumor tissue. Here we report a LED photobleaching method and its application for 3D multiplexed optical mapping of the TME. We built a high-power LED light irradiation device and temperature-controlled chamber for completely bleaching fluorescent signals throughout optically cleared tumor tissues without compromise of tissue and protein antigen integrity. With newly developed tissue mounting and selected region-tracking methods, we established a cyclic workflow involving IF staining, tissue clearing, 3D confocal microscopy, and LED photobleaching. By registering microscope channel images generated through three work cycles, we produced 8-plex image data from individual 400 μm-thick tumor macrosections that visualize various vascular, immune, and cancer cells in the same TME at tissue-wide and cellular levels in 3D. Our method was also validated for quantitative 3D spatial analysis of cellular remodeling in the TME after immunotherapy. These results demonstrate that our LED photobleaching system and its workflow offer a novel approach to increase the multiplexing power of 3D IF microscopy for studying tumor heterogeneity and response to therapy.

[Profile and immune environment of upper tract urothelial carcinoma]

INTRODUCTION AND OBJECTIVES

Upper Tract Urothelial Carcinoma (UTUC) are tumors that share similarities with bladder tumors. Immunotherapy is already used for bladder locations and appears to have interest for UTUC. In order to rationalize the immunotherapy development pipeline it seemed necessary to describe the immune infiltrate of a cohort of UTUC treated with nephroureterectomy and to determine the expression of a panel of immune checkpoints and co-stimulatory molecules on tumor cells as well as on infiltrating and circulating lymphocytes.

MATERIALS AND METHODS

This is a monocentric, prospective and exploratory work. Patients treated with total nephroureterectomy or segmental ureterectomy for presumably infiltrative (≥ T1) UTUC managed at the Saint-Louis Hospital were included from January 2019 to July 2020. A set of markers and immune checkpoints were studied by flow fluorocytometry on circulating lymphocytes (PBMCs) and tumor-infiltrating lymphocytes (TILs). Some markers were also studied by immunohistochemistry on tumor sample.

RESULTS

In total, 14 patients were included and 13 patients could be analyzed. 1 patient had no residual tumor. 5 tumors out of the 12 (41.7%) showed a lymphocytic inflammatory infiltrate. PD1 was the most represented checkpoint with a median expression rate of 41.4% on CD4+ TILs and 3.89% on circulating CD4+ T cells. This rate was 62.4% and 7.45% respectively on CD8+ T cells. TIGIT was the second most represented marker with a median expression rate on tumor-infiltrating CD4+ T cells of 25% and 2.9% on circulating CD4+ T cells. The median expression level of TIGIT on tumor-infiltrating CD8+ T cells was 23.3% and 3.2% on circulating CD8+ T cells. ICOS was highly expressed on CD4+ TILS with a median of 33.9% in contrast to CD8+ TILS (median: 6.67%). Variable expression of other checkpoints (ILT2, TIM3, LAG3 and OX40) was found without clear trend.

CONCLUSION

This exploratory work highlighted that PD1 was the most represented checkpoint. TIGIT was the second most represented checkpoint while ICOS, TIM3 and LAG3 were 3 other checkpoints whose expression was found to be less important. ILT2 and OX40 appeared to be weakly expressed.

LEVEL OF EVIDENCE

II.

A neutrophil extracellular traps-related classification predicts prognosis and response to immunotherapy in colon cancer

Neutrophil extracellular traps (NETs) have been categorized as a form of inflammatory cell death mode of neutrophils (NETosis) involved in natural immunity and the regulation of adaptive immunity. More and more studies revealed the ability of NETs to reshape the tumor immune microenvironment (TIME) by limiting antitumor effector cells, which may impair the efficacy of immunotherapy. To explore whether NETs-related genes make vital impacts on Colon carcinoma (COAD), we have carried out a systematic analysis and showed several findings in the present work. First, we obtained the patient's data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset, aiming to detect two NETs-associated subtypes by consensus clustering. For the purpose of annotating the roles of NETs-related pathways, gene ontology enrichment analyses were adopted. Next, we constructed a 6 novel NETs-related genes score using the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model. We found that the NETs risk score was notably upregulated in COAD patient samples, and its levels were notably correlated with tumor clinicopathological and immune traits. Then, according to NETs-associated molecular subtypes and the risk signature, this study compared immune cell infiltration calculated through the estimate, CIBERSORT, TIMER, ssGSEA algorithms, tumor immune dysfunction, as well as exclusion (TIDE). Furthermore, we confirm that MPO(myeloperoxidase) was significantly upregulated in COAD patient samples, and its levels were significantly linked to tumor malignancy and clinic outcome. Moreover, multiplex immunohistochemistry (mIHC) spatial analysis confirmed that MPO was closely related to Treg and PD-1 + Treg in spatial location which suggested MPO may paly an important role in TIME formation. Altogether, the obtained results indicated that a six NETs-related genes prognostic signature was conducive to estimating the prognosis and response of chemo-/immuno-therapy of COAD patients.

