The impact of preoperative treatments on the immune environment of rectal cancer.

To improve local disease control, the use of preoperative radiotherapy either alone or combined with chemotherapy has become standard practice in rectal cancer, but it is unclear how these treatments modify the antitumoral immune response. We aimed to evaluate tumor histopathologic features and the prognostic effect of host immune response in rectal cancer with variable treatment modalities. Ninety-five rectal cancers with short-course radiotherapy (SRT), 97 with long-course chemoradiotherapy (CRT), and 154 without preoperative treatments, were evaluated for histopathologic features including Crohn's-like reaction (CLR). CD3+ and CD8+ immunohistochemistry and tumor cells were analyzed from tumor tissue microarray samples to calculate T-cell densities and G-cross function values to estimate cancer cell-T-cell co-localization (proximity score). We found that lymphocyte densities were diminished after SRT, but CLR was scarcer after CRT. Proximity score and CLR density were prognostic for survival in cancer without preoperative treatments and could be combined into an enhanced prognostic score (immune grade). In the irradiated tumors, CLR density remained prognostic while the impact of T-cell infiltration was insufficient alone. In multivariable analysis, the immune grade proved to be an independent prognostic factor for survival. In conclusion, the immune contexture of rectal cancer harbors prognostic significance even after preoperative radiotherapy.

Establishing Criteria for Tumor Necrosis as Prognostic Indicator in Colorectal Cancer.

Tumor necrosis has been reported to represent an independent prognostic factor in colorectal cancer, but its evaluation methods have not been described in sufficient detail to introduce tumor necrosis evaluation into clinical use. To study the potential of tumor necrosis as a prognostic indicator in colorectal cancer, criteria for 3 methods for its evaluation were defined: the average percentage method (tumor necrosis percentage of the whole tumor), the hotspot method (tumor necrosis percentage in a single hotspot), and the linear method (the diameter of the single largest necrotic focus). Cox regression models were used to calculate cancer-specific mortality hazard ratios (HRs) for tumor necrosis categories in 2 colorectal cancer cohorts with more than 1800 cases. For reproducibility assessment, 30 cases were evaluated by 9 investigators, and Spearman's rank correlation coefficients and Cohen's kappa coefficients were calculated. We found that all 3 methods predicted colorectal cancer-specific survival independent of other prognostic parameters, including disease stage, lymphovascular invasion, and tumor budding. The greatest multivariable HRs were observed for the average percentage method (cohort 1: HR for ≥ 40% vs. <3% 3.03, 95% CI, 1.93-4.78; cohort 2: HR for ≥ 40% vs. < 3% 2.97; 95% CI, 1.63-5.40). All 3 methods had high reproducibility, with the linear method showing the highest mean Spearman's correlation coefficient (0.91) and Cohen's kappa (0.70). In conclusion, detailed criteria for tumor necrosis evaluation were established. All 3 methods showed good reproducibility and predictive ability. The findings pave the way for the use of tumor necrosis as a prognostic factor in colorectal cancer.

Training immunophenotyping deep learning models with the same-section ground truth cell label derivation method improves virtual staining accuracy.

Introduction: Deep learning (DL) models predicting biomarker expression in images of hematoxylin and eosin (H&E)-stained tissues can improve access to multi-marker immunophenotyping, crucial for therapeutic monitoring, biomarker discovery, and personalized treatment development. Conventionally, these models are trained on ground truth cell labels derived from IHC-stained tissue sections adjacent to H&E-stained ones, which might be less accurate than labels from the same section. Although many such DL models have been developed, the impact of ground truth cell label derivation methods on their performance has not been studied. Methodology: In this study, we assess the impact of cell label derivation on H&E model performance, with CD3+ T-cells in lung cancer tissues as a proof-of-concept. We compare two Pix2Pix generative adversarial network (P2P-GAN)-based virtual staining models: one trained with cell labels obtained from the same tissue section as the H&E-stained section (the 'same-section' model) and one trained on cell labels from an adjacent tissue section (the 'serial-section' model). Results: We show that the same-section model exhibited significantly improved prediction performance compared to the 'serial-section' model. Furthermore, the same-section model outperformed the serial-section model in stratifying lung cancer patients within a public lung cancer cohort based on survival outcomes, demonstrating its potential clinical utility. Discussion: Collectively, our findings suggest that employing ground truth cell labels obtained through the same-section approach boosts immunophenotyping DL solutions.

