Prognostic significance of spatial immune profiles in human solid cancers

Peritumoral Infiltration of Regulatory T Cells Reduces the Therapeutic Efficacy of Bacillus Calmette-Guérin Therapy for Bladder Carcinoma In Situ

OBJECTIVES

Intravesical instillation of bacillus Calmette-Guérin (BCG) is the standard treatment for bladder carcinoma in situ (CIS); however, factors that predict its therapeutic efficacy have not been identified. We focused on immune cells infiltrating within 20 μm of tumor cells and examined factors that predict the efficacy of intravesical BCG treatment.

METHODS

Formalin-fixed, paraffin-embedded tissue specimens from 82 patients with bladder CIS treated with intravesical BCG were used. Patients who relapsed after BCG treatment were grouped as non-responders, and those who did not were grouped as responders. Tissue sections were immunostained for CD4, CD8, and forkhead box P3 (FOXP3), a marker of regulatory T cells (Tregs). The number of immune cells positive for the above markers present within 20 μm of the lower edge of the basement membrane on which CIS is present was counted and compared between groups.

RESULTS

Both the peritumoral Treg density and Treg+/CD4+ cell ratio were significantly greater in nonresponders than in responders. The patients were divided into high and low groups based on Treg density and Treg+/CD4+ cell ratio cut-off values; recurrence-free survival was significantly longer in the low group than in the high group (p = 0.005 and p < 0.001, respectively).

CONCLUSIONS

The Treg density and Treg+/CD4+ cell ratio within 20 μm of bladder CIS may be useful predictors of therapeutic response to BCG.

Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic data of ovarian cancer

To unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell-cell communication between tumor and immune/stromal cells in the tumor microenvironment. Central to this communication are interactions between secreted ligands and cell-surface receptors, creating a highly connected signaling network among cells. Recent advancements in in situ-omics profiling, particularly spatial transcriptomic (ST) technology, provide unique opportunities to directly characterize ligand-receptor signaling networks that power cell-cell communication. In this paper, we propose a novel statistical method, LRnetST, to characterize the ligand-receptor interaction networks between adjacent tumor and immune/stroma cells based on ST data. LRnetST utilizes a directed acyclic graph model with a novel approach to handle the zero-inflated distributions of ST data. It also leverages existing ligand-receptor regulation databases as prior information, and employs a bootstrap aggregation strategy to achieve robust network estimation. Application of LRnetST to ST data of high-grade serous ovarian tumor samples revealed both common and distinct ligand-receptor regulations across different tumors. Some of these interactions were validated through both a MERFISH dataset and a CosMx SMI dataset of independent ovarian tumor samples. These results cast light on biological processes relating to the communication between tumor and immune/stromal cells in ovarian tumors. An open-source R package of LRnetST is available on GitHub at https://github.com/jie108/LRnetST.

Natural killer cells occupy unique spatial neighborhoods in HER2- and HER2+ human breast cancers

Tumor-infiltrating lymphocytes are considered clinically beneficial in breast cancer, but the significance of natural killer (NK) cells is less well characterized. As increasing evidence has demonstrated that the spatial organization of immune cells in tumor microenvironments is a significant parameter for impacting disease progression as well as therapeutic responses, an improved understanding of tumor-infiltrating NK cells and their location within tumor contextures is needed to improve the design of effective NK cell-based therapies. In this study, we developed a multiplex immunohistochemistry (mIHC) antibody panel designed to quantitatively interrogate leukocyte lineages, focusing on NK cells and their phenotypes, in two independent breast cancer patient cohorts (n = 26 and n = 30). Owing to the clinical evidence supporting a significant role for NK cells in HER2+ breast cancer in mediating responses to Trastuzumab, we further evaluated HER2- and HER2+ specimens separately. Consistent with literature, we found that CD3+ T cells were the dominant leukocyte subset across breast cancer specimens. In comparison, NK cells, identified by CD56 or NKp46 expression, were scarce in all specimens with low granzyme B expression indicating reduced cytotoxic functionality. Whereas NK cell density and phenotype did not appear to be influenced by HER2 status, spatial analysis revealed distinct NK cells phenotypes regarding their proximity to neoplastic tumor cells that associated with HER2 status. Spatial cellular neighborhood analysis revealed multiple unique neighborhood compositions surrounding NK cells, where NK cells from HER2- tumors were more frequently found proximal to neoplastic tumor cells, whereas NK cells from HER2+ tumors were instead more frequently found proximal to CD3+ T cells. This study establishes the utility of quantitative mIHC to evaluate NK cells at the single-cell spatial proteomics level and illustrates how spatial characteristics of NK cell neighborhoods vary within the context of HER2- and HER2+ breast cancers.

Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing

As our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed significant trust as the first-line diagnostic method. However, conventional brightfield tests have been limited to low-order assays that are visually interrogated. We have developed a hybrid method of brightfield chromogenic multiplexing that overcomes these limitations and enables high-order multiplex assays. However, how compatible high-order brightfield multiplexed images are with advanced analytical algorithms has not been extensively evaluated. In the present study, we address this gap by developing a novel 6-marker prostate cancer assay that targets diverse aspects of the tumor microenvironment such as prostate-specific biomarkers (PSMA and p504s), immune biomarkers (CD8 and PD-L1), a prognostic biomarker (Ki-67), as well as an adjunctive diagnostic biomarker (basal cell cocktail) and apply the assay to 143 differentially graded adenocarcinoma prostate tissues. The tissues were then imaged on our spectroscopic multiplexing imaging platform and mined for proteomic and spatial features that were correlated with cancer presence and disease grade. Extracted features were used to train a UMAP model that differentiated healthy from cancerous tissue with an accuracy of 89% and identified clusters of cells based on cancer grade. For spatial analysis, cell-to-cell distances were calculated for all biomarkers and differences between healthy and adenocarcinoma tissues were studied. We report that p504s positive cells were at least 2× closer to cells expressing PD-L1, CD8, Ki-67, and basal cell in adenocarcinoma tissues relative to the healthy control tissues. These findings offer a powerful insight to understand the fingerprint of the prostate tumor microenvironment and indicate that high-order chromogenic multiplexing is compatible with digital analysis. Thus, the presented chromogenic multiplexing system combines the clinical applicability of brightfield assays with the emerging diagnostic power of high-order multiplexing in a digital pathology friendly format that is well-suited for translational studies to better understand mechanisms of tumor development and growth.

Deciphering the tumor immune microenvironment from a multidimensional omics perspective: insight into next-generation CAR-T cell immunotherapy and beyond

Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.

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

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

The spatial landscape of T cells in the microenvironment of stage III lung adenocarcinoma

This study aimed to provide more information for prognostic stratification for patients through an analysis of the T-cell spatial landscape. It involved analyzing stained tissue sections of 80 patients with stage III lung adenocarcinoma (LUAD) using multiplex immunofluorescence and exploring the spatial landscape of T cells and their relationship with prognosis in the center of the tumor (CT) and invasive margin (IM). In this study, multivariate regression suggested that the relative clustering of CT CD4+ conventional T cell (Tconv) to inducible Treg (iTreg), natural regulatory T cell (nTreg) to Tconv, terminal CD8+ T cell (tCD8) to helper T cell (Th), and IM Treg to tCD8 and the relative dispersion of CT nTreg to iTreg, IM nTreg to nTreg were independent risk factors for DFS. Finally, we constructed a spatial immunological score named the GT score, which had stronger prognostic correlation than IMMUNOSCORE® based on CD3/CD8 cell densities. The spatial layout of T cells in the tumor microenvironment and the proposed GT score can reflect the prognosis of patients with stage III LUAD more effectively than T-cell density. The exploration of the T-cell spatial landscape may suggest potential cell-cell interactions and therapeutic targets and better guide clinical decision-making. © 2024 The Pathological Society of Great Britain and Ireland.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Association between spatial distribution of leukocyte subsets and clinical presentation of head and neck squamous cell carcinoma

Background

Interactions between tumor cells and cells in the microenvironment contribute to tumor development and metastasis. The spatial arrangement of individual cells in relation to each other influences the likelihood of whether and how these cells interact with each other.

Methods

This study investigated the effect of spatial distribution on the function of leukocyte subsets in the microenvironment of human head and neck squamous cell carcinoma (HNSCC) using multiplex immunohistochemistry (IHC). Leukocyte subsets were further classified based on analysis of two previously published HNSCC single-cell RNA datasets and flow cytometry (FC).

Results

IHC revealed distinct distribution patterns of leukocytes differentiated by CD68 and CD163. While CD68hiCD163lo and CD68hiCD163hi cells accumulated near tumor sites, CD68loCD163hi cells were more evenly distributed in the tumor stroma. PD-L1hi and PD-1hi cells accumulated predominantly around tumor sites. High cell density of PD-L1hi CD68hiCD163hi cells or PD-1hi T cells near the tumor site correlated with improved survival. FC and single cell RNA revealed high variability within the CD68/CD163 subsets. CD68hiCD163lo and CD68hiCD163hi cells were predominantly macrophages (MΦ), whereas CD68loCD163hi cells appeared to be predominantly dendritic cells (DCs). Differentiation based on CD64, CD80, CD163, and CD206 revealed that TAM in HNSCC occupy a broad spectrum within the classical M1/M2 polarization. Notably, the MΦ subsets expressed predominantly CD206 and little CD80. The opposite was observed in the DC subsets.

