Analytical validation of the Immunoscore and its associated prognostic value in patients with colon cancer

OralEpitheliumDB: A Dataset for Oral Epithelial Dysplasia Image Segmentation and Classification

Early diagnosis of potentially malignant disorders, such as oral epithelial dysplasia, is the most reliable way to prevent oral cancer. Computational algorithms have been used as an auxiliary tool to aid specialists in this process. Usually, experiments are performed on private data, making it difficult to reproduce the results. There are several public datasets of histological images, but studies focused on oral dysplasia images use inaccessible datasets. This prevents the improvement of algorithms aimed at this lesion. This study introduces an annotated public dataset of oral epithelial dysplasia tissue images. The dataset includes 456 images acquired from 30 mouse tongues. The images were categorized among the lesion grades, with nuclear structures manually marked by a trained specialist and validated by a pathologist. Also, experiments were carried out in order to illustrate the potential of the proposed dataset in classification and segmentation processes commonly explored in the literature. Convolutional neural network (CNN) models for semantic and instance segmentation were employed on the images, which were pre-processed with stain normalization methods. Then, the segmented and non-segmented images were classified with CNN architectures and machine learning algorithms. The data obtained through these processes is available in the dataset. The segmentation stage showed the F1-score value of 0.83, obtained with the U-Net model using the ResNet-50 as a backbone. At the classification stage, the most expressive result was achieved with the Random Forest method, with an accuracy value of 94.22%. The results show that the segmentation contributed to the classification results, but studies are needed for the improvement of these stages of automated diagnosis. The original, gold standard, normalized, and segmented images are publicly available and may be used for the improvement of clinical applications of CAD methods on oral epithelial dysplasia tissue images.

Predictors of response to immunotherapy in colorectal cancer

Colorectal cancer (CRC) is a major cause of cancer-related deaths globally. While treatment advancements have improved survival rates, primarily through targeted therapies based on KRAS, NRAS, and BRAF mutations, personalized treatment strategies for CRC remain limited. Immunotherapy, mainly immune checkpoint blockade, has shown efficacy in various cancers but is effective in only a small subset of patients with CRC with deficient mismatch repair (dMMR) proteins or high microsatellite instability (MSI). Recent research has challenged the notion that CRC is immunologically inert, revealing subsets with high immunogenicity and diverse lymphocytic infiltration. Identifying precise biomarkers beyond dMMR and MSI is crucial to expanding immunotherapy benefits. Hence, exploration has extended to various biomarker sources, such as the tumor microenvironment, genomic markers, and gut microbiota. Recent studies have introduced a novel classification system, consensus molecular subtypes, that aids in identifying patients with CRC with an immunogenic profile. These findings underscore the necessity of moving beyond single biomarkers and toward a comprehensive understanding of the immunological landscape in CRC, facilitating the development of more effective, personalized therapies.

Failed Induction of the TH1 System in TH2 Dominant Patients: The Cancer-Permissive Immune Macroenvironment

Tumor microenvironment infiltration by cells of the T helper cell type 1 (TH1) system, including TH1 cells, M1 macrophages, natural killer cells, and CD8+ T cells, is associated with better cancer prognosis. In contrast, tumor microenvironment infiltration by cells of the TH2 system, including TH2 cells, M2 macrophages, and innate lymphoid cells type 2, as well as immune suppressive myeloid-derived suppressor cells and regulatory T cells, is associated with poorer cancer prognosis. Beyond the tumor itself and a myriad of other modifying factors, such as genetic and epigenetic influences on tumorigenesis, the overall immune state of the patient, termed the macroenvironment, has also been shown to significantly influence cancer outcomes. Alterations in the tricarboxylic acid (TCA) cycle (TCA cycle breaks) involving loss of function of succinate dehydrogenase, isocitrate dehydrogenase, and fumarate hydratase have been shown to be associated with an intracellular metabolic shift away from oxidative phosphorylation and into glycolysis in cells that are transforming into cancer cells. The same loss of function of succinate dehydrogenase and isocitrate dehydrogenase has also been identified as inducing a shift in macrophages toward glycolysis that is associated with M1 macrophage polarization. M1 macrophages make interleukin 12, which stimulates TH1 cells and natural killer cells to produce interferon gamma (IFN-γ), which in turn stimulates M1 macrophage activity, forming an activation loop. IFN-γ also drives activation of CD8+ T cells. Thus, M1 macrophage activation initiates and sustains activation of the TH1 system of cells. In this fashion, TCA cycle breaks at succinate dehydrogenase and isocitrate dehydrogenase that promote cellular transformation into cancer cells are also associated with upregulation of the TH1 system that provides anti-cancer immune surveillance. The TH1 and TH2 systems are known to inhibit each other's activation. It is this author's hypothesis that, in patients whose macroenvironment is sufficiently TH2-dominant, the metabolic shift toward glycolysis induced by TCA cycle breaks that gives rise to mutagenic changes in tissue parenchymal cells is not counterbalanced by adequate activation of M1 macrophages, thus giving rise to cancer cell development. For instance, the atopic TH2-high asthma phenotype, a TH2 dominance-based comorbidity, is associated with a more than doubled incidence of colon, breast, lung, and prostate cancer, compared with non-asthmatics. Failure of TCA cycle breaks to induce M1 polarization of tissue-resident macrophages yields a tissue environment in which the tissue-resident macrophages fail to routinely perform M1-associated functions such as phagocytizing newly developing cancer cells. Failure of M1 phenotypic expression in both tissue-resident macrophages and monocyte-derived macrophages recruited to the tumor microenvironment yields both a loss of direct antitumor M1 macrophage actions and failure of TH1 system activation in general, including failure of CD8+ T cell activation, yielding a cancer-permissive tumor microenvironment and a poorer prognosis in patients with existing cancers. This paper proposes a conceptual framework that connects established elements in the existing research and points to the utility of a patient profiling process, aimed at personalization of treatment through identification and targeting of elements in each patient's tumor microenvironment and macroenvironment that contribute to unfavorable prognosis.

Principles of risk assessment in colon cancer: immunity is key

In clinical practice, the administration of adjuvant chemotherapy (ACT) following tumor surgical resection raises a critical dilemma for stage II colon cancer (CC) patients. The prognostic features used to identify high-risk CC patients rely on the pathological assessment of tumor cells. Currently, these factors are considered for stratifying patients who may benefit from ACT at early CC stages. However, the extent to which these factors predict clinical outcomes (i.e. recurrence, survival) remains highly controversial, also uncertainty persists regarding patients' response to treatment, necessitating further investigation. Therefore, an imperious need is to explore novel biomarkers that can reliably stratify patients at risk, to optimize adjuvant treatment decisions. Recently, we evaluated the prognostic and predictive value of Immunoscore (IS), an immune digital-pathology assay, in stage II CC patients. IS emerged as the sole significant parameter for predicting disease-free survival (DFS) in high-risk patients. Moreover, IS effectively stratified patients who would benefit most from ACT based on their risk of recurrence, thus predicting their outcomes. Notably, our findings revealed that digital IS outperformed the visual quantitative assessment of the immune response conducted by expert pathologists. The latest edition of the WHO classification for digestive tumor has introduced the evaluation of the immune response, as assessed by IS, as desirable and essential diagnostic criterion. This supports the revision of current cancer guidelines and strongly recommends the implementation of IS into clinical practice as a patient stratification tool, to guide CC treatment decisions. This approach may provide appropriate personalized therapeutic decisions that could critically impact early-stage CC patient care.

Digital Pathology for Better Clinical Practice

(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin-eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists' evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.

