The immune contexture in cancer prognosis and treatment

Oncolytic vaccinia virus harboring CLEC2A gene enhances viral replication and antitumor efficacy

In the field of innovative cancer treatment strategies, oncolytic vaccinia virus (VV)es have gained traction as promising vectors. In the current study, we inserted the human C-type lectin domain family 2 member A (CLEC2A) gene into VV, creating a replicating therapeutic, oncoVV-CLEC2A. The findings reveal that oncoVV-CLEC2A effectively suppresses colorectal proliferation of mouse xenografts and a range of human cancer cell lines by augmenting viral reproduction capabilities, including the lung cancer H460 cell line, colorectal cancer cell lines (HCT116 and SW620), and hepatocellular carcinoma HuH-7 cell line. Moreover, it is evident that oncoVV-CLEC2A can induce antitumor immunity by boosting cytokine production but not antivirus response, and enhancing calreticulin expression. Further investigation indicates that oncoVV-CLEC2A can enhance antitumor capabilities by activating natural killer cells to produce interferon-γ and induce M1-like macrophage polarization. These findings shed light on the antitumor mechanisms of oncoVV-CLEC2A, provide a theoretical basis for oncolytic therapies, and lay the groundwork for novel strategies for modifying VVs.

Clinical landscape of macrophage-reprogramming cancer immunotherapies

Tumour-associated macrophages (TAMs) sustain a tumour-supporting and immunosuppressive milieu and therefore aggravate cancer prognosis. To modify TAM behaviour and unlock their anti-tumoural potential, novel TAM-reprogramming immunotherapies are being developed at an accelerating rate. At the same time, scientific discoveries have highlighted more sophisticated TAM phenotypes with complex biological functions and contradictory prognostic associations. To understand the evolving clinical landscape, we reviewed current and past clinically evaluated TAM-reprogramming cancer therapeutics and summarised almost 200 TAM-reprogramming agents investigated in more than 700 clinical trials. Observable overall trends include a high frequency of overlapping strategies against the same therapeutic targets, development of more complex strategies to improve previously ineffective approaches and reliance on combinatory strategies for efficacy. However, strong anti-tumour efficacy is uncommon, which encourages re-directing efforts on identifying biomarkers for eligible patient populations and comparing similar treatments earlier. Future endeavours will benefit from considering the shortcomings of past treatment strategies and accommodating the emerging complexity of TAM biology.

Potential Role of Lymphocyte CD44 in Determining Treatment Selection Between Stereotactic Body Radiation Therapy and Surgery for Early-Stage Non-Small Cell Lung Cancer

PURPOSE

Stereotactic body radiation therapy (SBRT) versus surgery for operable early-stage non-small cell lung cancer (ES-NSCLC) remains highly debated. Herein, we used spatial proteomics to identify whether any molecular biomarker(s) associate with the efficacy of either modality, in efforts to optimize treatment selection between surgery and SBRT for this population.

METHODS AND MATERIALS

We evaluated biopsy tissue samples from 44 patients with ES-NSCLC treated with first-line SBRT (cohort 1) by GeoMx Digital Spatial Profiling (DSP) with a panel of 70 proteins in 5 spatial molecular compartments: tumor (panCK+), leukocyte (CD45+), lymphocyte (CD3+), macrophage (CD68+), and stroma (α-SMA+). To validate the findings in cohort 1, biopsy samples from 52 patients with ES-NSCLC who received SBRT (cohort 2) and 62 patients with ES-NSCLC who underwent surgery (cohort 3) were collected and analyzed by multiplex immunofluorescence (mIF).

RESULTS

In cohort 1, higher CD44 expression in the lymphocyte compartment was associated with poorer recurrence-free survival (RFS) (DSP: P < .001; mIF: P < .001) and higher recurrence rate (DSP: P = .001; mIF: P = .004). mIF data from cohort 2 validated these findings (P < .05 for all). From cohort 3, higher lymphocyte CD44 predicted higher RFS after surgery (P = .003). Intermodality comparisons demonstrated that SBRT was associated with significantly higher RFS over surgery in CD44-low patients (P < .001), but surgery was superior to SBRT in CD44-high cases (P = .016).

CONCLUSIONS

Lymphocyte CD44 may not only be a predictor of SBRT efficacy in this population but also an important biomarker (pending validation by large prospective data) that could better sharpen selection for SBRT versus surgery in ES-NSCLC.

Emerging role of immunogenic cell death in cancer immunotherapy: Advancing next-generation CAR-T cell immunotherapy by combination

Immunogenic cell death (ICD) is a stress-driven form of regulated cell death (RCD) in which dying tumor cells' specific signaling pathways are activated to release damage-associated molecular patterns (DAMPs), leading to the robust anti-tumor immune response as well as a reversal of the tumor immune microenvironment from "cold" to "hot". Chimeric antigen receptor (CAR)-T cell therapy, as a landmark in anti-tumor immunotherapy, plays a formidable role in hematologic malignancies but falls short in solid tumors. The Gordian knot of CAR-T cells for solid tumors includes but is not limited to, tumor antigen heterogeneity or absence, physical and immune barriers of tumors. The combination of ICD induction therapy and CAR-T cell immunotherapy is expected to promote the intensive use of CAR-T cell in solid tumors. In this review, we summarize the characteristics of ICD, stress-responsive mechanism, and the synergistic effect of various ICD-based therapies with CAR-T cells to effectively improve anti-tumor capacity.

Virtual multiplexed immunofluorescence staining from non-antibody-stained fluorescence imaging for gastric cancer prognosis

BACKGROUND

Multiplexed immunofluorescence (mIF) staining, such as CODEX and MIBI, holds significant clinical value for various fields, such as disease diagnosis, biological research, and drug development. However, these techniques are often hindered by high time and cost requirements.

METHODS

Here we present a Multimodal-Attention-based virtual mIF Staining (MAS) system that utilises a deep learning model to extract potential antibody-related features from dual-modal non-antibody-stained fluorescence imaging, specifically autofluorescence (AF) and DAPI imaging. The MAS system simultaneously generates predictions of mIF with multiple survival-associated biomarkers in gastric cancer using self- and multi-attention learning mechanisms.

FINDINGS

Experimental results with 180 pathological slides from 94 patients with gastric cancer demonstrate the efficiency and consistent performance of the MAS system in both cancer and noncancer gastric tissues. Furthermore, we showcase the prognostic accuracy of the virtual mIF images of seven gastric cancer related biomarkers, including CD3, CD20, FOXP3, PD1, CD8, CD163, and PD-L1, which is comparable to those obtained from the standard mIF staining.

INTERPRETATION

The MAS system rapidly generates reliable multiplexed staining, greatly reducing the cost of mIF and improving clinical workflow.

FUNDING

Stanford 2022 HAI Seed Grant; National Institutes of Health 1R01CA256890.

Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion

The cellular and molecular heterogeneity of tumors is a major obstacle to cancer immunotherapy. Here, we use a systems biology approach to derive a signature of the main sources of heterogeneity in the tumor microenvironment (TME) from lung cancer transcriptomics. We demonstrate that this signature, which we called iHet, is conserved in different cancers and associated with antitumor immunity. Through analysis of single-cell and spatial transcriptomics data, we trace back the cellular origin of the variability explaining the iHet signature. Finally, we demonstrate that iHet has predictive value for cancer immunotherapy, which can be further improved by disentangling three major determinants of anticancer immune responses: activity of immune cells, immune infiltration or exclusion, and cancer-cell foreignness. This work shows how transcriptomics data can be integrated to derive a holistic representation of the phenotypic heterogeneity of the TME and to predict its unfolding and fate during immunotherapy with immune checkpoint blockers.

Serine Depletion Promotes Antitumor Immunity by Activating Mitochondrial DNA-Mediated cGAS-STING Signaling

Serine is critical for supporting cancer metabolism, and depriving malignant cells of this nonessential amino acid exerts antineoplastic effects, in large part, through disrupting metabolic pathways. Given the intricate relationship between cancer metabolism and the immune system, the metabolic defects imposed by serine deprivation might impact tumor-targeting immunity. In this study, we demonstrated that restricting endogenous and exogenous sources of serine in colorectal cancer cells results in mitochondrial dysfunction, leading to mitochondrial DNA (mtDNA) accumulation in the cytosol and consequent cGAS-STING1-driven type I IFN secretion. Depleting mtDNA or blocking its release attenuated cGAS-STING1 activation during serine deprivation. In vivo studies revealed that serine deprivation limits tumor growth, accompanied by enhanced type I IFN signaling and intratumoral infiltration of immune effector cells. Notably, the tumor-suppressive and immune-enhancing effects of serine restriction were impaired by T-cell depletion and IFN receptor blockade. Moreover, disrupting cGAS-STING1 signaling in colorectal cancer cells limited the immunostimulatory and tumor-suppressive effects of serine deprivation. Lastly, serine depletion increased the sensitivity of tumors to an immune checkpoint inhibitor targeting PD-1. Taken together, these findings reveal a role for serine as a suppressor of antitumor immunity, suggesting that serine deprivation may be employed to enhance tumor immunogenicity and improve responsiveness to immune checkpoint inhibitors. Significance: Depriving cancer cells of serine provokes mitochondrial perturbations that induce cytosolic mitochondrial DNA accumulation and subsequent activation of cGAS-STING signaling, stimulating tumor-targeting immune responses that can be enhanced with PD-1 targeted therapy. See related commentary by Borges and Garg, p. 2569.