Conclusion

The distribution patterns and their distinct interactions via the PD-L1/PD-1 pathway suggest divergent roles of CD68/CD163 subsets in the HNSCC microenvironment. PD-L1/PD-1 interactions appear to occur primarily between specific cell types close to the tumor site. Whether PD-L1/PD-1 interactions have a positive or negative impact on patient survival appears to depend on both the spatial localization and the entity of the interacting cells. Co-expression of other markers, particularly CD80 and CD206, supports the hypothesis that CD68/CD163 IHC subsets have distinct functions. These results highlight the association between spatial leukocyte distribution patterns and the clinical presentation of HNSCC.

Nanovaccines: An effective therapeutic approach for cancer therapy

Cancer vaccines hold considerable promise for the immunotherapy of solid tumors. Nanomedicine offers several strategies for enhancing vaccine effectiveness. In particular, molecular or (sub) cellular vaccines can be delivered to the target lymphoid tissues and cells by nanocarriers and nanoplatforms to increase the potency and durability of antitumor immunity and minimize negative side effects. Nanovaccines use nanoparticles (NPs) as carriers and/or adjuvants, offering the advantages of optimal nanoscale size, high stability, ample antigen loading, high immunogenicity, tunable antigen presentation, increased retention in lymph nodes, and immunity promotion. To induce antitumor immunity, cancer vaccines rely on tumor antigens, which are administered in the form of entire cells, peptides, nucleic acids, extracellular vesicles (EVs), or cell membrane-encapsulated NPs. Ideal cancer vaccines stimulate both humoral and cellular immunity while overcoming tumor-induced immune suppression. Herein, we review the key properties of nanovaccines for cancer immunotherapy and highlight the recent advances in their development based on the structure and composition of various (including synthetic and semi (biogenic) nanocarriers. Moreover, we discuss tumor cell-derived vaccines (including those based on whole-tumor-cell components, EVs, cell membrane-encapsulated NPs, and hybrid membrane-coated NPs), nanovaccine action mechanisms, and the challenges of immunocancer therapy and their translation to clinical applications.

Reversal of the immunosuppressive tumor microenvironment via platinum-based neoadjuvant chemotherapy in cervical cancer

Background

Immunotherapy favors patients with tumors; however, only 3-26.3% of patients with cervical cancer benefit from single-agent immune checkpoint inhibitors. Combined immunotherapy and chemotherapy has been explored against tumor; however, the combination remains controversial. This study aimed to investigate the tumor immune microenvironment (TIME) and the effects of platinum-based neoadjuvant chemotherapy (NACT) in cervical cancer to identify the clinical value of combining chemotherapy with immunotherapy.

Methods

Multiplex immunohistochemistry (IHC) with 11 markers (cluster of differentiation [CD]3, CD8, CD4, CD11c, CD68, forkhead box P3 [Foxp3], programmed cell death 1 [PD-1], programmed cell death 1 ligand 1 [PD-L1], indoleamine 2,3-dioxygenase [IDO], cyclin-dependent kinase inhibitor 2A [p16], and cytokeratin [CK]) was performed to evaluate TIME from 108 matched pre- and post-NACT cervical cancer samples. The mechanism of antitumor immunity triggered by NACT was explored using RNA sequencing (RNA-seq) from four paired samples and subsequently verified in 41 samples using IHC.

Results

The infiltration rate of the CD8+ T cells in treatment-naive cervical cancer was 0.73%, and those of Foxp3+ regulatory T cells (Tregs) and IDO+ cells were 0.87% and 17.15%, respectively. Moreover, immunoreactive T cells, dendritic cells, and macrophages were more in the stromal than the intratumor region. NACT increased dendritic, CD3+ T, CD8+ T, and CD4+ T cells and decreased Tregs. The aforementioned alterations occurred predominantly in the stromal region and were primarily in responders. Non-responders primarily showed decreased Tregs and no increase in CD8+ T or dendritic cell infiltration. Furthermore, dendritic cells interacted more closely with CD3+ T cells after NACT, an effect primarily observed in responders. RNA-seq data revealed activation of the antigen receptor-mediated signaling pathway and upregulation of major histocompatibility complex (MHC) I and MHC II after chemotherapy, validated using IHC.

Conclusions

NACT can reduce Tregs, and when tumor cells are effectively killed, antigen presentation is enhanced, subsequently activating antitumor immunity finitely. Our study provides the molecular characteristics and theoretical basis for the simultaneous or sequential combination of platinum-based NACT and immunotherapy for cervical cancer.