A novel immune-related gene signature for predicting immunotherapy outcomes and survival in clear cell renal cell carcinoma

Clear cell renal carcinoma (ccRCC) is one of the most common cancers worldwide. In this study, a new model of immune-related genes was developed to predict the overall survival and immunotherapy efficacy in patients with ccRCC. Immune-related genes were obtained from the ImmPort database. Clinical data and transcriptomics of ccRCC samples were downloaded from GSE29609 and The Cancer Genome Atlas. An immune-related gene-based prognostic model (IRGPM) was developed using the least absolute shrinkage and selection operator regression algorithm and multivariate Cox regression. The reliability of the developed models was evaluated by Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves. Furthermore, we constructed a nomogram based on the IRGPM and multiple clinicopathological factors, along with a calibration curve to examine the predictive power of the nomogram. Overall, this study investigated the association of IRGPM with immunotherapeutic efficacy, immune checkpoints, and immune cell infiltration. Eleven IRGs based on 528 ccRCC samples significantly associated with survival were used to construct the IRGPM. Remarkably, the IRGPM, which consists of 11 hub genes (SAA1, IL4, PLAUR, PLXNB3, ANGPTL3, AMH, KLRC2, NR3C2, KL, CSF2, and SEMA3G), was found to predict the survival of ccRCC patients accurately. The calibration curve revealed that the nomogram developed with the IRGPM showed high predictive performance for the survival probability of ccRCC patients. Moreover, the IRGPM subgroups showed different levels of immune checkpoints and immune cell infiltration in patients with ccRCC. IRGPM might be a promising biomarker of immunotherapeutic responses in patients with ccRCC. Overall, the established IRGPM was valuable for predicting survival, reflecting the immunotherapy response and immune microenvironment in patients with ccRCC.

Reprogramming the lipid metabolism of dendritic cells in tumor immunomodulation and immunotherapy

Dendritic cells (DCs) are the most potent antigen-presenting cells in the human body. They detect and process environmental signals and communicate with T cells to bridge innate and adaptive immunity. Cell activation, function, and survival are closely associated with cellular metabolism. An increasing number of studies have revealed that lipid metabolism affects DC activation as well as innate and acquired immune responses. Combining lipid metabolic regulation with immunotherapy can strengthen the ability of antigen-presentation and T-cell activation of DCs, improve the existing anti-tumor therapy, and overcome the defects of DC-related therapies in the current stage, which has great potential in cancer therapy. This review summarizes the lipid metabolism of DCs under physiological conditions, analyzes the role of reprogramming the lipid metabolism of DCs in tumor immune regulation, and discusses potential immunotherapeutic strategies.

Emerging Prognostic and Predictive Factors in Pancreatic Cancer

Pancreatic cancer is a lethal disease with increasing incidence and high recurrence rates and is currently resistant to conventional therapies. Moreover, it displays extensive morphologic and molecular intratumoral and intertumoral heterogeneity and a mostly low mutational burden, failing to induce significant antitumor immunity. Thus, immunotherapy has shown limited effect in pancreatic cancer, except in rare tumors with microsatellite instability, constituting <1% of the cases. Currently, new methods, including single-cell and single-nucleus RNA sequencing, have refined and expanded the 2-group molecular classification based on bulk RNA sequencing (classical and basal-like subtypes), identifying hybrid forms and providing us with a comprehensive map of the tumor cell subsets that drive gene expression during tumor evolution, simultaneously giving us insight into therapy resistance and metastasis. Additionally, deeper profiling of the tumor microenvironment of pancreatic cancer by using spatial analyses and multiplex imaging techniques has improved our understanding of the heterogeneous distribution of both adaptive and innate immune components with their protumor and antitumor properties. By integrating host immune response patterns, as defined by spatial transcriptomic and proteomic analysis and multiplex immunofluorescence, with molecular and morphologic features of the tumors, we can increasingly understand the genetic, immunologic, and morphologic background of pancreatic cancer and recognize the potential predictors for different treatment modalities.

Single-cell characterization of macrophages in uveal melanoma uncovers transcriptionally heterogeneous subsets conferring poor prognosis and aggressive behavior

Uveal melanoma (UM) is the most frequent primary intraocular malignancy with high metastatic potential and poor prognosis. Macrophages represent one of the most abundant infiltrating immune cells with diverse functions in cancers. However, the cellular heterogeneity and functional diversity of macrophages in UM remain largely unexplored. In this study, we analyzed 63,264 single-cell transcriptomes from 11 UM patients and identified four transcriptionally distinct macrophage subsets (termed MΦ-C1 to MΦ-C4). Among them, we found that MΦ-C4 exhibited relatively low expression of both M1 and M2 signature genes, loss of inflammatory pathways and antigen presentation, instead demonstrating enhanced signaling for proliferation, mitochondrial functions and metabolism. We quantified the infiltration abundance of MΦ-C4 from single-cell and bulk transcriptomes across five cohorts and found that increased MΦ-C4 infiltration was relevant to aggressive behaviors and may serve as an independent prognostic indicator for poor outcomes. We propose a novel subtyping scheme based on macrophages by integrating the transcriptional signatures of MΦ-C4 and machine learning to stratify patients into MΦ-C4-enriched or MΦ-C4-depleted subtypes. These two subtypes showed significantly different clinical outcomes and were validated through bulk RNA sequencing and immunofluorescence assays in both public multicenter cohorts and our in-house cohort. Following further translational investigation, our findings highlight a potential therapeutic strategy of targeting macrophage subsets to control metastatic disease and consistently improve the outcome of patients with UM.