Toll-like receptors 1-9 in small bowel neuroendocrine tumors-Clinical significance and prognosis.

Toll-like receptors (TLRs) are pattern recognition receptors of the innate immunity. TLRs are known to mediate both antitumor effects and tumorigenesis. TLRs are abundant in many cancers, but their expression in small bowel neuroendocrine tumors (SB-NETs) is unknown. We aimed to characterize the expression of TLRs 1-9 in SB-NETs and lymph node metastases and evaluate their prognostic relevance. The present study included 125 patients with SB-NETs, of whom 95 had lymph node metastases, from two Finnish hospitals. Tissue samples were stained immunohistochemically for TLR expression, assessed based on cytoplasmic and nucleic staining intensity and percentage of positively stained cells. Statistical methods for survival analysis included Kaplan-Meier method and Cox regression adjusted for confounding factors. Disease-specific survival (DSS) was the primary outcome. TLRs 1-2 and 4-9 were expressed in SB-NETs and lymph node metastases. TLR3 showed no positive staining. In primary SB-NETs, TLRs 1-9 were not associated with survival. For lymph node metastases, high cytoplasmic TLR7 intensity associated with worse DSS compared to low cytoplasmic intensity (26.4% vs. 84.9%, p = 0.028). Adjusted mortality hazard (HR) was 3.90 (95% CI 1.07-14.3). The expression of TLRs 1-6 and 8-9 in lymph node metastases were not associated with survival. SB-NETs and their lymph node metastases express cytoplasmic TLR 1-2 and 4-9 and nucleic TLR5. High TLR7 expression in SB-NET lymph node metastases was associated with worse prognosis. The current research has future perspective, as it can help create base for clinical drug trials to target specific TLRs with agonists or antagonists to treat neuroendocrine tumors.

Appendectomy and Long-term Colorectal Cancer Incidence, Overall and by Tumor Fusobacterium nucleatum Status.

OBJECTIVE: To test hypotheses that appendectomy history might lower long-term colorectal cancer risk and that the risk reduction might be strong for tumors enriched with Fusobacterium nucleatum, bacterial species implicated in colorectal carcinogenesis. BACKGROUND: The absence of the appendix, an immune system organ and a possible reservoir of certain pathogenic microbes, may affect the intestinal microbiome, thereby altering long-term colorectal cancer risk. METHODS: Utilizing databases of prospective cohort studies, namely the Nurses' Health Study and the Health Professionals Follow-up Study, we examined the association of appendectomy history with colorectal cancer incidence overall and subclassified by the amount of tumor tissue Fusobacterium nucleatum​​ (Fusobacterium animalis). We used an inverse probability weighted multivariable-adjusted duplication-method Cox proportional hazards regression model. RESULTS: During the follow-up of 139,406 participants (2,894,060 person-years), we documented 2811 incident colorectal cancer cases, of which 1065 cases provided tissue F. nucleatum analysis data. The multivariable-adjusted hazard ratio of appendectomy for overall colorectal cancer incidence was 0.92 (95% CI, 0.84-1.01). Appendectomy was associated with lower F. nucleatum-positive cancer incidence (multivariable-adjusted hazard ratio, 0.53; 95% CI, 0.33-0.85; P=0.0079), but not F. nucleatum-negative cancer incidence (multivariable-adjusted hazard ratio, 0.98; 95% CI, 0.83-1.14), suggesting a differential association by F. nucleatum status (Pheterogeneity=0.015). This differential association appeared to persist in various participant/patient strata including tumor location and microsatellite instability status. CONCLUSIONS: Appendectomy likely lowers the future long-term incidence of F. nucleatum-positive (but not F. nucleatum-negative) colorectal cancer. Our findings do not support the existing hypothesis that appendectomy may increase colorectal cancer risk.