Spatial Proximity and Relative Distribution of Tumor-Infiltrating Lymphocytes and Macrophages Predict Survival in Melanoma

Tumor microenvironment plays a crucial role in primary cutaneous melanoma (CM) progression. Although the role of tumor-infiltrating lymphocyte (TIL) density has been known for a long time, its spatial distribution and impact with or without tumor-associated macrophages (TAMs) remain controversial. Herein, we investigated spatial proximity between tumor cells and immune cells in 113 primary CM and its correlation with disease-free (DFS) and overall survival (OS). The study cohort included clinical stage II (n = 79) and stage III (n = 34) primary CM with a Breslow thickness of >2 mm (with a median age of 64 years, including 72 men and 41 women). In univariate models, patients with SOX10+ melanoma cells with high proximity to CD8+ TILs in a 20 μm radius showed longer DFS (hazard ratio [HR], 0.58; 95% CI, 0.36-0.93; P = .025) and OS (HR, 0.55; 95% CI, 0.32-0.92; P = .023). Furthermore, at multivariate combined analysis, patients with SOX10+ melanoma cells with high proximity to CD8+ TILs or low proximity to CD163+ TAMs in a 20 μm radius showed an increased OS (aHR, 0.37; 95% CI, 0.14-0.96; P = .04) compared with melanoma patients with low proximity to CD8+ TILs or high proximity to CD163+ TAMs. In a subgroup analysis including 92 patients, a significant negative impact on DFS (aHR, 4.49; 95% CI, 1.73-11.64; P = .002) and OS (aHR, 3.97; 95% CI, 1.37-11.49; P = .01) was observed in sentinel lymph node (SLN)-negative patients with a high proximity of CD163+ TAMs to CD8+ TILs. These findings could help identify high-risk patients in the context of thick melanoma and a negative SLN. Our study suggests the importance of quantifying not only the density of immune cells but also the individual and combined relative spatial distributions of tumor cells and immune cells for clinical outcomes in SLN-negative primary CM patients.

Clinical Proteomics for Solid Organ Tissues

The evaluation of biopsied solid organ tissue has long relied on visual examination using a microscope. Immunohistochemistry is critical in this process, labeling and detecting cell lineage markers and therapeutic targets. However, while the practice of immunohistochemistry has reshaped diagnostic pathology and facilitated improvements in cancer treatment, it has also been subject to pervasive challenges with respect to standardization and reproducibility. Efforts are ongoing to improve immunohistochemistry, but for some applications, the benefit of such initiatives could be impeded by its reliance on monospecific antibody-protein reagents and limited multiplexing capacity. This perspective surveys the relevant challenges facing traditional immunohistochemistry and describes how mass spectrometry, particularly liquid chromatography-tandem mass spectrometry, could help alleviate problems. In particular, targeted mass spectrometry assays could facilitate measurements of individual proteins or analyte panels, using internal standards for more robust quantification and improved interlaboratory reproducibility. Meanwhile, untargeted mass spectrometry, showcased to date clinically in the form of amyloid typing, is inherently multiplexed, facilitating the detection and crude quantification of 100s to 1000s of proteins in a single analysis. Further, data-independent acquisition has yet to be applied in clinical practice, but offers particular strengths that could appeal to clinical users. Finally, we discuss the guidance that is needed to facilitate broader utilization in clinical environments and achieve standardization.

Tunneling nanotubes: The intercellular conduits contributing to cancer pathogenesis and its therapy

Tunneling nanotubes (TNTs) are intercellular conduits which meet the communication needs of non-adjacent cells situated in the same tissue but at distances up to a few hundred microns. TNTs are unique type of membrane protrusion which contain F-actin and freely hover over substratum in the extracellular space to connect the distant cells. TNTs, known to form through actin remodeling mechanisms, are intercellular bridges that connect cytoplasm of two cells, and facilitate the transfer of organelles, molecules, and pathogens among the cells. In tumor microenvironment, TNTs act as communication channel among cancer, normal, and immune cells to facilitate the transfer of calcium waves, mitochondria, lysosomes, and proteins, which in turn contribute to the survival, metastasis, and chemo-resistance in cancer cells. Recently, TNTs were shown to mediate the transfer of nanoparticles, drugs, and viruses between cells, suggesting that TNTs could be exploited as a potential route for delivery of anti-cancer agents and oncolytic viruses to the target cells. The present review discusses the emerging concepts and role of TNTs in the context of chemo- and radio-resistance with implications in the cancer therapy.

Retrospective study of transcriptomic profiling identifies Thai triple-negative breast cancer patients who may benefit from immune checkpoint and PARP inhibitors

Background

Triple-negative breast cancer (TNBC) is a rare and aggressive breast cancer subtype. Unlike the estrogen receptor-positive subtype, whose recurrence risk can be predicted by gene expression-based signature, TNBC is more heterogeneous, with diverse drug sensitivity levels to standard regimens. This study explored the benefit of gene expression-based profiling for classifying the molecular subtypes of Thai TNBC patients.

Methods

The nCounter-based Breast 360 gene expression was used to classify Thai TNBC retrospective cohort subgroups. Their expression profiles were then compared against the previously established TNBC classification system. The differential characteristics of the tumor microenvironment and DNA damage repair signatures across subgroups were also explored.