Effects of tumour budding on adjuvant chemotherapy in colorectal cancer

BACKGROUND

High tumour budding has been indicated as a risk factor of poor survival in colorectal cancer. This study aimed to investigate the impact of tumour budding grades and the use of adjuvant chemotherapy on prognosis in patients with colorectal cancer.

METHODS

This study included consecutive colorectal cancer patients who underwent radical surgery for primary colorectal adenocarcinoma at The Sixth Hospital of Sun Yat-sen University between 2009 and 2019. Tumour budding was assessed based on the recommendations of the International Tumor Budding Consensus Conference using haematoxylin and eosin (H&E)-stained slides with tumour samples. The primary outcome of interest was to correlate tumour budding with disease-free survival and overall survival; the secondary outcome was investigation of the impact of adjuvant therapy on different tumour budding grades. In addition, a subgroup analysis was performed for the effects of lymphocytic infiltration on adjuvant chemotherapy in patients with Bd3.

RESULTS

Of 709 eligible patients, 412 with colorectal cancer were included. According to the International Tumor Budding Consensus Conference, 210 (50.9 per cent), 127 (30.8 per cent) and 75 (18.2 per cent) were classified as low budding (Bd1), intermediate budding (Bd2) and high budding (Bd3) respectively. Patients with Bd1, Bd2 and Bd3 had 5-year disease-free survival rates of 82.9 per cent, 70.1 per cent and 49.3 per cent respectively, and 5-year overall survival rates of 90 per cent, 79.5 per cent and 62.7 per cent respectively (P <0.001). Adjuvant chemotherapy yielded a significant survival benefit in patients with Bd3 (5-year disease-free survival, 65 per cent versus 31.4 per cent, P <0.001; 5-year overall survival, 84.4 per cent versus 63.1 per cent, P <0.001), but not in those with Bd1 or Bd2. In patients with Bd3, the benefit of adjuvant chemotherapy was maintained in those with low, but not high lymphocytic infiltration.

CONCLUSION

High grade of tumour budding was strongly correlated with poorer survival outcomes in colorectal cancer. Patients with Bd3 benefited from adjuvant chemotherapy, with the exclusion of patients with high lymphocytic infiltration.

International Validation of the Immunoscore Biopsy in Patients With Rectal Cancer Managed by a Watch-and-Wait Strategy

PURPOSE

No biomarker capable of improving selection and monitoring of patients with rectal cancer managed by watch-and-wait (W&W) strategy is currently available. Prognostic performance of the Immunoscore biopsy (ISB) was recently suggested in a preliminary study.

METHODS

This international validation study included 249 patients with clinical complete response (cCR) managed by W&W strategy. Intratumoral CD3+ and CD8+ T cells were quantified on pretreatment rectal biopsies by digital pathology and converted to ISB. The primary end point was time to recurrence (TTR; the time from the end of neoadjuvant treatment to the date of local regrowth or distant metastasis). Associations between ISB and outcomes were analyzed by stratified Cox regression adjusted for confounders. Immune status of tumor-draining lymph nodes (n = 161) of 17 additional patients treated by neoadjuvant chemoradiotherapy and surgery was investigated by 3'RNA-Seq and immunofluorescence.

RESULTS

Recurrence-free rates at 5 years were 91.3% (82.4%-100.0%), 62.5% (53.2%-73.3%), and 53.1% (42.4%-66.5%) with ISB High, ISB Intermediate, and ISB Low, respectively (hazard ratio [HR; Low v High], 6.51; 95% CI, 1.99 to 21.28; log-rank P = .0004). ISB was also significantly associated with disease-free survival (log-rank P = .0002), and predicted both local regrowth and distant metastasis. In multivariate analysis, ISB was independent of patient age, sex, tumor location, cT stage (T, primary tumor; c, clinical), cN stage (N, regional lymph node; c, clinical), and was the strongest predictor for TTR (HR [ISB High v Low], 6.93; 95% CI, 2.08 to 23.15; P = .0017). The addition of ISB to a clinical-based model significantly improved the prediction of recurrence. Finally, B-cell proliferation and memory in draining lymph nodes was evidenced in the draining lymph nodes of patients with cCR.

CONCLUSION

The ISB is validated as a biomarker to predict both local regrowth and distant metastasis, with a gradual scaling of the risk of pejorative outcome.

Detection and quantitative analysis of tumor-associated tertiary lymphoid structures

Tumor-associated tertiary lymphoid structures (TLSs) are ectopic lymphoid formations within tumor tissue, with mainly B and T cell populations forming the organic aggregates. The presence of TLSs in tumors has been strongly associated with patient responsiveness to immunotherapy regimens and improving tumor prognosis. Researchers have been motivated to actively explore TLSs due to their bright clinical application prospects. Various studies have attempted to decipher TLSs regarding their formation mechanism, structural composition, induction generation, predictive markers, and clinical utilization. Meanwhile, the scientific approaches to qualitative and quantitative descriptions are crucial for TLS studies. In terms of detection, hematoxylin and eosin (H&E), multiplex immunohistochemistry (mIHC), multiplex immunofluorescence (mIF), and 12-chemokine gene signature have been the top approved methods. However, no standard methods exist for the quantitative analysis of TLSs, such as absolute TLS count, analysis of TLS constituent cells, structural features, TLS spatial location, density, and maturity. This study reviews the latest research progress on TLS detection and quantification, proposes new directions for TLS assessment, and addresses issues for the quantitative application of TLSs in the clinic.

Multi-Institutional Evaluation of Pathologists' Assessment Compared to Immunoscore

BACKGROUND

The Immunoscore (IS) is a quantitative digital pathology assay that evaluates the immune response in cancer patients. This study reports on the reproducibility of pathologists' visual assessment of CD3+- and CD8+-stained colon tumors, compared to IS quantification.

METHODS

An international group of expert pathologists evaluated 540 images from 270 randomly selected colon cancer (CC) cases. Concordance between pathologists' T-score, corresponding hematoxylin-eosin (H&E) slides, and the digital IS was evaluated for two- and three-category IS.

RESULTS

Non-concordant T-scores were reported in more than 92% of cases. Disagreement between semi-quantitative visual assessment of T-score and the reference IS was observed in 91% and 96% of cases before and after training, respectively. Statistical analyses showed that the concordance index between pathologists and the digital IS was weak in two- and three-category IS, respectively. After training, 42% of cases had a change in T-score, but no improvement was observed with a Kappa of 0.465 and 0.374. For the 20% of patients around the cut points, no concordance was observed between pathologists and digital pathology analysis in both two- and three-category IS, before or after training (all Kappa < 0.12).

CONCLUSIONS

The standardized IS assay outperformed expert pathologists' T-score evaluation in the clinical setting. This study demonstrates that digital pathology, in particular digital IS, represents a novel generation of immune pathology tools for reproducible and quantitative assessment of tumor-infiltrated immune cell subtypes.

A type I interferon footprint in pre-operative biopsies is an independent biomarker that in combination with CD8+ T cell quantification can improve the prediction of response to neoadjuvant treatment of rectal adenocarcinoma

Tailored treatment for patients with rectal cancer requires clinically available markers to predict their response to neoadjuvant treatment. The quantity of tumor-infiltrating lymphocytes (TILs) in pre-operative tumor biopsies has been suggested to predict a favorable response, but opposing results exist. A biopsy-adapted Immunoscore (ISB) based on TILs has recently emerged as a promising predictor of tumor regression and prognosis in (colo)rectal cancer. We aimed to refine the ISB for prediction of response using multiplex immunofluorescence (mIF) on pre-operative rectal cancer biopsies. We combined the distribution and density of conventional T cell subsets and γδT cells with a type I Interferon (IFN)-driven response assessed using Myxovirus resistance protein A (MxA) expression. We found that pathological complete response (pCR) following neoadjuvant treatment was associated with type I IFN. Stratification of patients according to the density of CD8+ in the entire tumor tissue and MxA+ cells in tumor stroma, where equal weight was assigned to both parameters, resulted in improved predictive quality compared to the ISB. This novel stratification approach using these two independent parameters in pre-operative biopsies could potentially aid in identifying patients with a good chance of achieving a pCR following neoadjuvant treatment.