Cervical carcinoma induces NLRP3 inflammasome activation and IL-1ß release in human peripheral blood monocytes affecting patients' overall survival

PURPOSE

Our group previously demonstrated that genetic variants in inflammasome genes contribute to protection against the establishment of human papilloma virus (HPV)-associated cervical carcinoma (CC). The objective of this study was to better understand the contribution of inflammasome and its cytokines in the CC microenvironment.

METHODS

The inflammasome activation was analyzed in CC tumoral cell lines and healthy donors (HD)' monocytes in co-culture. In vitro results were then compared to CC patients' public databases.

RESULTS

CC cells did not produce IL-1ß or IL-18 themselves, however, when in co-culture with HD monocytes, induced IL-1ß release in those leucocytes. Inflammasome activation appears to be partially dependent on the NLRP3 receptor. Public data analysis revealed that IL1B expression is increased in the CC compared to normal uterine cervix, and that patients with high IL1B expression had a shorter overall survival.

CONCLUSION

CC microenvironment can activate the inflammasome and IL-1ß release in surrounding monocytes, which could be detrimental for CC prognosis.

Hope and Challenges: Immunotherapy in EGFR-Mutant NSCLC Patients

EGFR tyrosine kinase inhibitors (TKIs) are the preferred initial treatment for non-small cell lung cancer (NSCLC) patients harboring sensitive EGFR mutations. Sadly, remission is transient, and no approved effective treatment options are available for EGFR-TKI-advanced EGFR-mutant NSCLCs. Although immunotherapy with immune checkpoint inhibitors (ICIs) induces sustained cancer remission in a subset of NSCLCs, ICI therapy exhibits limited activity in most EGFR-mutant NSCLCs. Mechanistically, the strong oncogenic EGFR signaling in EGFR-mutant NSCLCs contributes to a non-inflamed tumor immune microenvironment (TIME), characterized by a limited number of CD8+ T cell infiltration, a high number of regulatory CD4+ T cells, and an increased number of inactivated infiltrated T cells. Additionally, EGFR-mutant NSCLC patients are generally non-smokers with low levels of PD-L1 expression and tumor mutation burden. Promisingly, a small population of EGFR-mutant NSCLCs still durably respond to ICI therapy. The hope of ICI therapy from pre-clinical studies and clinical trials is reviewed in EGFR-mutant NSCLCs. The challenges of application ICI therapy in EGFR-mutant NSCLCs are also reviewed.

Immune Cell Abundance and T-cell Receptor Landscapes Suggest New Patient Stratification Strategies in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a molecularly and spatially heterogeneous disease frequently characterized by impairment of immunosurveillance mechanisms. Despite recent success with immunotherapy treatment, disease progression still occurs quickly after treatment in the majority of cases, suggesting the need to improve patient selection strategies. In the quest for biomarkers that may help inform response to checkpoint blockade, we characterized the tumor microenvironment (TME) of 162 HNSCC primary tumors of diverse etiologic and spatial origin, through gene expression and IHC profiling of relevant immune proteins, T-cell receptor (TCR) repertoire analysis, and whole-exome sequencing. We identified five HNSCC TME categories based on immune/stromal composition: (i) cytotoxic, (ii) plasma cell rich, (iii) dendritic cell rich, (iv) macrophage rich, and (v) immune-excluded. Remarkably, the cytotoxic and plasma cell rich subgroups exhibited a phenotype similar to tertiary lymphoid structures (TLS), which have been previously linked to immunotherapy response. We also found an increased richness of the TCR repertoire in these two subgroups and in never smokers. Mutational patterns evidencing APOBEC activity were enriched in the plasma cell high subgroup. Furthermore, specific signal propagation patterns within the Ras/ERK and PI3K/AKT pathways associated with distinct immune phenotypes. While traditionally CD8/CD3 T-cell infiltration and immune checkpoint expression (e.g., PD-L1) have been used in the patient selection process for checkpoint blockade treatment, we suggest that additional biomarkers, such as TCR productive clonality, smoking history, and TLS index, may have the ability to pull out potential responders to benefit from immunotherapeutic agents.

SIGNIFICANCE

Here we present our findings on the genomic and immune landscape of primary disease in a cohort of 162 patients with HNSCC, benefitting from detailed molecular and clinical characterization. By employing whole-exome sequencing and gene expression analysis of relevant immune markers, TCR profiling, and staining of relevant proteins involved in immune response, we highlight how distinct etiologies, cell intrinsic, and environmental factors combine to shape the landscape of HNSCC primary disease.

