Cancer classification using the Immunoscore: a worldwide task force

Highly expressed centromere protein L indicates adverse survival and associates with immune infiltration in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is characterized by rapid progression, high recurrence rate and poor prognosis. Early prediction for the prognosis and immunotherapy efficacy is of great significance to improve the survival of HCC patients. However, there is still no reliable predictor at present. This study is aimed to explore the role of centromere protein L (CENPL) in predicting prognosis and its association with immune infiltration in HCC.

METHODS

The expression of CENPL was identified through analyzing the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data. The association between CENPL expression and clinicopathological features was investigated by the Wilcoxon signed-rank test or Kruskal Wallis test and logistic regression. The role of CENPL in prognosis was examined via Kaplan-Meier method and Log-rank test as well as univariate and multivariate Cox regression analysis. Besides, in TIMER and GEPIA database, we investigated the correlation between CENPL level and immunocyte and immunocyte markers, and the prognostic-related methylation sites in CENPL were identified by MethSurv.

RESULTS

CENPL had a high expression in HCC samples. Increased CENPL was prominently associated with unfavorable survival, and maybe an independent prognostic factor of worse overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), progression-free interval (PFI). Additionally, CENPL expression was significantly correlated with immune cell infiltration and some markers. CENPL also contained a methylation site that was notably related to poor prognosis.

CONCLUSIONS

Elevated CENPL may be a promising prognostic marker and associate with immune infiltration in HCC.

Cancer immunotherapy: it's time to better predict patients' response

In less than a decade, half a dozen immune checkpoint inhibitors have been approved and are currently revolutionising the treatment of many cancer (sub)types. With the clinical evaluation of novel delivery approaches (e.g. oncolytic viruses, cancer vaccines, natural killer cell-mediated cytotoxicity) and combination therapies (e.g. chemo/radio-immunotherapy) as well as the emergence of novel promising targets (e.g. TIGIT, LAG-3, TIM-3), the 'immunotherapy tsunami' is not about to end anytime soon. However, this enthusiasm in the field is somewhat tempered by both the relatively low percentage (<15%) of patients who display an effective anti-cancer immune response and the inability to accurately identify them. Recently, several existing or acquired features/parameters have been shown to impact the efficacy of immune checkpoint inhibitors. In the present review, we critically discuss current knowledge regarding predictive biomarkers for checkpoint inhibitor-based immunotherapy, highlight the missing/unclear links and emphasise the importance of characterising each neoplasm and its microenvironment in order to better guide the course of treatment.

Prognostic impact of tumor-infiltrating lymphocytes in non-small cell lung carcinomas

INTRODUCTION

Tumor-infiltrating lymphocytes represent a pivotal component of the host anti-tumor response. Thus, they considerably influence the evolution of cancers including non-small cell lung carcinomas. Even if, this important role is consensual, many discordant results are published in the literature about the prognostic role of the different populations of tumor-infiltrating lymphocytes. The aim of our work was to evaluate the prognostic impact of CD8+, CD4+, and forkhead box protein P3+ lymphocytes in the tumor microenvironment of non-small cell lung carcinomas.

METHODS

We conducted a retrospective descriptive study, which included non-small cell lung carcinomas diagnosed in the department of pathology and followed in the medical oncology department of the same hospital between 2011 and 2015. Tumor-infiltrating lymphocytes were analyzed by the immunohistochemical method for forkhead box protein P3, CD4, and CD8. Intratumoral and stromal-labeled lymphocytes were quantified by manual counting at high magnification (×400). Forkhead box protein P3+/CD8+, forkhead box protein P3+/CD4+, and CD8+/CD4+ ratios were subsequently calculated. The prognostic value of tumor-infiltrating lymphocytes was assessed in respect of overall survival, recurrence-free survival, and relapse-free survival.

RESULTS

Thirty-nine patients were included. The mean age of patients was 59.6 years. A complete surgical resection (p = 0.009), and a CD8/CD4 ratio (p = 0.008) were prognostic factors for overall survival. Complete surgical resection (p = 0.003), the forkhead box protein P3/CD8 (p = 0.005), and forkhead box protein P3/CD4 (p = 0.037) ratios were prognostic factors for recurrence-free survival. The CD8+ tumor-infiltrating lymphocytes rate (p = 0.037) was a prognostic factor for relapse-free survival with a threshold of 67.8/high power field. Microscopic subtype (p = 0.037) was a prognostic factor for relapse-free survival when only adenocarcinoma and squamous cell carcinoma were considered. In multivariate analysis, age (p = 0.004) and a CD8/CD4 ratio (p = 0.016) were independent predictors of overall survival.

CONCLUSION

Despite the limitations of our study, our results confirm the prognostic value of tumor-infiltrating lymphocytes in non-small cell lung carcinomas and the importance of the combined quantification of their different subpopulations.

Evaluating prognostic value and relevant gene signatures of tumor microenvironment characterization in esophageal carcinoma

Background

Tumor microenvironment (TME) cells are an important part of tumor tissues. There is increasing evidence that the TME plays a vital role in tumor prognosis, and is associated with patient survival in various kinds of malignances. To date, very little research has been conducted on how to effectively use TME to better evaluate the prognosis of patients with esophageal carcinoma (EC). The concept of a "TME score" was introduced to better distinguish the prognosis of patients.

Methods

We employed bioinformatic methods to investigate the TME infiltration patterns of 160 patients with EC from the Cancer Genome Atlas (TCGA) cohort. TME clusters were identified using k-means clustering methods with 1,000 resampling times. The significance of the survival difference among patients belonging to different TME clusters was assessed by the log-rank test and Kaplan-Meier survival curves. Correlations between immune cell types and survival were calculated by a Cox regression, and the Pearson correlation coefficient (PCC) was used to measure the relationship among different immune cell types. We classified patient into 2 subtypes based on the optimal breakpoint of TME score determined by R package maxstat.

Results

Two TME phenotypes were defined based on the immune cell type fractions, and patients with a high TME score phenotype had a better prognosis than those with a low TME score phenotype. Kaplan-Meier analysis for differentially expressed micro ribonucleic acids (RNAs) and messenger RNAs also showed that different TME score subtypes were significantly associated with the prognosis of EC. Just as tumor mutational burden can predict the efficacy of immunotherapy, the TME score can predict the efficacy of immune checkpoint inhibitors (ICIs). The genomic alterations of 2 TME score subtypes of EC further revealed that genomic instability is prevalent in TMEs, and patients with a low TME score subtype have a more unstable chromosome status than those with a high subtype.

Conclusions

Thus, TME score is an emerging prognostic biomarker for predicting the efficacy of ICIs.

Systemic Inflammation Associates With a Myeloid Inflamed Tumor Microenvironment in Primary Resected Colon Cancer-May Cold Tumors Simply Be Too Hot?

Systemic inflammation measured by the acute-phase protein CRP associates with poor outcome across cancer types. In contrast, local tumor-associated inflammation, primarily evaluated by T-lymphocytes, correlates with favorable prognosis. Yet, little is known whether these two responses are related or opposing processes and why elevated CRP in relation to cancer is detrimental for clinical outcome. As proof of concept, we developed a platform combining multiplexed IHC and digital imaging, enabling a virtual readout of both lymphoid and myeloid immune markers and their spatial patterns in the primary tumors of resected stage II and III colon cancer (CC) patients with and without accompanying systemic inflammation. Twenty-one patients with elevated CRP (>30 mg/l) and 15 patients with low CRP (<10 mg/l) were included in the analyses. Whole slides from the primary tumors were stained for markers of adaptive (CD8+, CD4+, foxp3 regulatory T cells, CD20+ B cells) and innate (CD68+ macrophages, CD66b+ neutrophils) immunity and the immune checkpoint molecule PD-L1. Associations between individual immune markers, preoperative CRP values, mismatch repair status (MMR), and risk of recurrence or death were assessed. Unsupervised hierarchical clustering was used to explore whether distinct immune phenotypes were present. Tumors from systemically inflamed patients (CRP >30 mg/l) displayed significantly more myeloid features in terms of higher densities of CD66b+neutrophils (p = 0.001) and CD68+macrophages (p = 0.04) and less lymphoid features (lower CD8 T cell, p = 0.03, and foxp3 regulatory T cell densities, p = 0.03) regardless of MMR status. Additionally, systemically inflamed patients harbored lower mean distances between neutrophils and tumor cells within the TME. Intriguingly, microsatellite instable (MSI) tumor status correlated with systemic inflammation. However, using a combinatorial approach, we found that regardless of an adaptive composite score (compounded CD4+ and CD8+ T cells), a high innate score (CD66b+ neutrophils and CD68+ macrophages) associated significantly with elevated CRP. In conclusion, tumor-associated systemic inflammation correlated with a myeloid-dominated TME in a small cohort of resectable CC patients. Our data highlight the importance of a comprehensive immune classification of tumors including players of innate immunity and support a role for CRP as an informative biomarker of the immune response taking place at the tumor site.