Multicenter International Study of the Consensus Immunoscore for the Prediction of Relapse and Survival in Early-Stage Colon Cancer

Background: The prognostic value of Immunoscore was evaluated in Stage II/III colon cancer (CC) patients, but it remains unclear in Stage I/II, and in early-stage subgroups at risk. An international Society for Immunotherapy of Cancer (SITC) study evaluated the pre-defined consensus Immunoscore in tumors from 1885 AJCC/UICC-TNM Stage I/II CC patients from Canada/USA (Cohort 1) and Europe/Asia (Cohort 2). METHODS: Digital-pathology is used to quantify the densities of CD3+ and CD8+ T-lymphocyte in the center of tumor (CT) and the invasive margin (IM). The time to recurrence (TTR) was the primary endpoint. Secondary endpoints were disease-free survival (DFS), overall survival (OS), prognosis in Stage I, Stage II, Stage II-high-risk, and microsatellite-stable (MSS) patients. RESULTS: High-Immunoscore presented with the lowest risk of recurrence in both cohorts. In Stage I/II, recurrence-free rates at 5 years were 78.4% (95%-CI, 74.4−82.6), 88.1% (95%-CI, 85.7−90.4), 93.4% (95%-CI, 91.1−95.8) in low, intermediate and high Immunoscore, respectively (HR (Hi vs. Lo) = 0.27 (95%-CI, 0.18−0.41); p < 0.0001). In Cox multivariable analysis, the association of Immunoscore to outcome was independent (TTR: HR (Hi vs. Lo) = 0.29, (95%-CI, 0.17−0.50); p < 0.0001) of the patient’s gender, T-stage, sidedness, and microsatellite instability-status (MSI). A significant association of Immunoscore with survival was found for Stage II, high-risk Stage II, T4N0 and MSS patients. The Immunoscore also showed significant association with TTR in Stage-I (HR (Hi vs. Lo) = 0.07 (95%-CI, 0.01−0.61); P = 0.016). The Immunoscore had the strongest (69.5%) contribution χ2 for influencing survival. Patients with a high Immunoscore had prolonged TTR in T4N0 tumors even for patients not receiving chemotherapy, and the Immunoscore remained the only significant parameter in multivariable analysis. CONCLUSION: In early CC, low Immunoscore reliably identifies patients at risk of relapse for whom a more intensive surveillance program or adjuvant treatment should be considered.

Neo-peripheral adaptive immune score predicts neoadjuvant chemotherapy for locally advanced breast cancer

PURPOSE

Whether peripheral immune cell subsets can predict pathological complete response (pCR) in breast cancer patients remains to be elucidated. We aimed to dissect the relationship between peripheral immune cell subsets and pCR.

METHODS

Two hundred and twenty-six eligible patients from two prospective clinical trials (SHPD001 and SHPD002) in China were randomly divided into a training cohort and a validation cohort. The breast cancer subtypes in this study included hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative (n = 95), HER2-positive (n = 100), and triple negative (n = 31) breast cancer. We defined the "Neo-Peripheral Adaptive Immune Score" for neoadjuvant chemotherapy (neoPAI Score) based on the percentages of CD4 + T cells, CD8 + T cells, B cells, and the CD4 + /CD8 + ratio in peripheral blood. We also evaluated the ability of the neoPAI Score derived from tumor-infiltrating immune cells (TIICs) to predict survival by employing The Cancer Genome Atlas-Breast Cancer (TCGA-BRCA) database.

RESULTS

In the training cohort, multivariate analysis showed that HR status [odds ratio (OR) 0.325; 95% confidence interval (CI) 0.135-0.761; P = 0.010], HER2 status (OR 2.657; 95% CI 1.266-5.730; P = 0.011), Ki67 index (OR 3.191; 95% CI 1.509-6.956; P = 0.003), histological grade (OR 2.297; 95% CI 1.031-5.290; P = 0.045) and neoPAI Score (OR 4.451; 95% CI 1.608-13.068; P = 0.005) were independent predictors of pCR. In the validation cohort, histological grade (OR 3.779; 95% CI 3.793-1.136 × 10³; P = 0.008) and neoPAI Score (OR 90.828; 95% CI 3.827-9.843 × 10³; P = 0.019) were independent predictors of pCR. The Immune Model that integrated the neoPAI Score was more accurate in predicting pCR than the Clinical Model that exclusively contained clinicopathological parameters in both cohorts. In TCGA-BRCA database, the neoPAI Score constructed from TIICs can predict the progression-free interval (P = 0.048) of breast cancer.

CONCLUSION

The neoPAI Score defined by the percentages of peripheral immune cell subsets could be used as a potential biomarker for neoadjuvant chemotherapy efficacy.

Type I and II interferon signaling in colorectal cancer liver metastasis

Metastatic colorectal cancer is one of the leading causes of cancer-related deaths worldwide. Traditional chemotherapy extended the lifespan of cancer patients by only a few months, but targeted therapies and immunotherapy prolonged survival and led to long-term remissions in some cases. Type I and II interferons have direct pro-apoptotic and anti-proliferative effects on cancer cells and stimulate anti-cancer immunity. As a result, interferon production by cells in the tumor microenvironment is in the spotlight of immunotherapies as it affects the responses of anti-cancer immune cells. However, promoting effects of interferons on colorectal cancer metastasis have also been reported. Here we summarize our knowledge about pro- and anti-metastatic effects of type I and II interferons in colorectal cancer liver metastasis and discuss possible therapeutic implications.

Artificial intelligence for quantifying Crohn's-like lymphoid reaction and tumor-infiltrating lymphocytes in colorectal cancer

Crohn's-like lymphoid reaction (CLR) and tumor-infiltrating lymphocytes (TILs) are crucial for the host antitumor immune response. We proposed an artificial intelligence (AI)-based model to quantify the density of TILs and CLR in immunohistochemical (IHC)-stained whole-slide images (WSIs) and further constructed the CLR-I (immune) score, a tissue level- and cell level-based immune factor, to predict the overall survival (OS) of patients with colorectal cancer (CRC). The TILs score and CLR score were obtained according to the related density. And the CLR-I score was calculated by summing two scores. The development (Hospital 1, N = 370) and validation (Hospital 2 & 3, N = 144) cohorts were used to evaluate the prognostic value of the CLR-I score. The C-index and integrated area under the curve were used to assess the discrimination ability. A higher CLR-I score was associated with a better prognosis, which was identified by multivariable analysis in the development (hazard ratio for score 3 vs score 0 = 0.22, 95% confidence interval 0.12-0.40, P < 0.001) and validation cohort (0.21, 0.05-0.78, P = 0.020). The AI-based CLR-I score outperforms the single predictor in predicting OS which is objective and more prone to be deployed in clinical practice.