The Role of NCS1 in Immunotherapy and Prognosis of Human Cancer

The Neural Calcium Sensor1 (NCS1) is a crucial protein that binds to Ca2+ and is believed to play a role in regulating tumor invasion and cell proliferation. However, the role of NCS1 in immune infiltration and cancer prognosis is still unknown. Our study aimed to explore the expression profile, immune infiltration pattern, prognostic value, biological function, and potential compounds targeting NCS1 using public databases. High expression of NCS1 was detected by immune histochemical staining in LIHC (Liver hepatocellular carcinoma), BRCA (Breast invasive carcinoma), KIRC (Kidney renal clear cell carcinoma), and SKCM (Skin Cutaneous Melanoma). The expression of NCS1 in cancer was determined by TCGA (The Cancer Genome Atlas Program), GTEx (The Genotype-Tissue Expression), the Kaplan-Meier plotter, GEO (Gene Expression Omnibus), GEPIA2.0 (Gene Expression Profiling Interactive Analysis 2.0), HPA (The Human Protein Atlas), UALCAN, TIMER2.0, TISIDB, Metascape, Drugbank, chEMBL, and ICSDB databases. NCS1 has genomic mutations as well as aberrant DNA methylation in multiple cancers compared to normal tissues. Also, NCS1 was significantly different in the immune microenvironment, tumor mutational burden (TMB), microsatellite instability (MSI), and immune infiltrate-associated cells in different cancers, which could be used for the typing of immune and molecular subtypes of cancer and the presence of immune checkpoint resistance in several cancers. Univariate regression analysis, multivariate regression analysis, and gene enrichment analysis to construct prognostic models revealed that NCS1 is involved in immune regulation and can be used as a prognostic biomarker for SKCM, LIHC, BRCA, COAD, and KIRC. These results provide clues from a bioinformatic perspective and highlight the importance of NCS1 in a variety of cancers.

Advances in immunotyping of colorectal cancer

Immunotherapy has transformed treatment for various types of malignancy. However, the benefit of immunotherapy is limited to a minority of patients with mismatch-repair-deficient (dMMR) and microsatellite instability-high (MSI-H) (dMMR-MSI-H) colorectal cancer (CRC). Understanding the complexity and heterogeneity of the tumor immune microenvironment (TIME) and identifying immune-related CRC subtypes will improve antitumor immunotherapy. Here, we review the current status of immunotherapy and typing schemes for CRC. Immune subtypes have been identified based on TIME and prognostic gene signatures that can both partially explain clinical responses to immune checkpoint inhibitors and the prognosis of patients with CRC. Identifying immune subtypes will improve understanding of complex CRC tumor heterogeneity and refine current immunotherapeutic strategies.

Programmed Death Ligand 1 Expression in Lung Adenocarcinoma: An Analysis of the Histomorphological Features

Background

Immunotherapy is now a vital target therapy in the advanced cases of lung adenocarcinoma. The outstanding result of therapies with medications that inhibit the interaction of programmed death ligand 1 with programmed death protein 1 has revolutionarized prognostic treatment regimes.

Aims

The study was undertaken with the objectives to analyze the detailed histomorphological features of adenocarcinoma lung with programmed death ligand-1 (PD-L1) expression in tumor cells and to compare the histomorphological features with PD-L1 negative group.

Materials and Methods

The present study is a retrospective case series with 100 cases of non-small cell lung cancer-adenocarcinoma phenotype in which testing for PD-L1 had been done using immunohistochemistry. Detailed histomorphological analysis and comparison was performed for both the PD-L1 positive and negative phenotype.

Results

Histomorphological features of 25 cases with positive PD-L1 positivity in the tumor cells and 75 cases that were negative for PD-L1 were analyzed. The most frequent pattern in the category that was PD-L1 positive was singly scattered cells or loose clusters present in 84% cases followed by solid nests that was identified in 60% cases. The presence of solid nests in the PD-L1 positive category was statistically significant (P = 0.018). Mucin was identified in 24% cases, and tumor necrosis was documented in 60% cases with PD-L1 positivity. In the cluster that was PD-L1 positive, 92% cases had moderate-to-severe nuclear pleomorphism.

Conclusion

The identification of histomorphological patterns and characteristics may aid in triaging cases that have the likelihood to harbor PD-L1-positive phenotype, which has predictive and prognostic outcome.

A PD-L1 Antibody-Conjugated PAMAM Dendrimer Nanosystem for Simultaneously Inhibiting Glycolysis and Promoting Immune Response in Fighting Breast Cancer

Breast cancer is the most frequent malignancy affecting women, yet current therapeutic strategies remain ineffective for patients with late-stage or metastatic disease. Here an effective strategy is reported for treating metastatic breast cancer. Specifically, a self-assembling dendrimer nanosystem decorated with an antibody against programmed cell death ligand 1 (PD-L1) is established for delivering a small interfering RNA (siRNA) to target 3-phosphoinositide-dependent protein kinase-1 (PDK1), a kinase involved in cancer metabolism and metastasis. This nanosystem, named PPD, is designed to target PD-L1 for cancer-specific delivery of the siRNA to inhibit PDK1 and modulate cancer metabolism while promoting programmed cell death 1 (PD-1)/PD-L1 pathway-based immunotherapy. Indeed, PPD effectively generates simultaneous inhibition of PDK1-induced glycolysis and the PD-1/PD-L1 pathway-related immune response, leading to potent inhibition of tumor growth and metastasis without any notable toxicity in tumor-bearing mouse models. Collectively, these results highlight the potential use of PPD as an effective and safe tumor-targeting therapy for breast cancer. This study constitutes a successful proof of principle exploiting the intrinsic features of the tumor microenvironment and metabolism alongside a unique self-assembling dendrimer platform to achieve specific tumor targeting and siRNA-based gene silencing in combined and precision cancer therapy.

