Immunoprofiling as a predictor of patient's response to cancer therapy-promises and challenges

Cancer stem cell-derived exosomes in CD8+ T cell exhaustion

Tumor-derived extracellular vesicles (EVs) are one of the most important ways of intercellular communication and signaling. Cancer stem cells (CSCs) secrete EVs to modulate immune checkpoint molecules and evade immune surveillance. Activated CD8+ T cells known as cytotoxic T lymphocytes (CTLs) are the most powerful anti-cancer adaptive cells. Their activity is compromised upon encountering cells and signaling within the tumor microenvironment (TME), resulting in hyporesponsiveness called exhaustion. CSC-derived exosomes express programmed death ligand-1 (PD-L1) and upregulate programmed death-1 (PD-1) on CD8+ T cells to promote their exhaustion. PD-L1 expression on tumor-derived exosomes appears to be induced by CSC-derived exosomes containing transforming growth factor (TGF)-β. Tenascin-C is another constituent of CSC exosomes that acts on mammalian target of rapamycin (mTOR) signaling in T cells. Glycolysis is a metabolic event promoted by the inducing effect of CSC-derived exosomes on hypoxia-inducible factor-1α (HIF-1α). CSC interaction with CD8+ T cells is even more complex as the CSC-derived exosomes contain Notch1 to stimulate stemness in non-tumor cells, and the inducible effect of Notch1 on PD-1 promotes CD8+ T cell exhaustion. CSC exosome targeting has not been extensively studied yet. Advances in the field will open up new therapeutic windows and shape the future of cancer immunotherapy.

Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities

The integration of artificial intelligence (AI) into point-of-care (POC) biosensing has the potential to revolutionize diagnostic methodologies by offering rapid, accurate, and accessible health assessment directly at the patient level. This review paper explores the transformative impact of AI technologies on POC biosensing, emphasizing recent computational advancements, ongoing challenges, and future prospects in the field. We provide an overview of core biosensing technologies and their use at the POC, highlighting ongoing issues and challenges that may be solved with AI. We follow with an overview of AI methodologies that can be applied to biosensing, including machine learning algorithms, neural networks, and data processing frameworks that facilitate real-time analytical decision-making. We explore the applications of AI at each stage of the biosensor development process, highlighting the diverse opportunities beyond simple data analysis procedures. We include a thorough analysis of outstanding challenges in the field of AI-assisted biosensing, focusing on the technical and ethical challenges regarding the widespread adoption of these technologies, such as data security, algorithmic bias, and regulatory compliance. Through this review, we aim to emphasize the role of AI in advancing POC biosensing and inform researchers, clinicians, and policymakers about the potential of these technologies in reshaping global healthcare landscapes.

A novel CD8+ T cell-related gene signature as a prognostic biomarker in hepatocellular carcinoma

CD8+ T cells have great roles in tumor suppression and elimination of various tumors including hepatocellular carcinoma (HCC). Nonetheless, potential prognostic roles of CD8+ T cell-related genes (CD8Gs) in HCC remains unknown. In our study, 416 CD8Gs were identified in HCC, which were enriched in inflammatory and immune signaling pathways. Using The Cancer Genome Atlas dataset, a 5-CD8Gs risk model (KLRB1, FYN, IL2RG, FCER1G, and DGKZ) was constructed, which was verified in International Cancer Genome Consortium and gene expression omnibus datasets. Furthermore, we found that overall survival was independently correlated with the CD8Gs signature, and it was associated with immune- and cancer-related signaling pathways and immune cells infiltration. Finally, drug sensitivity data indicated that 10 chemotherapeutic drugs held promise as therapeutics for HCC patients with high-risk. In conclusion, multi-databases analysis showed that 5-CD8Gs and their signature could be an indicator to predict candidate drugs for HCC therapy.

Differential Immune Infiltration Profiles in Colitis-Associated Colorectal Cancer versus Sporadic Colorectal Cancer

BACKGROUND

Chronic inflammation is a significant factor in colorectal cancer (CRC) development, especially in colitis-associated CRC (CAC). T-cell exhaustion is known to influence inflammatory bowel disease (IBD) progression and antitumor immunity in IBD patients. This study aimed to identify unique immune infiltration characteristics in CAC patients.

METHODS

We studied 20 CAC and 20 sporadic CRC (sCRC) patients, who were matched by tumor stage, grade, and location. Immunohistochemical staining targeted various T-cell markers (CD3, CD4, CD8, and FOXP3), T-cell exhaustion markers (TOX and TIGIT), a B-cell marker (CD20), and a neutrophil marker (CD66b) in tumor and tumor-free mucosa from both groups. The quantification of the tumor immune stroma algorithm assessed immune-infiltrating cells.

RESULTS

CAC patients had significantly lower TOX+ cell infiltration than sCRC in tumors (p = 0.02) and paracancerous tissues (p < 0.01). Right-sided CAC showed increased infiltration of TOX+ cells (p = 0.01), FOXP3+ regulatory T-cells (p < 0.01), and CD20+ B-cells (p < 0.01) compared to left-sided CAC. In sCRC, higher tumor stages (III and IV) had significantly lower TIGIT+ infiltrate than stages I and II. In CAC, high CD3+ (p < 0.01) and CD20+ (p < 0.01) infiltrates correlated with improved overall survival. In sCRC, better survival was associated with decreased TIGIT+ cells (p < 0.038) and reduced CD8+ infiltrates (p = 0.02).

CONCLUSION

In CAC, high CD3+ and CD20+ infiltrates relate to improved survival, while this association is absent in sCRC. The study revealed marked differences in TIGIT and TOX expression, emphasizing distinctions between CAC and sCRC. T-cell exhaustion appears to have a different role in CAC development.

