Computerised scoring protocol for identification and quantification of different immune cell populations in breast tumour regions by the use of QuPath software

Dissecting the immune infiltrate of primary luminal B-like breast carcinomas in relation to age

The impact of aging on the immune landscape of luminal breast cancer (Lum-BC) is poorly characterized. Understanding the age-related dynamics of immune editing in Lum-BC is anticipated to improve the therapeutic benefit of immunotherapy in older patients. To this end, here we applied the 'multiple iterative labeling by antibody neo-deposition' (MILAN) technique, a spatially resolved single-cell multiplex immunohistochemistry method. We created tissue microarrays by sampling both the tumor center and invasive front of luminal breast tumors collected from a cohort of treatment-naïve patients enrolled in the prospective monocentric IMAGE (IMmune system and AGEing) study. Patients were subdivided into three nonoverlapping age categories (35-45 = 'young', n = 12; 55-65 = 'middle', n = 15; ≥70 = 'old', n = 26). Additionally, depending on localization and amount of cytotoxic T lymphocytes, the tumor immune types 'desert' (n = 22), 'excluded' (n = 19), and 'inflamed' (n = 12) were identified. For the MILAN technique we used 58 markers comprising phenotypic and functional markers allowing in-depth characterization of T and B lymphocytes (T&B-lym). These were compared between age groups and tumor immune types using Wilcoxon's test and Pearson's correlation. Cytometric analysis revealed a decline of the immune cell compartment with aging. T&B-lym were numerically less abundant in tumors from middle-aged and old compared to young patients, regardless of the geographical tumor zone. Likewise, desert-type tumors showed the smallest immune-cell compartment and were not represented in the group of young patients. Analysis of immune checkpoint molecules revealed a heterogeneous geographical pattern of expression, indicating higher numbers of PD-L1 and OX40-positive T&B-lym in young compared to old patients. Despite the numerical decline of immune infiltration, old patients retained higher expression levels of OX40 in T helper cells located near cancer cells, compared to middle-aged and young patients. Aging is associated with important numerical and functional changes of the immune landscape in Lum-BC. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Tumor-Infiltrating Lymphocyte Scoring in Neoadjuvant-Treated Breast Cancer

Neoadjuvant chemotherapy (NAC) is now the standard of care for patients with locally advanced breast cancer (BC). TIL scoring is prognostic and adds predictive value to the residual cancer burden evaluation after NAC. However, NAC induces changes in the tumor, and the reliability of TIL scoring in post-NAC samples has not yet been studied. H&E- and dual CD3/CD20 chromogenic IHC-stained tissues were scored for stromal and intra-tumoral TIL by two experienced pathologists on pre- and post-treatment BC tissues. Digital TIL scoring was performed using the HALO® image analysis software (version 2.2). In patients with residual disease, we show a good inter-pathologist correlation for stromal TIL on H&E-stained tissues (CCC value 0.73). A good correlation for scoring with both staining methods (CCC 0.81) and the digital TIL scoring (CCC 0.77) was also observed. Overall concordance for TIL scoring in patients with a complete response was however poor. This study reveals there is good reliability for TIL scoring in patients with detectable residual tumors after NAC treatment, which is comparable to the scoring of untreated breast cancer patients. Based on the good consistency observed with digital TIL scoring, the development of a validated algorithm in the future might be advantageous.

Analysis of gene and protein expression in the endometrium for validation of an ex vivo model of the equine uterus using PCR, digital and visual histopathology