High density and proximity of CD8+ T cells to tumor cells are correlated with better response to nivolumab treatment in metastatic pleural mesothelioma

BACKGROUND

The efficacy of immune checkpoint inhibitors (ICIs) in pleural mesothelioma has recently been established. The response to ICIs can be predicted by quantitative analysis of cells and their spatial distribution in the tumor microenvironment (TME). However, the detailed composition of the TME in pleural mesothelioma has not been reported. We evaluated the association between the TME and response to ICIs in this cancer.

METHODS

A retrospective analysis of 22 pleural mesothelioma patients treated with nivolumab in different centers was performed using surgical specimens. Four patients had a partial response to nivolumab (response group) and 18 patients had stable or progressive disease (nonresponse group). The number of CD4, CD8, FoxP3, CK, and PD-L1 positive cells, cell density, and cell-to-cell distance were analyzed by multiplex immunofluorescence.

RESULTS

PD-L1 expression did not differ significantly between the response and nonresponse groups. The density of total T cells and of CD8⁺ T cells was significantly higher in the response than in the nonresponse group. CD8⁺ T cells were more clustered and located closer to tumor cells, whereas regulatory T cells were located further from tumor cells in the response than in the nonresponse group.

CONCLUSIONS

High density and spatial proximity of CD8⁺ T cells to tumor cells were associated with better response to nivolumab, whereas the proximity of regulatory T cells to tumor cells was associated with worse response, suggesting that the distinct landscape of the TME could be a potential predictor of ICI efficacy in pleural mesothelioma.

Ophiopogon japonicus and its active compounds: A review of potential anticancer effects and underlying mechanisms

BACKGROUND

Ophiopogon japonicus (Thunb.) Ker Gawl., a well-known Chinese herb, has been used in traditional Chinese medicine for thousands of years. Extensive in vitro and in vivo studies have shown that O. japonicus and its active compounds exhibit potential anticancer effects in a variety of cancer cells in vitro and suppress tumor growth and metastasis without causing serious toxicity in vivo.

PURPOSE

This review aims to systemically summarize and discuss the anticancer effects and the underlying mechanisms of O. japonicus extracts and its active compounds.

METHODS

The review is prepared following the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Various scientific databases including Web of Science, PubMed, Scopus, and Chinese National Knowledge Infrastructure were searched using the keywords: Ophiopogon japonicus, tumor, cancer, carcinoma, content, pharmacokinetics, and toxicity.

RESULTS

O. japonicus extracts and the active compounds, such as ruscogenin-1-O-[β-d-glucopyranosyl(1→2)][β-d-xylopyranosyl(1→3)]-β-d-fucopyranoside (DT-13), ophiopogonin B, and ophiopogonin D, exert potential anticancer effects, including the induction of cell cycle arrest, activation of apoptosis and autophagy, and inhibition of metastasis and angiogenesis. In addition, the mechanisms underlying these effects, as well as the pharmacokinetics, toxicity and clinical utility of O. japonicus extracts and active compounds are discussed. Furthermore, this review highlights the research and application prospects of these compounds in immunotherapy and combination chemotherapy.

CONCLUSIONS

The traditional herb O. japonicus and its phytochemicals could be safe and reliable anticancer drug candidates, alone or in combination with chemotherapeutic drugs. We hope that this review, which highlights the anticancer properties of O. japonicus, will contribute to drug optimization, therapeutic development, and future studies on cancer therapies based on this medicinal plant.

P2X1 and P2X7 Receptor Overexpression Is a Negative Predictor of Survival in Muscle-Invasive Bladder Cancer

Bladder cancer is amongst the most common causes of cancer death worldwide. Muscle-invasive bladder cancer (MIBC) bears a particularly poor prognosis. Overexpression of purinergic P2X receptors (P2XRs) has been associated with worse outcome in several malignant tumors. Here, we investigated the role of P2XRs in bladder cancer cell proliferation in vitro and the prognostic value of P2XR expression in MIBC patients. Cell culture experiments with T24, RT4, and non-transformed TRT-HU-1 cells revealed a link between high ATP concentrations in the cell culture supernatants of bladder cell lines and a higher grade of malignancy. Furthermore, proliferation of highly malignant T24 bladder cancer cells depended on autocrine signaling through P2X receptors. P2X1R, P2X4R, and P2X7R expression was immunohistochemically analyzed in tumor specimens from 173 patients with MIBC. High P2X1R expression was associated with pathological parameters of disease progression and reduced survival time. High combined expression of P2X1R and P2X7R increased the risk of distant metastasis and was an independent negative predictor of overall and tumor-specific survival in multivariate analyses. Our results suggest that P2X1R/P2X7R expression scores are powerful negative prognostic markers in MIBC patients and that P2XR-mediated pathways are potential targets for novel therapeutic strategies in bladder cancer.