The Ratio of CD86+/CD163+ Macrophages Predicts Postoperative Recurrence in Stage II-III Colorectal Cancer

Tumor-associated macrophages (TAMs) are pivotal for tumor progression and metastasis. We investigated the stromal CD86+TAM/CD163+TAM (CD86/CD163) ratio as a novel prognostic biomarker for stage II-III colorectal cancer (CRC). Two independently clinical cohorts of stage II-III CRC were retrospectively enrolled in this study. TAMs were detected using immunohistochemical staining for CD86 and CD163. The stromal CD86/CD163 ratio was calculated as a prognostic biomarker for recurrence-free survival (RFS) and overall survival (OS). Patients with a low CD86/CD163 ratio had shorter RFS (HR=0.193, p<0.001) and OS (HR=0.180, p<0.001) than patients with a high CD86/CD163 ratio in the training cohort. CD86/CD163 ratio may be an independent predictor for RFS (HR=0.233, p<0.001) and OS (HR=0.224, p<0.001) in the training cohort. We obtained equivalent results in the validation cohort. The CD86/CD163 ratio tends to have better predictive values than tumor stage in the training (AUC: 0.682 vs 0.654, p=0.538) and validation (AUC: 0.697 vs 0.659, p=0.586) cohorts. CD86/CD163 ratio effectively predicts RFS for stage II (HR=0.203, p<0.001) and stage III CRC (HR=0.302, p<0.001). CD86/CD163 ratio also effectively predicts RFS in CRC patients with adjutant chemotherapy (HR=0.258, p<0.001) and without adjutant chemotherapy (HR=0.205, p<0.001). The stromal CD86/CD163 ratio could be used for individual risk assessment of recurrence and mortality for stage II-III CRC. Together with tumor stage, this ratio will aid in the personal treatment.

Immunobiology of Melanoma

Despite the ability of immune-based interventions to dramatically increase the survival of patients with melanoma, a significant subset fail to benefit from this treatment, underscoring the need for accurate means to identify the patient population likely to respond to immunotherapy. Understanding how melanoma evades natural or manipulated immune responses could provide the information needed to identify such resistant individuals. Efforts to address this challenge are hampered by the vast immune diversity characterizing tumor microenvironments that remain largely understudied. It is thus important to more clearly elucidate the complex interactions that take place between the tumor microenvironment and host immune system.

Myeloid Cell Infiltration Correlates With Prognosis in Cholangiocarcinoma and Varies Based on Tumor Location

Cholangiocarcinoma (CC) is an uncommon malignancy with increasing incidence and dismal prognosis. We conducted a comprehensive analysis of the CC tumor immune microenvironment (TIME) based on tumor location to identify therapeutic targets. We hypothesized that the TIME of CC would vary by primary tumor location and that high tumor infiltration by CD8+ T cells and low infiltration by M2 macrophages would be associated with improved survival. A retrospective analysis was conducted of 99 CC tumor samples surgically resected between 2000 and 2014. Tissue microarrays were constructed from each tumor and stained by immunohistochemistry for 24 markers of immune cells, immune activation or inhibition, programmed cell death-ligand 1, and mesothelin. Most tumors were amply infiltrated with by CD4+, CD8+, and FoxP3+ T cells, as well as by myeloid cells. Mesothelin expression ≥1+ by immunohistochemistry was found in 68% of tumors. We identified higher densities of M1 macrophages in primary distal extrahepatic CC, as well as metastatic lesions. Mesothelin expression was also significantly higher in distal extrahepatic CC. There was no association with survival of infiltration by CD4+, CD8+, or FoxP3+ T cells, mesothelin expression, or programmed cell death-ligand 1 percentage expression, however, high CD14+ myeloid cells and high CD163+ M2 macrophages were associated with worse survival. In conclusion, the CC TIME is a heterogenous milieu highly infiltrated by innate and adaptive immune cells, which differs based on primary tumor location and between primary tumors and metastatic lesions. The correlation of intratumoral M2 macrophages and myeloid cells with a worse prognosis may suggest promising immunotherapeutic targets in CC.

Immune Microenvironment in Gallbladder Adenocarcinomas

Programmed death-1 (PD1) expression has not been reported in gallbladder adenocarcinoma. In this study we examined PD1 expression in gallbladder cancer to explore the correlation between PD1 expression and the clinicopathologic parameters. We found that 98% (46/47) cases expressed programmed death-ligand 1 (PD-L1) with 85% cases being PD-L1 3+. PD1+ tumor-infiltrating lymphocytes (TILs) were present in 78.7% cases (37/47). The tumor size was significantly smaller and the stromal CD3+ TILs were significantly higher in tumors with PD1+ TILs than those with PD1- TILs. In the tumors with size of <3 cm, stromal CD3+ TILs >115/HPF or stromal CD8+ TILs >45/HPF were associated with much better survival than those with stromal CD3+ TILs ≤115/HPF or stromal CD8+ TILs ≤45/HPF. In tumors with the size of 3 cm or larger, PD1+ TILs or stromal CD8+ TILs >45/HPF carried a significantly poorer survival than PD1- tumors or stromal CD8+ TILs <=45/HPF. No correlation was identified between PD1 expression and lymphovascular invasion, distant metastasis, pathologic tumor stage or prognostic stage. Multivariate survival analysis showed that tumor TNM stage and age were independent prognostic factors in gallbladder adenocarcinomas. We conclude that gallbladder adenocarcinomas may have high PD-L1 expression and PD1+ TILs. Smaller tumor size and greater amount of stromal CD3+ T cells were found in tumors with PD1+ TILs. In small tumors (<3 cm), high stromal CD3+ TILs or high stromal CD8+ TILs were associated with better survival. However, in large tumors (≥3 cm), PD1+ TILs or high stromal CD8+ TILs carried a poorer survival. Our study implied that immune-based therapy including PD1/PD-L1 checkpoint blockade might be useful in gallbladder adenocarcinomas.

Metavariables Resuming Host Immune Features and Nodal Involvement Are Associated with Oncological Outcomes in Oral Cavity Squamous Cell Carcinoma

Oral cavity squamous cell carcinoma (OSCC) is a common head and neck cancer characterized by a poor prognosis associated with locoregional or distant failure. Among the predictors of prognosis, a dense infiltration of adaptive immune cells is protective and associated with improved clinical outcomes. However, few tools are available to integrate immune contexture variables into clinical settings. By using digital microscopy analysis of a large retrospective OSCC cohort (n = 182), we explored the clinical significance of tumor-infiltrating CD8+ T-cells. To this end, CD8+ T-cells counts were combined with well-established clinical variables and peripheral blood immune cell parameters. Through variable clustering, five metavariables (MV) were obtained and included descriptors of nodal (NODALMV) and primary tumor (TUMORMV) involvement, the frequency of myeloid (MYELOIDMV) or lymphoid (LYMPHOIDMV) peripheral blood immune cell populations, and the density of tumor-infiltrating CD8+ T-cells (TI-CD8MV). The clinical relevance of the MV was evaluated in the multivariable survival models. The NODALMV was significantly associated with all tested outcomes (p < 0.001), the LYMPHOIDMV showed a significant association with the overall, disease-specific and distant recurrence-free survival (p < 0.05) and the MYELOIDMV with the locoregional control only (p < 0.001). Finally, TI-CD8MV was associated with distant recurrence-free survival (p = 0.029). Notably, the performance in terms of survival prediction of the combined effect of NODALMV and immune metavariables (LYMPHOIDMV, MYELOIDMV and TI-CD8MV) was superior to the TNM stage for most of the outcomes analyzed. These findings indicate that the analysis of the baseline host immune features are promising tools to complement clinical features, in stratifying the risk of recurrences.

Prognostic Impact of YKL-40 Immunohistochemical Expression in Patients with Colorectal Cancer

This study aims to examine the clinicopathological and prognostic significance of the YKL-40 immunohistochemical expression of tumor and immune cells through human colorectal cancer (CRC) tissue. We performed immunohistochemistry for YKL-40 and investigated the clinicopathological and prognostic impact of the YKL-40 expression of tumor (T-YKL-40) and immune cells (I-YKL-40) in CRC. We also evaluated the correlation between YKL-40 and PD-L1 expression and the immunoscore. YKL-40 was expressed in 22.6% and 64.2% of T-YKL-40 and I-YKL-40, respectively, out of the 265 CRC tissues. The I-YKL-40 expression significantly correlated with well and moderately differentiated tumors. The PD-L1 expression in immune cells significantly correlated with the I-YKL-40 expression, but not T-YKL-40 expression (p = 0.020 and p = 0.846, respectively). The I-YKL-40 expression significantly correlated with a worse overall survival rate but not recurrence-free survival (p = 0.047 and p = 0.080, respectively). However, there was no significant correlation between the T-YKL-40 expression and survival. In CRCs with a high immunoscore, patients with I-YKL-40 expression demonstrated worse overall and recurrence-free survival than those without I-YKL-40 expression. Our results demonstrated that I-YKL-40 expression significantly correlated with tumor differentiation and PD-L1 expression in immune cells. I-YKL-40 expression can be useful for the prognostic stratification of CRC patients.