Clinical Usefulness of Immune Profiling for Differential Diagnosis between Crohn's Disease, Intestinal Tuberculosis, and Behcet's Disease

It is important to make a differential diagnosis between inflammatory diseases of the bowel with similar clinical and endoscopic features. The profiling of immune cells could be helpful for accurately diagnosing inflammatory bowel diseases. We compared immune marker expression between Crohn's disease (CD), intestinal Behcet's disease (BD), and intestinal tuberculosis (TB) and evaluated the usefulness of immune profiling in differentiating between these diseases. Biopsy specimens were acquired around ulcerations on the terminal ileum or cecum from five patients with each disease. Panel 1 included multiplex immunohistochemistry staining for CD8, CD4, Foxp3, CD20, programmed death-1, and granzyme B. CD56, CD68, CD163, CD11c, and HLA-DR were analyzed in panel 2. The differences in cytotoxic T cells (CD8+CD4-Fopx3-CD20-), helper T cells (CD8-CD4+Fopx3-CD20-), and regulatory T cells (CD8-CD4+Fopx3+CD20-) were also not significant. However, M1 macrophage (CD68+CD163-HLA-DR-) cell densities were significantly higher in intestinal BD than in other diseases. The expression level of dendritic cells (CD56-CD68-CD163-CD11c+HLA-DR+) was highest in intestinal TB and lowest in intestinal BD. The expression of immune cells, including M1 macrophages and dendritic cells, was different between CD, intestinal BD, and intestinal TB. Immune profiling can be helpful for establishing differential diagnoses of inflammatory bowel diseases.

A new prediction model of hepatocellular carcinoma based on N7-methylguanosine modification

PURPOSE

Hepatocellular carcinoma (HCC) is a kind of primary liver cancer. It is a common malignant tumor of digestive system that is difficult to predict the prognosis of patients. As an important epigenetic modification, N7 methyl guanosine (m7G) is indispensable in gene regulation. This regulation may affect the development and occurrence of cancer. However, the prognosis of long non coding RNAs (lncRNAs) in HCC is limited, especially how m7G-related lncRNAs regulate the development of HCC has not been reported.

METHODS

The Cancer Genome Atlas (TCGA) provides us with the expression data and corresponding clinical information of HCC patients we need. We used a series of statistical methods to screen four kinds of m7G-related lncRNAs related to HCC prognosis and through a series of verifications, the results were in line with our expectations. Finally, we also explored the IC50 difference and correlation analysis of various common chemotherapy drugs.

RESULT

Our study identified four differentially expressed m7g-related lncRNAs associated with HCC prognosis. Survival curve analysis showed that high risk lncRNAs would lead to poor prognosis of HCC patients. M7G signature's AUC was 0.789, which shows that the prognosis model we studied has certain significance in predicting the prognosis of HCC patients. Moreover, our study found that different risk groups have different immune and tumor related pathways through gene set enrichment analysis. In addition, many immune cell functions are significantly different among different risk groups, such as T cell functions, including coordination of type I INF response and coordination of type II INF response. The expression of PDCD1, HHLA2, CTLA-4 and many other immune checkpoints in different risk groups is also different. Additionally, we analyzed the differences of IC50 and risk correlation of 15 chemotherapeutic drugs among different risk groups.

CONCLUSION

A novel lncRNAs associated with m7G predicts the prognosis of HCC.

Multiplexed molecular imaging with surface enhanced resonance Raman scattering nanoprobes reveals immunotherapy response in mice via multichannel image segmentation

Visualizing the presence and distribution of multiple specific molecular markers within a tumor can reveal the composition of its microenvironment, inform diagnosis, stratify patients, and guide treatment. Raman imaging with multiple molecularly-targeted surface enhanced Raman scattering (SERS) nanoprobes could help investigate emerging cancer treatments preclinically or enable personalized treatment assessment. Here, we report a comprehensive strategy for multiplexed imaging using SERS nanoprobes and machine learning (ML) to monitor the early effects of immune checkpoint blockade (ICB) in tumor-bearing mice. We used antibody-functionalized SERS nanoprobes to visualize 7 + 1 immunotherapy-related targets simultaneously. The multiplexed images were spectrally resolved and then spatially segmented into superpixels based on the unmixed signals. The superpixels were used to train ML models, leading to the successful classification of mice into treated and untreated groups, and identifying tumor regions with variable responses to treatment. This method may help predict treatment efficacy in tumors and identify areas of tumor variability and therapy resistance.

Influence of Androgen Deprivation Therapy on the PD-L1 Expression and Immune Activity in Prostate Cancer Tissue

Immune checkpoint inhibitors have become a promising new therapy for cancer treatment. However, due to prostate cancer’s high heterogeneity and immune-suppressive tumour microenvironment, clinical trials with immune checkpoint inhibitors for prostate cancer resulted in low or no response. This descriptive and retrospective study investigates the influence of androgen deprivation therapy (ADT) on PD-L1 expression and CD8+ T-cell tumour infiltration and activity in primary prostate cancer tissue. Therefore, immunohistochemistry was used to assess PD-L1, CD8+ T-cell, and the immune activation marker Granzyme B (GrB) in PCa tissue before and under ADT. In line with previous studies, few prostate cancer tissues showed PD-L1 expression and CD8+ T-cell infiltration. However, PD-L1 expression levels on tumour cells or infiltrating immune cells above 5% generated an immune-suppressive tumour microenvironment harbouring hypofunctional CD8+ T-cells. Moreover, analysis of a longitudinal patient cohort before and under ADT revealed that ADT increased hypofunctional CD8+ T cells in the tumour area suggesting a tumour immune milieu optimal for targeting with immunotherapy.

Construction of a Novel Immune-Related mRNA Signature to Predict the Prognosis and Immune Characteristics of Human Colorectal Cancer

Background: Anti-cancer immunotherapeutic approaches have gained significant efficacy in multiple cancer types. However, not all patients with colorectal cancer (CRC) could benefit from immunotherapy due to tumor heterogeneity. The purpose of this study was to construct an immune-related signature for predicting the immune characteristics and prognosis of CRC.

Methods: RNA-sequencing data and corresponding clinical information of patients with CRC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and immune-related genes (IRGs) were downloaded from the Immunology Database and Analysis Portal (ImmPort). Then, we utilized univariate, lasso regression, and multivariate cox regression to identify prognostic IRGs and develop the immune-related signature. Subsequently, a nomogram was established based on the signature and other prognostic factors, and its predictive capacity was assessed by receiver operating characteristic (ROC) and decision curve analysis (DCA). Finally, associations between the signature and the immune characteristics of CRC were assessed.