Tumor immune contexture is a determinant of anti-CD19 CAR T cell efficacy in large B cell lymphoma

Axicabtagene ciloleucel (axi-cel) is an anti-CD19 chimeric antigen receptor (CAR) T cell therapy approved for relapsed/refractory large B cell lymphoma (LBCL) and has treatment with similar efficacy across conventional LBCL subtypes. Toward patient stratification, we assessed whether tumor immune contexture influenced clinical outcomes after axi-cel. We evaluated the tumor microenvironment (TME) of 135 pre-treatment and post-treatment tumor biopsies taken from 51 patients in the ZUMA-1 phase 2 trial. We uncovered dynamic patterns that occurred within 2 weeks after axi-cel. The biological associations among Immunoscore (quantification of tumor-infiltrating T cell density), Immunosign 21 (expression of pre-defined immune gene panel) and cell subsets were validated in three independent LBCL datasets. In the ZUMA-1 trial samples, clinical response and overall survival were associated with pre-treatment immune contexture as characterized by Immunoscore and Immunosign 21. Circulating CAR T cell levels were associated with post-treatment TME T cell exhaustion. TME enriched for chemokines (CCL5 and CCL22), γ-chain receptor cytokines (IL-15, IL-7 and IL-21) and interferon-regulated molecules were associated with T cell infiltration and markers of activity. Finally, high density of regulatory T cells in pre-treatment TME associated with reduced axi-cel–related neurologic toxicity. These findings advance the understanding of LBCL TME characteristics associated with clinical responses to anti-CD19 CAR T cell therapy and could foster biomarker development and treatment optimization for patients with LBCL.

Analysis of tumor biopsies from the pivotal phase 1/2 ZUMA-1 trial identifies pre-treatment T cell–related characteristics that are associated with clinical response and neurologic toxicity after anti-CD19 CAR T cell therapy in patients with large B cell lymphoma.

Prognostic significance of immunoscore related markers in bladder cancer

BACKGROUND

The significance of total and specific subpopulations of tumor-infiltrating lymphocytes (TILs) in cancer is now well-documented. In the present study, we investigated the relevance of CD3+, CD8 +, CD45RO +, and FOXP3 + TILs to the prognosis and survival of patients with bladder cancer and the disease's clinical-pathological parameters.

METHODS

Infiltration of each subset was immunohistochemically evaluated in both stromal and intratumoral regions of tumor tissues from 85 patients with urothelial cell carcinoma of the bladder, with known survival.

RESULTS

Our results indicated that intratumoral CD45RO+ lymphocytes were significantly higher in high-grade tumors than in low-grade ones (P = 0.028). The frequencies of intratumoral CD3+ (P = 0.002), CD8 + (P = 0.008), intratumoral (P = 0.002), and stromal (P = 0.017) CD45RO+ lymphocytes were also higher in patients with muscular invasion than those without invasion. The frequencies of intratumoral CD3+ (P = 0.043), CD8+ (P = 0.003), CD45RO+ (P = 0.023), and total CD45RO+ (P = 0.015), showed variation in patients with different T-stage, as well; mostly increased in T2 versus Ta and T1. Comparing patients in different stages revealed an increase in the frequencies of total CD3+ (P = 0.011), intratumoral CD3+ (P = 0.006), total CD8+ (P = 0.012), intratumoral CD8+ (P = 0.009) and stromal CD8+ (P = 0.034), as well as total and stromal CD45RO+ lymphocytes (P = 0.01 and P = 0.034, respectively) in stage II comparing to stage I, while the frequencies of stromal CD3+ (P = 0.077) and CD8+ (P = 0.053) cells tended to be decreased in stage III compared to stage II.

CONCLUSIONS

We collectively observed that the frequency of immune cells, especially CD45RO+, CD3+, and CD8+ lymphocytes, were significantly higher in early-progressed tumors. This observation could be explained by continuous and prolonged stimulation of immune cells with tumor antigens during tumor progression or an increase in the recruiting factors, especially in the early stages, to eliminate tumor cells. However, with tumor progression to the late stages, the inhibitory microenvironment provided by tumor cells suppresses or changes the functionality of the effector and memory immune cells to help tumor growth. However, more functional studies with larger sample sizes are needed to reveal the real status of the immune system in patients with bladder cancer.

Predictive Value of Circulating Tumor Cells Based on Subtraction Enrichment for Recurrence Risk in Stage II Colorectal Cancer

Current guidelines recommend adjuvant chemotherapy (ACT) for stage II colorectal cancer (CRC) patients by using clinical high risk factors, with which circulating tumor cells (CTCs) were not considered. Here, an assessment to detect CTCs based on subtraction enrichment mediated by magnetic beads conjugated with CD45, immunofluorescence staining of CK, and fluorescence in situ hybridization of CEP8 is established. Both CEP8- and CK-positive CTCs have the potential to improve the risk stratification of stage II CRC patients. Patients with preoperative CTCs of ≥4 had a significantly higher recurrence risk than those with preoperative CTCs of <4 in two external validation cohorts (P < 0.0001). In the subgroup with clinical high risk, when preoperative CTCs were <4, patients did not benefit from ACT (P = 0.5764); however, when preoperative CTCs were ≥4, patients received benefit from ACT (P = 0.0064). Additionally, regardless of clinical risk status and preoperative CTC levels, if postoperative CTC levels were ≥4 for more than three consecutive time points (monitoring time interval, 2-6 months), the recurrence rate was 100%. Our findings suggested that the subtraction enrichment of CTCs could provide a reliable method to stratify the recurrence risk and make therapeutic decisions after surgery in stage II CRC patients.

Development of a Fully Automated Method to Obtain Reproducible Lymphocyte Counts in Patients With Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer worldwide. Although clinical outcome varies among patients diagnosed within the same TNM stage it is the cornerstone in treatment decisions as well as follow-up programmes. Tumor-infiltrating lymphocytes have added value when evaluating survival outcomes. The aim of this study was to develop a fully automated method for quantification of subsets of T lymphocytes in the invasive margin and central tumor in patients with CRC based on Deep Learning powered artificial intelligence. The study cohort consisted of 163 consecutive patients with a primary diagnosis of CRC followed by a surgical resection. Double-labeling immunohistochemical staining with cytokeratin in combination with CD3 or CD8, respectively, was performed on 1 representative slide from each patient. Visiopharm Quantitative Digital Pathology software was used to develop Application Protocol Packages for visualization of architectural details (background, normal epithelium, cancer epithelium, surrounding tissue), identification of central tumor and invasive margin as well as subsequent quantitative analysis of immune cells. Fully automated counts for CD3 and CD8 positive T cells were obtained in 93% and 92% of the cases, respectively. In the remaining cases, manual editing was required. In conclusion, the development of a fully automated method for counting CD3 + and CD8 + lymphocytes in a cohort of patients with CRC provided excellent results eliminating not only observer variability in lymphocyte counts but also in identifying the regions of interest for the quantitative analysis. Validation of the performance of the Application Protocol Packages including clinical correlation is needed.

Combination of CDX2 H-score quantitative analysis with CD3 AI-guided analysis identifies patients with a good prognosis only in stage III colon cancer

AIM

Stratification of colon cancer (CC) of patients with stage II and III for risk of relapse is still needed especially to drive adjuvant therapy administration. Our study evaluates the prognostic performance of two known biomarkers, CDX2 and CD3, standalone or their combined information in stage II and III CC.

PATIENTS AND METHODS

CDX2 and CD3 expression was evaluated in Prodige-13 study gathering 443 stage II and 398 stage III primary CC on whole slide colectomy. We developed for this study an H-score to quantify CDX2 expression and used our artificial intelligence (AI)-guided tissue analysis ColoClass to detect CD3 in tumour core and invasive margin. Association between biomarkers and relapse-free survival was investigated.

RESULTS

Univariate analysis showed that the combined variable CD3-TC and CD3-IM was associated with prognosis in both stage II and stage III. CDX2, on the contrary, was associated with prognosis only in stage III. We subsequently associated CDX2 and combined immune parameters only in stage III. This multivariate analysis allowed us to distinguish a proportion of stage III CC harbouring a high CDX2 expression and a high immune infiltration with a particularly good prognosis compared to their counterpart.