Tertiary lymphoid structures and their therapeutic implications in cancer

Tertiary lymphoid structures (TLSs) are ectopic lymphoid aggregates formed by the structured accumulation of immune cells such as B cells and T cells in non-lymphoid tissues induced by infection, inflammation, and tumors. They play a crucial role in the immune response, particularly in association with tumor development, where they primarily exert anti-tumor immune functions during tumorigenesis. Current research suggests that TLSs inhibit tumor growth by facilitating immune cell infiltration and are correlated with favorable prognosis in various solid tumors, serving as an indicator of immunotherapy effectiveness to some extent. Therefore, TLSs hold great promise as a valuable biomarker. Most importantly, immunotherapies aimed to prompting TLSs formation are anticipated to be potent adjuncts to current cancer treatment. This review focuses on the formation process of TLSs and their potential applications in cancer therapy.

Radio-miRs: a comprehensive view of radioresistance-related microRNAs

Radiotherapy is a key treatment option for a wide variety of human tumors, employed either alone or alongside with other therapeutic interventions. Radiotherapy uses high-energy particles to destroy tumor cells, blocking their ability to divide and proliferate. The effectiveness of radiotherapy is due to genetic and epigenetic factors that determine how tumor cells respond to ionizing radiation. These factors contribute to the establishment of resistance to radiotherapy, which increases the risk of poor clinical prognosis of patients. Although the mechanisms by which tumor cells induce radioresistance are unclear, evidence points out several contributing factors including the overexpression of DNA repair systems, increased levels of reactive oxygen species, alterations in the tumor microenvironment, and enrichment of cancer stem cell populations. In this context, dysregulation of microRNAs or miRNAs, critical regulators of gene expression, may influence how tumors respond to radiation. There is increasing evidence that miRNAs may act as sensitizers or enhancers of radioresistance, regulating key processes such as the DNA damage response and the cell death signaling pathway. Furthermore, expression and activity of miRNAs have shown informative value in overcoming radiotherapy and long-term radiotoxicity, revealing their potential as biomarkers. In this review, we will discuss the molecular mechanisms associated with the response to radiotherapy and highlight the central role of miRNAs in regulating the molecular mechanisms responsible for cellular radioresistance. We will also review radio-miRs, radiotherapy-related miRNAs, either as sensitizers or enhancers of radioresistance that hold promise as biomarkers or pharmacological targets to sensitize radioresistant cells.

The impact of the expression level of growth differentiation factor 15 in tumor tissue on the response to immunotherapy in non-small cell lung cancer

BACKGROUND

Growth differentiation factor-15 (GDF-15), a member of the TGF-β superfamily, is overexpressed in various cancers and facilitates immune evasion by inhibiting T-cell activation. GDFATHER-TRIAL's phase 2a results demonstrated promising outcomes when combining the GDF-15 neutralizing antibody visugromab (CTL002) with nivolumab, enhancing the response to immunotherapy. This study evaluated the prognostic significance of GDF-15 expression in non-small cell lung cancer (NSCLC) tumor tissues in terms of immunotherapy response.

METHODS

This retrospective study included 50 patients with metastatic NSCLC treated with nivolumab at Gazi University Hospital between January 2021 and July 2023. GDF-15 expression was evaluated using immunochemistry staining and categorized based on the intensity of cytoplasmic or membranous staining. Samples were divided into a low expression group (scores 0 and 1) and a high expression group (scores 2 and 3). The primary outcomes were progression-free survival (PFS) and overall survival (OS), which were analyzed using Kaplan‒Meier and Cox proportional hazards models. Objective response rates were assessed in secondary outcomes.

RESULTS

Of the 50 patients, 43 were men (86%), with a median age of 63.9 years. Half of the patients exhibited low GDF-15 expression. High GDF-15 expression correlated with shorter PFS and OS. The median PFS was 7.8 months for the low-expression group versus 4.4 months for the high-expression group (HR, 0.41; 95% CI, 0.20-0.83; p = 0.013). The median OS was 18.1 months for the low-expression group compared to 11.8 months for the high-expression group (HR, 0.36; 95% CI, 0.16-0.78; p = 0.007). The objective response rate was significantly greater in the low GDF-15 group (52%) than in the high GDF-15 group (24%) (p = 0.040).

CONCLUSION

Elevated GDF-15 expression in NSCLC tumor tissues is associated with poorer response to nivolumab, suggesting that GDF-15 is a potential prognostic biomarker for immunotherapy efficacy. These findings warrant further validation through prospective studies to optimize treatment strategies for NSCLC patients.

Connectivity Network Feature Sharing in Single-Cell RNA Sequencing Data Identifies Rare Cells

Single-cell RNA sequencing is a valuable technique for identifying diverse cell subtypes. A key challenge in this process is that the detection of rare cells is often missed by conventional methods due to low abundance and subtle features of these cells. To overcome this, we developed SCLCNF (Local Connectivity Network Feature Sharing in Single-Cell RNA sequencing), a novel approach that identifies rare cells by analyzing features uniquely expressed in these cells. SCLCNF creates a cellular connectivity network, considering how each cell relates to its neighbors. This network helps to pinpoint coexpression patterns unique to rare cells, utilizing a rarity score to confirm their presence. Our method performs better in detecting rare cells than existing techniques, offering enhanced robustness. It has proven to be effective in human gastrula data sets for accurately pinpointing rare cells, and in sepsis data sets where it uncovers previously unidentified rare cell populations.

Three-Year Analysis of Adjuvant Therapy in Postoperative Melanoma including Acral and Mucosal Subtypes

BACKGROUND

Adjuvant therapy has improved the clinical prognosis for postoperative melanoma patients. However, the long-term efficacy of this therapy on the melanoma acral and mucosal subtypes has not been fully evaluated in previous trials. This study assessed the 3-year recurrence-free survival and overall survival of patients with melanoma, including the acral and mucosal subtypes, treated with anti-PD-1 antibody (Ab) or with the combination of the BRAF and MEK inhibitors dabrafenib and trametinib.

METHODS

We retrospectively analyzed both the 3-year time to relapse (TTR) and overall survival (OS) of 120 patients treated with anti-PD-1 antibody (Ab), or with the combination of dabrafenib and trametinib.

RESULTS

The overall median TTR was 18.4 months, with a range of 0.69 to 36 months. The 3-year TTR of the acral and mucosal types was 28.1% and 38.5%, respectively. Baseline tumor thickness (TT) and acral type were associated with the TTR in subgroup analysis. Moreover, we classified 104 acral and non-acral cutaneous patients into the anti-PD-1 Abs or dabrafenib plus trametinib combined therapies cohort in multiple analyses. The acral subtype and TT were detected as important prognostic factors. In the 3-year OS, only tumor ulceration was associated with the OS in both univariate and multiple analyses. There was no significant difference in baseline or treatment-related factors of the mucosal type (p > 0.05).

CONCLUSION

This study suggests that adjuvant therapy is more effective with non-acral cutaneous melanoma than either the acral or mucosal types at the 3-year TTR endpoint.

Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon Cancer

Tumor-associated macrophages are transcriptionally heterogeneous, but the spatial distribution and cell interactions that shape macrophage tissue roles remain poorly characterized. Here, we spatially resolve five distinct human macrophage populations in normal and malignant human breast and colon tissue and reveal their cellular associations. This spatial map reveals that distinct macrophage populations reside in spatially segregated micro-environmental niches with conserved cellular compositions that are repeated across healthy and diseased tissue. We show that IL4I1+ macrophages phagocytose dying cells in areas with high cell turnover and predict good outcome in colon cancer. In contrast, SPP1+ macrophages are enriched in hypoxic and necrotic tumor regions and portend worse outcome in colon cancer. A subset of FOLR2+ macrophages is embedded in plasma cell niches. NLRP3+ macrophages co-localize with neutrophils and activate an inflammasome in tumors. Our findings indicate that a limited number of unique human macrophage niches function as fundamental building blocks in tissue. Significance: This work broadens our understanding of the distinct roles different macrophage populations may exert on cancer growth and reveals potential predictive markers and macrophage population-specific therapy targets.

Tertiary lymphoid structures as a potential prognostic biomarker for combined hepatocellular-cholangiocarcinoma

BACKGROUND

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA), as a rare primary hepatic tumor, is challenging to accurately assess in terms of the clinical outcomes and prognostic risk factors in patients. This study aimed to clarify the function of tertiary lymphoid structure (TLS) status in predicting the outcome of cHCC-CCA and to preliminarily explore the possible mechanism of TLS formation.

METHODS

The TLSs, with different spatial distributions and densities, of 137 cHCC-CCA were quantified, and their association with prognosis was assessed by Cox regression and Kaplan-Meier analyses. We further validated TLS possible efficacy in predicting immunotherapy responsiveness in two cHCC-CCA case reports. TLS composition and its relationship to CXCL12 expression were analysed by fluorescent multiplex immunohistochemistry.