Results: In total, 472 samples downloaded from TCGA were divided into the training cohort (236 samples) and internal validation cohort (236 samples), and the GEO cohort was downloaded as an external validation cohort (122 samples). A total of 476 differently expressed IRGs were identified, 17 of which were significantly correlated to the prognosis of CRC patients. Finally, 10 IRGs were filtered out to construct the risk score signature, and patients were divided into low- and high-risk groups according to the median of risk scores in the training cohort. The high-risk score was significantly correlated with unfavorable survival outcomes and aggressive clinicopathological characteristics in CRC patients, and the results were further confirmed in the internal validation cohort, entire TCGA cohort, and external validation cohort. Immune infiltration analysis revealed that patients in the low-risk group infiltrated with high tumor-infiltrating immune cell (TIIC) abundances compared to the high-risk group. Moreover, we also found that the immune checkpoint biomarkers were significantly overexpressed in the low-risk group.

Conclusion: The prognostic signature established by IRGs showed a promising clinical value for predicting the prognosis and immune characteristics of human CRC, which contribute to individualized treatment decisions.

Instructive Hydrogels for Primary Tumor Cell Culture: Current Status and Outlook

Primary tumor organoids (PTOs) growth in hydrogels have emerged as an important in vitro model that recapitulates many characteristics of the native tumor tissue, and have important applications in fundamental cancer research and for the development of useful therapeutic treatment. This paper begins with reviewing the methods of isolation of primary tumor cells. Then, recent advances on the instructive hydrogels as biomimetic extracellular matrix for primary tumor cell culture and construction of PTO models are summarized. Emerging microtechnology for growth of PTOs in microscale hydrogels and the applications of PTOs are highlighted. This paper concludes with an outlook on the future directions in the investigation of instructive hydrogels for PTO growth.

A nomogram-based immunoprofile predicts clinical outcomes for stage II and III human colorectal cancer

An immunoscore for colorectal cancer (CRC) has higher prognostic significance than the TNM staging system. However, the tumor immune microenvironment contains various components that affect clinical prognosis. Therefore, a broader range of immune markers is required to establish an accurate immunoprofile to assess the prognosis of patients with CRC. Using immunohistochemistry combined with multispectral immunohistochemistry and objective assessments, the infiltration of four immune cell types (CD4⁺/CD8⁺/forkhead box p3⁺/CD33⁺ cells), as well as the expression of six co-signaling molecules [programmed cell death 1 (PD1) ligand 1/PD1/T-cell immunoglobulin mucin family member 3/lymphocyte-activating 3/tumor necrosis factor receptor superfamily, member 4/inducible T-cell costimulator] and indoleamine 2,3-dioxygenase 1 were investigated in two independent cohorts of CRC. The patients' overall survival (OS) was evaluated using the Kaplan-Meier method. Using the Cox proportional hazards model, independent prognostic factors of patients were assessed and a nomogram-based immunoprofile system was developed. The predictive ability of the nomogram was determined using a concordance index (C-index) and calibration curve. To facilitate clinical application, a simplified nomogram-based immunoprofile was constructed. Using receiver operating characteristic (ROC) analysis, the predictive accuracy for OS was compared between the immunoprofile and the TNM staging system for patients with stage II/III CRC. According to multivariate analysis for the primary cohort, independent prognostic factors for OS were CD8⁺ tumor-infiltrating lymphocytes, CD33⁺ myeloid-derived suppressor cells and TNM stage, which were included in the nomogram. The C-index of the nomogram for predicting OS was 0.861 (95% CI: 0.796-0.925) for the internal validation and 0.759 (95% CI: 0.714-0.804) for the external validation cohort. The simplified nomogram-based immunoprofile system was able to separate same-stage patients into different risk subgroups, particularly for TNM stage II (P<0.0001) and III (P=0.0002) patients. Pairwise comparison of ROC curves for the immunoprofile and TNM stage systems for patients with stage II/III CRC revealed statistically significant differences (P=0.046) and the Z-statistic value was 1.995. In conclusion, the nomogram-based immunoprofile system provides prognostic accuracy regarding clinical outcomes and is a useful supplement to the TNM staging system for patients with stage II/III CRC.

Analysis of Immune Landscape Reveals Prognostic Significance of Cytotoxic CD4+ T Cells in the Central Region of pMMR CRC

Background

Mismatch repair proficient colorectal cancer (pMMR CRC) lacks effective treatments and has a poor prognosis, which can be attributed to the complexity of tumor microenvironment. The coordinated function of immune cells is vital to anti-tumor immunity. However, the spatial characteristics of immune cells in the pMMR CRC immune microenvironment and their relationship with clinical prognosis are not fully understood. Meanwhile, the immune modulatory effect of neoadjuvant chemotherapy (NCT), which is the first-line treatment of pMMR CRC, needs further investigation. Therefore, this study aims to explore the spatial dynamics of immune cells and its prognostic value in pMMR CRC.

Methods

We analyzed the various immune cells in formalin-fixed, paraffin-embedded tumor tissues which were collected from 77 patients with stage II/III of pMMR CRC, including 39 non-NCT treated and 38 NCT treated patients. We used the optimized multiplex immunohistochemistry (mIHC) to identify and quantify the density, type and location of immune cells in pMMR CRC. Multivariate survival analysis was performed to assess the relationship of immune profiles and clinical prognosis of pMMR CRC patients.

Results

The densities of most T cell subsets, B cells and macrophages were higher in the central region of the pMMR CRC than in the invasion margin. Tumor infiltrating lymphocytes (TILs), especially the infiltration of CD4⁺ GzmB⁺ T cells in the central region of the tumor was identified to be positively correlated with the prognosis of the patients. Multivariate analysis confirmed that CD4⁺ GzmB⁺ T cells population was an independent predictor of disease-free survival (DFS) in non-NCT group. Meanwhile, NCT enhanced the infiltration of CD4⁺ GzmB⁺ T cells in the central region of the pMMR CRC, which was also identified as an independent protective factor of overall survival (OS) and DFS in NCT group.

Conclusion

We demonstrated that the level of CD4⁺ GzmB⁺ T cells located in the center of tumor could provide great prognostic value for pMMR CRC patients. And the application of neoadjuvant chemotherapy further improves the infiltration of CD4⁺ GzmB⁺ T cells in the central compartment. Further studies into the application of CD4⁺ GzmB⁺ T cells in tumor immunotherapy are needed.