Systemic inflammation markers and cancer incidence in the UK Biobank

Systemic inflammation markers have been linked to increased cancer risk and mortality in a number of studies. However, few studies have estimated pre-diagnostic associations of systemic inflammation markers and cancer risk. Such markers could serve as biomarkers of cancer risk and aid in earlier identification of the disease. This study estimated associations between pre-diagnostic systemic inflammation markers and cancer risk in the prospective UK Biobank cohort of approximately 440,000 participants recruited between 2006 and 2010. We assessed associations between four immune-related markers based on blood cell counts: systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and risk for 17 cancer sites by estimating hazard ratios (HR) using flexible parametric survival models. We observed positive associations with risk for seven out of 17 cancers with SII, NLR, PLR, and negative associations with LMR. The strongest associations were observed for SII for colorectal and lung cancer risk, with associations increasing in magnitude for cases diagnosed within one year of recruitment. For instance, the HR for colorectal cancer per standard deviation increment in SII was estimated at 1.09 (95% CI 1.02-1.16) in blood drawn five years prior to diagnosis and 1.50 (95% CI 1.24-1.80) in blood drawn one month prior to diagnosis. We observed associations between systemic inflammation markers and risk for several cancers. The increase in risk the last year prior to diagnosis may reflect a systemic immune response to an already present, yet clinically undetected cancer. Blood cell ratios could serve as biomarkers of cancer incidence risk with potential for early identification of disease in the last year prior to clinical diagnosis.

Genomic, Microbial and Immunological Microenvironment of Colorectal Polyps

Simple Summary

Colorectal cancers (CRC) initiate from small cell clusters known as polyps. Colonoscopic surveillance and removal of polyps is an important strategy to prevent CRC progression. Recent advances in sequencing technologies have highlighted genetic mutations in polyps that potentially contribute to CRC development. However, CRC might be considered more than a genetic disease, as emerging evidence describes early changes to immune surveillance and gut microbiota in people with polyps. Here, we review the molecular landscape of colorectal polyps, considering their genomic, microbial and immunological features, and discuss the potential clinical utility of these data.

Abstract

Colorectal cancer (CRC) develops from pre-cancerous cellular lesions in the gut epithelium, known as polyps. Polyps themselves arise through the accumulation of mutations that disrupt the function of key tumour suppressor genes, activate proto-oncogenes and allow proliferation in an environment where immune control has been compromised. Consequently, colonoscopic surveillance and polypectomy are central pillars of cancer control strategies. Recent advances in genomic sequencing technologies have enhanced our knowledge of key driver mutations in polyp lesions that likely contribute to CRC. In accordance with the prognostic significance of Immunoscores for CRC survival, there is also a likely role for early immunological changes in polyps, including an increase in regulatory T cells and a decrease in mature dendritic cell numbers. Gut microbiotas are under increasing research interest for their potential contribution to CRC evolution, and changes in the gut microbiome have been reported from analyses of adenomas. Given that early changes to molecular components of bowel polyps may have a direct impact on cancer development and/or act as indicators of early disease, we review the molecular landscape of colorectal polyps, with an emphasis on immunological and microbial alterations occurring in the gut and propose the potential clinical utility of these data.

Fundamental and Essential Knowledge for Pathologists Engaged in the Research and Practice of Immune Checkpoint Inhibitor-Based Cancer Immunotherapy

Extensive research over 100 years has demonstrated that tumors can be eliminated by the autologous immune system. Without doubt, immunotherapy is now a standard treatment along with surgery, chemotherapy, and radiotherapy; however, the field of cancer immunotherapy is continuing to develop. The current challenges for the use of immunotherapy are to enhance its clinical efficacy, reduce side effects, and develop predictive biomarkers. Given that histopathological analysis provides molecular and morphological information on humans in vivo, its importance will continue to grow. This review article outlines the basic knowledge that is essential for the research and daily practice of immune checkpoint inhibitor-based cancer immunotherapy from the perspective of histopathology.

Toward precision immunotherapy using multiplex immunohistochemistry and in silico methods to define the tumor immune microenvironment

Recent developments in cancer immunotherapy promise better outcomes for cancer patients, although clinical trials for difficult to treat cancers such as malignant brain cancer present special challenges, showing little response to first generation immunotherapies. Reasons for differences in immunotherapy response in some cancer types are likely due to the nature of tumor microenvironment, which harbors multiple cell types which interact with tumor cells to establish immunosuppression. The cell types which appear to hold the key in regulating tumor immunosuppression are the tumor-infiltrating immune cells. The current standard treatment for difficult to treat cancer, including the most malignant brain cancer, glioblastoma, continues to offer a bleak outlook for patients. Immune-profiling and correlation with pathological and clinical data will lead to a deeper understanding of the tumor immune microenvironment and contribute toward the selection, optimization and development of novel precision immunotherapies. Here, we review the current understanding of the tumor microenvironmental landscape in glioblastoma with a focus on next-generation technologies including multiplex immunofluorescence and computational approaches to map the brain tumor microenvironment to decipher the role of the immune system in this lethal malignancy.

Regulation of the epigenetic landscape by immune cell oxidants

Excessive production of microbicidal oxidants by neutrophils can damage host tissue. The short-term response of cells to oxidative stress is well understood, but the mechanisms behind long-term consequences require further clarification. Epigenetic pathways mediate cellular adaptation, and are therefore a potential target of oxidative stress. Indeed, there is evidence that many proteins and metabolites involved in epigenetic pathways are redox sensitive. In this review we provide an overview of the epigenetic landscape and discuss the potential for redox regulation. Using this information, we highlight specific examples where neutrophil oxidants react with epigenetic pathway components. We also use published data from redox proteomics to map out known intersections between oxidative stress and epigenetics that may signpost helpful directions for future investigation. Finally, we discuss the role neutrophils play in adaptive pathologies with a focus on tumour initiation and progression. We hope this information will stimulate further discourse on the emerging field of redox epigenomics.

Evaluation of cytokines in the tumor microenvironment of lung cancer using bronchoalveolar lavage fluid analysis

INTRODUCTION

Lung cancer is the leading cause of death by cancer. In recent years, immunotherapy with checkpoint inhibitors (ICI) emerged as a promising new therapeutic approach. However, a deeper understanding of the immunologic responses adjacent to the tumor known as tumor microenvironment (TME) is needed. Our study investigated TME of lung cancer by analyzing cytokines in bronchoalveolar lavage fluid (BALF).

MATERIALS AND METHODS

Between January 2018 and June 2019, 119 patients were prospectively enrolled in this study. For each cancer patient, levels of 16 cytokines (fractalkine, granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon gamma (IFN-γ), tumor necrosis factor alpha (TNF-α), and interleukins (IL): IL-1b, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-17A, and IL-23) were measured in BALF and serum and compared to healthy individuals and patients with other lung diseases.

RESULTS

There were several significant differences of cytokine levels of patients with lung cancer compared to healthy individuals. However, none of them remained in the multivariate analysis compared to other lung diseases in either BALF or serum. Furthermore, there were no significant differences between the groups in cell differentiation of either BALF or serum. Cytokine levels in BALF were generally near the lower detection limit and showed almost no correlation with their respective levels measured in serum of the same individual.

CONCLUSIONS

Cytokines in BALF and serum of lung cancer patients may indicate unspecific inflammation. BAL is not recommendable as a tool to investigate TME of lung cancer. Therefore, cytokines measured in BALF are probably not appropriate as predictors in patients treated with ICIs.

Prognostic Score Model Based on Ten Differentially Methylated Genes for Predicting Clinical Outcomes in Patients with Adenocarcinoma of the Colon

Purpose

We aimed to screen novel genetic biomarkers for use in a prognostic score (PS) model for the accurate prediction of survival outcomes for patients with colon adenocarcinoma (COAD).

Methods

Gene expression and methylation data were downloaded from The Cancer Genome Atlas database, and the samples were randomly divided into training and validation sets for the screening of differentially methylated genes (DMGs) and differentially expressed genes (DEGs). Co-methylated genes were screened using weighted gene co-expression network analysis. Functional enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery. Univariate and multivariate Cox regression analyses were performed to identify prognosis-related genes and clinical factors. Receiver operating characteristic curve analysis was carried out to evaluate the predictive performance of the PS model.

Results

In total, 1434 DEGs and 1038 DMGs were screened in the training set, among which 284 were found to be overlapping genes. For 127 of these overlapping genes, the methylation and expression levels were significantly negatively correlated. An optimal signature from 10 DMGs was identified to construct the PS model. Patients with a high PS seemed to have worse outcomes than those with a low PS. Moreover, cancer recurrence and the PS model status were independent prognostic factors.

Conclusion

This PS model based on an optimal 10-gene signature would help in the stratification of patients with COAD and improve the assessment of their clinical outcomes.

Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data

Simple Summary

Immune modulation is considered a hallmark of cancer initiation and progression, and has offered promising opportunities for therapeutic manipulation. Multiplex immunofluorescence (mIF) technology has enabled the tumor immune microenvironment (TIME) to be studied at an increased scale, in terms of both the number of markers and the number of samples. Another benefit of mIF technology is the ability to measure not only the abundance but also the spatial location of multiple cells types within a tissue sample simultaneously, allowing for assessment of the co-localization of different types of immune markers. Thus, the use of mIF technologies have enable researchers to characterize patient, clinical, and tumor characteristics in the hope of identifying patients whom might benefit from immunotherapy treatments. In this review we outline some of the challenges and opportunities in the statistical analyses of mIF data to study the TIME.