CONCLUSION

This study validated the prognostic role of CDX2 and CD3 evaluated with immunohistochemistry procedures in stage III but not in stage II. This association would be conceivable in a routine pathology laboratory and could help oncologist to consider chemotherapy de-escalation for a part of stage III patients.

The Immunological Contribution of a Novel Metabolism-Related Signature to the Prognosis and Anti-Tumor Immunity in Cervical Cancer

Cervical cancer is the most frequently diagnosed malignancy in the female reproductive system. Conventional stratification of patients based on clinicopathological characters has gradually been outpaced by a molecular profiling strategy. Our study aimed to identify a reliable metabolism-related predictive signature for the prognosis and anti-tumor immunity in cervical cancer. In this study, we extracted five metabolism-related hub genes, including ALOX12B, CA9, FAR2, F5 and TDO2, for the establishment of the risk score model. The Kaplan-Meier curve suggested that patients with a high-risk score apparently had a worse prognosis in the cervical cancer training cohort (TCGA, n = 304, p < 0.0001), validation cohort (GSE44001, n = 300, p = 0.0059) and pan-cancer cohorts (including nine TCGA tumors). Using a gene set enrichment analysis (GSEA), we observed that the model was correlated with various immune-regulation-related pathways. Furthermore, pan-cancer cohorts and immunohistochemical analysis showed that the infiltration of tumor infiltrating lymphocytes (TILs) was lower in the high-score group. Additionally, the model could also predict the prognosis of patients with cervical cancer based on the expression of immune checkpoints (ICPs) in both the discovery and validation cohorts. Our study established and validated a metabolism-related prognostic model, which might improve the accuracy of predicting the clinical outcome of patients with cervical cancer and provide guidance for personalized treatment.

Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer

Background

Glycerolipid metabolism is involved in the genesis and progression of colon cancer. The current study aims at exploring the prognostic value and potential molecular mechanism of glycerolipid metabolism-related genes in colon cancer from the perspective of multi-omics.

Methods

Clinical information and mRNA expression data of patients with colon cancer were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Single-sample gene set enrichment analysis (ssGSEA) was applied to calculate the glycerolipid metabolism-related gene enrichment score (GLMS). Univariable and multivariable Cox regression analyses were used to study the prognostic value of GLMS in TCGA-COAD and GSE39582 cohorts. The molecular mechanism of the prognostic factor was investigated via immune cell infiltration estimation and correlation analysis of cancer hallmark pathways. Single-cell transcriptomic dataset GSE146771 was used to identify the cell populations which glycerolipid metabolism targeted on.

Results

The GLMS was found to be associated with tumor location and consensus molecular types (CMSs) of colon cancer in TCGA-COAD cohort (P < 0.05). Patients in the low-GLMS group exhibited poorer overall survival (OS) in TCGA cohort (P = 0.03; HR, 0.63; 95% CI, 0.42-0.94), which was further validated in the GSE39582 dataset (P < 0.001; HR, 0.57; 95% CI, 0.43-0.76). The association between the GLMS and OS remained significant in the multivariable analysis (TCGA cohort: P = 0.04; HR, 0.64; 95% CI, 0.42-0.98; GSE39582 cohort: P < 0.001; HR, 0.60; 95% CI, 0.45-0.80). The GLMS was positively correlated with cancer hallmark pathways including bile acid metabolism, xenobiotic metabolism, and peroxisome and negatively correlated with pathways such as interferon gamma response, allograft rejection, apoptosis, and inflammatory response (P < 0.05). Increased immune infiltration and upregulated expression of immune checkpoints were observed in patients with lower GLMS (P < 0.05). Single-cell datasets verified the different distribution of GLMS in cell subsets, with significant enrichment of GLMS in malignant cells and Tprolif cells.

Conclusion

We demonstrated that GLMS was a potential independent prognostic factor for colon cancer. The GLMS was also correlated with several cancer hallmark pathways, as well as immune microenvironment.

Comparison of Immune Response Assessment in Colon Cancer by Immunoscore (Automated Digital Pathology) and Pathologist Visual Scoring

Simple Summary

The immune response to colon cancer (CC) is highly variable among patients and is clinically relevant. In this study, we compared the immune response assessment for early-stage CC, as measured by Immunoscore (IS), to pathologist visual scoring of the CD3+ and CD8+ T-cell densities at the tumor site (T-score). The objectives were to determine the inter-observer agreement between pathologists and the concordance between the two methods. Agreement between pathologists was minimal to weak. Moreover, a weak concordance between the two methods was observed, leading to misclassification of 48% of cases by pathologist scoring. Due to the high level of immune infiltrate heterogeneity resulting in disagreement of interpretation among pathologists, IS is unlikely to be reproduced via non-standardized methods.

Abstract

Adjunction of immune response into the TNM classification system improves the prediction of colon cancer (CC) prognosis. However, immune response measurements have not been used as robust biomarkers of pathology in clinical practice until the introduction of Immunoscore (IS), a standardized assay based on automated artificial intelligence assisted digital pathology. The strong prognostic impact of the immune response, as assessed by IS, has been widely validated and IS can help to refine treatment decision making in early CC. In this study, we compared pathologist visual scoring to IS. Four pathologists evaluated tumor specimens from 50 early-stage CC patients and classified the CD3+ and CD8+ T-cell densities at the tumor site (T-score) into 2 (High/Low) categories. Individual and overall pathologist scoring of immune response (before and after training for immune response assessment) were compared to the reference IS (High/Low). Pathologists’ disagreement with the reference IS was observed in almost half of the cases (48%) and training only slightly improved the accuracy of pathologists’ classification. Agreement among pathologists was minimal with a Kappa of 0.34 and 0.57 before and after training, respectively. The standardized IS assay outperformed expert pathologist assessment in the clinical setting.

Landscape of Immunotherapy Options for Colorectal Cancer: Current Knowledge and Future Perspectives beyond Immune Checkpoint Blockade

Colorectal cancer is the third most prevalent malignancy in Western countries and a major cause of death despite recent improvements in screening programs and early detection methods. In the last decade, a growing effort has been put into better understanding how the immune system interacts with cancer cells. Even if treatments with immune checkpoint inhibitors (anti-PD1, anti-PD-L1, anti-CTLA4) were proven effective for several cancer types, the benefit for colorectal cancer patients is still limited. However, a subset of patients with deficient mismatch repair (dMMR)/microsatellite-instability-high (MSI-H) metastatic colorectal cancer has been observed to have a prolonged benefit to immune checkpoint inhibitors. As a result, pembrolizumab and nivolumab +/− ipilimumab recently obtained the Food and Drug Administration approval. This review aims to highlight the body of knowledge on immunotherapy in the colorectal cancer setting, discussing the potential mechanisms of resistance and future strategies to extend its use.

Classification of early-stage colon cancer with Immunoscore®: clinical evidence and case studies

Immunoscore^® is a digital pathology diagnostic immunoassay used to complement tumor node metastasis staging for the prediction of recurrence risk in patients with early-stage colon cancer. In combination with standard clinicopathological features, Immunoscore informs adjuvant chemotherapy decision-making for patients with early-stage colon cancer. Immunoscore has been validated in patients with stage II/III colon cancer and demonstrated to be a stronger prognostic factor for survival than tumor node metastasis staging alone. Immunoscore improves the prognostic definition of patients with colon cancer, the identification of those patients at high risk of tumor recurrence, and the ability to predict which patients will derive most benefit from the use of adjuvant chemotherapy. Immunoscore has robust analytical performance characteristics which include good interlaboratory reproducibility and overall assay precision.

The "Immunoscore" in rectal cancer: could we search quality beyond quantity of life?