Development of a multiplex immuno-oncology biomarker and digital pathology workflow for assessment of urothelial carcinoma

BACKGROUND

Immune checkpoint inhibitors (ICI) therapies have demonstrated significant benefit in the treatment of many tumors including high grade urothelial cancer (HGUC) of the bladder. However, variability in patients' clinical responses highlights the need for biomarkers to aid patient stratification. ICI relies on an intact host immune response. In this context, we hypothesize that key players in the antitumor immune response such as markers of activated cytotoxic T lymphocytes (CD8, granzyme-B) and immune suppression (FOXP3) may help to identify patients who will derive the greatest therapeutic benefit from ICI. A major obstacle for deployment of such a strategy is the limited quantities of tumor-derived biopsy material. Therefore, in this technical study, we develop a multiplex biomarker with digital workflow. We explored the (1) concordance of conventional single stain results using digital image analysis, and (2) agreement between digital scoring versus manual analysis.

METHODS

(1) For concordance study of single and multiplex stains, triplicate core tissue microarrays of 207 muscle invasive, HGUC of bladder had sequential 4-micron sections cut and stained with CD8, FOXP3 and granzyme-B. An inhouse developed tri-chromogen multiplex immunohistochemistry (m-IHC) assay consisting of CD8 (green), granzyme B (brown), and FOXP3 (red) was used to stain the next sequential tissue section. (2) Agreement between manual and digital analysis was performed on 19 whole slide sections of HGUC cystectomy specimens. All slides were scanned using Aperio ScanScope AT Digital Scanner at 40X. Quantitative digital image analysis was performed using QuPath version 0.2.3 open-source software. Scores from triplicate cores were averaged for each HGUC specimen for each marker. Intraclass correlation coefficients were used to compare percent positive cells between the single- and multi-plex assays. Lin's concordance correlation coefficients were used for manual versus digital analysis.

RESULTS AND CONCLUSIONS

m-IHC offers significant advantages in characterizing the host immune microenvironment particularly in limited biopsy tissue material. Utilizing a digital image workflow resulted in significant concordance between m-IHC and individual single stains (p < 0.001 for all assessments). Moderate to good agreements were achieved between manual and digital scoring. Our technical work demonstrated potential uses of multiplex marker in assessing the host immune status and could be used in conjunction with PD-L1 as a predictor of response to ICI therapy.

Immunoprofiling: An Encouraging Method for Predictive Factors Examination in Lung Cancer Patients Treated with Immunotherapy

The efficiency of immunotherapy using monoclonal antibodies that inhibit immune checkpoints has been proven in many clinical studies and well documented by numerous registration approaches. To date, PD-L1 expression on tumor and immune cells, tumor mutation burden (TMB), and microsatellite instability (MSI) are the only validated predictive factors used for the qualification of cancer patients for immunotherapy. However, they are not the ideal predictive factors. No response to immunotherapy could be observed in patients with high PD-L1 expression, TMB, or MSI. On the other hand, the effectiveness of this treatment method also may occur in patients without PD-L1 expression or with low TMB and with microsatellite stability. When considering the best predictive factor, we should remember that the effectiveness of immunotherapy relies on an overly complex process depending on many factors. To specifically stimulate lymphocytes, not only should their activity in the tumor microenvironment be unlocked, but above all, they should recognize tumor antigens. The proper functioning of the anticancer immune system requires the proper interaction of many elements of the specific and non-specific responses. For these reasons, a multi-parameter analysis of the immune system at its different activity levels is considered a very future-oriented predictive marker. Such complex immunological analysis is performed using modern molecular biology techniques. Based on the gene expression studies, we can determine the content of individual immune cells within the tumor, its stroma, and beyond. This includes all cell types from active memory cytotoxic T cells, M1 macrophages, to exhausted T cells, regulatory T cells, and M2 macrophages. In this article, we summarize the possibilities of using an immune system analysis to predict immunotherapy efficacy in cancer patients. Moreover, we present the advantages and disadvantages of immunoprofiling as well as a proposed future direction for this new method of immune system analysis in cancer patients who receive immunotherapy.

Multiplex Immunofluorescence Tyramide Signal Amplification for Immune Cell Profiling of Paraffin-Embedded Tumor Tissues

Every day, more evidence is revealed regarding the importance of the relationship between the response to cancer immunotherapy and the cancer immune microenvironment. It is well established that a profound characterization of the immune microenvironment is needed to identify prognostic and predictive immune biomarkers. To this end, we find phenotyping cells by multiplex immunofluorescence (mIF) a powerful and useful tool to identify cell types in biopsy specimens. Here, we describe the use of mIF tyramide signal amplification for labeling up to eight markers on a single slide of formalin-fixed, paraffin-embedded tumor tissue to phenotype immune cells in tumor tissues. Different panels show different markers, and the different panels can be used to characterize immune cells and relevant checkpoint proteins. The panel design depends on the research hypothesis, the cell population of interest, or the treatment under investigation. To phenotype the cells, image analysis software is used to identify individual marker expression or specific co-expression markers, which can differentiate already selected phenotypes. The individual-markers approach identifies a broad number of cell phenotypes, including rare cells, which may be helpful in a tumor microenvironment study. To accurately interpret results, it is important to recognize which receptors are expressed on different cell types and their typical location (i.e., nuclear, membrane, and/or cytoplasm). Furthermore, the amplification system of mIF may allow us to see weak marker signals, such as programmed cell death ligand 1, more easily than they are seen with single-marker immunohistochemistry (IHC) labeling. Finally, mIF technologies are promising resources for discovery of novel cancer immunotherapies and related biomarkers. In contrast with conventional IHC, which permits only the labeling of one single marker per tissue sample, mIF can detect multiple markers from a single tissue sample, and at the same time, deliver extensive information about the cell phenotypes composition and their spatial localization. In this matter, the phenotyping process is critical and must be done accurately by a highly trained personal with knowledge of immune cell protein expression and tumor pathology.