RESULTS

A high intratumoural TLS score was correlated with prolonged survival, whereas a high TLS density in adjacent tissue indicated a worse prognosis in cHCC-CCA. Mature TLSs were related to favorable outcomes and showed more CD8 + T cells infiltrating tumor tissues. We further divided the cHCC-CCA patients into four immune grades by combining the peri-TLS and intra-TLS, and these grades were an independent prognostic factor. In addition, our reported cases suggested a potential value of TLS in predicting immunotherapy response in cHCC-CCA patients. Our findings suggested that CXCL12 expression in cHCC-CCA tissue was significantly correlated with TLS presence.

CONCLUSION

The spatial distribution and density of TLSs revealing the characteristics of the cHCC-CCA immune microenvironment, significantly correlated with prognosis and provided a potential immunotherapy response biomarker for cHCC-CCA.

Non-neoplastic cells as prognostic biomarkers in diffuse large B-cell lymphoma: A system review and meta-analysis

The microenvironment of diffuse large B-cell lymphoma (DLBCL) is composed of various components, including immune cells and immune checkpoints, some of which have been correlated with the prognosis of DLBCL, but their results remain controversial. Therefore, we conducted a systematic review and meta-analysis to investigate the association between the microenvironment and prognosis in DLBCL. We searched PubMed, Web of Science, and EMBASE for relevant articles between 2001 and 2022. Twenty-five studies involving 4495 patients with DLBCL were included in the analysis. This meta-analysis confirmed that high densities of Foxp3+Tregs and PD-1+T cells are good indicators for overall survival (OS) in DLBCL, while high densities of programmed cell death protein ligand1(PD-L1)-positive expression cells and T-cell immunoglobulin-and mucin domain-3-containing molecule 3 (TIM-3)-positive expression tumor-infiltrating cells (TILs) play a contrary role in OS. Additionally, higher numbers of T-cell intracytoplasmic antigen-1(TIA-1)-positive expression T cells imply better OS and progression-free survival (PFS), while high numbers of lymphocyte activation gene(LAG)-positive expression TILs predict bad OS and PFS. Various non-tumoral cells in the microenvironment play important roles in the prognosis of DLBCL.

Cancer organoids 2.0: modelling the complexity of the tumour immune microenvironment

The development of neoplasia involves a complex and continuous interplay between malignantly transformed cells and the tumour microenvironment (TME). Cancer immunotherapies targeting the immune TME have been increasingly validated in clinical trials but response rates vary substantially between tumour histologies and are often transient, idiosyncratic and confounded by resistance. Faithful experimental models of the patient-specific tumour immune microenvironment, capable of recapitulating tumour biology and immunotherapy effects, would greatly improve patient selection, target identification and definition of resistance mechanisms for immuno-oncology therapeutics. In this Review, we discuss currently available and rapidly evolving 3D tumour organoid models that capture important immune features of the TME. We highlight diverse opportunities for organoid-based investigations of tumour immunity, drug development and precision medicine.

PD-L1+ macrophage and tumor cell abundance and proximity to T cells in the pretreatment large B-cell lymphoma microenvironment impact CD19 CAR-T cell immunotherapy efficacy

CD19-targeted chimeric antigen receptor T-cell (CAR-T) immunotherapy has transformed the management of relapsed/refractory large B-cell lymphoma (LBCL), yet durable remissions are observed in less than half of treated patients. The tumor microenvironment (TME) is a key and understudied factor impacting CD19 CAR-T therapy outcomes. Using NanoString nCounter transcriptome profiling (n = 24) and multiplex immunohistochemistry (mIHC, n = 15), we studied the TME in pretreatment biopsies from patients with LBCL undergoing CD19 CAR-T therapy. Patients who achieved complete response (CR) after CAR-T therapy demonstrated higher expression of genes associated with T-cell trafficking and function, whereas those who did not achieve CR had higher expression of genes associated with macrophages and T-cell dysfunction. Distinct patterns of immune infiltration and fibrosis in the TME were associated with CAR-T therapy outcomes, and these findings were corroborated using artificial intelligence-assisted image analyses. Patients who achieved CR had a lower proportion of the biopsy occupied by an interspersed immune infiltrate and a higher proportion of hypocellular/fibrotic regions. Furthermore, mIHC revealed lower density of CD4+ T cells and higher densities of both macrophages and tumor cells expressing PD-L1 in non-CR patients. Spatial analysis revealed that PD-1+ T cells were in close proximity to PD-L1+ macrophages or PD-L1+ tumor cells in patients who did not compared to those who did achieve CR after CAR-T therapy. These findings suggest that morphologic patterns in the TME and engagement of the PD-1/PD-L1 axis in pretreatment biopsies may impact CD19 CAR-T immunotherapy response in patients with LBCL.

Immune-based Therapies for Penile Cancer

This article reviews penile squamous cell carcinoma (PSCC), a rare genitourinary cancer that has been increasing in prevalence. It discusses emerging therapies, focusing on immunotherapy, vaccine therapy, and cell-based treatments, especially in the context of human papillomavirus-related PSCC. Factors influencing these therapies are discussed. These include the immune microenvironment, programmed cell death ligand-1 expression, and tumor immune cell infiltration. This article also highlights immune checkpoint inhibitors and related clinical trials. This review supports the use of personalized medicine in treating PSCC. It stresses the need for collaborative studies and data sharing to create specific treatment plans and achieve better outcomes.

Advancing bladder cancer management: development of a prognostic model and personalized therapy

Background

Bladder cancer (BLCA) was recognized as a significant public health challenge due to its high incidence and mortality rates. The influence of molecular subtypes on treatment outcomes was well-acknowledged, necessitating further exploration of their characterization and application. This study was aimed at enhancing the understanding of BLCA by mapping its molecular heterogeneity and developing a robust prognostic model using single-cell and bulk RNA sequencing data. Additionally, immunological characteristics and personalized treatment strategies were investigated through the risk score.

Methods

Single-cell RNA sequencing (scRNA-seq) data from GSE135337 and bulk RNA-seq data from several sources, including GSE13507, GSE31684, GSE32894, GSE69795, and TCGA-BLCA, were utilized. Molecular subtypes, particularly the basal-squamous (Ba/Sq) subtype associated with poor prognosis, were identified. A prognostic model was constructed using LASSO and Cox regression analyses focused on genes linked with the Ba/Sq subtype. this model was validated across internal and external datasets to ensure predictive accuracy. High- and low-risk groups based on the risk score derived from TCGA-BLCA data were analyzed to examine their immune-related molecular profiles and treatment responses.

Results

Six molecular subtypes were identified, with the Ba/Sq subtype being consistently associated with poor prognosis. The prognostic model, based on basal-squamous subtype-related genes (BSSRGs), was shown to have strong predictive performance across diverse clinical settings with AUC values at 1, 3, and 5 years indicating robust predictability in training, testing, and entire datasets. Analysis of the different risk groups revealed distinct immune infiltration and microenvironments. Generally higher tumor mutation burden (TMB) scores and lower tumor immune dysfunction and exclusion (TIDE) scores were exhibited by the low-risk group, suggesting varied potentials for systemic drug response between the groups. Finally, significant differences in potential systemic drug response rates were also observed between risk groups.

Conclusions

The study introduced and validated a new prognostic model for BLCA based on BSSRGs, which was proven effective in prognosis prediction. The potential for personalized therapy, optimized by patient stratification and immune profiling, was highlighted by our risk score, aiming to improve treatment efficacy. This approach was promised to offer significant advancements in managing BLCA, tailoring treatments based on detailed molecular and immunological insights.

Mismatch repair-proficient tumor footprints in the sands of immune desert: mechanistic constraints and precision platforms

Mismatch repair proficient (MMRp) tumors of colorectal origin are one of the prevalent yet unpredictable clinical challenges. Despite earnest efforts, optimal treatment modalities have yet to emerge for this class. The poor prognosis and limited actionability of MMRp are ascribed to a low neoantigen burden and a desert-like microenvironment. This review focuses on the critical roadblocks orchestrated by an immune evasive mechanistic milieu in the context of MMRp. The low density of effector immune cells, their weak spatiotemporal underpinnings, and the high-handedness of the IL-17-TGF-β signaling are intertwined and present formidable challenges for the existing therapies. Microbiome niche decorated by Fusobacterium nucleatum alters the metabolic program to maintain an immunosuppressive state. We also highlight the evolving strategies to repolarize and reinvigorate this microenvironment. Reconstruction of anti-tumor chemokine signaling, rational drug combinations eliciting T cell activation, and reprograming the maladapted microbiome are exciting developments in this direction. Alternative vulnerability of other DNA damage repair pathways is gaining momentum. Integration of liquid biopsy and ex vivo functional platforms provide precision oncology insights. We illustrated the perspectives and changing landscape of MMRp-CRC. The emerging opportunities discussed in this review can turn the tide in favor of fighting the treatment dilemma for this elusive cancer.