Current Progress on Predictive Biomarkers for Response to Immune Checkpoint Inhibitors in Gastric Cancer: How to Maximize the Immunotherapeutic Benefit?

Gastric cancer is the fifth most prevalent cancer and the fourth leading cause of cancer death globally. Delayed diagnosis and pronounced histological and molecular variations increase the complexity and challenge of treatment. Pharmacotherapy, which for a long time was systemic chemotherapy based on 5-fluorouracil, is the mainstay of management for advanced gastric cancer. Trastuzumab and programmed cell death 1 (PD-1) inhibitors have altered the therapeutic landscape, contributing to noticeably prolonged survivorship in patients with metastatic gastric cancer. However, research has revealed that immunotherapy is only beneficial to some individuals. Biomarkers, such as programmed cell death ligand 1 (PD-L1), microsatellite instability (MSI), and tumor mutational load (TMB), have been shown to correlate with immune efficacy in numerous studies and are increasingly employed for the selection of patients most likely to respond to immunotherapy. Gut microorganisms, genetic mutations like POLE/POLD1 and NOTCH4, tumor lymphoid infiltrating cells (TILs), and other novel biomarkers have the potential to develop into new predictors. Prospective immunotherapy for gastric cancer should be guided by a biomarker-driven precision management paradigm, and multidimensional or dynamic marker testing could be the way to go.

A Novel Aging-Related Prognostic lncRNA Signature Correlated with Immune Cell Infiltration and Response to Immunotherapy in Breast Cancer

Breast cancer (BC) is among the most universal malignant tumors in women worldwide. Aging is a complex phenomenon, caused by a variety of factors, that plays a significant role in tumor development. Consequently, it is crucial to screen for prognostic aging-related long non-coding RNAs (lncRNAs) in BC. The BC samples from the breast-invasive carcinoma cohort were downloaded from The Cancer Genome Atlas (TCGA) database. The differential expression of aging-related lncRNAs (DEarlncRNAs) was screened by Pearson correlation analysis. Univariate Cox regression, LASSO-Cox analysis, and multivariate Cox analysis were performed to construct an aging-related lncRNA signature. The signature was validated in the GSE20685 dataset from the Gene Expression Omnibus (GEO) database. Subsequently, a nomogram was constructed to predict survival in BC patients. The accuracy of prediction performance was assessed through the time-dependent receiver operating characteristic (ROC) curves, Kaplan-Meier analysis, principal component analyses, decision curve analysis, calibration curve, and concordance index. Finally, differences in tumor mutational burden, tumor-infiltrating immune cells, and patients' response to chemotherapy and immunotherapy between the high- and low-risk score groups were explored. Analysis of the TCGA cohort revealed a six aging-related lncRNA signature consisting of MCF2L-AS1, USP30-AS1, OTUD6B-AS1, MAPT-AS1, PRR34-AS1, and DLGAP1-AS1. The time-dependent ROC curve proved the optimal predictability for prognosis in BC patients with areas under curves (AUCs) of 0.753, 0.772, and 0.722 in 1, 3, and 5 years, respectively. Patients in the low-risk group had better overall survival and significantly lower total tumor mutational burden. Meanwhile, the high-risk group had a lower proportion of tumor-killing immune cells. The low-risk group could benefit more from immunotherapy and some chemotherapeutics than the high-risk group. The aging-related lncRNA signature can provide new perspectives and methods for early BC diagnosis and therapeutic targets, especially tumor immunotherapy.

Prognostic value of various immune cells and Immunoscore in triple-negative breast cancer

Background

This study aimed to evaluate the expression status and prognostic role of various immunoregulatory cells and test in triple-negative breast cancer (TNBC).

Methods

The expression of five markers (CD3/CD4/CD8/CD19/CD163) of tumor immune cells was evaluated retrospectively in tumor sections from 68 consecutive cases of TNBC by immunohistochemistry. Computational image analysis was used to quantify the density and distribution of each immune marker within the tumor region, tumor invasive margin, and expression hotspots. Immunoscores were calculated using an automated approach. Other clinical characteristics were also analyzed.