In the past, most research in equine reproduction has been performed in vivo but the use of in vitro and ex vivo models has recently increased. This study aimed to evaluate the functional stability of an ex vivo hemoperfused model for equine uteri with molecular characterization of marker genes and their proteins. In addition, the study validated the respective protein expression and the aptness of the software QuPath for identifying and scoring immunohistochemically stained equine endometrium. After collection, uteri (n = 12) were flushed with preservation solution, transported to the laboratory on ice, and perfused with autologous blood for 6 h. Cycle stage was determined by examination of the ovaries for presence of Graafian follicles or corpora lutea and analysis of plasma progesterone concentration (estrus: n = 4; diestrus: n = 4; anestrus: n = 4). Samples were obtained directly after slaughter, after transportation, and during perfusion (240, 300, 360 min). mRNA expression levels of progesterone (PGR), estrogen (ESR1) and oxytocin (OXTR) receptor as well as of MKI67 (marker of cell growth) and CASP3 (marker of apoptosis) were analyzed by RT-qPCR, and correlation to protein abundance was validated by immunohistochemical staining. Endometrial samples were analyzed by visual and computer-assisted evaluation of stained antigens via QuPath. For PGR, effects of the perfusion and cycle stage on expression were found (P < 0.05), while ESR1 was affected only by cycle stage (P < 0.05) and OXTR was unaffected by perfusion and cycle stage. MKI67 was lower after 360 min of perfusion as compared to samples collected before perfusion (P < 0.05). For CASP3, differences in gene expression were found after transport and samples taken after 240 min (P < 0.05). Immunohistochemical staining revealed effects of perfusion on stromal and glandular cells for steroid hormone receptors, but not for Ki-67 and active Caspase 3. OXTR was visualized in all layers of the endometrium and was unaffected by perfusion. Comparison of QuPath and visual analysis resulted in similar results. For most cell types and stained antigens, the correlation coefficient was r > 0.5. In conclusion, the isolated hemoperfused model of the equine uterus was successfully validated at the molecular level, demonstrating stability of key marker gene expression. The utility of computer-assisted immunohistochemical analysis of equine endometrial samples was also confirmed.

Cyto R-CNN and CytoNuke Dataset: Towards reliable whole-cell segmentation in bright-field histological images

BACKGROUND AND OBJECTIVE

Cell segmentation in bright-field histological slides is a crucial topic in medical image analysis. Having access to accurate segmentation allows researchers to examine the relationship between cellular morphology and clinical observations. Unfortunately, most segmentation methods known today are limited to nuclei and cannot segment the cytoplasm.

METHODS

We present a new network architecture Cyto R-CNN that is able to accurately segment whole cells (with both the nucleus and the cytoplasm) in bright-field images. We also present a new dataset CytoNuke, consisting of multiple thousand manual annotations of head and neck squamous cell carcinoma cells. Utilizing this dataset, we compared the performance of Cyto R-CNN to other popular cell segmentation algorithms, including QuPath's built-in algorithm, StarDist, Cellpose and a multi-scale Attention Deeplabv3+. To evaluate segmentation performance, we calculated AP50, AP75 and measured 17 morphological and staining-related features for all detected cells. We compared these measurements to the gold standard of manual segmentation using the Kolmogorov-Smirnov test.

RESULTS

Cyto R-CNN achieved an AP50 of 58.65% and an AP75 of 11.56% in whole-cell segmentation, outperforming all other methods (QuPath 19.46/0.91%; StarDist 45.33/2.32%; Cellpose 31.85/5.61%, Deeplabv3+ 3.97/1.01%). Cell features derived from Cyto R-CNN showed the best agreement to the gold standard (D¯=0.15) outperforming QuPath (D¯=0.22), StarDist (D¯=0.25), Cellpose (D¯=0.23) and Deeplabv3+ (D¯=0.33).

CONCLUSION

Our newly proposed Cyto R-CNN architecture outperforms current algorithms in whole-cell segmentation while providing more reliable cell measurements than any other model. This could improve digital pathology workflows, potentially leading to improved diagnosis. Moreover, our published dataset can be used to develop further models in the future.

Expression of cell surface zinc transporter LIV1 in triple negative breast cancer is an indicator of poor prognosis and therapy failure

Triple negative breast cancers (TNBC) are an aggressive molecular subtype of breast carcinoma (BC) identified by the lack of receptor expression for estrogen, progesterone, & human epidermal growth factor receptor-2. Lack of tangible drug targets warrants further research in TNBC. LIV1, is a zinc (Zn) transporter known to be overexpressed in few cancer types including BCs. Recently, in the United States of America, FDA approved the use of a new drug targeting LIV1, antibody drug conjugate SGN-LIV1A for treatment of TNBC patients. Though LIV1 also has a role in modulating immune cells by its differential transport of Zn, a correlation between the tumor cell expression of LIV1 and immune cell infiltrations were scantily reported. Further adequate baseline data on LIV1 expression in other populations have not been documented. Our objective was to screen a large Indian cohort of TNBC patient samples for LIV1, categorize the immune cell infiltration using CD4/CD8 expression and correlate the findings with therapy outcomes. Further, we also investigated for LIV1 expression in matched samples of primary & secondary tumors; pre & postchemotherapy in TNBC patients. Results showed an elevated expression of LIV1 in TNBC samples as compared to adjacent normal, the mean Q scores being 183.06 ± 6.39 and 120.78 ± 7.37 (p < 0.0001), respectively. Similarly, LIV1 levels were elevated in secondary tumors than primary & in patient samples postchemotherapy as compared to naïve. In the TNBC cohort, using automated method, cell morphology parameters were computed and analysis showed LIV1 levels were elevated in grade 3 TNBC samples presenting with altered cell morphology parameters namely cell size, cell perimeter, & nucleus size. Thus indicating LIV1 expressing TNBC samples portrayed an aggressive phenotype. Finally, TNBC patients with 3+ staining intensity showed poor survival (4.44 year) as compared to patients with 2+ LIV1 expression (5.47 year), emphasizing that LIV1 expression is a poor prognostic factor in TNBC. In conclusion, the study reports elevated expression of LIV1 in a large Indian TNBC cohort; high expression is a poor prognostic factor and correlated with aggressive disease and indicating the need for LIV1 targeted therapies.

