The immune microenvironment landscape shows treatment-specific differences in rectal cancer patients

lncRNA EGOT Is the Marker of HPV Infection and a Prognostic Factor for HNSCC Patients

Background: High-risk human papillomavirus (HPV) contributes to oropharyngeal cancers through mechanisms involving the deregulation of host cell functions by oncoproteins E6 and E7. Changes in the epigenome, particularly involving long non-coding RNAs (lncRNAs), are crucial for understanding HPV-related carcinogenesis. Methods: This study aimed to analyze the expression levels of lncRNAs in HPV-related head and neck squamous cell carcinoma (HNSCC) to determine their biological and clinical significance, addressing the current gap in clinically validated biomarkers for early screening and therapeutic interventions. Results: The study highlights the significant overexpression of the EGOT gene in HPV-positive HNSCC samples, suggesting its potential as a marker to distinguish between HPV-negative and HPV-positive cases. Furthermore, high EGOT expression correlates with better overall survival (OS) and indicates possible resistance to therapy, making it a valuable prognostic factor. Conclusions: These findings underscore the potential of incorporating EGOT expression analysis in clinical practice for improved patient stratification and treatment outcomes in HNSCC.

ImmuNet: a segmentation-free machine learning pipeline for immune landscape phenotyping in tumors by multiplex imaging

Tissue specimens taken from primary tumors or metastases contain important information for diagnosis and treatment of cancer patients. Multiplex imaging allows in situ visualization of heterogeneous cell populations, such as immune cells, in tissue samples. Most image processing pipelines first segment cell boundaries and then measure marker expression to assign cell phenotypes. In dense tissue environments, this segmentation-first approach can be inaccurate due to segmentation errors or overlapping cells. Here, we introduce the machine-learning pipeline "ImmuNet", which identifies positions and phenotypes of cells without segmenting them. ImmuNet is easy to train: human annotators only need to click on an immune cell and score its expression of each marker-drawing a full cell outline is not required. We trained and evaluated ImmuNet on multiplex images from human tonsil, lung cancer, prostate cancer, melanoma, and bladder cancer tissue samples and found it to consistently achieve error rates below 5%-10% across tissue types, cell types, and tissue densities, outperforming a segmentation-based baseline method. Furthermore, we externally validate ImmuNet results by comparing them to flow cytometric cell count measurements from the same tissue. In summary, ImmuNet is an effective, simpler alternative to segmentation-based approaches when only cell positions and phenotypes, but not their shapes, are required for downstream analyses. Thus, ImmuNet helps researchers to analyze cell positions in multiplex tissue images more easily and accurately.

Detection of dendritic cell subsets in the tumor microenvironment by multiplex immunohistochemistry

Dendritic cells (DCs) are essential in antitumor immunity. In humans, three main DC subsets are defined: two types of conventional DCs (cDC1s and cDC2s) and plasmacytoid DCs (pDCs). To study DC subsets in the tumor microenvironment (TME), it is important to correctly identify them in tumor tissues. Tumor-derived DCs are often analyzed in cell suspensions in which spatial information about DCs which can be important to determine their function within the TME is lost. Therefore, we developed the first standardized and optimized multiplex immunohistochemistry panel, simultaneously detecting cDC1s, cDC2s, and pDCs within their tissue context. We report on this panel's development, validation, and quantitative analysis. A multiplex immunohistochemistry panel consisting of CD1c, CD303, X-C motif chemokine receptor 1, CD14, CD19, a tumor marker, and DAPI was established. The ImmuNet machine learning pipeline was trained for the detection of DC subsets. The performance of ImmuNet was compared with conventional cell phenotyping software. Ultimately, frequencies of DC subsets within several tumors were defined. In conclusion, this panel provides a method to study cDC1s, cDC2s, and pDCs in the spatial context of the TME, which supports unraveling their specific roles in antitumor immunity.

Relevance of shrinkage versus fragmented response patterns in rectal cancer

AIMS

Partial response to neoadjuvant chemoradiotherapy (CRT) presents with one of two main response patterns: shrinkage or fragmentation. This study investigated the relevance of these response patterns in rectal cancer, correlation with other response indicators, and outcome.

METHODS AND RESULTS

The study included a test (n = 197) and a validation cohort (n = 218) of post-CRT patients with rectal adenocarcinoma not otherwise specified and a partial response. Response patterns were scored by two independent observers using a previously developed three-step flowchart. Tumour regression grading (TRG) was established according to both the College of American Pathologists (CAP) and Dworak classifications. In both cohorts, the predominant response pattern was fragmentation (70% and 74%), and the scoring interobserver agreement was excellent (k = 0.85). Patients with a fragmented pattern presented with significantly higher pathological stage (ypTNM II-IV, 78% versus 35%; P < 0.001), less tumour regression with Dworak (P = 0.004), and CAP TRG (P = 0.005) compared to patients with a shrinkage pattern. As a predictor of prognosis, the shrinkage pattern outperformed the TRG classification and stratified patients better in overall (fragmented pattern, hazard ratio [HR] 2.04, 95% confidence interval [CI] 1.19-3.50, P = 0.008) and disease-free survival (DFS; fragmented pattern, HR 2.50, 95% CI 1.23-5.10, P = 0.011) in the combined cohorts. The multivariable regression analyses revealed pathological stage as the only independent predictor of DFS.

CONCLUSIONS

The heterogeneous nature of tumour response following CRT is reflected in fragmentation and shrinkage. In rectal cancer there is a predominance of the fragmented pattern, which is associated with advanced stage and less tumour regression. While not independently associated with survival, these reproducible patterns give insights into the biology of tumour response.