Identification of an Immune Gene Signature Based on Tumor Microenvironment Characteristics in Colon Adenocarcinoma

Tumor microenvironment (TME) changes are related to the occurrence and development of colon adenocarcinoma (COAD). This study aimed to analyze the characteristics of the immune microenvironment in CC, as well as the microenvironment's relationship with the clinical features of CC. Based on The Cancer Genome Atlas (TCGA) and GSE39582 cohorts, the scores of 22 tumor infiltrating lymphocytes (TILs) were calculated using CIBERSORT. ConsensusClusterPlus was used for unsupervised clustering. Three TME subtypes (TMEC1, TMEC2, and TME3) were identified based on TIL scores. TMEC2 was associated with the worst prognosis. Random forest, k-means clustering, and principal component analysis were used to construct the TME score risk signature. The median TME score was used to divide the samples into high- and low-risk groups. The prognoses of the patients with high TME scores were worse than those of the patients with low TME scores. A high TME score was an independent prognostic risk factor for patients with colon cancer. The Gene Set Enrichment Analysis (GSEA) results showed that those with high TME scores were enriched in FOCAL_ADHESION, ECM_RECEPTOR_INTERACTION, and PATHWAYS_IN_CANCER. Our findings will provide a new strategy for immunotherapy in patients with CC.

Immunoprofiling in Neuroendocrine Neoplasms Unveil Immunosuppressive Microenvironment

Checkpoint inhibitors have shown promising results in a variety of tumors; however, in neuroendocrine tumors (NET) and neuroendocrine carcinomas (NEC), low response rates were reported. We aimed herein to investigate the tumor immune microenvironment in NET/NEC to determine whether checkpoint pathways like programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) might play a role in immune escape and whether other escape mechanisms might need to be targeted to enable a functional antitumor response. Forty-eight NET and thirty NEC samples were analyzed by immunohistochemistry (IHC) and mRNA immunoprofiling including digital spatial profiling. Through IHC, both NET/NEC showed stromal, but less intratumoral CD3+ T cell infiltration, although this was significantly higher in NEC compared to NET. Expression of PD1, PD-L1, and T cell immunoglobulin and mucin domain-containing protein 3 (TIM3) on immune cells was low or nearly absent. mRNA immunoprofiling revealed low expression of IFNγ inducible genes in NET and NEC without any spatial heterogeneity. However, we observed an increased mRNA expression of chemokines, which attract myeloid cells in NET and NEC, and a high abundance of genes related to immunosuppressive myeloid cells and genes with immunosuppressive functions like CD47 and CD74. In conclusion, NET and NEC lack signs of an activation of the adaptive immune system, but rather show abundance of several immunosuppressive genes that represent potential targets for immunomodulation.

Immune contexture analysis in immuno-oncology: applications and challenges of multiplex fluorescent immunohistochemistry

The tumor microenvironment is an integral player in cancer initiation, tumor progression, response and resistance to anti-cancer therapy. Understanding the complex interactions of tumor immune architecture (referred to as 'immune contexture') has therefore become increasingly desirable to guide our approach to patient selection, clinical trial design, combination therapies, and patient management. Quantitative image analysis based on multiplexed fluorescence immunohistochemistry and deep learning technologies are rapidly developing to enable researchers to interrogate complex information from the tumor microenvironment and find predictive insights into treatment response. Herein, we discuss current developments in multiplexed fluorescence immunohistochemistry for immune contexture analysis, and their application in immuno-oncology, and discuss challenges to effectively use this technology in clinical settings. We also present a multiplexed image analysis workflow to analyse fluorescence multiplexed stained tumor sections using the Vectra Automated Digital Pathology System together with FCS express flow cytometry software. The benefit of this strategy is that the spectral unmixing accurately generates and analyses complex arrays of multiple biomarkers, which can be helpful for diagnosis, risk stratification, and guiding clinical management of oncology patients.

Cytotoxic CD8+ T cells in cancer and cancer immunotherapy

The functions of, and interactions between, the innate and adaptive immune systems are vital for anticancer immunity. Cytotoxic T cells expressing cell-surface CD8 are the most powerful effectors in the anticancer immune response and form the backbone of current successful cancer immunotherapies. Immune-checkpoint inhibitors are designed to target immune-inhibitory receptors that function to regulate the immune response, whereas adoptive cell-transfer therapies use CD8⁺ T cells with genetically modified receptors—chimaeric antigen receptors—to specify and enhance CD8⁺ T-cell functionality. New generations of cytotoxic T cells with genetically modified or synthetic receptors are being developed and evaluated in clinical trials. Furthermore, combinatory regimens might optimise treatment effects and reduce adverse events. This review summarises advances in research on the most prominent immune effectors in cancer and cancer immunotherapy, cytotoxic T cells, and discusses possible implications for future cancer treatment.

Identification of prognostic and immune-related gene signatures in the tumor microenvironment of endometrial cancer

Uterine corpus endometrial cancer (UCEC) is one of the most prevalent female malignancies in clinical practice. Due to the lack of effective biomarkers and personalized treatments, the prognosis of advanced-stage EC remains unfavorable. Modulation of the immune microenvironment is closely related to the onset and development of endometrial cancer. In the present study, we attempt to systematically analyze the characteristics of the immune microenvironment of endometrial cancer and investigate its association with clinical features by applying bioinformatics. RNA-Seq in TCGA (The Cancer Genome Atlas) and clinical follow-up information of patents were used for analysis. The Tumor Microenvironment (TME) score infiltration patterns of 523 endometrial cancer patients were evaluated using CIBERSORT. Random forest, multivariable cox analysis were used to build the TME score. Fisher's exact test was used to compare the genes that show significant differences in the frequency of mutations between groups. Two TME phenotypes were defined. There is a significant relationship between the TME score and grade. High TME score samples are highly expressed in immune activation, TGF pathway activation and immune checkpoint genes, and low TME score samples have high frequency mutations of PTEN, CSE1L and ITGB3. Therefore, describing the comprehensive landscape of UCEC's TME characteristics may help explain patients' response to immunotherapy and provide new strategies for cancer treatment.

Immune profiling of pediatric solid tumors

Pediatric cancers, particularly high-risk solid tumors, urgently need effective and specific therapies. Their outlook has not appreciably improved in decades. Immunotherapies such as immune checkpoint inhibitors offer much promise, but most are only approved for use in adults. Though several hundred clinical trials have tested immune-based approaches in childhood cancers, few have been guided by biomarkers or clinical-grade assays developed to predict patient response and, ultimately, to help select those most likely to benefit. There is extensive evidence in adults to show that immune profiling has substantial predictive value, but few studies focus on childhood tumors, because of the relatively small disease population and restricted use of immune-based therapies. For instance, only one published study has retrospectively examined the immune profiles of pediatric brain tumors after immunotherapy. Furthermore, application and integration of advanced multiplex techniques has been extremely limited. Here, we review the current status of immune profiling of pediatric solid tumors, with emphasis on tumor types that represent enormous unmet clinical need, primarily in the context of immune checkpoint inhibitor therapy. Translating optimized and informative immune profiling into standard practice and access to personalized combination therapy will be critical if childhood cancers are to be treated effectively and affordably.