STAC3 as a poor prognostic biomarker in renal clear cell carcinoma: relationship with immune infiltration

Calcium ions (Ca2+) are crucial in tumorigenesis and progression, with their elevated levels indicating a negative prognosis in Kidney Renal Clear Cell Carcinoma (KIRC). The influence of genes regulating calcium ions on the survival outcomes of KIRC patients and their interaction with the tumor's immune microenvironment is yet to be fully understood. This study analyzed gene expression data from KIRC tumor and adjacent non-tumor tissues using the TCGA-KIRC dataset to pinpoint genes that are differentially expressed in KIRC. Intersection of these genes with those regulating calcium ions highlighted specific calcium ion-regulating genes that exhibit differential expression in KIRC. Subsequently, prognostic risk models were developed using univariate Cox and LASSO-Cox regression analyses to verify their diagnostic precision. Additionally, the study investigated the correlation between tumor immunity and KIRC patient outcomes, assessing the contribution of STAC3 genes to tumor immunity. Further exploration entailed SSGASE, single-cell analysis, pseudotime analysis and both in vivo and in vitro experiments to evaluate STAC3's role in tumor immunity and progression. Notably, STAC3 was significantly overexpressed in tumor specimens and positively correlated with the degree of malignancy of KIRC, affecting patients' prognosis. Elevated STAC3 expression correlated with enhanced immune infiltration in KIRC tumors. Furthermore, silencing STAC3 curtailed KIRC cell proliferation, migration, invasion, and stemness properties. Experimental models in mice confirmed that STAC3 knockdown led to a reduction in tumor growth. Elevated STAC3 expression is intricately linked with immune infiltration in KIRC tumors, as well as with the aggressive biological behaviors of tumor cells, including their proliferation, migration, and invasion. Targeting STAC3 presents a promising strategy to augment the efficacy of current therapeutic approaches and to better the survival outcomes of patients with KIRC.

Ferroptosis crosstalk in anti-tumor immunotherapy: molecular mechanisms, tumor microenvironment, application prospects

Immunotherapies for cancer, specifically immune checkpoint inhibition (ICI), have shown potential in reactivating the body's immune response against tumors. However, there are challenges to overcome in addressing drug resistance and improving the effectiveness of these treatments. Recent research has highlighted the relationship between ferroptosis and the immune system within immune cells and the tumor microenvironment (TME), suggesting that combining targeted ferroptosis with immunotherapy could enhance anti-tumor effects. This review explores the potential of using immunotherapy to target ferroptosis either alone or in conjunction with other therapies like immune checkpoint blockade (ICB) therapy, radiotherapy, and nanomedicine synergistic treatments. It also delves into the roles of different immune cell types in promoting anti-tumor immune responses through ferroptosis. Together, these findings provide a comprehensive understanding of synergistic immunotherapy focused on ferroptosis and offer innovative strategies for cancer treatment.

Expression of immune checkpoint molecules TIGIT and TIM-3 by tumor-infiltrating lymphocytes predicts poor outcome in sinonasal mucosal melanoma

BACKGROUND

Sinonasal mucosal melanoma (SNMM) is a rare but aggressive tumor with a poor prognosis. The co-inhibitory receptors T cell immunoglobulin and mucinodomain containing-3 (TIM-3), lymphocyte activation gene-3 (LAG-3) and T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) are promising new targets in anti-cancer immunotherapy. The expression profiles of these immune checkpoint molecules (ICMs) and potential prognostic implications have not been characterized in SNMM yet.

METHODS

Immunohistochemical staining for TIGIT, LAG-3 and TIM-3 was performed on tumor tissue samples from 27 patients with primary SNMM. Associations between ICM expression and demographic parameters, AJCC tumor stage, overall survival, and recurrence-free survival were retrospectively analyzed.

RESULTS

SNMM patients with low numbers of TIGIT+ and TIM-3+ tumor infiltrating lymphocytes (TILs) in the primary tumor survived significantly longer than patients with a high degree of TIGIT+ and TIM-3+ TILs. High infiltration with TIM-3+ or TIGIT+ lymphocytes was associated with the higher T4 stage and decreased 5-year survival.

CONCLUSION

We identified high densities of TIM-3+ and TIGIT+ TILs as strong negative prognostic biomarkers in SNMM. This suggests that TIM-3 and TIGIT contribute to immunosuppression in SNMM and provides a rationale for novel treatment strategies based on this next generation of immune checkpoint inhibitors. Prospective studies with larger case numbers are warranted to confirm our findings and their implications for immunotherapy.

The role of CD8 PET imaging in guiding cancer immunotherapy

Currently, immunotherapy is being widely used for treating cancers. However, the significant heterogeneity in patient responses is a major challenge for its successful application. CD8-positive T cells (CD8+ T cells) play a critical role in immunotherapy. Both their infiltration and functional status in tumors contribute to treatment outcomes. Therefore, accurate monitoring of CD8+ T cells, a potential biomarker, may improve therapeutic strategy. Positron emission tomography (PET) is an optimal option which can provide molecular imaging with enhanced specificity. This review summarizes the mechanism of action of CD8+ T cells in immunotherapy, and highlights the recent advancements in PET-based tracers that can visualize CD8+ T cells and discusses their clinical applications to elucidate their potential role in cancer immunotherapy.

Immune landscape of renal cell carcinoma with metastasis to the pancreas

INTRODUCTION

Clear cell Renal Cell Carcinoma (ccRCC) has a poor prognosis once metastatic. However, certain metastatic sites have been reported to have a different impact on the patient prognosis. For example, patients with pancreatic metastases have a much more favorable prognosis than those with metastases to other organs. The biological basis for this observation remains poorly understood. The aim of this study was to characterize the immune landscape of pancreatic metastases and the corresponding primary tumors in order to identify possible immunological features that correlate with disease biology.

PATIENTS AND METHODS

A detailed assessment of immune cell populations was performed using a total of 1,700 microscopic images from ccRCCs from 11 patients, their corresponding pancreatic metastases and ccRCCs from 10 patients without pancreatic metastases. Tumor specimens were stained for CD45, CD8, CD163 and FOXP3 and the densities of the respective immune cells were assessed semiquantitatively in the intratumoral and extratumoral compartment. Multispectral imaging was performed in selected tumors.

RESULTS

We found that pancreatic metastases show the lowest intratumoral infiltration with CD8+ cytotoxic T lymphocytes of all tumor specimens analyzed. The frequency of CD8+ lymphocytes was on 1.9 fold lower in pancreatic metastases (median density 8.3 cells per field of view [FOV] = 1.23 mm2) when compared to the corresponding primary tumor (15.6 cells per FOV, P = 0.0002) and more than 3-fold lower when compared to ccRCCs without pancreatic metastases (27.2 cells per FOV, P = 0.0012). There was also a significantly reduced intratumoral infiltration with immunosuppressive FOXP3+ lymphocytes in pancreatic metastases (2.6 cells per FOV, P = 0.009) and corresponding primary tumors (2 cells per FOV, P = 0.028) when compared to ccRCCs without pancreatic metastases (5.6 cells per FOV).

CONCLUSIONS

In this proof-of-concept study, we show that pancreatic metastases of ccRCC present with unique immunological features including a low intratumoral density of CD8+ and FOXP3+ lymphocytes. The low counts of CD8+ and FOXP3+ lymphocytes may reflect less aggressive features of ccRCC with pancreatic metastasis that may result in a more favorable patient prognosis.

Anti-hepatoma immunotherapy of Pholiota adiposa polysaccharide-coated selenium nanoparticles by reversing M2-like tumor-associated macrophage polarization

Targeting macrophages to regulate the tumor microenvironment is a promising strategy for treating cancer. This study developed a stable nano drug (PAP-SeNPs) using Se nanoparticles (SeNPs) and the Pholiota adiposa polysaccharide component (PAP-1a) and reported their physical stability, M2-like macrophages targeting efficacy and anti-hepatoma immunotherapy potential, as well as their molecular mechanisms. Furthermore, the zero-valent and well-dispersed spherical PAP-SeNPs were also successfully synthesized with an average size of 55.84 nm and a negative ζ-potential of -51.45 mV. Moreover, it was observed that the prepared PAP-SeNPs were stable for 28 days at 4 °C. Intravital imaging highlighted that PAP-SeNPs had the dual effect of targeting desirable immune organs and tumors. In vitro analyses showed that the PAP-SeNPs polarized M2-like macrophages towards the M1 phenotype to induce hepatoma cell death, triggered by the time-dependent lysosomal endocytosis in macrophages. Mechanistically, PAP-SeNPs significantly activated the Tlr4/Myd88/NF-κB axis to transform tumor-promoting macrophages into tumor-inhibiting macrophages and successfully initiated antitumor immunotherapy. Furthermore, PAP-SeNPs also enhanced CD3+CD4+ T cells and CD3+CD8+ T cells, thereby further stimulating anti-hepatoma immune responses. These results suggest that the developed PAP-SeNPs is a promising immunostimulant that can assist hepatoma therapy.