Abstract

Immune modulation is considered a hallmark of cancer initiation and progression. The recent development of immunotherapies has ushered in a new era of cancer treatment. These therapeutics have led to revolutionary breakthroughs; however, the efficacy of immunotherapy has been modest and is often restricted to a subset of patients. Hence, identification of which cancer patients will benefit from immunotherapy is essential. Multiplex immunofluorescence (mIF) microscopy allows for the assessment and visualization of the tumor immune microenvironment (TIME). The data output following image and machine learning analyses for cell segmenting and phenotyping consists of the following information for each tumor sample: the number of positive cells for each marker and phenotype(s) of interest, number of total cells, percent of positive cells for each marker, and spatial locations for all measured cells. There are many challenges in the analysis of mIF data, including many tissue samples with zero positive cells or “zero-inflated” data, repeated measurements from multiple TMA cores or tissue slides per subject, and spatial analyses to determine the level of clustering and co-localization between the cell types in the TIME. In this review paper, we will discuss the challenges in the statistical analysis of mIF data and opportunities for further research.

Immunology of Lynch Syndrome

PURPOSE OF REVIEW

Patients with Lynch syndrome have a high probability of developing colorectal and other carcinomas. This review provides a comprehensive assessment of the immunologic aspects of Lynch syndrome pathogenesis and provides an overview of potential immune interventions for patients with Lynch syndrome polyps and Lynch syndrome-associated carcinomas.

RECENT FINDINGS

Immunogenic properties of the majority of Lynch syndrome polyps and associated cancers include microsatellite instability leading to a high mutational burden and the development of novel frameshift peptides, i.e., neoantigens. In addition, patients with Lynch syndrome develop T cell responses in the periphery and in the tumor microenvironment (TME) to tumor-associated antigens, and a proinflammatory cytokine TME has also been identified. However, Lynch syndrome lesions also possess immunosuppressive entities such as alterations in MHC class I antigen presentation, TGFβ receptor mutations, regulatory T cells, and upregulation of PD-L1 on tumor-associated lymphocytes. The rich immune microenvironment of Lynch syndrome polyps and associated carcinomas provides an opportunity to employ the spectrum of immune-mediating agents now available to induce and enhance host immune responses and/or to also reduce immunosuppressive entities. These agents can be employed in the so-called prevention trials for the treatment of patients with Lynch syndrome polyps and for trials in patients with Lynch syndrome-associated cancers.

Tenascin-C immobilizes infiltrating T lymphocytes through CXCL12 promoting breast cancer progression

Immune checkpoint therapy, where CD8 tumor infiltrating T lymphocytes (TIL) are reactivated, is a promising anti-cancer treatment approach, yet with low response rates. The extracellular matrix, in particular tenascin-C, may generate barriers for TIL. To investigate this possibility, we used a MMTV-NeuNT and syngeneic mammary gland grafting model derived thereof with engineered tenascin-C levels and observed accumulation of CD8 TIL in tenascin-C-rich stroma. Inhibition studies revealed that tenascin-C induced CXCL12 through TLR4. By binding CXCL12, tenascin-C retained CD8 TIL in the stroma. Blockade of CXCR4, the receptor of CXCL12, enhanced macrophage and CD8 TIL infiltration and reduced tumor growth and subsequent metastasis. Retention of CD8 TIL by tenascin-C/CXCL12 was also observed in human breast cancer by tissue staining. Moreover, whereas high CD8 TIL numbers correlated with longer metastasis-free survival, this was not the case when also tenascin-C and CXCL12 levels were high. Altogether, these results may be useful for improving tumor immunity as diagnostic tool and to formulate a future "TIL-matrix-release-and-reactivate" strategy.

Immunotherapy in colorectal cancer

The immune tumor microenvironment (TME) of colorectal cancer (CRC) is a crucial contributor to disease biology, making it an important target for therapeutic intervention. The diversity of immune cell populations within various subsets of CRC has led to the discovery that immune characterization of the TME has both prognostic and predictive value for patients. The convergence of improved molecular and cellular characterization of CRC along with the widespread use of immunotherapy in solid tumors has led to a revolution in the approach to clinical care. Monoclonal antibodies (mAbs) which target key immune checkpoints, such as programmed death-1 (PD-1) and cytotoxic T-lymphocyte antigen 4 (CTLA-4), have demonstrated remarkable clinical activity in microsatellite instability-high (MSI-H) CRCs and are now used in routine practice. The observation that MSI-H cancers are highly infiltrated with immune cells and carry a high neoantigen load led to the successful targeting of these cancers with immunotherapy. More recently, the Food and Drug Administration (FDA) approved a PD-1 inhibitor for microsatellite stable (MSS) cancers with high tumor mutation burden. However, the anti-tumor activity of immunotherapy is rare in the majority of CRC. While immune cell characterization does provide prognostic value in these patients, these observations have not yet led to therapeutic interventions. By delineating factors that predict efficacy, resistance, and therapeutic targets, ongoing research will inform the development of effective combination strategies for the vast majority of MSS CRC and immunotherapy-resistant MSI-H cancers.

The REASON score: an epigenetic and clinicopathologic score to predict risk of poor survival in patients with early stage oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a capricious cancer with poor survival rates, even for early-stage patients. There is a pressing need to develop more precise risk assessment methods to appropriately tailor clinical treatment. Genome-wide association studies have not produced a viable biomarker. However, these studies are limited by using heterogeneous cohorts, not focusing on methylation although OSCC is a heavily epigenetically-regulated cancer, and not combining molecular data with clinicopathologic data for risk prediction. In this study we focused on early-stage (I/II) OSCC and created a risk score called the REASON score, which combines clinicopathologic characteristics with a 12-gene methylation signature, to predict the risk of 5-year mortality.

METHODS

We combined data from an internal cohort (n = 515) and The Cancer Genome Atlas (TCGA) cohort (n = 58). We collected clinicopathologic data from both cohorts to derive the non-molecular portion of the REASON score. We then analyzed the TCGA cohort DNA methylation data to derive the molecular portion of the risk score.

RESULTS

5-year disease specific survival was 63% for the internal cohort and 86% for the TCGA cohort. The clinicopathologic features with the highest predictive ability among the two the cohorts were age, race, sex, tobacco use, alcohol use, histologic grade, stage, perineural invasion (PNI), lymphovascular invasion (LVI), and margin status. This panel of 10 non-molecular features predicted 5-year mortality risk with a concordance (c)-index = 0.67. Our molecular panel consisted of a 12-gene methylation signature (i.e., HORMAD2, MYLK, GPR133, SOX8, TRPA1, ABCA2, HGFAC, MCPH1, WDR86, CACNA1H, RNF216, CCNJL), which had the most significant differential methylation between patients who survived vs. died by 5 years. All 12 genes have already been linked to survival in other cancers. Of the genes, only SOX8 was previously associated with OSCC; our study was the first to link the remaining 11 genes to OSCC survival. The combined molecular and non-molecular panel formed the REASON score, which predicted risk of death with a c-index = 0.915.

CONCLUSIONS

The REASON score is a promising biomarker to predict risk of mortality in early-stage OSCC patients. Validation of the REASON score in a larger independent cohort is warranted.

A Serum Metabolomics Classifier Derived from Elderly Patients with Metastatic Colorectal Cancer Predicts Relapse in the Adjuvant Setting

Simple Summary

Around 30–40% of patients with early stage colorectal cancer (eCRC) experience relapse after surgery. Current recommendations for adjuvant therapy are based on suboptimal risk-stratification tools. In elderly patients, risk of relapse assessment is particularly important to ultimately avoid unnecessary chemotherapy-related toxicity in this frailer population. Serum metabolomics via NMR spectroscopy may improve risk stratification by identifying patients with residual micrometastases after surgery and thus at higher risk of relapse. We evaluated the serum metabolomic fingerprints of 94 elderly patients with eCRC (65 relapse free and 29 relapsed), and of 75 elderly patients with metastatic disease. Metabolomics efficiently discriminated patients with relapse-free eCRC from those with metastatic disease, correctly predicting relapse in 69% of relapsed eCRC patients. The metabolomic score was strongly and independently associated with prognosis. Our data suggest metabolomics as a valid addition to standard tools to refine risk stratification for eCRC and warrant further investigation.

Abstract

Adjuvant treatment for patients with early stage colorectal cancer (eCRC) is currently based on suboptimal risk stratification, especially for elderly patients. Metabolomics may improve the identification of patients with residual micrometastases after surgery. In this retrospective study, we hypothesized that metabolomic fingerprinting could improve risk stratification in patients with eCRC. Serum samples obtained after surgery from 94 elderly patients with eCRC (65 relapse free and 29 relapsed, after 5-years median follow up), and from 75 elderly patients with metastatic colorectal cancer (mCRC) obtained before a new line of chemotherapy, were retrospectively analyzed via proton nuclear magnetic resonance spectroscopy. The prognostic role of metabolomics in patients with eCRC was assessed using Kaplan–Meier curves. PCA-CA-kNN could discriminate the metabolomic fingerprint of patients with relapse-free eCRC and mCRC (70.0% accuracy using NOESY spectra). This model was used to classify the samples of patients with relapsed eCRC: 69% of eCRC patients with relapse were predicted as metastatic. The metabolomic classification was strongly associated with prognosis (p-value 0.0005, HR 3.64), independently of tumor stage. In conclusion, metabolomics could be an innovative tool to refine risk stratification in elderly patients with eCRC. Based on these results, a prospective trial aimed at improving risk stratification by metabolomic fingerprinting (LIBIMET) is ongoing.