Because of the function and anatomical environment of the rectum, therapeutic strategies for local advanced rectal cancer (LARC) must deal with two challenging stressors that are a high-risk of local and distal recurrences and a high-risk of poor quality of life (QoL). Over the last three decades, advances in screening tests, therapies, and combined-modality treatment options and strategies have improved the prognosis of patients with LARC. However, owing to the heterogeneous nature of LARC and genetic status, the patient may not respond to a specific therapy and may be at increased risk of side-effects without the life-prolonging benefit. Indeed, each therapy can cause its own side-effects, which may worsen by a combination of treatments resulting in long-term poor QoL. In LARC, QoL has become even more essential with the increasing incidence of rectal cancer in young individuals. Herein, we analyzed the value of the Immunoscore-Biopsy (performed on tumor biopsy at diagnosis) in predicting outcomes, alone or in association with clinical and imaging data, for each therapy used in LARC.

Immuno-oncology trends: preclinical models, biomarkers, and clinical development

The landscape in immuno-oncology (I-O) has undergone profound changes since its early beginnings up through the rapid advances happening today. The current drug development pipeline consists of thousands of potential I-O therapies and therapy combinations, many of which are being evaluated in clinical trials. The efficient and successful development of these assets requires the investment in and utilization of appropriate tools and technologies that can facilitate the rapid transitions from preclinical evaluation through clinical development. These tools include (i) appropriate preclinical models, (ii) biomarkers of pharmacodynamic, predictive and monitoring utility, and (iii) evolving clinical trial designs that allow rapid and efficient evaluation during the development process. This article provides an overview of how novel discoveries and insights into each of these three areas have the potential to further address the clinical management needs for patients with cancer.

Preoperative Systemic Inflammatory Biomarkers Are Independent Predictors of Disease Recurrence in ER+ HER2- Early Breast Cancer

The host's immune system plays a crucial role in determining the clinical outcome of many cancers, including breast cancer. Peripheral blood neutrophils and lymphocytes counts may be surrogate markers of systemic inflammation and potentially reflect survival outcomes. The aim of the present study is to assess the role of preoperative systemic inflammatory biomarkers to predict local or distant relapse in breast cancer. In particular we investigated ER+ HER2- early breast cancer, considering its challenging risk stratification. A total of 1,763 breast cancer patients treated at tertiary referral Breast Unit were reviewed. Neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR) and lymphocyte-to-monocyte (LMR) ratios were assessed from the preoperative blood counts. Multivariate analyses for 5-years locoregional recurrence-free (LRRFS), distant metastases-free (DMFS) and disease-free survivals (DFS) were performed, taking into account both blood inflammatory biomarkers and clinical-pathological variables. Low NLR and high LMR were independent predictors of longer LRRFS, DMFS and DFS, and low PLR was predictive of better LRRFS and DMFS in the study population. In 999 ER+ HER2- early breast cancers, high PLR was predictive of worse LRRFS (HR 0.42, p=0.009), while high LMR was predictive of improved LRRFS (HR 2.20, p=0.02) and DFS (HR 2.10, p=0.01). NLR was not an independent factor of 5-years survival in this patients' subset. Inflammatory blood biomarkers and current clinical assessment of the disease were not in agreement in terms of estimate of relapse risk (K-Cohen from -0.03 to 0.02). In conclusion, preoperative lymphocyte ratios, in particular PLR and LMR, showed prognostic relevance in ER+ HER2- early breast cancer. Therefore, they may be used in risk stratification and therapy escalation/de-escalation in patients with this type of tumor.

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

Background

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

Methods

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

Results

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

Conclusion

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

Development of a Deep-Learning Pipeline to Recognize and Characterize Macrophages in Colo-Rectal Liver Metastasis

Quantitative analysis of Tumor Microenvironment (TME) provides prognostic and predictive information in several human cancers but, with few exceptions, it is not performed in daily clinical practice since it is extremely time-consuming. We recently showed that the morphology of Tumor Associated Macrophages (TAMs) correlates with outcome in patients with Colo-Rectal Liver Metastases (CLM). However, as for other TME components, recognizing and characterizing hundreds of TAMs in a single histopathological slide is unfeasible. To fasten this process, we explored a deep-learning based solution. We tested three Convolutional Neural Networks (CNNs), namely UNet, SegNet and DeepLab-v3, with three different segmentation strategies, semantic segmentation, pixel penalties and instance segmentation. The different experiments are compared according to the Intersection over Union (IoU), a metric describing the similarity between what CNN predicts as TAM and the ground truth, and the Symmetric Best Dice (SBD), which indicates the ability of CNN to separate different TAMs. UNet and SegNet showed intrinsic limitations in discriminating single TAMs (highest SBD 61.34±2.21), whereas DeepLab-v3 accurately recognized TAMs from the background (IoU 89.13±3.85) and separated different TAMs (SBD 79.00±3.72). This deep-learning pipeline to recognize TAMs in digital slides will allow the characterization of TAM-related metrics in the daily clinical practice, allowing the implementation of prognostic tools.

Spatial architecture of the immune microenvironment orchestrates tumor immunity and therapeutic response

Tumors are not only aggregates of malignant cells but also well-organized complex ecosystems. The immunological components within tumors, termed the tumor immune microenvironment (TIME), have long been shown to be strongly related to tumor development, recurrence and metastasis. However, conventional studies that underestimate the potential value of the spatial architecture of the TIME are unable to completely elucidate its complexity. As innovative high-flux and high-dimensional technologies emerge, researchers can more feasibly and accurately detect and depict the spatial architecture of the TIME. These findings have improved our understanding of the complexity and role of the TIME in tumor biology. In this review, we first epitomized some representative emerging technologies in the study of the spatial architecture of the TIME and categorized the description methods used to characterize these structures. Then, we determined the functions of the spatial architecture of the TIME in tumor biology and the effects of the gradient of extracellular nonspecific chemicals (ENSCs) on the TIME. We also discussed the potential clinical value of our understanding of the spatial architectures of the TIME, as well as current limitations and future prospects in this novel field. This review will bring spatial architectures of the TIME, an emerging dimension of tumor ecosystem research, to the attention of more researchers and promote its application in tumor research and clinical practice.

Immunotherapy in colorectal cancer

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

The Association Between Inflammation and Immunosuppression: Implications for ICI Biomarker Development

Evasion of immune destruction is considered one of the hallmarks of cancer. Chronic inflammation can enable immune escape by suppressing immune surveillance and permitting the development of tumors and creating a tumor microenvironment that sustains cancer. This includes generating mechanisms that prevent the effectiveness of anti-tumor treatment including immune checkpoint inhibitor therapy. In this review, we explore the interplay of inflammation and immunosuppression, their effects on the tumor microenvironment, and their implications for immune checkpoint inhibitor therapy particularly in the context of predictive biomarkers for their use.

Therapeutic Implications of the Immunoscore in Patients with Colorectal Cancer

Four decades were needed to progress from the first demonstration of the independent prognostic value of lymphocytes infiltration in rectal cancers to the first recommendation from the international guidelines for the use of a standardized immune assay, namely the "Immunoscore" (IS), to accurately prognosticate colon cancers beyond the TNM-system. The standardization process included not only the IS conceptualization, development, fine-tuning, and validation by a large international consortium, but also a demonstration of the robustness and reproducibility across the world and testing of international norms and their effects on the IS. This is the first step of a major change of paradigm that now perceives cancer as the result of contradicting driving forces, i.e., the tumor expansion and the immune response, interacting dynamically and influencing the prognosis and the response to therapies. This prompted us to evaluate and evidence the capacity of the tumor immune status, as reflected by the IS, to accurately predict chemotherapy responses in an international, randomized cohort study of colon cancer. Moreover, we developed a derived IS performed on initial diagnostic biopsies (ISB) to assess response levels to neoadjuvant therapies. In rectal cancer, ISB was positively correlated with the degree of histologic response to neoadjuvant chemoradiotherapy and identified - alone and even more accurately if combined with clinical data- patients eligible for a noninvasive strategy. Based on these results, we are currently setting up an international cohort for confirmation. The potential role of IS with immunotherapies must be anticipated.