Evolving Management of Breast Cancer in the Era of Predictive Biomarkers and Precision Medicine

Breast cancer is the most common cancer among women in the world as well as in the United States. Molecular and histological differentiation have helped clinicians optimize treatments with various therapeutics, including hormonal therapy, chemotherapy, immunotherapy, and radiation therapy. Recently, immunotherapy has become the standard of care in locally advanced triple-negative breast cancer and an option across molecular subtypes for tumors with a high tumor mutation burden. Despite the advancements in personalized medicine directing the management of localized and advanced breast cancers, the emergence of resistance to these therapies is the leading cause of death among breast cancer patients. Therefore, there is a critical need to identify and validate predictive biomarkers to direct treatment selection, identify potential responders, and detect emerging resistance to standard therapies. Areas of active scientific and clinical research include novel personalized and predictive biomarkers incorporating tumor microenvironment, tumor immune profiling, molecular characterization, and histopathological differentiation to predict response and the potential emergence of resistance.

Orchestrated Codelivery of Peptide Antigen and Adjuvant to Antigen-Presenting Cells by Using an Engineered Chimeric Peptide Enhances Antitumor T-Cell Immunity

The intrinsic pharmacokinetic limitations of traditional peptide-based cancer vaccines hamper effective cross-presentation and codelivery of antigens (Ag) and adjuvants, which are crucial for inducing robust antitumor CD8+ T-cell responses. In this study, we report the development of a versatile strategy that simultaneously addresses the different pharmacokinetic challenges of soluble subunit vaccines composed of Ags and cytosine-guanosine oligodeoxynucleotide (CpG) to modulate vaccine efficacy via translating an engineered chimeric peptide, eTAT, as an intramolecular adjuvant. Linking Ags to eTAT enhanced cytosolic delivery of the Ags. This, in turn, led to improved activation and lymph node-trafficking of Ag-presenting cells and Ag cross-presentation, thus promoting Ag-specific T-cell immune responses. Simple mixing of eTAT-linked Ags and CpG significantly enhanced codelivery of Ags and CpG to the Ag-presenting cells, and this substantially augmented the adjuvant effect of CpG, maximized vaccine immunogenicity, and elicited robust and durable CD8+ T-cell responses. Vaccination with this formulation altered the tumor microenvironment and exhibited potent antitumor effects, with generally further enhanced therapeutic efficacy when used in combination with anti-PD1. Altogether, the engineered chimeric peptide-based orchestrated codelivery of Ag and adjuvant may serve as a promising but simple strategy to improve the efficacy of peptide-based cancer vaccines.

Machine learning evaluation of immune infiltrate through digital tumour score allows prediction of survival outcome in a pooled analysis of three international stage III colon cancer cohorts

BACKGROUND

T-cell immune infiltrates are robust prognostic variables in localised colon cancer. Evaluation of prognosis using artificial intelligence is an emerging field. We evaluated whether machine learning analysis improved prediction of patient outcome in comparison with analysis of T cell infiltrate only or in association with clinical variables.

METHODS

We used data from two phase III clinical trials (Prodige-13 and PETACC08) and one retrospective Italian cohort (HARMONY). Cohorts were split into training (N = 692), internal validation (N = 297) and external validation (N = 672) sets. Tumour slides were stained with CD3mAb. CD3 Machine Learning (CD3ML) score was computed using graphical parameters within the tumour tiles obtained from CD3 slides. CD3 infiltrates in tumour core and invasive margin were automatically detected. Associations of CD3 infiltrates and CD3ML with 5-year Disease-Free Survival (DFS) were examined using univariate and multivariable survival models by Cox regression.

FINDINGS

CD3 density both in the invasive margin and the tumour core were significantly associated with DFS in the different sets. Similarly, CD3ML score was significantly associated with DFS in all sets. CD3 assessment did not provide added value on top of CD3ML assessment (Likelihood Ratio Test (LRT), p = 0.13). In contrast, CD3ML improved prediction of DFS when combined with a clinical risk stage (LRT, p = 0.001). Stratified by clinical risk score (High or Low), patients with low CD3ML score had better DFS.

INTERPRETATION

In all tested sets, machine learning analysis of tumour cells improved prediction of prognosis compared to clinical parameters. Adding tumour-infiltrating lymphocytes assessment did not improve prognostic determination.

FUNDING

This research received no external funding.

An Updated Review on KRAS Mutation in Lung Cancer (NSCLC) and Its Effects on Human Health

The largest cause of cancer-related fatalities worldwide is lung cancer. In its early stages, lung cancer often exhibits no signs or symptoms. Its signs and symptoms often appear when the condition is advanced. The Kirsten rat sarcoma virus oncogene homolog is one of the most frequently mutated oncogenes found in non-small cell lung cancer. Patients who have these mutations may do worse than those who do not, in terms of survival. To understand the nuances in order to choose the best treatment options for each patient, including combination therapy and potential resistance mechanisms, given the quick development of pharmaceuticals, it is necessary to know the factors that might contribute to this disease. It has been observed that single nucleotide polymorphisms altering let-7 micro-RNA might impact cancer propensity. On the other hand, gefitinib fails to stop the oncogenic protein from directly interacting with phosphoinositide3-kinase, which may explain its resistance towards cancer cells. Additionally, Atorvastatin may be able to overpower gefitinib resistance in these cancer cells that have this mutation regardless of the presence of phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha. De novo lipogenesis is also regulated by this virus. To overcome these effects, several targeted therapies have been proposed. One such therapy is to use inhibitors of focal adhesion kinases. When this is inhibited, viral oncogene mutant cancers are effectively stopped because it functions downstream of the virus. Mutant oncoproteins like epidermal growth factor receptor may depend on Heat Shock protein90 chaperones more frequently than they do on natural counterparts that make it more attractive therapeutic target for this virus. Inhibition of the phosphoinositide 3-kinase pathway is frequent in lung cancer, and fabrication of inhibitors against this pathway can also be an effective therapeutic strategy. Blocking programmed cell death ligand1 is another therapy that may help T cells to recognize and eliminate cancerous cells. This homolog is a challenging therapeutic target due to its complex structural makeup and myriad biological characteristics. Thanks to the unrelenting efforts of medical research, with the use of some inhibitors, immunotherapy, and other combination methods, this problem is currently expected to be overcome.

Molecular subtypes of colorectal cancer in the era of precision oncotherapy: Current inspirations and future challenges

BACKGROUND

Colorectal cancer (CRC) is among the most hackneyed malignancies. Even patients with identical clinical symptoms and the same TNM stage still exhibit radically different clinical outcomes after receiving equivalent treatment regimens, indicating extensive heterogeneity of CRC. Myriad molecular subtypes of CRC have been exploited for decades, including the most compelling consensus molecular subtype (CMS) classification that has been broadly applied for patient stratification and biomarker-drug combination formulation. Encountering barriers to clinical translation, however, CMS classification fails to fully reflect inter- or intra-tumor heterogeneity of CRC. As a consequence, addressing heterogeneity and precisely managing CRC patients with unique characteristics remain arduous tasks for clinicians.

REVIEW

In this review, we systematically summarize molecular subtypes of CRC and further elaborate on their clinical applications, limitations, and future orientations.

CONCLUSION

In recent years, exploration of subtypes through cell lines, animal models, patient-derived xenografts (PDXs), organoids, and clinical trials contributes to refining biological insights and unraveling subtype-specific therapies in CRC. Therapeutic interventions including nanotechnology, clustered regulatory interspaced short palindromic repeat/CRISPR-associated nuclease 9 (CRISPR/Cas9), gut microbiome, and liquid biopsy are powerful tools with the possibility to shift the immunologic landscape and outlook for CRC precise medicine.

Effect of HLA Genotype on Anti-PD-1 Antibody Treatment for Advanced Renal Cell Carcinoma in the SNiP-RCC Study

Immune checkpoint blockade therapies are widely used for cancer treatment, including advanced renal cell carcinoma (RCC). This study aimed to investigate the impact of zygosity in HLA genes and individual HLA genotypes on the efficacy of an anti-PD-1 Ab, nivolumab, in treating advanced RCC. Patient enrollment was conducted across 23 institutions in Japan from August 19, 2019, to September 30, 2020, with follow-up concluding on March 31, 2021. HLA genotype imputation of HLA-A, B, and C, DQB1, and DRB1 loci was performed. Among 222 patients, the presence of at least one homozygosity of the HLA-II allele significantly improved the best objective response (hazard ratio, 0.34; 95% confidence interval, 0.21-0.96; p = 0.042). The HLA evolutionary divergence (HED) of the HLA-A and HLA-B loci was higher than the HLA-C (p < 0.0001 and p < 0.0001, respectively), with high HED of the HLA-B locus correlating to clinical benefits in nivolumab treatment (hazard ratio, 0.44; 95% confidence interval, 0.21-0.90; p = 0.024) and improving cancer-specific survival compared with the low group (p = 0.0202). Additionally, high HED of the HLA-B locus was correlated with the number of infiltrated CD8+ cells in the tumor microenvironment (correlation coefficient, 0.4042). These findings indicate that the diversity of the HLA-B locus plays a significant role in the anti-tumor effect of nivolumab treatment in advanced RCC, potentially offering insights for improved risk stratification in nivolumab treatment and leading to better medical management of advanced RCC.