Expression of IDO1 in Tumor Microenvironment Significantly Predicts the Risk of Recurrence/Distant Metastasis for Patients With Esophageal Squamous Cell Carcinoma

In this study, we aimed to explore immune markers predicting locoregional recurrence/distant metastasis (R/M) for patients with esophageal squamous cell carcinoma (ESCC) post-surgical intervention by using a novel high-throughput spatial tool to quantify multiple immune proteins expressed in ESCC and lymphocytes in tumor microenvironment (TME-L). First, formalin-fixed paraffin-embedded tissues from surgical patients with ESCC (n = 94) were constructed on a microarray, which was then divided into discovery (n = 36) and validation cohorts (n = 58). Using a newly developed GeoMx digital spatial profiling tool, 31 immune proteins in paired ESCC and TME-L, morphologically segmented by PANCK and CD45, respectively, from the discovery cohort were quantified, releasing 2,232 variables. Next, the correlation matrix was analyzed using the Corrplot package in R Studio, resulting in 6 closely correlated clusters. The Least Absolute Shrinkage and Selection Operator regression scoring model predictive of R/M risk with superior specificity was successfully established based on the 3 following hierarchically clustered immune proteins: ARG1 in ESCC/PANCK+, STING, and IDO1 in TME-L/CD45+. Moreover, the expression of IDO1 in TME-L, rather than in ESCC, significantly predicted the R/M risk score with an area under curve of 0.9598. In addition, its correlation with R/M status was further validated by dual immunohistochemistry staining of IDO1 and CD45 in discovery and validation cohorts. Above all, our findings not only provide a more accurate scoring approach based on quantitative immune proteins for the prediction of R/M risk, but also propose that IDO1 in TME-L potentially plays a driving role in mediating R/M in ESCC.

Implications of Rectal Cancer Radiotherapy on the Immune Microenvironment: Allies and Foes to Therapy Resistance and Patients' Outcome

Aside from surgical resection, locally advanced rectal cancer is regularly treated with neoadjuvant chemoradiotherapy. Since the concept of cancer treatment has shifted from only focusing on tumor cells as drivers of disease progression towards a broader understanding including the dynamic tumor microenvironment (TME), the impact of radiotherapy on the TME and specifically the tumor immune microenvironment (TIME) is increasingly recognized. Both promoting as well as suppressing effects on anti-tumor immunity have been reported in response to rectal cancer (chemo-)radiotherapy and various targets for combination therapies are under investigation. A literature review was conducted searching the PubMed database for evidence regarding the pleiotropic effects of (chemo-)radiotherapy on the rectal cancer TIME, including alterations in cytokine levels, immune cell populations and activity as well as changes in immune checkpoint proteins. Radiotherapy can induce immune-stimulating and -suppressive alterations, potentially mediating radioresistance. The response is influenced by treatment modalities, including the dosage administered and the highly individual intrinsic pre-treatment immune status. Directly addressing the main immune cells of the TME, this review aims to highlight therapeutical implications since efficient rectal cancer treatment relies on personalized strategies combining conventional therapies with immune-modulating approaches, such as immune checkpoint inhibitors.

Pseudobudding: ruptured glands do not represent true tumor buds

Tumor budding (TB) is a strong biomarker of poor prognosis in colorectal cancer and other solid cancers. TB is defined as isolated single cancer cells or clusters of up to four cancer cells at the invasive tumor front. In areas with a large inflammatory response at the invasive front, single cells and cell clusters surrounding fragmented glands are observed appearing like TB. Occurrence of these small groups is referred to as pseudobudding (PsB), which arises due to external influences such as inflammation and glandular disruption. Using a combination of orthogonal approaches, we show that there are clear biological differences between TB and PsB. TB is representative of active invasion by presenting features of epithelial-mesenchymal transition and exhibiting increased deposition of extracellular matrix within the surrounding tumor microenvironment (TME), whereas PsB represents a reactive response to heavy inflammation where increased levels of granulocytes within the surrounding TME are observed. Our study provides evidence that areas with a strong inflammatory reaction should be avoided in the routine diagnostic assessment of TB. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The current understanding of the immune landscape relative to radiotherapy across tumor types

Radiotherapy is part of the standard of care treatment for a great majority of cancer patients. As a result of radiation, both tumor cells and the environment around them are affected directly by radiation, which mainly primes but also might limit the immune response. Multiple immune factors play a role in cancer progression and response to radiotherapy, including the immune tumor microenvironment and systemic immunity referred to as the immune landscape. A heterogeneous tumor microenvironment and the varying patient characteristics complicate the dynamic relationship between radiotherapy and this immune landscape. In this review, we will present the current overview of the immunological landscape in relation to radiotherapy in order to provide insight and encourage research to further improve cancer treatment. An investigation into the impact of radiation therapy on the immune landscape showed in several cancers a common pattern of immunological responses after radiation. Radiation leads to an upsurge in infiltrating T lymphocytes and the expression of programmed death ligand 1 (PD-L1) which can hint at a benefit for the patient when combined with immunotherapy. In spite of this, lymphopenia in the tumor microenvironment of 'cold' tumors or caused by radiation is considered to be an important obstacle to the patient's survival. In several cancers, a rise in the immunosuppressive populations is seen after radiation, mainly pro-tumoral M2 macrophages and myeloid-derived suppressor cells (MDSCs). As a final point, we will highlight how the radiation parameters themselves can influence the immune system and, therefore, be exploited to the advantage of the patient.