Precision immunity: Immunoscore and neoadjuvant treatment in bladder cancer

This review details the clinical utility of Immunoscore, measuring the immune response to cancer within the tumor microenvironment, in bladder cancer. Immunoscore was recently introduced into ESMO Clinical Practice Guidelines for gastrointestinal cancer and into the WHO classification of the Digestive System Tumors. In muscle-invasive bladder cancer (MIBC), the standard-of-care treatment is neo-adjuvant chemotherapy and cystectomy. However, only 50% of the patients are still alive at 5 years. The degree of histologic response positively correlated with Immunoscore and patients at lower risk of relapse or death were associated with a high-Immunoscore. Immunoscore is also predicting response to neoadjuvant chemotherapy-based treatment in several indications. This paves the way for the use of Immunoscore in clinical practice not only in gastrointestinal tumors but also in bladder cancer, and beyond.

The immune contexture and Immunoscore in cancer prognosis and therapeutic efficacy

The international American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) tumour-node-metastasis (TNM) staging system provides the current guidelines for the classification of cancer. However, among patients within the same stage, the clinical outcome can be very different. More recently, a novel definition of cancer has emerged, implicating at all stages a complex and dynamic interaction between tumour cells and the immune system. This has enabled the definition of the immune contexture, representing the pre-existing immune parameters associated with patient survival. Even so, the role of distinct immune cell types in modulating cancer progression is increasingly emerging. An immune-based assay named the 'Immunoscore' was defined to quantify the in situ T cell infiltrate and was demonstrated to be superior to the AJCC/UICC TNM classification for patients with colorectal cancer. This Review provides a broad overview of the main immune parameters positively or negatively shaping cancer development, including the Immunoscore, and their prognostic and predictive value. The importance of the immune system in cancer control is demonstrated by the requirement for a pre-existing intratumour adaptive immune response for effective immunotherapies, such as checkpoint inhibitors. Finally, we discuss how the combination of multiple immune parameters, rather than individual ones, might increase prognostic and/or predictive power.

Usefulness and robustness of Immunoscore for personalized management of cancer patients

This review details the analytical performance characteristics of the consensus Immunoscore, measuring the immune response to cancer, improving the estimation of risk of recurrence, and predicting response to treatment for patients with colon cancer. The analytical validation of Immunoscore has been documented. Immunoscore is a robust, reproducible, quantitative, and standardized immune assay, with a high prognostic performance, independent of all of the prognostic markers currently used in clinical practice. Immunoscore evaluation within the tumor microenvironment is clinically relevant, and Immunoscore was recently introduced into ESMO Clinical Practice Guidelines for colon cancer and into the WHO classification of the Digestive System Tumors. This paves the way for the use of Immunoscore in clinical practice in colorectal tumors and likely soon in many other solid tumors.

Immunity to live: an immunopathoscore using the consensus Immunoscore to best define the risk of recurrence and death in stage IV metastatic patients

The consensus Immunoscore is a routine assay quantifying the adaptive immune response within the tumor microenvironment. Its evaluation in the primary tumor of patients with stages I/II/III colorectal cancer (CRC) has prognostic value that has been confirmed in multiple studies. For metastatic patients, the evaluation of the consensus Immunoscore within resected metastases also significantly predicts the recurrence and survival of Stage IV patients. Since recurrence rates post-surgery are still very high, it is important to best evaluate risk parameters using the main patho-molecular and immune parameters. After preoperative treatment and curative resection of 582 metastases from 221 patients, clinico-pathological parameters, RAS mutation, and Immunoscore within metastases were assessed. Immunoscore and clinico-pathological parameters (number of metastases, surgical margin, histopathological growth pattern, and steatohepatitis) were associated with relapse in multivariable analysis. A Pathological Score (PS) that combines relevant clinico-pathological factors for relapse and Immunoscore was significantly (P < .0001) associated with Time to recurrence. In multivariable analysis, only Immunoscore (P < .001) and RAS mutations (P= .03) were prognostic and significantly associated with overall survival. Thus, among all parameters clinically relevant in the metastatic settings, PS and Immunoscore allow the stratification of stage IV CRC patients and identify patients with higher risk of recurrence. Immunoscore remained the major prognostic factor for overall survival (OS). In its latest edition, the WHO classification of Digestive System Tumors introduced for the first time the immune response as an essential and desirable diagnostic criterion for CRC. These novel results highlight the clinical utility of Immunoscore in Stage IV patients.

Immuno-Interface Score to Predict Outcome in Colorectal Cancer Independent of Microsatellite Instability Status

Simple Summary

For pathologists, how to precisely diagnose cancer from microscopy slides of tumor tissue samples so that each patient may receive the optimal treatment for his specific type of disease is a major task. Recent research based on digital pathology image analysis enables new approaches to assess tumor-host interaction at a microscopic level. The current study applies a novel spatial analysis method which computes Immunogradient indicators to estimate the migration of immune cells towards the tumor across the tumor/stroma interface. These indicators, computed for two types of immune cells (CD8 and CD20), proved to be independent prognostic factors in this study of 87 patients with colorectal cancer. The indicators were combined with infiltrative tumor growth pattern, assessed by a pathologist, into a new immuno-interface score which enabled prediction of the patient survival independent of other clinical, pathology and molecular characteristics of the tumor. The study demonstrates the value of computational pathology to advance the precision of clinical decision-making.

Abstract

Tumor-associated immune cells have been shown to predict patient outcome in colorectal (CRC) and other cancers. Spatial digital image analysis-based cell quantification increases the informative power delivered by tumor microenvironment features and leads to new prognostic scoring systems. In this study we evaluated the intratumoral density of immunohistochemically stained CD8, CD20 and CD68 cells in 87 cases of CRC (48 were microsatellite stable, MSS, and 39 had microsatellite instability, MSI) in both the intratumoral tumor tissue and within the tumor-stroma interface zone (IZ) which was extracted by a previously developed unbiased hexagonal grid analytics method. Indicators of immune-cell gradients across the extracted IZ were computed and explored along with absolute cell densities, clinicopathological and molecular data, including gene mutation (BRAF, KRAS, PIK3CA) and MSI status. Multiple regression modeling identified (p < 0.0001) three independent prognostic factors: CD8+ and CD20+ Immunogradient indicators, that reflect cell migration towards the tumor, were associated with improved patient survival, while the infiltrative tumor growth pattern was linked to worse patient outcome. These features were combined into CD8-CD20 Immunogradient and immuno-interface scores which outperformed both tumor-node-metastasis (TNM) staging and molecular characteristics, and importantly, revealed high prognostic value both in MSS and MSI CRCs.

Differential gene expression of tumor-infiltrating CD8+ T cells in advanced versus early-stage colorectal cancer and identification of a gene signature of poor prognosis

Background

Cytotoxic CD8⁺ T cell-mediated response is the most important arm of adaptive immunity, which dictates the capacity of the host immune response in eradicating tumor cells. Due to tumor intrinsic and/or extrinsic factors, the density and function of CD8⁺ tumor-infiltrating lymphocytes (TILs) could be compromised, leading to poor prognosis and survival.