Results

Thai TNBC cohort could be classified into four main subgroups, corresponding to the LAR, BL-2, and M subtypes based on Lehmann's TNBC classification. The PAM50 gene set classified most samples as basal-like subtypes except for Group 1. Group 1 exhibited similar enrichment of the metabolic and hormone response pathways to the LAR subtype. Group 2 shared pathway activation with the BL-2 subtype. Group 3 showed an increase in the EMT pathway, similar to the M subtype. Group 4 showed no correlation with Lehmann's TNBC. The tumor microenvironment (TME) analysis showed high TME cell abundance with increased expression of immune blockade genes in Group 2. Group 4 exhibited low TME cell abundance and reduced immune blockade gene expressions. We also observed distinct signatures of the DNA double-strand break repair genes in Group 1.

Conclusions

Our study reported unique characteristics between the four TNBC subgroups and showed the potential use of immune checkpoint and PARP inhibitors in subsets of Thai TNBC patients. Our findings warrant further clinical investigation to validate TNBC's sensitivity to these regimens.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Intratumoral Niches of B Cells and Follicular Helper T Cells, and the Absence of Regulatory T Cells, Associate with Longer Survival in Early-Stage Oral Tongue Cancer Patients

In early oral squamous cell carcinoma (OSCC), the occurrence of clusters between CD20 B cells and CD4 T cells in the invasive margin (IM) can be captured by using the CD20 cluster score, and is positively associated with patient survival. However, the exact contribution of different CD4 T cell subsets, as well as B cell subsets toward patient prognosis is largely unknown. To this end, we studied regulatory T cells ((Treg cells) FOXP3 and CD4), T helper-type 1 cells ((Th1 cells) Tbet and CD4), follicular helper T cells ((Tfh cells) Bcl6 and CD4), B cells (CD20), germinal center B cells ((GC B cells) BCL6 and CD20), and follicular dendritic cells ((fDCs) CD21) for their density, location, and interspacing using multiplex in situ immunofluorescence of 75 treatment-naïve, primary OSCC patients. We observed that Treg, Th1-, Tfh-, and GC B cells, but not fDCs, were abundantly present in the stroma as compared with the tumor, and in the IM as compared with in the center of the tumor. Patients with high CD20 cluster scores had a high density of all three CD4 T cell subsets and GC B cells in the stromal IM as compared with patients with low CD20 cluster scores. Notably, enriched abundance of Tfh cells (HR 0.20, p = 0.04), and diminished abundance of Treg cells (HR 0.10, p = 0.03), together with an overall short distance between Tfh and B cells (HR:0.08, p < 0.01), but not between Treg and B cells (HR 0.43, p = 0.28), were significantly associated with overall survival of patients with OSCC. Our study identified the prognostic value of clusters between CD20 B cells and Tfh cells in the stromal IM of OSCC patients, and enabled an improved understanding of the clinical value of a high CD20 cluster score, which requires validation in larger clinical cohorts.

CAR T Cell Therapy in Hematological Malignancies: Implications of the Tumor Microenvironment and Biomarkers on Efficacy and Toxicity

Chimeric antigen receptor (CAR) T cell therapy has ushered in a new era in cancer treatment. Remarkable outcomes have been demonstrated in patients with previously untreatable relapsed/refractory hematological malignancies. However, optimizing efficacy and reducing the risk of toxicities have posed major challenges, limiting the success of this therapy. The tumor microenvironment (TME) plays an important role in CAR T cell therapy’s effectiveness and the risk of toxicities. Increasing research studies have also identified various biomarkers that can predict its effectiveness and risk of toxicities. In this review, we discuss the various aspects of the TME and biomarkers that have been implicated thus far and discuss the role of creating scoring systems that can aid in further refining clinical applications of CAR T cell therapy and establishing a safe and efficacious personalised medicine for individuals.

Spatially resolved immune microenvironmental profiling for follicular thyroid carcinoma with minimal capsular invasion

Spatial profiles of the tumor-immune microenvironment are associated with disease progression and clinicopathological factors in various cancers. Follicular thyroid carcinoma (FTC) is the second most common thyroid cancer, where the presence of capsular invasion or angioinvasion determines the pathological diagnosis; however, little is known about the immune microenvironment profiles associated with the acquisition of invasive potential of FTC. In this study, we focused on FTC with minimal capsular invasion, and the spatially resolved immune microenvironment of FTC was studied in the discovery (n = 13) and validation cohorts (n = 40). CD8⁺ T cells, helper T cells, regulatory T cells, B cells, natural killer cells, tumor-associated macrophages, CD66⁺ granulocytes, mature dendritic cells, and mast cells were quantitatively evaluated in single tissue sections, via a 12-marker multiplex immunohistochemistry and image cytometry. Cell densities and compositions of immune cells were spatially stratified by six tissue regions including tumor center, subcapsular region, capsular invasion, adjacent stroma of capsular invasion, peritumoral stroma, and adjacent normal. Lymphoid cell lineages in the tumor center and subcapsular regions were significantly lower than those in adjacent normal and peritumoral stroma, potentially related to the lymphoid lineage exclusion from the intratumoral regions of FTC. Interestingly, immune cell composition profiles in the capsular invasive front were distinct from those of intratumoral region. The ratios of T cells to CD66b⁺ granulocytes with capsular invasion were significantly higher than those without capsular invasion, suggesting the presence of a unique immune microenvironment at the invasive front between tumor foci and stroma. In addition, tumor cells at the capsular invasive front showed significantly higher expression of tumor programmed cell death ligand 1 (PD-L1) than those at the tumor center. This study revealed spatial immune profiles associated with capsular invasion of FTC, providing new insights into the mechanisms underlying its development and initial invasion.