Results

For all patients, Kaplan–Meier survival analysis showed that high CD3+ signals in the tumor region (disease-free survival (DFS), P=0.0014; overall survival (OS), P=0.0031) and total region (DFS, P=0.0014; OS, P=0.0031) were significantly associated with better survival. High CD4+ levels in the tumor region and total regions were significantly associated with better survival (P&lt;0.05). For Hotspot analysis, CD3+ was associated with significantly better survival for all Top1, Top2, and Top3 densities (DFS and OS, P&lt;0.05). High CD4+ levels were significantly associated with better prognosis for Top1 and Top3 densities (DFS and OS, P&lt;0.05). For stage IIB and IIIC patients, CD3+ in the tumor region and all Top hotspots was found to be significantly correlated with survival (DFS and OS, P&lt;0.05). CD4+ cells were significantly associated with survival in the tumor region, total region, and Top3 density (DFS, P=0.0213; OS, P=0.0728). CD8+ cells were significantly associated with survival in the invasive margin, Top2 density, and Top3 density. Spatial parameter analysis showed that high colocalization of tumor cells and immune cells (CD3+, CD4+, or CD8+) was significantly associated with patient survival.

Conclusion

Computational image analysis is a reliable tool for evaluating the density and distribution of immune regulatory cells and for calculating the Immunoscore in TNBC. The Immunoscore retains its prognostic significance in TNBC later than IIB stage breast cancer. Future studies are required to confirm its potential to predict tumor responses to chemotherapy and immune therapy.

Construction and validation of a prognosis signature based on the immune microenvironment in gastric cancer

Background

Gastric cancer (GC) is an aggressive malignant tumor with a high degree of heterogeneity, and its immune microenvironment is closely associated with tumor growth, development and drug resistance. Therefore, a classification system of gastric cancer based explicitly on the immune microenvironment context might enrich the strategy for gastric cancer prognosis and therapy.

Methods

A total of 668 GC patients were collected from TCGA-STAD (n = 350), GSE15459 (n = 192), GSE57303 (n = 70) and GSE34942 (n = 56) datasets. Three immune-related subtypes (immunity-H, -M, and -L) were identified by hierarchical cluster analysis based on the ssGSEA score of 29 immune microenvironment-related gene sets. The immune microenvironment-related prognosis signature (IMPS) was constructed via univariate Cox regression, Lasso-Cox regression and multivariate Cox regression, and nomogram model combining IMPS and clinical variables was further constructed by the “rms” package. RT-PCR was applied to validate the expression of 7 IMPS genes between two human GC cell lines (AGS and MKN45) and one normal gastric epithelial cell line (GES-1).

Results

The patients classified as immunity-H subtype exhibited highly expressed immune checkpoint and HLA-related genes, with enriched naïve B cells, M1 macrophages and CD8 T cells. We further constructed and validated a 7-gene (CTLA4, CLDN6, EMB, GPR15, ENTPD2, VWF and AKR1B1) prognosis signature, termed as IMPS. The patients with higher IMPS expression were more likely to be associated with higher pathology grade, more advanced TNM stages, higher T and N stage, and higher ratio of death. In addition, the prediction values of the combined nomogram in predicting 1-year (AUC = 0.750), 3-year (AUC = 0.764) and 5-year (AUC = 0.802) OS was higher than IMPS and individual clinical characteristics.

Conclusions

The IMPS is a novel prognosis signature associated with the immune microenvironment and clinical characteristics. The IMPS and the combined nomogram model provide a relatively reliable predictive index for predicting the survival outcomes of gastric cancer.

Characterization of butyrate-metabolism in colorectal cancer to guide clinical treatment

Colorectal cancer (CRC) is the third most prevalent one in the world among the most common malignant tumors. Numerous studies have shown that butyrate has demonstrated promise as an antitumor agent in a variety of human cancer types. However, butyrate remains understudied in CRC tumorigenesis and progression. In this study, we explored therapeutic strategies to treat CRC by examining the role of butyrate metabolism. First, from the Molecular Signature Database (MSigDB), we identified 348 butyrate metabolism-related genes (BMRGs). Next, we downloaded 473 CRC and 41 standard colorectal tissue samples from The Cancer Genome Atlas (TCGA) database and the transcriptome data of GSE39582 dataset from Gene Expression Omnibus (GEO) database. Then we evaluated the expression patterns of butyrate metabolism-related genes with difference analysis in CRC. Through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, a prognostic model was constructed based on differentially expressed BMRGs. In addition, we discovered an independent prognostic marker for CRC patients. According to the expression levels and coefficients of identified BMRGs, the risk scores of all CRC samples were calculated. Utilizing differentially expressed genes in the high- and low-risk groups, we also constructed a Protein-Protein Interaction (PPI) network to visualize the interactions between proteins. Through the results of PPI network, we screened out differentially expressed target butyrate metabolism-related genes from ten hub genes. Finally, we performed clinical correlation analysis, immune cell infiltration analysis, and mutation analysis for these target genes. One hundred and seventy three differentially expressed butyrate metabolism-related genes were screened out in all the CRC samples. The prognostic model was established with univariate Cox regression and LASSO regression analysis. CRC patients' overall survival was significantly lower in the high-risk group than in the low-risk group for both training and validation set. Among the ten hub genes identified from the PPI network, four target butyrate metabolism-related genes were identified containing FN1, SERPINE1, THBS2, and COMP, which might provide novel markers or targets for treating CRC patients. Eighteen butyrate metabolism-related genes were used to develop a risk prognostic model that could be helpful for doctors to predict CRC patients' survival rate. Using this model, it is beneficial to forecast the response of CRC patients to immunotherapy and chemotherapy, thus making it easier to custom tailor cancer chemotherapy and immunotherapy to the individual patient.