Nanomaterials for cancer therapy: current progress and perspectives

Cancer is a disease with complex pathological process. Current chemotherapy faces problems such as lack of specificity, cytotoxicity, induction of multi-drug resistance and stem-like cells growth. Nanomaterials are materials in the nanorange 1–100 nm which possess unique optical, magnetic, and electrical properties. Nanomaterials used in cancer therapy can be classified into several main categories. Targeting cancer cells, tumor microenvironment, and immune system, these nanomaterials have been modified for a wide range of cancer therapies to overcome toxicity and lack of specificity, enhance drug capacity as well as bioavailability. Although the number of studies has been increasing, the number of approved nano-drugs has not increased much over the years. To better improve clinical translation, further research is needed for targeted drug delivery by nano-carriers to reduce toxicity, enhance permeability and retention effects, and minimize the shielding effect of protein corona. This review summarizes novel nanomaterials fabricated in research and clinical use, discusses current limitations and obstacles that hinder the translation from research to clinical use, and provides suggestions for more efficient adoption of nanomaterials in cancer therapy.

Gene expression profiles for an immunoscore model in bone and soft tissue sarcoma

Background: Immune infiltration is a prognostic marker to clinical outcomes in various solid tumors. However, reports that focus on bone and soft tissue sarcoma are rare. The study aimed to analyze and identify how immune components influence prognosis and develop a novel prognostic system for sarcomas.

Methods: We retrieved the gene expression data from 3 online databases (GEO, TCGA, and TARGET). The immune fraction was estimated using the CIBERSORT algorithm. After that, we re-clustered samples by K-means and constructed immunoscore by the least absolute shrinkage and selection operator (LASSO) Cox regression model. Next, to confirm the prognostic value, nomograms were constructed.

Results: 334 samples diagnosed with 8 tumor types (including osteosarcoma) were involved in our analysis. Patients were next re-clustered into three subgroups (OS, SAR1, and SAR2) through immune composition. Survival analysis showed a significant difference between the two soft tissue groups: patients with a higher proportion of CD8+ T cells, macrophages M1, and mast cells had favorable outcomes (p=0.0018). Immunoscore models were successfully established in OS and SAR2 groups consisting of 12 and 9 cell fractions, respectively. We found immunosocre was an independent factor for overall survival time. Patients with higher immunoscore had poor prognosis (p<0.0001). Patients with metastatic lesions scored higher than those counterparts with localized tumors (p<0.05).

Conclusions: Immune fractions could be a useful tool for the classification and prognosis of bone and soft tissue sarcoma patients. This proposed immunoscore showed a promising impact on survival prediction.

Proposal of a scoring system for predicting pathological risk based on a semiautomated analysis of whole slide images in oral squamous cell carcinoma

BACKGROUND

The study aimed to evaluate the risk factors based on pathological findings comprehensively in oral squamous cell carcinoma (OSCC) using image analysis.

METHODS

Scanned images of hematoxylin and eosin-, pan-cytokeratin-, CD3-, and CD8-stained slides of OSCC cases from 256 patients were analyzed, and six variables were obtained including the tumor-stroma ratio, tumor budding per tumor bed area, and tumor infiltrating lymphocytes-associated variables. We determined the "score" of all cases based on the variables, and all cases were classified into low-, intermediate-, and high-risk groups.

RESULTS

A significant difference in prognosis was confirmed between the risk groups (p < 0.001), and even when evaluated within different tumor-node-metastasis (TNM) stages, the high-risk groups were associated with poor survival.

CONCLUSIONS

We report our work on a possible descriptive model that can predict prognosis based on pathological and imaging findings regardless of the TNM stage.

Extracellular Granzyme A Promotes Colorectal Cancer Development by Enhancing Gut Inflammation

If not properly regulated, the inflammatory immune response can promote carcinogenesis, as evident in colorectal cancer (CRC). Aiming to gain mechanistic insight into the link between inflammation and CRC, we perform transcriptomics analysis of human CRC, identifying a strong correlation between expression of the serine protease granzyme A (GzmA) and inflammation. In a dextran sodium sulfate and azoxymethane (DSS/AOM) mouse model, deficiency and pharmacological inhibition of extracellular GzmA both attenuate gut inflammation and prevent CRC development, including the initial steps of cell transformation and epithelial-to-mesenchymal transition. Mechanistically, extracellular GzmA induces NF-κB-dependent IL-6 production in macrophages, which in turn promotes STAT3 activation in cultured CRC cells. Accordingly, colon tissues from DSS/AOM-treated, GzmA-deficient animals present reduced levels of pSTAT3. By identifying GzmA as a proinflammatory protease that promotes CRC development, these findings provide information on mechanisms that link immune cell infiltration to cancer progression and present GzmA as a therapeutic target for CRC.

Identification, Validation, and Utilization of Immune Cells in Pancreatic Ductal Adenocarcinoma Based on Marker Genes

The immune response affects tumor biological behavior and progression. The specific immune characteristics of pancreatic ductal adenocarcinoma (PDAC) can determine the metastatic abilities of cancerous cells and the survival of patients. Therefore, it is important to characterize the specific immune landscape in PDAC tissue samples, and the effect of various types of therapy on that immune composition. Previously, a set of marker genes was identified to assess the immune cell composition in different types of cancer tissue samples. However, gene expression and subtypes of immune cells may vary across different types of cancers. The aim of this study was to provide a method to identify immune cells specifically in PDAC tissue samples. The method is based on defining a specific set of marker genes expressed by various immune cells in PDAC samples. A total of 90 marker genes were selected and tested for immune cell type-specific definition in PDAC; including 43 previously used, and 47 newly selected marker genes. The immune cell-type specificity was checked mathematically by calculating the “pairwise similarity” for all candidate genes using the PDAC RNA-sequenced dataset available at The Cancer Genome Atlas. A set of 55 marker genes that identify 22 different immune cell types for PDAC was created. To validate the method and the set of marker genes, an independent mRNA expression dataset of 24 samples of PDAC patients who received various types of (neo)adjuvant treatments was used. The results showed that by applying our method we were able to identify PDAC specific marker genes to characterize immune cell infiltration in tissue samples. The method we described enabled identifying different subtypes of immune cells that were affected by various types of therapy in PDAC patients. In addition, our method can be easily adapted and applied to identify the specific immune landscape in various types of tissue samples.

Expression of E26 transformation specific-1 (ETS-1) in tumour-infiltrating lymphocytes (TILs) is adverse prognostic factor in invasive breast cancer

AIM OF THE STUDY

The microenvironment depicts the relationship between tumour cells and immune response, and every insight into stromal lymphocytes could contribute to explain their role and activity. E26 transformation specific-1 (ETS-1) is a transcription factor that is active in cell proliferation. We analysed its immunohistochemical expression in tumour infiltrating lymphocytes (TILs) in invasive breast cancer and correlated its immunohistochemical score (IHS) to traditional predictive and prognostic factors and survival.

MATERIALS AND METHODS

The sample contains data of 121 patients with invasive breast cancer, not otherwise specified (NOS) who underwent mammectomy and lymphadenectomy in 2002 at the Clinical Hospital Centre Zagreb, Croatia. Paraffin blocks of the tumour tissue were collected from the pathological archive. Three representative areas of every patient were chosen and multiple tissue samples were made. Immunohistochemical staining with rabbit anti-ETS-1 (Novocastra, UK) and the ABC method was performed on a DAKO Autostainer. The expression of ETS-1 in stromal TILs was analysed on an Olympus 41 microscope. The IHS score was calculated and correlated with clinical and pathological parameters, as well as disease-free survival (DFS) and overall survival (OS).

RESULTS

In almost all patients (95%), some expression of ETS-1 in TILs was found. A moderate/high score of ETS-1 correlated with larger tumour size and higher histological grade, high proliferation index and low progesterone receptors (PgR). The patients with moderate/high ETS-1 expression in TILs had shorter DFS than patients with weak/negative ETS-1 expression.

CONCLUSION

In invasive breast cancer NOS, expression of ETS-1 in TILs is an adverse prognostic factor.

Machine-Learning-Based Evaluation of Intratumoral Heterogeneity and Tumor-Stroma Interface for Clinical Guidance

Assessment of intratumoral heterogeneity and tumor-host interaction within the tumor microenvironment is becoming increasingly important for innovative cancer therapy decisions because of the unique information it can generate about the state of the disease. However, its assessment and quantification are limited by ambiguous definitions of the tumor-host interface and by human cognitive capacity in current pathology practice. Advances in machine learning and artificial intelligence have opened the field of digital pathology to novel tissue image analytics and feature extraction for generation of high-capacity computational disease management models. A particular benefit is expected from machine-learning applications that can perform extraction and quantification of subvisual features of both intratumoral heterogeneity and tumor microenvironment aspects. These methods generate information about cancer cell subpopulation heterogeneity, potential tumor-host interactions, and tissue microarchitecture, derived from morphologically resolved content using both explicit and implicit features. Several studies have achieved promising diagnostic, prognostic, and predictive artificial intelligence models that often outperform current clinical and pathology criteria. However, further effort is needed for clinical adoption of such methods through development of standardizable high-capacity workflows and proper validation studies.