GaWRDenMap: a quantitative framework to study the local variation in cell-cell interactions in pancreatic disease subtypes

Spatial pattern modelling concepts are being increasingly used in capturing disease heterogeneity. Quantification of heterogeneity in the tumor microenvironment is extremely important in pancreatic ductal adenocarcinoma (PDAC), which has been shown to co-occur with other pancreatic diseases and neoplasms with certain attributes that make visual discrimination difficult. In this paper, we propose the GaWRDenMap framework, that utilizes the concepts of geographically weighted regression (GWR) and a density function-based classification model, and apply it to a cohort of multiplex immunofluorescence images from patients belonging to six different pancreatic diseases. We used an internal cohort of 228 patients comprised of 34 Chronic Pancreatitis (CP), 71 PDAC, 70 intraductal papillary mucinous neoplasm (IPMN), 16 mucinous cystic neoplasm (MCN), 29 pancreatic intraductal neoplasia (PanIN) and 8 IPMN-associated PDAC patients. We utilized GWR to model the relationship between epithelial cells and immune cells on a spatial grid. The GWR model estimates were used to generate density signatures which were used in subsequent pairwise classification models to distinguish between any two pairs of disease groups. Image-level, as well as subject-level analysis, were performed. When applied to this dataset, our classification model showed significant discrimination ability in multiple pairwise comparisons, in comparison to commonly used abundance-based metrics, like the Morisita-Horn index. The model was able to best discriminate between CP and PDAC at both the subject- and image-levels. It was also able to reasonably discriminate between PDAC and IPMN. These results point to a potential difference in the spatial arrangement of epithelial and immune cells between CP, PDAC and IPMN, that could be of high diagnostic significance. Further validation on a more comprehensive dataset would be warranted.

The seen and the unseen: Molecular classification and image based-analysis of gastrointestinal cancers

Gastrointestinal cancers account for 22.5% of cancer related deaths worldwide and represent circa 20% of all cancers. In the last decades, we have witnessed a shift from histology-based to molecular-based classifications using genomic, epigenomic, and transcriptomic data. The molecular based classification revealed new prognostic markers and may aid the therapy selection. Because of the high-costs to perform a molecular classification, in recent years immunohistochemistry-based surrogate classification were developed which permit the stratification of patients, and in parallel multiple groups developed hematoxylin and eosin whole slide image analysis for sub-classifying these entities. Hence, we are witnessing a return to an image-based classification with the purpose to infer hidden information from routine histology images that would permit to detect the patients that respond to specific therapies and would be able to predict their outcome. In this review paper, we will discuss the current histological, molecular, and immunohistochemical classifications of the most common gastrointestinal cancers, gastric adenocarcinoma, and colorectal adenocarcinoma, and will present key aspects for developing a new artificial intelligence aided image-based classification of these malignancies.

Spatial Profiles of Intratumoral PD-1+ Helper T Cells Predict Prognosis in Head and Neck Squamous Cell Carcinoma

Background

Functional interactions between immune cells and neoplastic cells in the tumor immune microenvironment have been actively pursued for both biomarker discovery for patient stratification, as well as therapeutic anti-cancer targets to improve clinical outcomes. Although accumulating evidence indicates that intratumoral infiltration of immune cells has prognostic significance, limited information is available on the spatial infiltration patterns of immune cells within intratumoral regions. This study aimed to understand the intratumoral heterogeneity and spatial distribution of immune cell infiltrates associated with cell phenotypes and prognosis in head and neck squamous cell carcinoma (HNSCC).

Methods

A total of 88 specimens of oropharyngeal squamous cell carcinoma, categorized into discovery (n = 38) and validation cohorts (n = 51), were analyzed for immune contexture by multiplexed immunohistochemistry (IHC) and image cytometry-based quantification. Tissue segmentation was performed according to a mathematical morphological approach using neoplastic cell IHC images to dissect intratumoral regions into tumor cell nests versus intratumoral stroma.

Results

Tissue segmentation revealed heterogeneity in intratumoral T cells, varying from tumor cell nest-polarized to intratumoral stroma-polarized distributions. Leukocyte composition analysis revealed higher ratios of TH1/TH2 in tumor cell nests with higher percentages of helper T cells, B cells, and CD66b+ granulocytes within intratumoral stroma. A discovery and validation approach revealed a high density of programmed death receptor-1 (PD-1)+ helper T cells in tumor cell nests as a negative prognostic factor for short overall survival. CD163+ tumor-associated macrophages (TAM) provided the strongest correlation with PD-1+ helper T cells, and cases with a high density of PD-1+ helper T cells and CD163+ TAM had a significantly shorter overall survival than other cases.