Efficacy and biomarker analysis of second-line nab-paclitaxel plus sintilimab in patients with advanced biliary tract cancer

Biliary tract cancer (BTC) is a highly aggressive malignancy with limited second-line therapy. We conducted this phase 2 trial to evaluate the efficacy and safety of second-line nab-paclitaxel plus sintilimab in advanced BTC. Histologically confirmed advanced BTC patients with documented disease progression after first-line chemotherapy were enrolled. Subjects received nab-paclitaxel 125 mg/m2 on days 1 and 8 plus sintilimab 200 mg on day 1, administered every 3 weeks. The primary end point was the objective response rate (ORR). The secondary end points were progression-free survival (PFS), overall survival (OS), and adverse reactions. Simultaneously, next-generation sequencing, programmed cell death ligand 1 immunohistochemistry and multiplex immunofluorescence of tumor-infiltrating lymphocytes were applied to explore potential biomarkers. Twenty-six subjects were consecutively enrolled. The ORR was 26.9% (7/26), including two complete responses and five partial responses, which met the primary end point. The disease control rate was 61.5% (16/26). The median PFS was 169 days (about 5.6 months, 95% confidence interval [CI] 60-278 days). The median OS was 442 days (about 14.7 months, 95% CI 298-586 days). Grade 3 treatment-related adverse events (TRAEs) were mainly anemia (27%), leukopenia (23%), neutropenia (19%), and peripheral sensory neuropathy (8%). No grade 4 or 5 TRAEs occurred. Biomarker analysis suggested that positive PD-L1 and high proportions of CD8+ T-cell infiltration were correlated with improved clinical outcome. Nab-paclitaxel plus sintilimab is a potentially effective and tolerable second-line regimen for advanced BTC that deserves to be studied in large-scale trials. PD-L1 status and CD8+ T cell infiltration might be promising biomarkers for efficacy prediction.

The single cell immunogenomic landscape after neoadjuvant immunotherapy combined chemotherapy in esophageal squamous cell carcinoma

Neoadjuvant immunotherapy represents promising strategy in the treatment of esophageal squamous cell carcinoma (ESCC). However, the mechanisms underlying its impact on treatment sensitivity or resistance remain a subject of controversy. In this study, we conducted single-cell RNA and T/B cell receptor (scTCR/scBCR) sequencing of CD45+ immune cells on samples from 10 patients who received neoadjuvant immunotherapy and chemotherapy. We also validated our findings using multiplexed immunofluorescence and analyzed bulk RNA-seq from other cohorts in public database. By integrating analysis of 87357 CD45+ cells, we found GZMK + effector memory T cells (Tem) were relatively enriched and CXCL13+ exhausted T cells (Tex) and regulator T cells (Treg) decreased among responders, indicating a persistent anti-tumor memory process. Additionally, the enhanced presence of BCR expansion and somatic hypermutation process within TNFRSF13B + memory B cells (Bmem) suggested their roles in antigen presentation. This was further corroborated by the evidence of the T-B co-stimulation pattern and CXCL13-CXCR5 axis. The complexity of myeloid cell heterogeneity was also particularly pronounced. The elevated expression of S100A7 in ESCC, as detected by bulk RNA-seq, was associated with an exhausted and immunosuppressive tumor microenvironment. In summary, this study has unveiled a potential regulatory network among immune cells and the clonal dynamics of their functions, and the mechanisms of exhaustion and memory conversion between GZMK + Tem and TNFRSF13B + Bmem from antigen presentation and co-stimulation perspectives during neoadjuvant PD-1 blockade treatment in ESCC.

Assessment of AURKA expression and prognosis prediction in lung adenocarcinoma using machine learning-based pathomics signature

Objective

This study aimed to develop quantitative feature-based models from histopathological images to assess aurora kinase A (AURKA) expression and predict the prognosis of patients with lung adenocarcinoma (LUAD).

Methods

A dataset of patients with LUAD was derived from the cancer genome atlas (TCGA) with information on clinical characteristics, RNA sequencing and histopathological images. The TCGA-LUAD cohort was randomly divided into training (n = 229) and testing (n = 98) sets. We extracted quantitative image features from histopathological slides of patients with LUAD using computational approaches, constructed a predictive model for AURKA expression in the training set, and estimated their predictive performance in the test set. A Cox proportional hazards model was used to assess whether the pathomic scores (PS) generated by the model independently predicted LUAD survival.

Results

High AURKA expression was an independent risk factor for overall survival (OS) in patients with LUAD (hazard ratio = 1.816, 95 % confidence intervals = 1.257-2.623, P = 0.001). The model based on histopathological image features had significant predictive value for AURKA expression: the area under the curve of the receiver operating characteristic curve in the training set and validation set was 0.809 and 0.739, respectively. Decision curve analysis showed that the model had clinical utility. Patients with high PS and low PS had different survival rates (P = 0.019). Multivariate analysis suggested that PS was an independent prognostic factor for LUAD (hazard ratio = 1.615, 95 % confidence intervals = 1.071-2.438, P = 0.022).

Conclusion

Pathomics models based on machine learning can accurately predict AURKA expression and the PS generated by the model can predict LUAD prognosis.

GraphCompass: spatial metrics for differential analyses of cell organization across conditions

SUMMARY

Spatial omics technologies are increasingly leveraged to characterize how disease disrupts tissue organization and cellular niches. While multiple methods to analyze spatial variation within a sample have been published, statistical and computational approaches to compare cell spatial organization across samples or conditions are mostly lacking. We present GraphCompass, a comprehensive set of omics-adapted graph analysis methods to quantitatively evaluate and compare the spatial arrangement of cells in samples representing diverse biological conditions. GraphCompass builds upon the Squidpy spatial omics toolbox and encompasses various statistical approaches to perform cross-condition analyses at the level of individual cell types, niches, and samples. Additionally, GraphCompass provides custom visualization functions that enable effective communication of results. We demonstrate how GraphCompass can be used to address key biological questions, such as how cellular organization and tissue architecture differ across various disease states and which spatial patterns correlate with a given pathological condition. GraphCompass can be applied to various popular omics techniques, including, but not limited to, spatial proteomics (e.g. MIBI-TOF), spot-based transcriptomics (e.g. 10× Genomics Visium), and single-cell resolved transcriptomics (e.g. Stereo-seq). In this work, we showcase the capabilities of GraphCompass through its application to three different studies that may also serve as benchmark datasets for further method development. With its easy-to-use implementation, extensive documentation, and comprehensive tutorials, GraphCompass is accessible to biologists with varying levels of computational expertise. By facilitating comparative analyses of cell spatial organization, GraphCompass promises to be a valuable asset in advancing our understanding of tissue function in health and disease.

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Extracellular vesicles as modulators of monocyte and macrophage function in tumors

The tumor microenvironment (TME) harbors several cell types, such as tumor cells, immune cells, and non-immune cells. These cells communicate through several mechanisms, such as cell-cell contact, cytokines, chemokines, and extracellular vesicles (EVs). Tumor-derived vesicles are known to have the ability to modulate the immune response. Monocytes are a subset of circulating innate immune cells and play a crucial role in immune surveillance, being recruited to tissues where they differentiate into macrophages. In the context of tumors, it has been observed that tumor cells can attract monocytes to the TME and induce their differentiation into tumor-associated macrophages with a pro-tumor phenotype. Tumor-derived EVs have emerged as essential structures mediating this process. Through the transfer of specific molecules and signaling factors, tumor-derived EVs can shape the phenotype and function of monocytes, inducing the expression of cytokines and molecules by these cells, thus modulating the TME towards an immunosuppressive environment.

Value of Contrast-Enhanced Ultrasound Combined with Immune-Inflammatory Markers in Predicting Axillary Lymph Node Metastasis of Breast Cancer

RATIONALE AND OBJECTIVES

To evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) combined with immune-inflammatory markers in predicting axillary lymph node metastasis (ALNM) in breast cancer patients.

METHODS

From January 2020 to June 2023, the clinicopathological data and ultrasound features of 401 breast cancer patients who underwent biopsy or surgery were recorded. Patients were randomly divided into a training set (321 patients) and a validation set (80 patients). The risk factors for ALNM were determined using univariate, least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analysis, and prediction models were constructed. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to assess their diagnostic performance.

RESULTS

Logistic regression analysis demonstrated that systemic immunoinflammatory index (SII), CA125, Ki67, pathological type, lesion size, enhancement pattern and Breast Imaging Reporting and Data System (BI-RADS) category were significant risk factors for ALNM. Three different models were constructed, and the combined model yielded an AUC of 0.903, which was superior to the clinical model (AUC=0.790) and ultrasound model (AUC=0.781). A nomogram was constructed based on the combined model, calibration curves and DCA demonstrated its satisfactory performance in predicting ALNM.

CONCLUSION

The nomogram combining ultrasound features and immune-inflammatory markers could serve as a valuable instrument for predicting ALNM in breast cancer patients.

DATA AVAILABILITY STATEMENT

The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding authors.