CD3+ and CD8+ T cell-based immune cell score as a prognostic factor in clear-cell renal cell carcinoma.

BACKGROUND AND PURPOSE: Immunoscore® is a prognostic parameter based on densities of lymphocyte populations in the tumor center and invasive margin. Immunoscore® is validated in colorectal cancer as a high Immunoscore® is associated with longer survival. Previous studies have suggested that Immunoscore® may also predict oncological outcomes in clear-cell renal cell carcinoma (ccRCC). This study aims to assess the prognostic role of immune cell score in ccRCC. MATERIAL AND METHODS: All patients with ccRCC undergoing surgery between 2007 and 2020 in Central Finland Central Hospital were retrospectively identified. CD3+ and CD8+ cell densities were calculated from tissue samples to determine the immune cell score using Immunoscore® principles. Receiver-operating characteristic analysis, Kaplan-Meier survival curve, and Cox regression were used to evaluate the association between immune cell score and survival. RESULTS: A total of 203 patients (mean age 66.5 years) were identified. The median follow-up time was 6.2 years. Based on the immune cell score, the patients were divided into three groups: low, intermediate, and high. In Cox regression analysis, adjusted with age, sex, and Charlson Comorbidity Index, no significant differences in disease-specific mortality were observed among the three groups. The hazard ratios (HRs) for disease-specific mortality were 0.93 (95% confidence interval [CI] 0.48-1.79) and 1.12 (0.52-2.37) for intermediate- and high-immune cell score groups when compared to low-immune cell score group, respectively. INTERPRETATION: This study found no association between immune cell score and survival. These results indicate that immune cell score may not serve as a prognostic tool in ccRCC.

Multiplexed analysis of macrophage polarisation in pulmonary metastases of microsatellite stable colorectal cancer.

Tumour-associated macrophages (TAMs) express a continuum of phenotypes ranging from an anti-tumoural M1-like phenotype to a pro-tumoural M2-like phenotype. During cancer progression, TAMs may shift to a more M2-like polarisation state, but the role of TAMs in CRC metastases is unclear. We conducted a comprehensive spatial and prognostic analysis of TAMs in CRC pulmonary metastases and corresponding primary tumours using multiplexed immunohistochemistry and machine learning-based image analysis. We obtained data from 106 resected pulmonary metastases and 74 corresponding primary tumours. TAMs in the resected pulmonary metastases were located closer to the cancer cells and presented a more M2-like polarised state in comparison to the primary tumours. Higher stromal M2-like macrophage densities in the invasive margin of pulmonary metastases were associated with worse 5-year overall survival (HR 3.19, 95% CI 1.35-7.55, p = 0.008). The results of this study highlight the value of multiplexed analysis of macrophage polarisation in cancer metastases and might have clinical implications in future cancer therapy.

Quantitative Multiplexed Analysis of Indoleamine 2,3-Dioxygenase (IDO) and Arginase-1 (ARG1) Expression and Myeloid Cell Infiltration in Colorectal Cancer.