Conclusion

This study reveals the significance of analyzing intratumoral cell nests and reports that an immune microenvironment with a high density of PD-1+ helper T cells in tumoral cell nests is a poor prognostic factor for HNSCC.

Prognostic significance of OX40+ lymphocytes in tumor stroma of surgically resected small-cell lung cancer

OX40 (CD134) is a co-stimulatory molecule mostly expressed on activated T lymphocytes. Previous reports have shown that OX40 can be an immuno-oncology target and a clinical biomarker for cancers of various organs. In this study, we collected formalin-fixed paraffin-embedded tumor samples from 124 patients with small-cell lung cancer (SCLC) who had undergone surgery. We analyzed the expression profiles of OX40 and other relevant molecules, such as CD4, CD8, and Foxp3, in tumor stroma and cancer nest using immunohistochemistry and investigated their association with survival. High infiltration of OX40⁺ lymphocytes (OX40^high) in tumor stroma was positively associated with relapse-free survival (RFS) and overall survival (OS) compared with low infiltration of OX40⁺ lymphocytes (OX40^low) (RFS, median, 26.0 months [95% confidence interval (CI), not reached (NR)–NR] vs 13.2 months [9.1–17.2], p = .024; OS, NR [95% CI, NR–NR] vs 29.8 months [21.3–38.2], p = .049). Multivariate analysis revealed that OX40^high in tumor stroma was an independent indicator of prolonged RFS. Moreover, RFS of patients with OX40^high/CD4^high in tumor stroma was significantly longer than that of patients with OX40^low/CD4^low. The RFS of patients with tumor stroma with OX40^high/CD8^high was significantly longer than that of patients with tumor stroma with OX40^low/CD8^high, OX40^high/CD8^low, or OX40^low/CD8^low. These findings suggest that OX40⁺ lymphocytes in tumor stroma play a complementary role in regulating the relapse of early-stage SCLC. Reinforcing immunity by coordinating the recruitment of OX40⁺ lymphocytes with CD4⁺ and CD8⁺ T cells in tumor stroma may constitute a potential immunotherapeutic strategy for patients with SCLC.

Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence

Immunotherapies play critical roles in cancer treatment. However, given that only a few patients respond to immune checkpoint blockades and other immunotherapeutic strategies, more novel technologies are needed to decipher the complicated interplay between tumor cells and the components of the tumor immune microenvironment (TIME). Tumor immunomics refers to the integrated study of the TIME using immunogenomics, immunoproteomics, immune-bioinformatics, and other multi-omics data reflecting the immune states of tumors, which has relied on the rapid development of next-generation sequencing. High-throughput genomic and transcriptomic data may be utilized for calculating the abundance of immune cells and predicting tumor antigens, referring to immunogenomics. However, as bulk sequencing represents the average characteristics of a heterogeneous cell population, it fails to distinguish distinct cell subtypes. Single-cell-based technologies enable better dissection of the TIME through precise immune cell subpopulation and spatial architecture investigations. In addition, radiomics and digital pathology-based deep learning models largely contribute to research on cancer immunity. These artificial intelligence technologies have performed well in predicting response to immunotherapy, with profound significance in cancer therapy. In this review, we briefly summarize conventional and state-of-the-art technologies in the field of immunogenomics, single-cell and artificial intelligence, and present prospects for future research.

Immune infiltration-related N6-methyladenosine RNA methylation regulators influence the malignancy and prognosis of endometrial cancer

N6-methyladenosine (m6A) RNA methylation is associated with malignant tumor progression and is modulated by various m6A RNA methylation regulator proteins. However, its role in endometrial cancer is unclear. In this work, we analyzed sequence, copy number variation, and clinical data obtained from the TCGA database. Expression was validated using real-time quantitative polymerase chain reaction and immunohistochemistry. Changes in m6A RNA methylation regulators were closely related to the clinicopathological stage and prognosis of endometrial cancer. In particular, ZC3H13, YTHDC1, and METTL14 were identified as potential markers for endometrial cancer diagnosis and prognosis. The TIMER algorithm indicated that immune cell infiltration correlated with changes in ZC3H13, YTHDC1, and METTL14 expression. Meanwhile, ZC3H13 or YTHDC1 knockdown promoted the proliferation and invasion of endometrial cancer cells. Through gene enrichment analysis, we constructed a regulatory network in order to explore the potential molecular mechanism involving ZC3H13, YTHDC1, and METTL14. Virtual screening predicted interactions of potential therapeutic compounds with METTL14 and YTHDC1. These findings advance the understanding of RNA epigenetic modifications in endometrial cancer while identifying m6A regulators associated with immune infiltration, prognosis, and potential treatment strategies.