A prognostic value of CD45RA+, CD45RO+, CCL20+ and CCR6+ expressing cells as 'immunoscore' to predict cervical cancer induced by HPV

The interplay between cervical cancer (CC) and immune cells, mainly intratumoral lymphocytes, has a pivotal role in carcinogenesis. In this context, we evaluated the distribution of CD45RA⁺ and CD45RO⁺ cells as well as CCR6⁺ and CCL20⁺ cells in intraepithelial (IE) and marginal stroma (MS) areas from cervical intraepithelial neoplasia (CIN) I-III, and CC as 'immunoscore' for HPV-induced CC outcome. We observed increased CD45RA⁺ and CD45RO⁺ cells distribution in IE and MS areas in the CC group compared to CIN groups and healthy volunteers. Interestingly, there is a remarkable reduction of CCL20⁺ expressing cells distribution according to lesion severity. The CC group had a significant decrease in CCL20⁺ and CCR6⁺-expressing cells distribution in both IE and MS areas compared to all groups. Using the 'immunoscore' model, we observed an increased number of women presenting high CD45RA⁺/CD45RO⁺ and low CCL20⁺/CCR6⁺ 'immunoscore' in the CC group. Our results suggested a pattern in cervical inflammatory process with increasing CD45RA⁺/CD45RO⁺, and decreasing CCL20⁺/CCR6⁺ expression in accordance with CIN severity. Taken together, these markers could be evaluated as 'immunoscore' predictors to CC response. A more comprehensive analysis of longitudinal studies should be conducted to associate CD45RA⁺/CD45RO⁺ and CCL20⁺/CCR6⁺ 'immunoscore' to CC progression and validate its value as a prognosis method.

Expression of B7-H4 and IDO1 is associated with drug resistance and poor prognosis in high-grade serous ovarian carcinomas

High-grade serous ovarian carcinoma (HGSC) is the most lethal gynecologic malignancy. While immune checkpoint inhibitors against PD-L1 and CTLA-4 have shown significant effects in multiple tumor types, the response rate to single-agent immune checkpoint inhibitors is low in HGSC. Alternative biomarkers and targets must be identified to guide patient selection and new therapeutic strategies in HGSC. Here, we aim to investigate the clinical significance of novel immune modulators, including B7-H4, IDO1, Tim3, IL6, and IL-8, in patients with HGSC. A total of 48 patients with HGSCs, comprising 24 cases that were sensitive and 24 that were resistant to standard paclitaxel and carboplatin chemotherapy, were selected for our initial analysis. A NanoString assay including 33 immune-related genes was used to compare the expression of different immune regulatory molecules in the sensitive and resistant groups. Differentially expressed proteins were verified using multiplex immunohistochemical staining on tissue arrays of 202 patients with HGSCs who underwent primary surgery at MDACC. We analyzed the expression levels of immune checkpoints and compared expression profiles with clinicopathologic features including response, progression-free survival, and overall survival. HGSC tumors resistant to therapy expressed higher levels of B7-H4 (69.3%), IDO1 (71.8%), Tim3 (89.1%), and inflammatory factors IL-6 and IL-8, and expressed higher Tim3 in stromal components. High expression of B7-H4 and IDO1 was associated with significantly lower overall survival and progression-free survival. B7-H4 and IDO1 were co-expressed in 49.1% of studied cases. A panel of immunomodulatory proteins including B7-H4, IDO1, Tim3, IL-6, and IL-8 are expressed at high levels in HGSCs. These modulators represent novel targets to enhance immunotherapy in patients with HGSCs.

Immune profiles in acute myeloid leukemia bone marrow associate with patient age, T-cell receptor clonality, and survival

The immunologic microenvironment in various solid tumors is aberrant and correlates with clinical survival. Here, we present a comprehensive analysis of the immune environment of acute myeloid leukemia (AML) bone marrow (BM) at diagnosis. We compared the immunologic landscape of formalin-fixed paraffin-embedded BM trephine samples from AML (n = 69), chronic myeloid leukemia (CML; n = 56), and B-cell acute lymphoblastic leukemia (B-ALL) patients (n = 52) at diagnosis to controls (n = 12) with 30 immunophenotype markers using multiplex immunohistochemistry and computerized image analysis. We identified distinct immunologic profiles specific for leukemia subtypes and controls enabling accurate classification of AML (area under the curve [AUC] = 1.0), CML (AUC = 0.99), B-ALL (AUC = 0.96), and control subjects (AUC = 1.0). Interestingly, 2 major immunologic AML clusters differing in age, T-cell receptor clonality, and survival were discovered. A low proportion of regulatory T cells and pSTAT1+cMAF- monocytes were identified as novel biomarkers of superior event-free survival in intensively treated AML patients. Moreover, we demonstrated that AML BM and peripheral blood samples are dissimilar in terms of immune cell phenotypes. To conclude, our study shows that the immunologic landscape considerably varies by leukemia subtype suggesting disease-specific immunoregulation. Furthermore, the association of the AML immune microenvironment with clinical parameters suggests a rationale for including immunologic parameters to improve disease classification or even patient risk stratification.

Integrated approaches for precision oncology in colorectal cancer: The more you know, the better

Colorectal cancer (CRC) is one of the most common human malignancies accounting for approximately 10 % of worldwide cancer incidence and mortality. While early-stage CRC is mainly a preventable and curable disease, metastatic colorectal cancer (mCRC) remains an unmet clinical need. Moreover, about 25 % of CRC cases are diagnosed only at the metastatic stage. Despite the extensive molecular and functional knowledge on this disease, systemic therapy for mCRC still relies on traditional 5-fluorouracil (5-FU)-based chemotherapy regimens. On the other hand, targeted therapies and immunotherapy have shown effectiveness only in a limited subset of patients. For these reasons, there is a growing need to define the molecular and biological landscape of individual patients to implement novel, rationally driven, tailored therapies. In this review, we explore current and emerging approaches for CRC management such as genomic, transcriptomic and metabolomic analysis, the use of liquid biopsies and the implementation of patients' preclinical avatars. In particular, we discuss the contribution of each of these tools in elucidating patient specific features, with the aim of improving our ability in advancing the diagnosis and treatment of colorectal tumors.

Complete Radiological Response of Recurrent Metastatic Adrenocortical Carcinoma to Pembrolizumab and Mitotane

Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis. Treatment options for ACC are limited, with resection the main intervention. Most cases present in late metastatic cases, and data regarding effective therapies is limited. We report a case of ACC in a 40-year-old woman with history of ACC postadrenalectomy, who presented with recurrent metastatic ACC in the left perinephric space. She was started on pembrolizumab which was added to her mitotane maintenance therapy. Complete radiological response was achieved after 4 cycles of pembrolizumab. As far as we know, this is the first case to achieve complete radiological response with mitotane and pembrolizumab in recurrent metastatic ACC, with negative prognostic markers and no prior radiotherapy. As our findings are in the setting of one clinical case, we suggest the need to perform a trial to assess the benefit of combining mitotane and pembrolizumab in treating metastatic ACC.

Colorectal Cancer and Immunity: From the Wet Lab to Individuals

Simple Summary

Tackling the current dilemma of colorectal cancer resistance to immunotherapy is puzzling and requires novel therapeutic strategies to emerge. However, characterizing the intricate interactions between cancer and immune cells remains difficult because of the complexity and heterogeneity of both compartments. Developing rationales is intellectually feasible but testing them can be experimentally challenging and requires the development of innovative procedures and protocols. In this review, we delineated useful in vitro and in vivo models used for research in the field of immunotherapy that are or could be applied to colorectal cancer management and lead to major breakthroughs in the coming years.

Abstract

Immunotherapy is a very promising field of research and application for treating cancers, in particular for those that are resistant to chemotherapeutics. Immunotherapy aims at enhancing immune cell activation to increase tumor cells recognition and killing. However, some specific cancer types, such as colorectal cancer (CRC), are less responsive than others to the current immunotherapies. Intrinsic resistance can be mediated by the development of an immuno-suppressive environment in CRC. The mutational status of cancer cells also plays a role in this process. CRC can indeed be distinguished in two main subtypes. Microsatellite instable (MSI) tumors show a hyper-mutable phenotype caused by the deficiency of the DNA mismatch repair machinery (MMR) while microsatellite stable (MSS) tumors show a comparatively more “stable” mutational phenotype. Several studies demonstrated that MSI CRC generally display good prognoses for patients and immunotherapy is considered as a therapeutic option for this type of tumors. On the contrary, MSS metastatic CRC usually presents a worse prognosis and is not responsive to immunotherapy. According to this, developing new and innovative models for studying CRC response towards immune targeted therapies has become essential in the last years. Herein, we review the in vitro and in vivo models used for research in the field of immunotherapy applied to colorectal cancer.

Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning

The clinical staging and prognosis of muscle-invasive bladder cancer (MIBC) routinely includes the assessment of patient tissue samples by a pathologist. Recent studies corroborate the importance of image analysis in identifying and quantifying immunological markers from tissue samples that can provide further insight into patient prognosis. In this paper, we apply multiplex immunofluorescence to MIBC tissue sections to capture whole-slide images and quantify potential prognostic markers related to lymphocytes, macrophages, tumour buds, and PD-L1. We propose a machine-learning-based approach for the prediction of 5 year prognosis with different combinations of image, clinical, and spatial features. An ensemble model comprising several functionally different models successfully stratifies MIBC patients into two risk groups with high statistical significance (p value < 1×10-5). Critical to improving MIBC survival rates, our method correctly classifies 71.4% of the patients who succumb to MIBC, which is significantly more than the 28.6% of the current clinical gold standard, the TNM staging system.

Transcriptome of Tumor-Infiltrating T Cells in Colorectal Cancer Patients Uncovered a Unique Gene Signature in CD4+ T Cells Associated with Poor Disease-Specific Survival

Colorectal cancer (CRC) is influenced by infiltration of immune cell populations in the tumor microenvironment. While elevated levels of cytotoxic T cells are associated with improved prognosis, limited studies have reported associations between CD4⁺ T cells and disease outcomes. We recently performed transcriptomic profiling and comparative analyses of sorted CD4⁺ and CD8⁺ tumor-infiltrating lymphocytes (TILs) from bulk tumors of CRC patients with varying disease stages. In this study, we compared the transcriptomes of CD4⁺ with CD8⁺ TILs. Functional annotation pathway analyses revealed the downregulation of inflammatory response-related genes, while T cell activation and angiogenesis-related genes were upregulated in CD4⁺ TILs. The top 200 deregulated genes in CD4⁺ TILs were aligned with the cancer genome atlas (TCGA) CRC dataset to identify a unique gene signature associated with poor prognosis. Moreover, 69 upregulated and 20 downregulated genes showed similar trends of up/downregulation in the TCGA dataset and were used to calculate "poor prognosis score" (ppScore), which was significantly associated with disease-specific survival. High ppScore patients showed lower expression of Treg-, Th1-, and Th17-related genes, and higher expression of Th2-related genes. Our data highlight the significance of T cells within the TME and identify a unique candidate prognostic gene signature for CD4⁺ TILs in CRC patients.

Tumor microenvironment-associated gene C3 can predict the prognosis of colorectal adenocarcinoma: a study based on TCGA

BACKGROUND

Colorectal cancer is one of the most common malignancies. With continuous exploration of the interaction between tumor cells and the immune system, tumor immunotherapy has become a revolution. However, CRC remains one of the less effective tumors for immunotherapy. The tumor microenvironment plays an important role in tumorigenesis and progression. The aim of this study is to explore tumor microenvironment-related genes that can predict the prognosis of colorectal adenocarcinoma, and also to provide new ideas for the mechanism of tumor development as well as immunotherapy.

METHODS

After estimating Stromalscore and Immunescore of colorectal adenocarcinoma tumor samples according to RNA-Seq expression data downloaded from TCGA, we screened for TME-related differential genes. We filtered prognosis-related core genes by constructing protein-protein interaction networks and making one-factor cox analysis for prognosis. Finally, the relative content of 22 immune cells in tumor tissues was evaluated, and then immune cells associated with core genes were identified.

RESULTS

We screened 773 differential genes related to the TME. Then we identified C3 as a core gene associated with prognosis. Single gene analysis showed that C3 expression was significantly higher in tumor tissues than in normal tissues (p < 0.001). High C3 expression was associated with lower overall survival (p = 0.046). Tumor immune cell analysis showed that mast cells resting, mast cells activated, T cells CD4 memory activated, eosinophils, and macrophages M0 were C3-associated immune cells.

CONCLUSIONS

C3 has potential as a biomarker for colorectal adenocarcinoma and could provide new research ideas for the diagnosis and treatment of colorectal adenocarcinoma, especially for immunotherapy.

Immune Cell Profiling of Peripheral Blood as Signature for Response During Checkpoint Inhibition Across Cancer Types

Despite encouraging results with immune checkpoint inhibition (ICI), a large fraction of cancer patients still does not achieve clinical benefit. Finding predictive markers in the complexity of the tumor microenvironment is a challenging task and often requires invasive procedures. In our study, we looked for putative variables related to treatment benefit among immune cells in peripheral blood across different tumor types treated with ICIs. For that, we included 33 patients with different solid tumors referred to our clinical unit for ICI. Peripheral blood mononuclear cells were isolated at baseline, 6 and 20 weeks after treatment start. Characterization of immune cells was carried out by multi-color flow cytometry. Response to treatment was assessed radiologically by RECIST 1.1. Clinical outcome correlated with a shift towards an effector-like T cell phenotype, PD-1 expression by CD8+T cells, low levels of myeloid-derived suppressor cells and classical monocytes. Dendritic cells seemed also to play a role in terms of survival. From these findings, we hypothesized that patients responding to ICI had already at baseline an immune profile, here called ‘favorable immune periphery’, providing a higher chance of benefitting from ICI. We elaborated an index comprising cell types mentioned above. This signature correlated positively with the likelihood of benefiting from the treatment and ultimately with longer survival. Our study illustrates that patients responding to ICI seem to have a pre-existing immune profile in peripheral blood that favors good outcome. Exploring this signature can help to identify patients likely to achieve benefit from ICI.

Clinicopathological Significances of Tumor-Stroma Ratio (TSR) in Colorectal Cancers: Prognostic Implication of TSR Compared to Hypoxia-Inducible Factor-1α Expression and Microvessel Density

The present study aimed to elucidate the clinicopathological significance and prognostic implications of tumor–stroma ratio (TSR) in colorectal cancers (CRCs). TSRs were investigated in 266 human CRC specimens. The correlations between TSR and clinicopathological characteristics and survival were evaluated. The hypoxia-inducible factor-1α (HIF-1α) immunohistochemical expression of tumor cells and microvessel density (MVD) of stroma were compared between stroma-low and stroma-high subgroups. Results: Stroma-low was found in 185 of 266 CRCs (69.5%). Stroma-low was significantly correlated with less frequent vascular and perineural invasion and distant metastasis than stroma-high. HIF-1α of tumor cells was more highly expressed in the stroma-high subgroup than in the stroma-low subgroup. In addition, MVD was significantly higher in the stroma-high subgroup compared to the stroma-low subgroup. The stroma-low rate was increased considerably in CRCs with a mucinous component and decreased in CRCs with a micropapillary component. There were significant correlations between stroma-low and better overall and recurrence-free survivals. Similar to the literature, we observed that stroma-low was significantly correlated with favorable tumor behaviors and better survival. The microscopic examination of TSR can be useful for predicting the prognosis of CRC patients.

Tumor-infiltrating lymphocytes in tissue material combined with systemic lymphocyte inflammation in patients with colorectal cancer

The efficacy of cancer immunotherapy has been actively explored in the treatment of various malignant neoplasms of the gastrointestinal tract. In light of recent reports, the present study aimed to investigate the combination of the absolute lymphocyte count (ALC), percentage of tumor-infiltrating lymphocyte (TILs) and tumor progression status in patients with colorectal cancer (CRC) who underwent surgery. The medical records of 160 patients diagnosed with CRC were retrospectively reviewed. TILs were determined as a percentage of mononuclear inflammatory cells in the total intratumoral or stromal area as determined in five high power fields (magnification, x200-400), at the invasive front and in the centre of the tumour. Blood samples were obtained within 3 days prior to and 7 days following the surgical treatment. The assessment of the TIL percentage was performed in the tissue at the invasive front and in the centre of the primary tumour mass in combination with the determination of ALC in whole blood samples. The samples were obtained prior to and after surgery from patients with CRC, and the tumour progression status was also assessed (TILs/ALC/tumour progression status). A significant association was observed between the percentage of TILs in the main mass of tumour and the tumour size (P=0.031), the pT stage (P=0.049) and the incidence of necrosis (P=0.037) following surgery. The histological type was associated with the evaluated combined parameters prior to surgery (P=0.046). Lymph node pouch invasion was associated with TILs at the invasive front of tumour and with ALC prior to and after surgery (P=0.006 and P=0.037). Furthermore, the data indicated that the percentage of TILs located on the invasive front and centre of the tumour, and the ALC prior to and following surgery correlated with the treatment status (P=0.032, P=0.018, P≤0.001 and P≤0.001). A significant association was noted between eight features and evaluated combined parameters following surgery. These included the tumour size (P=0.021), TNM stage (P<0.001), tumour deposits (P=0.001), incidence of necrosis (P=0.042) and lymph node metastasis (P<0.001). Furthermore, the degree of invasion of venous (P<0.001), lymphatic (P<0.001) and perineural (P<0.001) sites was also significantly associated with TILs, ALC obtained after surgical treatment and tumor progression status. The data demonstrated that local and systemic chronic inflammation was associated with tumour progression in patients with CRC.