Indoleamine 2,3-dioxygenase (IDO) and arginase-1 (ARG1) are amino acid-metabolizing enzymes, frequently highly expressed in cancer. Their expression may deplete essential amino acids, lead to immunosuppression, and promote cancer growth. Still, their expression patterns, prognostic significance, and spatial localization in the colorectal cancer microenvironment are incompletely understood. Using a custom 10-plex immunohistochemistry assay and supervised machine learning-based digital image analysis, we characterized IDO and ARG1 expression in monocytic cells, granulocytes, mast cells, and tumor cells in 833 colorectal cancer patients. We evaluated the prognostic value and spatial arrangement of IDO- and ARG1-expressing myeloid and tumor cells. IDO was mainly expressed not only by monocytic cells but also by some tumor cells, whereas ARG1 was predominantly expressed by granulocytes. Higher density of IDO+ monocytic cells was an independent prognostic factor for improved cancer-specific survival both in the tumor center (Ptrend = .0002; hazard ratio [HR] for the highest ordinal category Q4 [vs Q1], 0.51; 95% CI, 0.33-0.79) and the invasive margin (Ptrend = .0015). Higher density of granulocytes was associated with prolonged cancer-specific survival in univariable models, and higher FCGR3+ARG1+ neutrophil density in the tumor center also in multivariable analysis (Ptrend = .0020). Granulocytes were, on average, located closer to tumor cells than monocytic cells. Furthermore, IDO+ monocytic cells and ARG1- granulocytes were closer than IDO- monocytic cells and ARG1+ granulocytes, respectively. The mRNA expression of the IDO1 gene was assessed in myeloid and tumor cells using publicly available single-cell RNA sequencing data for 62 colorectal cancers. IDO1 was mainly expressed in monocytes and dendritic cells, and high IDO1 activity in monocytes was associated with enriched immunostimulatory pathways. Our findings provided in-depth information about the infiltration patterns and prognostic value of cells expressing IDO and/or ARG1 in the colorectal cancer microenvironment, highlighting the significance of host immune response in tumor progression.

Inverse relationship between Fusobacterium nucleatum amount and tumor CD274 (PD-L1) expression in colorectal carcinoma.

Objectives: The CD274 (programmed cell death 1 ligand 1, PD-L1)/PDCD1 (programmed cell death 1, PD-1) immune checkpoint axis is known to regulate the antitumor immune response. Evidence also supports an immunosuppressive effect of Fusobacterium nucleatum. We hypothesised that tumor CD274 overexpression might be inversely associated with abundance of F. nucleatum in colorectal carcinoma. Methods: We assessed tumor CD274 expression by immunohistochemistry and F. nucleatum DNA within tumor tissue by quantitative PCR in 812 cases among 4465 incident rectal and colon cancer cases that had occurred in two prospective cohort studies. Multivariable logistic regression analyses with inverse probability weighting were used to adjust for selection bias because of tissue data availability and potential confounders including microsatellite instability status, CpG island methylator phenotype, LINE-1 methylation level and KRAS, BRAF and PIK3CA mutations. Results: Fusobacterium nucleatum DNA was detected in tumor tissue in 109 (13%) cases. Tumor CD274 expression level was inversely associated with the amount of F. nucleatum in colorectal cancer tissue (P = 0.0077). For one category-unit increase in three ordinal F. nucleatum categories (negative vs. low vs. high), multivariable-adjusted odds ratios (with 95% confidence interval) of the low, intermediate and high CD274 categories (vs. negative) were 0.78 (0.41-1.51), 0.64 (0.32-1.28) and 0.50 (0.25-0.99), respectively (P trend = 0.032). Conclusions: Tumor CD274 expression level was inversely associated with the amount of F. nucleatum in colorectal cancer tissue, suggesting that different immunosuppressive mechanisms (i.e. PDCD1 immune checkpoint activation and tumor F. nucleatum enrichment) tend to be used by different tumor subgroups.

Results of intention-to-treat pulmonary metastasectomies in northern Finland revealing significant number of new lung primary carcinomas: time to move on from wedge resections?