Methods to Determine and Analyze the Cellular Spatial Distribution Extracted From Multiplex Immunofluorescence Data to Understand the Tumor Microenvironment

Image analysis using multiplex immunofluorescence (mIF) to detect different proteins in a single tissue section has revolutionized immunohistochemical methods in recent years. With mIF, individual cell phenotypes, as well as different cell subpopulations and even rare cell populations, can be identified with extraordinary fidelity according to the expression of antibodies in an mIF panel. This technology therefore has an important role in translational oncology studies and probably will be incorporated in the clinic. The expression of different biomarkers of interest can be examined at the tissue or individual cell level using mIF, providing information about cell phenotypes, distribution of cells, and cell biological processes in tumor samples. At present, the main challenge in spatial analysis is choosing the most appropriate method for extracting meaningful information about cell distribution from mIF images for analysis. Thus, knowing how the spatial interaction between cells in the tumor encodes clinical information is important. Exploratory analysis of the location of the cell phenotypes using point patterns of distribution is used to calculate metrics summarizing the distances at which cells are processed and the interpretation of those distances. Various methods can be used to analyze cellular distribution in an mIF image, and several mathematical functions can be applied to identify the most elemental relationships between the spatial analysis of cells in the image and established patterns of cellular distribution in tumor samples. The aim of this review is to describe the characteristics of mIF image analysis at different levels, including spatial distribution of cell populations and cellular distribution patterns, that can increase understanding of the tumor microenvironment.

Investigating T Cell Immunity in Cancer: Achievements and Prospects

T cells play a key role in tumour surveillance, both identifying and eliminating transformed cells. However, as tumours become established they form their own suppressive microenvironments capable of shutting down T cell function, and allowing tumours to persist and grow. To further understand the tumour microenvironment, including the interplay between different immune cells and their role in anti-tumour immune responses, a number of studies from mouse models to clinical trials have been performed. In this review, we examine mechanisms utilized by tumour cells to reduce their visibility to CD8⁺ Cytotoxic T lymphocytes (CTL), as well as therapeutic strategies trialled to overcome these tumour-evasion mechanisms. Next, we summarize recent advances in approaches to enhance CAR T cell activity and persistence over the past 10 years, including bispecific CAR T cell design and early evidence of efficacy. Lastly, we examine mechanisms of T cell infiltration and tumour regression, and discuss the strengths and weaknesses of different strategies to investigate T cell function in murine tumour models.

The role of tumor heterogeneity in immune-tumor interactions

The development of cancer stems from genetic instability and changes in genomic sequences, and hence, the heterogeneity exhibited by tumors is integral to the nature of cancer itself. Tumor heterogeneity can be further altered by factors that are not cancer cell intrinsic, i.e., by the microenvironment, including the patient's immune responses to tumors and administered therapies (immunotherapies, chemotherapies, and/or radiation therapies). The focus of this review is the impact of tumor heterogeneity on the interactions between immune cells and the tumor, taking into account that heterogeneity can exist at several levels. These levels include heterogeneity within an individual tumor, within an individual patient (particularly between the primary tumor and metastatic lesions), among the subtypes of a specific type of cancer, or within cancers that originate from different tissues. Because of the potential for immunity (either the natural immune system or via immunotherapeutics) to halt the progression of cancer, major clinical significance exists in understanding the impact of tumor heterogeneity on the associations between immune cells and tumor cells. Increased knowledge of why, whether, and how immune-tumor interactions occur provides the means to guide these interactions and improve outcomes for patients.

Prognostic significance of spatial immune profiles in human solid cancers

Immune-based tumor characteristics in the context of tumor heterogeneity are associated with suppression as well as promotion of cancer progression in various tumor types. As immunity typically functions based on intercellular contacts and short-distance cytokine communications, the location and spatial relationships of the tumor immune microenvironment can provide a framework to understand the biology and potential predictive biomarkers related to disease outcomes. Immune spatial analysis is a newly emerging form of cancer research based on recent methodological advances in in situ single-cell analysis, where cell-cell interaction and the tissue architecture can be analyzed in relation to phenotyping the tumor immune heterogeneity. Spatial characteristics of tumors can be stratified into the tissue architecture level and the single-cell level. At the tissue architecture level, the prognostic significance of the density of immune cell lineages, particularly T cells, is leveraged by understanding longitudinal changes in cell distribution in the tissue architecture such as intra-tumoral and peri-tumoral regions, and invasive margins. At the single-cell level, the proximity of the tumor to the immune cells correlates with disease aggressiveness and therapeutic resistance, providing evidence to understand biological interactions and characteristics of the tumor immune microenvironment. In this review, we summarize recent findings regarding spatial information of the tumor immune microenvironment and review advances and challenges in spatial single-cell analysis toward developing tissue-based biomarkers rooted in the immune spatial landscape.