Positive PD-L1 expression is predictive for patients with advanced EGFR wild-type non-small cell lung cancer treated with gemcitabine and cisplatin

This retrospective study aimed to investigate the association between programmed death ligand-1 (PD-L1) expression and the clinicopathological characteristics of patients with advanced epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLC). The predictive role and cut-off value of PD-L1 expression was subsequently investigated. A total of 172 patients with advanced EGFR wild-type NSCLC were enrolled. All patients received platinum-based doublet chemotherapy (gemcitabine plus cisplatin). PD-L1 expression in lung tissues was assessed using immunohistochemical methods. The χ² test was used to analyze the association between PD-L1 expression and clinicopathological characteristics. Survival time analysis was performed using the Kaplan-Meier method. The two groups, positive PD-L1 expression and negative PD-L1 expression, were compared using the log-rank test. Multivariate analysis using the Cox proportional hazard regression model was conducted to determine prognostic factors for overall survival (OS) and progression-free survival (PFS) times. Positive PD-L1 expression was observed in 48.3% (84/172), 40.7% (70/172), 21.5% (37/172) and 8.1% (14/172) of patients when using cut-off values of 1, 5, 10 and 50%, respectively. The χ² test revealed that elevated pretreatment C-reactive protein (CRP) level and cancer stage IV were significantly associated with positive PD-L1 expression. The OS and PFS of positive PD-L1 (1, 5, 10 and 50% cut-off) expression group were shorter compared with the negative PD-L1 (1, 5, 10 and 50% cut-off) expression group. Multivariate survival analysis revealed that PD-L1 expression ≥50% was significantly associated with decreased OS and PFS [OS time, P=0.001; hazard ratio (HR), 2.768; 95% confidence interval (CI), 1.551–4.940; PFS time, P=0.002; HR, 2.537; 95% CI, 1.423–4.524]. These results indicated that positive PD-L1 (50% cut-off) expression was an independent predictor of poor prognosis for patients with advanced NSCLC treated with gemcitabine plus cisplatin. PD-L1 expression was associated with CRP level and cancer stage. The results obtained in the present study suggest that positive PD-L1 expression serves a prognostic role in advanced NSCLC and that the optimal cut-off value may be 50%.

Offsetting Expression Profiles of Prognostic Markers in Prostate Tumor vs. Its Microenvironment

Diagnosis of the presence of tumors and subsequent prognosis based on tumor microenvironment becomes more clinically practical because tumor-adjacent tissues are easy to collect and they are more genetically homogeneous. The purpose of this study was to identify new prognostic markers in prostate stroma that are near the tumor. We have demonstrated the prognostic features of FGFR1, FRS2, S6K1, LDHB, MYPT1, and P-LDHA in prostate tumors using tissue microarrays (TMAs) which consist of 241 patient samples from Massachusetts General Hospital (MGH). In this study, we investigated these six markers in the tumor microenvironment using an Aperio Imagescope system in the same TMAs. The joint prognostic power of markers was further evaluated and classified using a new algorithm named Weighted Dichotomizing. The classifier was verified via rigorous 10-fold cross validation. Statistical analysis of the protein expression indicated that in tumor-adjacent stroma FGFR1 and MYPT1 were significantly correlated with patient outcomes and LDHB showed the outcome-association tendency. More interestingly, these correlations were completely opposite regarding tumor tissue as previously reported. The results suggest that prognostic testing should utilize either tumor-enriched tissue or stroma with distinct signature profiles rather than using mixture of both tissue types. The new classifier based on stroma tissue has potential value in the clinical management of prostate cancer patients.

Immunoprofiling of Colitis-associated and Sporadic Colorectal Cancer and its Clinical Significance

Immunoprofiling is useful for predicting prognosis in various malignancies and provides targets for immunotherapy. Quantitative multispectral imaging system, which allows simultaneous detection of multiple immune markers, is a novel method for examining the tumor immune environment. We compared the expression levels of various surface markers in immune cells between colitis-associated cancer (CAC) and sporadic colorectal cancer (CRC) and evaluated the clinical usefulness of immunoprofiling in CRC. Tumor specimens from 24 CAC patients and 48 sporadic CRC patients, matched by age, sex, and tumor location to CAC, were included in the analysis. The expression levels of CD3, CD8, Foxp3, and programmed death-ligand 1 (PD-L1) in immune cells at the invasive margins of tumor tissues were evaluated by quantitative multispectral imaging. The CAC group had significantly less levels of cells expressing CD3, CD8, Foxp3, or PD-L1 (all, p < 0.01). In the CAC group, patients whose immune cells had high expression of CD3⁺ and CD8⁺ had better overall survival. The immune profiling patterns of CAC patients were significantly distinct from those of sporadic CRC patients, suggesting that CAC and sporadic CRC have distinct disease phenotypes. Immunoprofiling can be helpful for evaluation of clinical prognosis in CAC.

Can CpG methylation serve as surrogate markers for immune infiltration in cancer?

Recent reports describe how genome-wide transcriptional analysis of cancer tissues can be exploited to identify molecular signatures of immune infiltration in cancer. We hypothesize that immune infiltration in cancer may also be defined by changes in certain epigenetic signatures. In this context, a primary objective is to identify site-specific CpG markers whose levels of methylation may be highly indicative of known transcriptional markers of immune infiltration such as GZMA, PRF1, T cell receptor genes, PDCD1, and CTLA4. This has been accomplished by integrating genome-wide transcriptional expression and methylation data for different types of cancer (melanoma, kidney cancers, lung cancers, gliomas, head and neck cancer). Our findings establish that cancers of related histology also have a high degree of similarity in immune-infiltration CpG markers. For example, the epigenetic immune infiltration signatures in lung adenocarcinoma (LUAD), mesothelioma (MESO), lung squamous cell carcinoma (LUSC), and head and neck squamous cell carcinoma (HNSC) are distinctly similar. So are glioblastoma multiforme (GBM) and brain lower grade glioma (LGG); and kidney renal papillary cell carcinoma (KIRP) and kidney renal clear cell carcinoma (KIRC). Kidney chromophobe (KICH), on the other hand has markers that are unique to this cohort. The strong relationships between immune infiltration and CpG methylation (for certain sites) in cancer tissues were not observed upon integrated analysis of publicly available cancer cell line datasets. Results from comparative pathways analyses offer further justification to methylation at certain CpG sites as being indicators of cancer immune infiltration, and possibly of predicting patient response to immunotherapeutic drugs. Achieving this target objective would significantly enhance therapeutic outcomes employing immunotherapy through focused patient-centric personalized medicine.