Background: A considerable proportion of intended pulmonary metastasectomies is known to turn out as new incidental primary lung cancers in final pathology. We aimed to analyse the trends and results of pulmonary metastasectomies using the intention-to-treat approach with an emphasis on final histopathological findings. Methods: All intention-to-treat pulmonary metastasectomies performed in Oulu University Hospital between 2000 and 2020 were included in the study. Long term survival was analysed with the Kaplan-Meier method and log-rank tests. A binary logistic regression analysis was performed to calculate odds ratios for incidental primary lung cancer in final histology. Results: A total of 154 intended pulmonary metastasectomies were performed to 127 individual patients. There was an increasing trend in pulmonary metastasectomies during the study period. Despite the increasing trend in comorbidities of the operated patients, the length of hospital stays decreased, and the postoperative complication rates remained stable. In final pathology reports, 9.7% were new primary lung cancers and 13.0% were benign nodules. A long disease-free interval (≥24 months) and smoking history were associated with incidental primary lung cancer in final histology. The short-term 30- and 90-day mortalities after pulmonary metastasectomy were 0.7%. The 5-year survival after pulmonary metastasectomy from all histologies was 52.8%, and from colorectal cancer metastasectomies (n=34) it was 73.5%. Conclusions: The significant amount of new primary lung cancer lesions in pulmonary metastasectomy specimens highlight the diagnostic importance of pulmonary metastasectomy. A segmentectomy could be considered as a primary procedure in pulmonary metastasectomy in patients with a long disease-free interval and a heavy smoking history.

Tertiary lymphoid structures in pulmonary metastases of microsatellite stable colorectal cancer.

Tertiary lymphoid structures (TLSs) are ectopic lymphoid aggregates located at sites of chronic inflammation and recognized as prognosticators in several cancers. We aimed to analyse the prognostic effect of TLSs in colorectal cancer (CRC) pulmonary metastases and primary tumours, with a comparison to the CD3+ and CD8+ cell density-based immune cell score (ICS). For TLS density and TLS maximum diameter analysis, 67 pulmonary metastases and 63 primary tumours were stained with haematoxylin and eosin. For ICS scoring and analysis, CD3 and CD8 immunohistochemistry was performed. Excellent interobserver agreement was achieved in all TLS measurements. Of all patients, 36 patients had low TLS density (< 0.222 follicles/mm) and 31 patients had high TLS density (≥ 0.222 follicles/mm) in the first resected pulmonary metastases. TLS density (adjusted HR 0.91, 0.48-1.73) or maximum diameter (adjusted HR 0.78, 0.40-1.51) did not have prognostic value in pulmonary metastases. In primary tumours, higher TLS density (adjusted HR 0.39, 0.18-0.87) and maximum diameter (adjusted HR 0.28, 0.11-0.73) were associated with lower mortality. In the pulmonary metastases, ICS had superior prognostic value to TLSs; however, TLSs and ICS were significantly associated. In conclusion, TLSs in CRC pulmonary metastases had no prognostic value but correlated with the ICS. TLSs in primary tumours associated with favourable prognosis.

Bayesian risk prediction model for colorectal cancer mortality through integration of clinicopathologic and genomic data.

Routine tumor-node-metastasis (TNM) staging of colorectal cancer is imperfect in predicting survival due to tumor pathobiological heterogeneity and imprecise assessment of tumor spread. We leveraged Bayesian additive regression trees (BART), a statistical learning technique, to comprehensively analyze patient-specific tumor characteristics for the improvement of prognostic prediction. Of 75 clinicopathologic, immune, microbial, and genomic variables in 815 stage II-III patients within two U.S.-wide prospective cohort studies, the BART risk model identified seven stable survival predictors. Risk stratifications (low risk, intermediate risk, and high risk) based on model-predicted survival were statistically significant (hazard ratios 0.19-0.45, vs. higher risk; P < 0.0001) and could be externally validated using The Cancer Genome Atlas (TCGA) data (P = 0.0004). BART demonstrated model flexibility, interpretability, and comparable or superior performance to other machine-learning models. Integrated bioinformatic analyses using BART with tumor-specific factors can robustly stratify colorectal cancer patients into prognostic groups and be readily applied to clinical oncology practice.

Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer.

Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR from histopathological images of colorectal cancer. The method is based on convolutional neural networks which were trained to classify colorectal cancer tissue in hematoxylin-eosin stained samples into three classes: stroma, tumor and other. The models were trained using a data set that consists of 1343 whole slide images. Three different training setups were applied with a transfer learning approach using domain-specific data i.e. an external colorectal cancer histopathological data set. The three most accurate models were chosen as a classifier, TSR values were predicted and the results were compared to a visual TSR estimation made by a pathologist. The results suggest that classification accuracy does not improve when domain-specific data are used in the pre-training of the convolutional neural network models in the task at hand. Classification accuracy for stroma, tumor and other reached 96.1% on an independent test set. Among the three classes the best model gained the highest accuracy (99.3%) for class tumor. When TSR was predicted with the best model, the correlation between the predicted values and values estimated by an experienced pathologist was 0.57. Further research is needed to study associations between computationally predicted TSR values and other clinicopathological factors of colorectal cancer and the overall survival of the patients.

Immunological and prognostic significance of tumour necrosis in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) causes the second most cancer deaths worldwide, but the disease course varies according to tumour characteristics and immunological factors. Our objective was to examine the associations of tumour necrosis with tumour characteristics, immune cell infiltrates, serum cytokine concentrations, as well as prognosis in CRC. METHODS: Three independent CRC cohorts, including 1413 patients, were analysed. Associations of the areal percentage of tumour necrosis with clinicopathologic parameters, tumour infiltrating immune cells, cytokine concentrations in systemic and mesenteric vein blood, and survival were examined. RESULTS: Higher tumour necrosis percentage associated with shorter colorectal cancer-specific survival independent of tumour grade, T, N or M-class, mismatch repair status, BRAF status, and other possible confounding factors. In the largest cohort (N = 1100), the HR for high tumour necrosis percentage (≥40% vs. <3%) was 3.22 (95% CI 1.68-6.17, Ptrend < 0.0001). Tumour necrosis percentage positively correlated with peripheral serum levels of CXCL8, a proinflammatory chemokine, and negatively correlated with mesenteric serum levels of CXCL10 and mast cell densities in the invasive margin of the tumour. CONCLUSIONS: Our results support the value of tumour necrosis as a prognostic factor in colorectal cancer. CXCL8 may have a role in the systemic effects of tumour necrosis.

Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients.

Histopathologic assessment is indispensable for diagnosing colorectal cancer (CRC). However, manual evaluation of the diseased tissues under the microscope cannot reliably inform patient prognosis or genomic variations crucial for treatment selections. To address these challenges, we develop the Multi-omics Multi-cohort Assessment (MOMA) platform, an explainable machine learning approach, to systematically identify and interpret the relationship between patients' histologic patterns, multi-omics, and clinical profiles in three large patient cohorts (n = 1888). MOMA successfully predicts the overall survival, disease-free survival (log-rank test P-value<0.05), and copy number alterations of CRC patients. In addition, our approaches identify interpretable pathology patterns predictive of gene expression profiles, microsatellite instability status, and clinically actionable genetic alterations. We show that MOMA models are generalizable to multiple patient populations with different demographic compositions and pathology images collected from distinctive digitization methods. Our machine learning approaches provide clinically actionable predictions that could inform treatments for colorectal cancer patients.

Spatially resolved multimarker evaluation of CD274 (PD-L1)/PDCD1 (PD-1) immune checkpoint expression and macrophage polarisation in colorectal cancer.