Methods

Using RNA-Seq, transcriptomes of sorted CD3⁺CD8⁺ TILs from treatment-naïve colorectal cancer (CRC) patients at advanced stages (III and IV) were compared with those from patients with early stages (I and II). A signature referred to as ‘poor prognosis CD8 gene signature (ppCD8sig)’ was identified and analyzed in The Cancer Genome Atlas CRC dataset. Scores for the ppCD8sig were calculated and classified as high, intermediate and low, and its prognostic significance was assessed using multivariate analysis and Cox proportional hazard model. Densities of CD3⁺ and CD8⁺ T cell infiltration in tumors from patients with high and low ppCD8sig scores were assessed by flow cytometry and immunostaining.

Results

Genes related to epigenetic regulation and response to hypoxia were upregulated in CD8⁺ TILs from patients with advanced stages, while genes related to T cell activation, cell proliferation and cell cycle were downregulated. Patients with high ppCD8sig score had poorer disease-specific survival (DSS) and shorter progression-free interval (PFI). The ppCD8sig was an independent prognostic indicator for DSS (HR 1.83, 95% CI 1.40 to 2.38, p<0.0001) and PFI (HR 1.42, 95% CI 1.04 to 1.93, p=0.026). Additionally, patients with high ppCD8sig score were more likely to have advanced stages (χ² p<0.0001) and residual disease after primary therapy (χ² p=0.046). Patients with high ppCD8sig score had reduced levels of CD3⁺ and CD8⁺ TILs and low Immunoscores (IS), compared to patients with low ppCD8sig score.

Conclusions

Our data provided insights into the altered regulation of biological mechanisms and signaling pathways in CD8⁺ TILs during CRC progression, and revealed a gene signature as an independent prognostic indicator. Patients with high ppCD8sig score had lower levels of TILs and low IS. These data further confirm the prognostic value of the identified ppCD8sig and potentially highlight its clinical relevance.

The consensus Immunoscore in phase 3 clinical trials; potential impact on patient management decisions

The consensus Immunoscore has a prognostic value that has been confirmed in two randomized phase 3 clinical trials, and it provides a reliable estimate of the recurrence risk in colon cancer. The latest edition of the WHO classification of the Digestive System Tumors introduced for the first time the immune response as an essential and desirable diagnostic criteria for digestive cancers. Therefore, the immune response and Immunoscore evaluation within the tumor microenvironment is clinically relevant. In addition, the evaluation of the Immunoscore in stage III colon cancer patients from the IDEA France clinical trial evaluating 3 versus 6 months of oxaliplatin-based adjuvant chemotherapy demonstrated the predictive value of Immunoscore for treatment duration. Immunoscore predicted response to 6 months FOLFOX chemotherapy both in low- and high-risk Stage III patients. Low-risk patients (T_1-3, N₁) with High-Immunoscore had the 3-year DFS of 91.4% when treated with the 6-month FOLFOX, and only 80.8% with the 3-month regimen. The international validation of the prognostic value of the consensus Immunoscore together with its predictive value to guide treatment provides important information for the personalized management of colon cancer patients.

Metastasis immune-based scores predict patient survival

Treatment of metastatic colorectal cancer is based upon the assumption that metastases are homogeneous within a patient. A comprehensive analysis of all metastases of each patient revealed the heterogeneity of the colorectal metastatic disease and its clinical impact. Complex tumor-immune interrelations shape the metastatic landscape. Adaptive immune cells and Immunoscore quantified in a random metastatic biopsy predict clinical outcome and their evaluation in the tumor microenvironment of the least infiltrated metastasis most accurately predict long-term survival. The adaptive immune cell infiltration was more informative than tumor regression and pathological response to predict long-term survival. These results highlight the clinical utility of Immunoscore for patient management. The immune response within the tumor microenvironment is an essential diagnostic criterion for colorectal cancer that has recently been integrated into the international WHO classification of Digestive System Tumors.

A Diagnostic Biopsy-Adapted Immunoscore Predicts Response to Neoadjuvant Treatment and Selects Patients with Rectal Cancer Eligible for a Watch-and-Wait Strategy

PURPOSE

No biomarker to personalize treatment in locally advanced rectal cancer (LARC) is currently available. We assessed in LARC whether a diagnostic biopsy-adapted immunoscore (IS_B) could predict response to neoadjuvant treatment (nT) and better define patients eligible to an organ preservation strategy ("Watch-and-Wait").

EXPERIMENTAL DESIGN

Biopsies from two independent cohorts (n ₁ = 131, n ₂ = 118) of patients with LARC treated with nT followed by radical surgery were immunostained for CD3⁺ and CD8⁺ T cells and quantified by digital pathology to determine IS_B. The expression of immune-related genes post-nT was investigated (n = 64 patients). Results were correlated with response to nT and disease-free survival (DFS). The IS_B prognostic performance was further assessed in a multicentric cohort (n = 73 patients) treated by Watch-and-Wait.

RESULTS

IS_B positively correlated with the degree of histologic response (P < 0.001) and gene expression levels for Th1 orientation and cytotoxic immune response, post-nT (P = 0.006). IS_B high identified patients at lower risk of relapse or death compared with IS_B low [HR, 0.21; 95% confidence interval (CI), 0.06-0.78; P = 0.009]. Prognostic performance of IS_B for DFS was confirmed in a validation cohort. IS_B was an independent parameter, more informative than pre- (P < 0.001) and post-nT (P < 0.05) imaging to predict DFS. IS_B combined with imaging post-nT discriminated very good responders that could benefit from organ preservation strategy. In the "Watch-and-Wait" cohort (n = 73), no relapse was observed in patients with IS_B high (23.3%).

CONCLUSIONS

IS_B predicts response to nT and survival in patients with LARC treated by surgery. Its usefulness in the selection of patients eligible for a Watch-and-Wait strategy is strongly suggested.

Tumour budding, poorly differentiated clusters, and T-cell response in colorectal cancer

BACKGROUND

Tumour budding and poorly differentiated clusters (PDC) represent forms of tumour invasion. We hypothesised that T-cell densities (reflecting adaptive anti-tumour immunity) might be inversely associated with tumour budding and PDC in colorectal carcinoma.

METHODS

Utilising 915 colon and rectal carcinomas in two U.S.-wide prospective cohort studies, and multiplex immunofluorescence combined with machine learning algorithms, we assessed CD3, CD4, CD8, CD45RO (PTPRC), and FOXP3 co-expression patterns in lymphocytes. Tumour budding and PDC at invasive fronts were quantified by digital pathology and image analysis using the International tumour Budding Consensus Conference criteria. Using covariate data of 4,420 incident colorectal cancer cases, inverse probability weighting (IPW) was integrated with multivariable logistic regression analysis that assessed the association of T-cell subset densities with tumour budding and PDC while adjusting for selection bias due to tissue availability and potential confounders, including microsatellite instability status.

FINDINGS

Tumour budding counts were inversely associated with density of CD3⁺CD8⁺ [lowest vs. highest: multivariable odds ratio (OR), 0.50; 95% confidence interval (CI), 0.35-0.70; P_trend < 0.001] and CD3⁺CD8⁺CD45RO⁺ cells (lowest vs. highest: multivariable OR, 0.44; 95% CI, 0.31-0.63; P_trend < 0.001) in tumour epithelial region. Tumour budding levels were associated with higher colorectal cancer-specific mortality (multivariable hazard ratio, 2.13; 95% CI, 1.57-2.89; P_trend < 0.001) in Cox regression analysis. There were no significant associations of PDC with T-cell subsets.

INTERPRETATION

Tumour epithelial naïve and memory cytotoxic T cell densities are inversely associated with tumour budding at invasive fronts, suggesting that cytotoxic anti-tumour immunity suppresses tumour microinvasion.