Weakly supervised deep learning to predict recurrence in low-grade endometrial cancer from multiplexed immunofluorescence images

Predicting recurrence in low-grade, early-stage endometrial cancer (EC) is both challenging and clinically relevant. We present a weakly-supervised deep learning framework, NaroNet, that can learn, without manual expert annotation, the complex tumor-immune interrelations at three levels: local phenotypes, cellular neighborhoods, and tissue areas. It uses multiplexed immunofluorescence for the simultaneous visualization and quantification of CD68 + macrophages, CD8 + T cells, FOXP3 + regulatory T cells, PD-L1/PD-1 protein expression, and tumor cells. We used 489 tumor cores from 250 patients to train a multilevel deep-learning model to predict tumor recurrence. Using a tenfold cross-validation strategy, our model achieved an area under the curve of 0.90 with a 95% confidence interval of 0.83-0.95. Our model predictions resulted in concordance for 96,8% of cases (κ = 0.88). This method could accurately assess the risk of recurrence in EC, outperforming current prognostic factors, including molecular subtyping.

Research advances in nanomedicine applied to the systemic treatment of colorectal cancer

The systematic treatment of colorectal cancer (CRC) still has room for improvement. The efficacy of chemotherapy, that of anti-vascular therapy, and that of immunotherapy have been unsatisfactory. In recent years, nanomaterials have been used as carriers to improve the bioavailability of anticancer drugs. For the treatment of colorectal cancer, nanodrugs increase the possibility of more precise targeted delivery. However, the actual benefits may cover more aspects. Nanocarriers can produce synergistic effects with anticancer drugs, including the scavenging of reactive oxygen species and co-delivery of a variety of drugs. Currently, immunotherapy has very limited clinical applications in CRC. Modified nanocarriers can activate the immune microenvironment, which can be used for staging antigen recognition or the immune response. Cancer vaccines based on nanomaterials and modified immune checkpoint inhibitors have shown therapeutic potential in animal models. Considering the direct or indirect relationship between the intestinal microflora and CRC, a variety of nanodrugs that regulate microbial function have been explored as an anticancer strategy, and the special structure of microorganisms can also be used as a basis for improving the delivery of traditional nanoparticles (NPs). This review summarizes recent research performed on nanocarriers in in vivo and in vitro models and the synergistic anticancer effects of nanocarriers, focusing on the interaction between NPs and the body, resulting in enhanced efficacy and immune activation. Furthermore, this review describes the current trend of NPs used in the treatment of CRC.

Immune gene patterns and characterization of the tumor immune microenvironment associated with cancer immunotherapy efficacy

Although immunotherapy has revolutionized cancer management, most patients do not derive benefits from it. Aiming to explore an appropriate strategy for immunotherapy efficacy prediction, we collected 6251 patients' transcriptome data from multicohort population and analyzed the data using a machine learning algorithm. In this study, we found that patients from three immune gene clusters had different overall survival when treated with immunotherapy (P < 0.001), and that these clusters had differential states of hypoxia scores and metabolism functions. The immune gene score showed good immunotherapy efficacy prediction (AUC was 0.737 at 20 months), which was well validated. The immune gene score, tumor mutation burden, and long non-coding RNA score were further combined to build a tumor immune microenvironment signature, which correlated more strongly with overall survival (AUC, 0.814 at 20 months) than when using a single variable. Thus, we recommend using the characterization of the tumor immune microenvironment associated with immunotherapy efficacy via a multi-omics analysis of cancer.

Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology

BACKGROUND

The currently available immunotherapies already changed the strategy how many cancers are treated from first to last line. Understanding even the most complex heterogeneity in tumor tissue and mapping the spatial cartography of the tumor immunity allows the best and optimized selection of immune modulating agents to (re-)activate the patient's immune system and direct it against the individual cancer in the most effective way.

RECENT FINDINGS

Primary cancer and metastases maintain a high degree of plasticity to escape any immune surveillance and continue to evolve depending on many intrinsic and extrinsic factors In the field of immune-oncology (IO) immune modulating agents are recognized as practice changing therapeutic modalities. Recent studies have shown that an optimal and lasting efficacy of IO therapeutics depends on the understanding of the spatial communication network and functional context of immune and cancer cells within the tumor microenvironment. Artificial intelligence (AI) provides an insight into the immune-cancer-network through the visualization of very complex tumor and immune interactions in cancer tissue specimens and allows the computer-assisted development and clinical validation of such digital biomarker.

CONCLUSIONS

The successful implementation of AI-supported digital biomarker solutions guides the clinical selection of effective immune therapeutics based on the retrieval and visualization of spatial and contextual information from cancer tissue images and standardized data. As such, computational pathology (CP) turns into "precision pathology" delivering individual therapy response prediction. Precision Pathology does not only include digital and computational solutions but also high levels of standardized processes in the routine histopathology workflow and the use of mathematical tools to support clinical and diagnostic decisions as the basic principle of a "precision oncology".