A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation

There is an urgent need to identify novel biomarkers that predict the prognosis of patients with NSCLC. In this study,we aim to find out mRNA signature closely related to the prognosis of NSCLC by new algorithm of bioinformatics. Identification of highly expressed mRNA in stage I/II patients with NSCLC was performed with the “Limma” package of R software. Survival analysis of patients with different mRNA expression levels was subsequently calculated by Cox regression analysis, and a multi-RNA signature was obtained by using the training set. Kaplan–Meier estimator, log-rank test and receiver operating characteristic (ROC) curves were used to analyse the predictive ability of the multi-RNA signature. RT-PCR used to verify the expression of the multi-RNA signature, and Westernblot used to verify the expression of proteins related to the multi-RNA signature. We identified fifteen survival-related mRNAs in the training set and classified the patients as high risk or low risk. NSCLC patients with low risk scores had longer disease-free survival than patients with high risk scores. The fifteen-mRNA signature was an independent prognostic factor, as shown by the ROC curve. ROC curve also showed that the combined model of the fifteen-mRNA signature and tumour stage had higher precision than stage alone. The expression of fifteen mRNAs and related proteins were higher in stage II NSCLC than in stage I NSCLC. Multi-gene expression profiles provide a moderate prognostic tool for NSCLC patients with stage I/II disease.

A nomogram-based immune-serum scoring system predicts overall survival in patients with lung adenocarcinoma

OBJECTIVE

The immunoscore, which is used to quantify immune infiltrates, has greater relative prognostic value than tumor, node, and metastasis (TNM) stage and might serve as a new system for classification of colorectal cancer. However, a comparable immunoscore for predicting lung adenocarcinoma (LUAD) prognosis is currently lacking.

METHODS

We analyzed the expression of 18 immune features by immunohistochemistry in 171 specimens. The relationship of immune marker expression and clinicopathologic factors to the overall survival (OS) was analyzed with the Kaplan-Meier method. A nomogram was developed by using the optimal features selected by least absolute shrinkage and selection operator (LASSO) regression in the training cohort (n = 111) and evaluated in the validation cohort (n = 60).

RESULTS

The indicators integrated in the nomogram were TNM stage, neuron-specific enolase, carcino-embryonic antigen, CD8center of tumor (CT), CD8invasive margin (IM), FoxP3CT, and CD45ROCT. The calibration curve showed prominent agreement between the observed 2- and 5-year OS and that predicted by the nomogram. To simplify the nomogram, we developed a new immune-serum scoring system (I-SSS) based on the points awarded for each factor in the nomogram. Our I-SSS was able to stratify same-stage patients into different risk subgroups. The combination of I-SSS and TNM stage had better prognostic value than the TNM stage alone.

CONCLUSIONS

Our new I-SSS can accurately and individually predict LUAD prognosis and may be used to supplement prognostication based on the TNM stage.

A comprehensive analysis of tumor microenvironment-related genes in colon cancer

BACKGROUND

The development and progression of colon cancer are significantly affected by the tumor microenvironment, which has attracted much attention. The goal of our study was primarily to find out all possible tumor microenvironment-related genes in colon cancer.

METHOD

This study quantified the immune and stromal landscape using the ESTIMATION algorithm using the gene expression matrix obtained from the UCSC Xena database. Dysregulated genes were harvested using the limma R package, and relevant pathways and biofunctions were identified using enrichment analysis. A least absolute shrinkage and selection operator (LASSO) regression was used to select the pivotal genes from the DEGs. Then, survival analysis was performed to determine the hub genes and a prognostic model was constructed by these hub genes with (or) TNM stage. Besides, associations between hub gene expressions and immune cell infiltration were assessed.

RESULTS

A total of 725 DEGs were identified. Most of the results of the enrichment analysis were immune-related items. 13 genes were selected as the hub genes and a moderate-to-strong positive correlation between most hub genes and several immune cells were observed. Besides, the prognostic value of the hub genes were comparable to TNM staging.

CONCLUSIONS

Our study provides a better understanding of how interactions between the 13 immune-prognostic hub genes and immune cells in the tumor microenvironment affect biological processes in colon cancer. These genes exhibit an equivalent ability to TNM staging in prognosis prediction. They are particularly expected to become novel prognostic biomarkers and targets of immunotherapies for colon cancer.

Histopathological and Immune Prognostic Factors in Colo-Rectal Liver Metastases

Simple Summary

Clinical management of colo-rectal liver metastasis would benefit from a refined stratification of patients in prognostic groups, in order to identify the best therapeutic option. Efforts are ongoing in the definition of parameters associated with clinical behaviors, which could help classifying patients in clinically relevant groups. Here we aimed at discussing the recent advances in this field, and we introduced current and new promising candidates, such as morphological tumor features and immune components, which have been showing significant association with survival. Some of these parameters are slowly reaching the clinic and further efforts are ongoing in the attempt to combine them in multiparametric scores.

Abstract

Prognostic studies are increasingly providing new tools to stratify colo-rectal liver metastasis patients into clinical subgroups, with remarkable implications in terms of clinical management and therapeutic choice. Here, the strengths and hurdles of current prognostic tools in colo-rectal liver metastasis are discussed. Alongside more classic histopathological parameters, which capture features related to the tumor component, such as tumor invasion, tumor growth pattern and regression score, we will discuss immune mediators, which are starting to be considered important features. Their objective quantification has shown significant results in prognostication studies, with most of the work focused on adaptive immune cells, namely T cells. As for macrophages, they are only starting to be appreciated and we will present recent advances in evaluation of macrophage morphological features. Deeper knowledge acquired by multiparametric analyses is rapidly uncovering the variety of immune players that should be assessed. The future projection is to implement deep-learning histopathological tools and to integrate histopathological and immune metrics in multiparametric scores, with the ultimate objective to achieve a deeper resolution of the tumor features and their relevance for colo-rectal liver metastasis.

A signature of estimate-stromal-immune score-based genes associated with the prognosis of lung adenocarcinoma

Background

Immune and stromal component evaluation is necessary to establish accurate prognostic markers for the prediction of clinical outcomes in lung adenocarcinoma (LUAD). We aimed to develop a gene signature based on the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE)-stromal-immune score in LUAD.

Methods

The transcriptomic profiles of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA), and the immune and stromal scores were derived using the ESTIMATE algorithm. The prognostic signature genes were selected from the differentially expressed genes (DEGs) using the robust partial likelihood-based cox proportional hazards regression method. The negative log-likelihood and the Akaike Information Criterion (AIC) were used to identify the optimal gene signature. The validation was carried out in 2 independent datasets from the Gene Expression Omnibus (GSE68571 and GSE72094).

Results

Patients with high ESTIMATE, stromal, and immune scores had better overall survivals (P=0.0035, P=0.066, and P=0.0077). The expression of thirty-seven genes was related to ESTIMATE-stromal-immune score. A risk stratification model was developed based on a gene signature containing CD74, JCHAIN, and PTGDS. The ESTIMATE-stromal-immune risk score was revealed to be a prognostic factor (P=0.009) after multivariate analysis. Four groups were classified based on this risk stratification model, yielding increasing survival outcomes (log-rank test, P=0.0051). This risk stratification model and other clinicopathological factors were combined to generate a nomogram. The calibration curves showed perfect agreement between the nomogram-predicted outcomes and those actually observed. Similar observations were made in 2 independent cohorts.

Conclusions

The gene signature based on the ESTIMATE-stromal-immune score could predict the prognosis of patients with LUAD.

Combination immunotherapy using G-CSF and oncolytic virotherapy reduces tumor growth in osteosarcoma

BACKGROUND

Osteosarcoma is the most common malignant solid tumor that affects bones, however, survival rates of patients with relapsed osteosarcoma have not improved in the last 30 years. Oncolytic virotherapy, which uses viruses designed to selectively replicate in cancer cells, has emerged as a promising treatment for solid tumors. Our group uses mesenchymal stem cells (MSCs) to transport oncolytic adenoviruses (OAds) to the tumor site, a therapeutic strategy called Celyvir. This treatment has been already applied in human patients, canine patients and different mouse models. In parallel, previous results have probed that administration of granulocyte-colony stimulating factor (G-CSF) increased immune infiltration in tumors. We then hypothesized that the mobilization of immune cells by G-CSF may increase the antitumor efficacy of Celyvir treatment by increasing the immune infiltration into the tumors.

METHODS

In this study, we use a murine version of Celyvir consisting in murine MSCs carrying the murine OAd dlE102-here called OAd-MSCs-in an immunocompetent model of osteosarcoma. We tested the antitumoral efficacy of the combination of OAd-MSCs plus G-CSF.

RESULTS

Our results show that treatment with OAd-MSCs or the union of OAd-MSCs with G-CSF (Combination) significantly reduced tumor growth of osteosarcoma in vivo. Moreover, treated tumors presented higher tumor infiltration of immune cells-especially tumor-infiltrating lymphocytes-and reduced T cell exhaustion, which seems to be enhanced in tumors treated with the Combination. The comparison of our results to those obtained from a cohort of pediatric osteosarcoma patients showed that the virotherapy induces immunological changes similar to those observed in patients with good prognosis.

CONCLUSIONS

The results open the possibility of using cellular virotherapy for the treatment of bone cancers. Indeed, its combination with G-CSF may be considered for the improvement of the therapy.