Impact of adjuvant chemotherapy on survival after pathological complete response in rectal cancer: a meta-analysis of 31,558 patients

BACKGROUND

Locally advanced rectal cancer (LARC) typically involves neoadjuvant chemoradiotherapy (nCRT) followed by surgery (total mesorectal excision, TME). While achieving a complete pathological response (pCR) is a strong indicator of a positive prognosis, the specific benefits of adjuvant chemotherapy after pCR remain unclear. To address this knowledge gap, we conducted a systematic review and meta-analysis to assess the potential advantages of adjuvant therapy in patients who achieve pCR.

METHODS

In this study, we searched Medline, Embase, and Web of Science databases for relevant research. We focused on binary outcomes, analyzing them using odds ratios (ORs) with 95% confidence intervals (CIs). To account for potential variability between studies, all endpoints were analyzed with DerSimonian and Laird random-effects models. We assessed heterogeneity using the I2 statistic and employed the R statistical software (version 4.2.3) for all analyses.

RESULTS

Thirty-four studies, comprising 31,558 patients, were included. The outcomes demonstrated a significant difference favoring the AC group in terms of overall survival (OS) (HR 0.75; 95% CI 0.60-0.94; p = 0.015; I2 = 0%), and OS in 5 years (OR 1.65; 95% CI 1.21-2.24; p = 0.001; I2 = 39%). There was no significant difference between the groups for disease-free survival (DFS) (HR 0.94; 95% CI 0.76-1.17; p = 0.61; I2 = 17%), DFS in 5 years (OR 1.19; 95% CI 0.82-1.74; p = 0.36; I2 = 43%), recurrence-free survival (RFS) (HR 1.10; 95% CI 0.87-1.40; p = 0.39; I2 = 0%), and relapse-free survival (OR 1.08; 95% CI 0.78-1.51; p = 0.62; I2 = 0%).

CONCLUSION

This systematic review and meta-analysis found a significant difference in favor of the ACT group in terms of survival after pCR. Therefore, the administration of this treatment as adjuvant therapy should be encouraged in clinical practice.

Integrated analysis of tertiary lymphoid structures and immune infiltration in ccRCC microenvironment revealed their clinical significances: a multicenter cohort study

BACKGROUND

Tertiary lymphoid structures (TLSs) serve as organized lymphoid aggregates that influence immune responses within the tumor microenvironment. This study aims to investigate the characteristics and clinical significance of TLSs and tumor-infiltrating lymphocytes (TILs) in clear cell renal cell carcinoma (ccRCC).

METHODS

TLSs and TILs were analyzed comprehensively in 754 ccRCC patients from 6 academic centers and 532 patients from The Cancer Genome Atlas. Integrated analysis was performed based on single-cell RNA-sequencing datasets from 21 ccRCC patients to investigate TLS heterogeneity in ccRCC. Immunohistochemistry and multiplex immunofluorescence were applied. Cox regression and Kaplan-Meier analyses were used to reveal the prognostic significance.

RESULTS

The study demonstrated the existence of TLSs and TILs heterogeneities in the ccRCC microenvironment. TLSs were identified in 16% of the tumor tissues in 113 patients. High density (>0.6/mm2) and maturation of TLSs predicted good overall survival (OS) (p<0.01) in ccRCC patients. However, high infiltration (>151) of scattered TILs was an independent risk factor of poor ccRCC prognosis (HR=14.818, p<0.001). The presence of TLSs was correlated with improved progression-free survival (p=0.002) and responsiveness to therapy (p<0.001). Interestingly, the combination of age and TLSs abundance had an impact on OS (p<0.001). Higher senescence scores were detected in individuals with immature TLSs (p=0.003).

CONCLUSIONS

The study revealed the contradictory features of intratumoral TLSs and TILs in the ccRCC microenvironment and their impact on clinical prognosis, suggesting that abundant and mature intratumoral TLSs were associated with decreased risks of postoperative ccRCC relapse and death as well as favorable therapeutic response. Distinct spatial distributions of immune infiltration could reflect effective antitumor or protumor immunity in ccRCC.

Dissecting gastric cancer heterogeneity and exploring therapeutic strategies using bulk and single-cell transcriptomic analysis and experimental validation of tumor microenvironment and metabolic interplay

Gastric cancer, the fifth most prevalent cancer worldwide, is often diagnosed in advanced stages with limited treatment options. Examining the tumor microenvironment (TME) and its metabolic reprogramming can provide insights for better diagnosis and treatment. This study investigates the link between TME factors and metabolic activity in gastric cancer using bulk and single-cell RNA-sequencing data. We identified two molecular subtypes in gastric cancer by analyzing the distinct expression patterns of 81 prognostic genes related to the TME and metabolism, which exhibited significant protein-level interactions. The high-risk subtype had increased stromal content, fibroblast and M2 macrophage infiltration, elevated glycosaminoglycans/glycosphingolipids biosynthesis, and fat metabolism, along with advanced clinicopathological features. It also exhibited low mutation rates and microsatellite instability, associating it with the mesenchymal phenotype. In contrast, the low-risk group showed higher tumor content and upregulated protein and sugar metabolism. We identified a 15-gene prognostic signature representing these characteristics, including CPVL, KYNU, CD36, and GPX3, strongly correlated with M2 macrophages, validated through single-cell analysis and an internal cohort. Despite resistance to immunotherapy, the high-risk group showed sensitivity to molecular targeted agents directed at IGF-1R (BMS-754807) and the PI3K-mTOR pathways (AZD8186, AZD8055). We experimentally validated these promising drugs for their inhibitory effects on MKN45 and MKN28 gastric cells. This study unveils the intricate interplay between TME and metabolic pathways in gastric cancer, offering potential for enhanced diagnosis, patient stratification, and personalized treatment. Understanding molecular features in each subtype enriches our comprehension of gastric cancer heterogeneity and potential therapeutic targets.

Decoding the immune landscape: a comprehensive analysis of immune-associated biomarkers in cervical carcinoma and their implications for immunotherapy strategies

Background and aims

Cervical cancer, a prevalent gynecological malignant tumor, poses a significant threat to women's health and lives. Immune checkpoint inhibitor (ICI) therapy has emerged as a promising avenue for treating cervical cancer. For patients with persistent or recurrent metastatic cervical cancer, If the sequence of dead receptor ligand-1 (PD-L1) is positive, ICI show significant clinical efficacy. PD-L1 expression serves as a valuable biomarker for assessing ICI therapeutic efficacy. However, the complex tumor immune microenvironment (TIME), encompassing immune cell composition and tumor-infiltrating lymphocyte (TIL) status, also exerts a profound influence on tumor immunity and prognosis. Given the remarkable strides made by ICI treatments in improving the survival rates of cervical cancer patients, it becomes essential to identify a comprehensive biomarker that integrates various TIME aspects to enhance the effectiveness of ICI treatment. Therefore, the quest for biomarkers linked to multiple facets of TIME in cervical cancer is a vital pursuit.

Methods

In this study, we have developed an Immune-Associated Gene Prognostic Index (IRGPI) with remarkable prognostic value specifically for cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). The Cancer Genome Atlas CESC dataset (n = 305) was meticulously analyzed to pinpoint key immune-related genes via weighted gene co-expression network analysis and differential gene expression assays. Subsequently, we employed Cox regression analysis to construct the IRGPI. Furthermore, the composition of immune cells and TIL status were examined using CIBERSORT and TIDE. Tumor expression of Epigen, LCN10, and P73 were determined with immunohistochemistry.

Results

The resulting IRGPI, composed of EPGN, LCN10, and TP73 genes, displayed a strong negative correlation with patient survival. The discovery was validated with a patient cohort from our hospital. The IRGPI not only predicts the composition of immune cell subtypes such as Macrophages M1, NK cells, Mast cells, Plasma cells, Neutrophils, Dendritic cells, T cells CD8, and T cells CD4 within CESC, but also indicates TIL exclusion, dysfunction, and PD-1 and PD-L1 expression. Therefore, the IRGPI emerges as a promising biomarker not only for prognostic assessment but also for characterizing multiple immune features in CESC. Additionally, our results underscored the significant associations between the IRGPI and immune cell composition, TIL exclusion, and dysfunction, along with PD-1 and PD-L1 expression in the TIME.

Conclusion

Consequently, the IRGPI stands out as a biomarker intimately connected to both the survival and TIME status of CESC patients, offering potential insights into immunotherapy strategies for CESC.

Immunotherapy-activated T cells recruit and skew late-stage activated M1-like macrophages that are critical for therapeutic efficacy

Total tumor clearance through immunotherapy is associated with a fully coordinated innate and adaptive immune response, but knowledge on the exact contribution of each immune cell subset is limited. We show that therapy-induced intratumoral CD8+ T cells recruited and skewed late-stage activated M1-like macrophages, which were critical for effective tumor control in two different murine models of cancer immunotherapy. The activated CD8+ T cells summon these macrophages into the tumor and their close vicinity via CCR5 signaling. Exposure of non-polarized macrophages to activated T cell supernatant and tumor lysate recapitulates the late-stage activated and tumoricidal phenotype in vitro. The transcriptomic signature of these macrophages is also detected in a similar macrophage population present in human tumors and coincides with clinical response to immune checkpoint inhibitors. The requirement of a functional co-operation between CD8+ T cells and effector macrophages for effective immunotherapy gives warning to combinations with broad macrophage-targeting strategies.