Pathways- and epigenetic-based assessment of relative immune infiltration in various types of solid tumors

Recent clinical studies document the power of immunotherapy in treating subsets of patients with advanced cancers. In this context and with multiple cancer immunotherapeutics already evaluated in the clinic and a large number in various stages of clinical trials, it is imperative to comprehensively examine genomics data to better comprehend the role of immunity in different cancers in predicting response to therapy and in directing appropriate therapies. The approach we chose is to scrutinize the pathways and epigenetic factors predicted to drive immune infiltration in different cancer types using publicly available TCGA transcriptional and methylation datasets, along with accompanying clinico-pathological data. We observed that the relative activation of T cells and other immune signaling pathways differs across cancer types. For example, pathways related to activation and proliferation of helper and cytotoxic T cells appear to be more highly enriched in kidney, skin, head and neck, and esophageal cancers compared to those of lung, colorectal, and liver or bile duct cancers. The activation of these immune-related pathways positively associated with prognosis in certain cancer types, most notably melanoma, head and neck, and cervical cancers. Integrated methylation and expression data (along with publicly available, ENCODE-generated histone ChIP Seq and DNAse hypersensitivity data) predict that epigenetic regulation is a primary factor driving transcriptional activation of a number of genes crucial to immunity in cancer, including T cell receptor genes (e.g., CD3D, CD3E), CTLA4, and GZMA. However, the extent to which epigenetic factors (primarily methylation at promoter regions) affect transcription of immune-related genes may vary across cancer types. For example, there is a high negative correlation between promoter CpG methylation and CD3D expression in renal and thyroid cancers, but not in brain tumors. The types of analyses we have undertaken provide insights into the relationships between immune modulation and cancer etiology and progression, offering clues into ways of therapeutically manipulating the immune system to promote immune recognition and immunotherapy.

A Practical Guide to Whole Slide Imaging: A White Paper From the Digital Pathology Association

Context.—

Whole slide imaging (WSI) represents a paradigm shift in pathology, serving as a necessary first step for a wide array of digital tools to enter the field. Its basic function is to digitize glass slides, but its impact on pathology workflows, reproducibility, dissemination of educational material, expansion of service to underprivileged areas, and intrainstitutional and interinstitutional collaboration exemplifies a significant innovative movement with far-reaching effects. Although the benefits of WSI to pathology practices, academic centers, and research institutions are many, the complexities of implementation remain an obstacle to widespread adoption. In the wake of the first regulatory clearance of WSI for primary diagnosis in the United States, some barriers to adoption have fallen. Nevertheless, implementation of WSI remains a difficult prospect for many institutions, especially those with stakeholders unfamiliar with the technologies necessary to implement a system or who cannot effectively communicate to executive leadership and sponsors the benefits of a technology that may lack clear and immediate reimbursement opportunity.

Objectives.—

To present an overview of WSI technology—present and future—and to demonstrate several immediate applications of WSI that support pathology practice, medical education, research, and collaboration.

Data Sources.—

Peer-reviewed literature was reviewed by pathologists, scientists, and technologists who have practical knowledge of and experience with WSI.

Conclusions.—

Implementation of WSI is a multifaceted and inherently multidisciplinary endeavor requiring contributions from pathologists, technologists, and executive leadership. Improved understanding of the current challenges to implementation, as well as the benefits and successes of the technology, can help prospective users identify the best path for success.

On the Road to Immunotherapy-Prospects for Treating Head and Neck Cancers With Checkpoint Inhibitor Antibodies

Head and neck cancers (HNC) represent a heterogeneous cluster of aggressive malignancies that account for 3% of all cancer cases in the UK. HNC is increasing in frequency particularly in the developing world, which is related to changes in risk factors. Unfortunately, the mortality rate is high, which is chiefly attributed to late diagnosis at stages where traditional treatments fail. Cancer immunotherapy has achieved great successes in anti-tumor therapy. Checkpoint inhibitor (CI) antibodies enhance anti-tumor activity by blocking inhibitory receptors to drive tumor-specific T and NK cell effector responses. Since their introduction in 2011, CI antibodies have been approved for many cancer types including HNC. Here, we examine the development of CI therapies and look forward to future developments for treatment of HNC with CI therapies.

Novel frontiers in detecting cancer metastasis

Cancer microenvironment is the critical battle ground between the cancer cells and host response. Thus, more emphasis is directed to study the relationship between cancer cells and the stromal cells. Multiplex microscopy is an emerging technique in which multiple cell populations within the cancer microenvironment may be stained so that spatial relationship between cancer cells and, in particular, the immune cells may be studied during different stages of cancer development. Recent discovery of mutational burden and neoantigens in cancer has opened new landscapes in the interaction of host immune cells and cancer neoantigens. The emerging role of miRNAs may become an added dimension to study cancer beyond traditional pathway of DNA directed RNA being associated with the malignant behavior of cancer. Circulating tumor cells, cancer markers and ctDNA can be used as markers for circulating cancer cells in the blood. Further studies are needed to validate if liquid biopsy of cancer may become a routine clinical tool to screen cancer or follow patients for recurrence or responses to treatment.

Measuring multiple parameters of CD8+ tumor-infiltrating lymphocytes in human cancers by image analysis

BACKGROUND

Immuno-oncology and cancer immunotherapies are areas of intense research. The numbers and locations of CD8+ tumor-infiltrating lymphocytes (TILs) are important measures of the immune response to cancer with prognostic, pharmacodynamic, and predictive potential. We describe the development, validation, and application of advanced image analysis methods to characterize multiple immunohistochemistry-derived CD8 parameters in clinical and nonclinical tumor tissues.