BACKGROUND: The CD274 (PD-L1)/PDCD1 (PD-1) immune checkpoint interaction may promote cancer progression, but the expression patterns and prognostic significance of PD-L1 and PD-1 in the colorectal cancer microenvironment are inadequately characterised. METHODS: We used a custom 9-plex immunohistochemistry assay to quantify the expression patterns of PD-L1 and PD-1 in macrophages, T cells, and tumour cells in 910 colorectal cancer patients. We evaluated cancer-specific mortality according to immune cell subset densities using multivariable Cox regression models. RESULTS: Compared to PD-L1- macrophages, PD-L1+ macrophages were more likely M1-polarised than M2-polarised and located closer to tumour cells. PD-L1+ macrophage density in the invasive margin associated with longer cancer-specific survival [Ptrend = 0.0004, HR for the highest vs. lowest quartile, 0.52; 95% CI: 0.34-0.78]. T cell densities associated with longer cancer-specific survival regardless of PD-1 expression (Ptrend < 0.005 for both PD-1+ and PD-1- subsets). Higher densities of PD-1+ T cell/PD-L1+ macrophage clusters associated with longer cancer-specific survival (Ptrend < 0.005). CONCLUSIONS: PD-L1+ macrophages show distinct polarisation profiles (more M1-like), spatial features (greater co-localisation with tumour cells and PD-1+ T cells), and associations with favourable clinical outcome. Our comprehensive multimarker assessment could enhance the understanding of immune checkpoints in the tumour microenvironment and promote the development of improved immunotherapies.

A pan-cancer analysis shows immunoevasive characteristics in NRF2 hyperactive squamous malignancies.

The NRF2 pathway is frequently activated in various cancer types, yet a comprehensive analysis of its effects across different malignancies is currently lacking. We developed a NRF2 activity metric and utilized it to conduct a pan-cancer analysis of oncogenic NRF2 signaling. We identified an immunoevasive phenotype where high NRF2 activity is associated with low interferon-gamma (IFNγ), HLA-I expression and T cell and macrophage infiltration in squamous malignancies of the lung, head and neck area, cervix and esophagus. Squamous NRF2 overactive tumors comprise a molecular phenotype with SOX2/TP63 amplification, TP53 mutation and CDKN2A loss. These immune cold NRF2 hyperactive diseases are associated with upregulation of immunomodulatory NAMPT, WNT5A, SPP1, SLC7A11, SLC2A1 and PD-L1. Based on our functional genomics analyses, these genes represent candidate NRF2 targets, suggesting direct modulation of the tumor immune milieu. Single-cell mRNA data shows that cancer cells of this subtype exhibit decreased expression of IFNγ responsive ligands, and increased expression of immunosuppressive ligands NAMPT, SPP1 and WNT5A that mediate signaling in intercellular crosstalk. In addition, we discovered that the negative relationship of NRF2 and immune cells are explained by stromal populations of lung squamous cell carcinoma, and this effect spans multiple squamous malignancies based on our molecular subtyping and deconvolution data.

The prognostic role of tumor budding and tumor-stroma ratio in pulmonary metastasis of colorectal carcinoma.

OBJECTIVE: To evaluate the prognostic value of tumor budding and tumor-stroma ratio (TSR) in resected pulmonary metastases of colorectal carcinoma (CRC). METHODS: In total, 106 pulmonary metastasectomies were performed to 74 patients in two study hospitals during 2000-2020. All relevant clinical data were retrospectively collected. Tumor budding based on the International Tumor Budding Consensus Conference recommendations and TSR in the first resected pulmonary metastases and primary tumors were evaluated from diagnostic hematoxylin-eosin-stained histopathological slides. RESULTS: 60 patients (85.7%) had low tumor budding (≤5 buds/field) and 10 patients (14.3%) had high tumor budding (>5 buds/field) in their first pulmonary metastases of CRC. 5-year overall survival rates of pulmonary metastasectomy in low and high total tumor budding were 28.3% and 37.3% (p = 0.387), respectively. 19 patients (27.1%) had low TSR and 51 patients (72.9%) had high TSR. The 5-year overall survival rates were 32.9% in low and 28.6% in high TSR of first pulmonary metastases (p = 0.746). Tumor budding and TSR did not provide prognostic value in Cox multivariate analysis. Tumor budding and TSR in resected pulmonary metastases were not associated with those of the primary tumor. CONCLUSION: Tumor budding and TSR in the resected pulmonary metastases of CRC showed no statistically significant prognostic value, however, additional well-powered confirmatory studies are needed.