Exploring prognostic and immunological characteristics of pancreatic ductal adenocarcinoma through comprehensive genomic analysis of tertiary lymphoid structures and CD8 + T-cells

PURPOSE

Tertiary lymphoid structures (TLSs) and CD8 + T-cells are potential prognostic indicators for pancreatic ductal adenocarcinoma (PDAC). We established a novel scoring system for evaluating the risk for PDAC based on TLS- and CD8 + T-cell-related genes.

METHODS

We analyzed single-cell sequence data from PDAC patients in the Genome Sequence Archive. Bioinformatics and machine algorithms established and validated a scoring method (T-C score) based on PDAC survival-related genes highly expressed in TLSs and CD8 + T-cells. Patients were stratified into the low- and high-T-C score groups. Differences in survival, pathway enrichment, mutation status, immune cell infiltration, expression of immune checkpoint-associated genes, tumor stemness, and response to antitumor therapy were compared through computer simulation methods.

RESULTS

Overall survival differed significantly between the training and validation cohorts' low- and high-T-C score groups. The low-T-C score group correlated with lower tumor mutation burden and lower levels of tumor stemness compared with the high-T-C score group. Patients with lower T-C scores exhibited advantages in immunotherapeutic responses and might be more sensitive to the chemotherapeutic regimen and multi-kinase inhibitors.

CONCLUSION

The T-C score could serve as an effective model for predicting the survival and therapeutic responses of patients with PDAC.

Guardians and Mediators of Metastasis: Exploring T Lymphocytes, Myeloid-Derived Suppressor Cells, and Tumor-Associated Macrophages in the Breast Cancer Microenvironment

Breast cancers (BCs) are solid tumors composed of heterogeneous tissues consisting of cancer cells and an ever-changing tumor microenvironment (TME). The TME includes, among other non-cancer cell types, immune cells influencing the immune context of cancer tissues. In particular, the cross talk of immune cells and their interactions with cancer cells dramatically influence BC dissemination, immunoediting, and the outcomes of cancer therapies. Tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and myeloid-derived suppressor cells (MDSCs) represent prominent immune cell populations of breast TMEs, and they have important roles in cancer immunoescape and dissemination. Therefore, in this article we review the features of TILs, TAMs, and MDSCs in BCs. Moreover, we highlight the mechanisms by which these immune cells remodel the immune TME and lead to breast cancer metastasis.

Bioorthogonal Quinone Methide Decaging Enables Live-Cell Quantification of Tumor-Specific Immune Interactions

Effective antitumor immunity hinges on the specific engagement between tumor and cytotoxic immune cells, especially cytotoxic T cells. Although investigating these intercellular interactions is crucial for characterizing immune responses and guiding immunotherapeutic applications, direct and quantitative detection of tumor-T cell interactions within a live-cell context remains challenging. We herein report a photocatalytic live-cell interaction labeling strategy (CAT-Cell) relying on the bioorthogonal decaging of quinone methide moieties for sensitive and selective investigation and quantification of tumor-T cell interactions. By developing quinone methide-derived probes optimized for capturing cell-cell interactions (CCIs), we demonstrated the capacity of CAT-Cell for detecting CCIs directed by various types of receptor-ligand pairs (e.g., CD40-CD40L, TCR-pMHC) and further quantified the strengths of tumor-T cell interactions that are crucial for evaluating the antitumor immune responses. We further applied CAT-Cell for ex vivo quantification of tumor-specific T cell interactions on splenocyte and solid tumor samples from mouse models. Finally, the broad compatibility and utility of CAT-Cell were demonstrated by integrating it with the antigen-specific targeting system as well as for tumor-natural killer cell interaction detection. By leveraging the bioorthogonal photocatalytic decaging chemistry on quinone methide, CAT-Cell provides a sensitive, tunable, universal, and noninvasive toolbox for unraveling and quantifying the crucial but delicate tumor-immune interactions under live-cell settings.

Prognostic value of tertiary lymphoid structures in hepatocellular carcinoma: a meta-analysis and systematic review

Background

Multiple investigations and scholarly articles have presented compelling evidence indicating that tertiary lymphoid structures (TLS) play a pivotal role in inhibiting and controlling the advancement of tumors. While there is an abundance of information highlighting the importance of TLS in different cancer types, their prognostic significance specifically in hepatocellular carcinoma (HCC) cancers remains unclear. Thus, this meta-analysis aimed to explore the prognostic relevance of TLS in HCC.

Methods

We conducted a thorough search across four databases, namely Web of Science, PubMed, Embase, and the Cochrane Library, to identify pertinent studies. The search utilized the keywords "tertiary lymphoid structures" and "hepatocellular carcinoma." The primary outcomes of interest encompassed overall survival (OS), recurrence-free survival (RFS), early recurrence, and late recurrence. The statistical effect size for these measures was expressed in terms of hazard ratios (HR).

Results

Six studies were incorporated into the analysis. Among them, four studies, encompassing 6 datasets and involving 1490 patients, and three studies, comprising 5 datasets and involving 656 patients, respectively, investigated the correlation between intratumoral and peritumoral TLSs and the prognosis in HCC patients. The meta-analysis revealed that the presence of intratumoral TLSs is linked to longer RFS and reduced early recurrence (HR, 0.60; 95% CI, 0.50-0.67; p <0.001 and HR, 0.49; 95% CI, 0.36-0.65; p <0.001, respectively). However, no significant association was observed with OS and late recurrence. Sensitivity analysis demonstrated the robustness of these findings, and heterogeneities were minimal. Additionally, the meta-analysis did not detect a relationship between peritumoral TLSs and OS or RFS in HCC patients.

Conclusion

The presence of intratumoral TLSs is correlated with better RFS and reduced early recurrence in HCC patients. Further investigation is warranted to elucidate the roles of peritumoral TLSs in the prognosis of HCC patients.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier CRD42023466793.

Effects of opioid drugs on immune function in cancer patients

Opioid receptor agonists are often used when cancer patients undergo surgery or analgesic treatment. As analgesics in clinical care, opioids can provide intraoperative or to chronic cancer pain relief. Immune function plays an important role in anti-cancer therapy, with cellular immunity, comprised principally of T-lymphocytes and natural killer cells, representing the primary anti-cancer immune response. However, it remains unclear whether immune function is further affected with the use of opioids in already immunocompromised cancer patients. This article provides a review of the effects of commonly used clinical opioids, including morphine, oxycodone, fentanyl and tramadol, on immune function in cancer patients. It provides a summary of current evidence regarding the immunomodulatory effects of opioids in the cancer setting and mechanisms underlying these interactions.

A spatial architecture-embedding HLA signature to predict clinical response to immunotherapy in renal cell carcinoma

An important challenge in the real-world management of patients with advanced clear-cell renal cell carcinoma (aRCC) is determining who might benefit from immune checkpoint blockade (ICB). Here we performed a comprehensive multiomics mapping of aRCC in the context of ICB treatment, involving discovery analyses in a real-world data cohort followed by validation in independent cohorts. We cross-connected bulk-tumor transcriptomes across >1,000 patients with validations at single-cell and spatial resolutions, revealing a patient-specific crosstalk between proinflammatory tumor-associated macrophages and (pre-)exhausted CD8+ T cells that was distinguished by a human leukocyte antigen repertoire with higher preference for tumoral neoantigens. A cross-omics machine learning pipeline helped derive a new tumor transcriptomic footprint of neoantigen-favoring human leukocyte antigen alleles. This machine learning signature correlated with positive outcome following ICB treatment in both real-world data and independent clinical cohorts. In experiments using the RENCA-tumor mouse model, CD40 agonism combined with PD1 blockade potentiated both proinflammatory tumor-associated macrophages and CD8+ T cells, thereby achieving maximal antitumor efficacy relative to other tested regimens. Thus, we present a new multiomics and spatial map of the immune-community architecture that drives ICB response in patients with aRCC.

The new era of lung cancer therapy: Combining immunotherapy with ferroptosis

Ferroptosis is an unconventional programmed cell death mode caused by phospholipid peroxidation dependent on iron. Emerging immunotherapies (especially immune checkpoint inhibitors) have the potential to enhance lung cancer patients' long-term survival. Although immunotherapy has yielded significant positive applications in some patients, there are still many mechanisms that can cause lung cancer cells to evade immunity, thus leading to the failure of targeted therapies. Immune-tolerant cancer cells are insensitive to conventional death pathways such as apoptosis and necrosis, whereas mesenchymal and metastasis-prone cancer cells are particularly vulnerable to ferroptosis, which plays a vital role in mediating immune tolerance resistance by tumors and immune cells. As a result, triggering lung cancer cell ferroptosis holds significant therapeutic potential for drug-resistant malignancies. Here, we summarize the mechanisms underlying the suppression of ferroptosis in lung cancer, highlight its function in the lung cancer immune microenvironment, and propose possible therapeutic strategies.