METHODS

Commercial resection tumors from nine cancer types, and paired screening/on-drug biopsies of non-small-cell lung carcinoma (NSCLC) patients enrolled in a phase 1/2 clinical trial investigating the PD-L1 antibody therapy durvalumab (NCT01693562), were immunostained for CD8. Additional NCT01693562 samples were immunostained with a CD8/PD-L1 dual immunohistochemistry assay. Whole-slide scanning was performed, tumor regions were annotated by a pathologist, and images were analyzed with customized algorithms using Definiens Developer XD software. Validation of image analysis data used cell-by-cell comparison to pathologist scoring across a range of CD8+ TIL densities of all nine cancers, relying primarily on 95% confidence in having at least moderate agreement regarding Lin concordance correlation coefficient (CCC = 0.88-0.99, CCC_lower = 0.65-0.96).

RESULTS

We found substantial variability in CD8+ TILs between individual patients and across the nine types of human cancer. Diffuse large B-cell lymphoma had several-fold more CD8+ TILs than some other cancers. TIL densities were significantly higher in the invasive margin versus tumor center for carcinomas of head and neck, kidney and pancreas, and NSCLC; the reverse was true only for prostate cancer. In paired patient biopsies, there were significantly increased CD8+ TILs 6 weeks after onset of durvalumab therapy (mean of 365 cells/mm2 over baseline; P = 0.009), consistent with immune activation. Image analysis accurately enumerated CD8+ TILs in PD-L1+ regions of lung tumors using the dual assay and also measured elongate CD8+ lymphocytes which constituted a fraction of overall TILs.

CONCLUSIONS

Validated image analysis accurately enumerates CD8+ TILs, permitting comparisons of CD8 parameters among tumor regions, individual patients, and cancer types. It also enables the more complex digital solutions needed to better understand cancer immunity, like analysis of multiplex immunohistochemistry and spatial evaluation of the various components comprising the tumor microenvironment.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01693562 . Study code: CD-ON-MEDI4736-1108. Interventional study (ongoing but not currently recruiting). Actual study start date: August 29, 2012. Primary completion date: June 23, 2017 (final data collection date for primary outcome measure).

Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells

Immune cells are important components of the tumor microenvironment and influence tumor growth and evolution at all stages of carcinogenesis. Notably, it is now well established that the immune infiltrate in human tumors can correlate with prognosis and response to therapy. The analysis of the immune infiltrate in the tumor microenvironment has become a major challenge for the classification of patients and the response to treatment. The co-expression of inhibitory receptors such as Program Cell Death Protein 1 (PD1; also known as CD279), Cytotoxic T Lymphocyte Associated Protein 4 (CTLA-4), T-Cell Immunoglobulin and Mucin Containing Protein-3 (Tim-3; also known as CD366), and Lymphocyte Activation Gene 3 (Lag-3; also known as CD223), is a hallmark of T cell exhaustion. We developed a multiparametric in situ immunofluorescence staining to identify and quantify at the cellular level the co-expression of these inhibitory receptors. On a retrospective series of frozen tissue of renal cell carcinomas (RCC), using a fluorescence multispectral imaging technology coupled with an image analysis software, it was found that co-expression of PD-1 and Tim-3 on tumor infiltrating CD8⁺ T cells is correlated with a poor prognosis in RCC. To our knowledge, this represents the first study demonstrating that this automated multiplex in situ technology may have some clinical relevance.

HLA class I loss and PD-L1 expression in lung cancer: impact on T-cell infiltration and immune escape

Immune-checkpoint inhibitors show encouraging results in cancer treatment, but the clinical benefit is limited exclusively to a subset of patients. We analyzed the density and composition of tumor T-cell infiltration in non-small-cell lung carcinoma (NSCLC) in relation to PD-L1 and HLA class I (HLA-I) expression. We found that positive HLA-I expression, independently on PD-L1 status, is the key factor determining the increased density of the immune infiltrate. When both markers were analyzed simultaneously, we identified four phenotypes of HLA-I and PD-L1 co-expression. They demonstrated different patterns of tumor infiltration and clinicopathologic characteristics, including the tumor size and lymphatic spread. All HLA-I+/PD-L1+ tumors had a high degree of intratumoral infiltration with CD8+T-lymphocytes, whereas HLA-I loss was associated with a significantly reduced number of tumor infiltrating T-lymphocytes mostly restrained in the stroma surrounding the tumor nest. HLA-I-negative/PD-L1-positive tumors had bigger size (T) and lower grade of infiltration with CD8+T-cells. It represents a cancer immune escape phenotype that combines two independent mechanisms of immune evasion: loss of HLA-I and upregulation of PD-L1. Using GCH-array analysis of human lung cancer cell lines we found that the loss of heterozygosity (LOH) with complete or partial deletion of HLA-I genes is the principal mechanism of HLA-I alterations. This irreversible defect, which could potentially decrease the clinical efficacy of lung cancer immunotherapy, appears to be underestimated. In conclusion, our results suggest that the analysis of HLA-I is very important for the selection of potential responders to cancer immunotherapy.

Multiparametric immune profiling in HPV- oral squamous cell cancer

Evaluation of T lymphocyte frequency provides prognostic information for patients with oral squamous cell cancer (OSCC). However, the effect of simultaneously evaluating T cell frequency and assessing suppressive elements and defects in antigen-processing machinery (APM) has not been clarified. Simultaneous characterization of CD3+, CD8+, FoxP3+, CD163+, and PD-L1+ cells using multispectral imaging was performed on sections from 119 patients with HPV- OSCC. Expression of β2-microglobulin, MHC class I heavy chain, and large multifunctional peptidase 10 was quantified, and all data were correlated with patient outcome. We found that, consistent with previous reports, high numbers of CD8+ T cells at the invasive margin correlated significantly with prolonged overall survival (OS), while the number of FoxP3+ or PD-L1+ cells did not. Compiling the number of FoxP3+ or PD-L1+ cells within 30 μm of CD8+ T cells identified a significant association with a high number of suppressive elements close to CD8+ T cells and reduced OS. Integrating this information into a cumulative suppression index (CSI) increased correlation with OS. Incorporating tumor expression levels of APM components with CSI further improved prognostic power. This multiparametric immune profiling may be useful for stratifying patients with OSCC for clinical trials.