The Clinical and Biological Significance of Estrogen Receptor-Low Positive Breast Cancer

Estrogen receptor (ER) status in breast cancer (BC) is determined using immunohistochemistry (IHC) with nuclear expression in ≥1% of cells defined as ER-positive. BC with 1%-9% expression (ER-low-positive), is a clinically and biologically unique subgroup. In this study, we hypothesized that ER-low-positive BC represents a heterogeneous group with a mixture of ER-positive and ER-negative tumor, which may explain their divergent clinical behavior. A large BC cohort (n = 8171) was investigated and categorized into 3 groups: ER-low-positive (1%-9%), ER-positive (≥10%), and ER-negative (<1%) where clinicopathological and outcome characteristics were compared. A subset of ER-low-positive cases was further evaluated using IHC, RNAscope, and RT-qPCR. PAM50 subtyping and ESR1 mRNA expression levels were assessed in ER-low-positive cases within The Cancer Genome Atlas data set. The reliability of image analysis software in assessment of ER expression in the ER-low-positive category was also assessed. ER-low-positive tumors constituted <2% of BC cases examined and showed significant clinicopathological similarity to ER-negative tumors. Most of these tumors were nonluminal types showing low ESR1 mRNA expression. Further validation of ER status revealed that 45% of these tumors were ER-negative with repeated IHC staining and confirmed by RNAscope and RT-qPCR. ER-low-positive tumors diagnosed on needle core biopsy were enriched with false-positive ER staining. BCs with 10% ER behaved similar to ER-positive, rather than ER-negative or low-positive BCs. Moderate concordance was found in assessment of ER-low-positive tumors, and this was not improved by image analysis. Routinely diagnosed ER-low-positive BC includes a proportion of ER-negative cases. We recommend repeat testing of BC showing 1%-9% ER expression and using a cutoff ≥10% expression to define ER positivity to help better inform treatment decisions.

Development of a deep learning-based model to diagnose mixed-type gastric cancer accurately

OBJECTIVE

The accurate diagnosis of mixed-type gastric cancer from pathology images presents a formidable challenge for pathologists, given its intricate features and resemblance to other subtypes of gastric cancer. Artificial Intelligence has the potential to overcome this hurdle. This study aimed to leverage deep machine learning techniques to establish a precise and efficient diagnostic approach for this cancer type which can also predict the metastatic risk using two software, U-Net and QuPath, which have not been trialled in gastric cancers.

METHODS

A U-Net neural network was trained to recognise, and segment differentiated components from 186 pathology images of mixed-type gastric cancer. Undifferentiated components in the same images were annotated using the open-source pathology imaging software QuPath. The outcomes from U-Net and QuPath were used to calculate the ratios of differentiation/undifferentiated components which were correlated to lymph node metastasis.

RESULTS

The models established by U-Net recognised ∼91% of the regions of interest, with precision, recall, and F1 values of 90.2%, 90.9% and 94.6%, respectively, indicating a high level of accuracy and reliability. Furthermore, the receiver operating characteristic curve analysis showed an area under the cure of 91%, indicating good performance. A bell-curve correlation between the differentiated/undifferentiated ratio and lymphatic metastasis was found (highest risk between 0.683 and 1.03), which is paradigm-shifting.

CONCLUSION

U-Net and QuPath exhibit promising accuracy in the identification of differentiated and undifferentiated components in mixed-type gastric cancer, as well as paradigm-shifting prediction of metastasis. These findings bring us one step closer to their potential clinical application.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

The prognostic and predictive role of tumor-infiltrating lymphocytes (FoxP3 + and CD8 +) and tumor-associated macrophages in early HER2 + breast cancer

PURPOSE

In HER2-positive (HER2 +) breast cancer, tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs) may influence the efficacy of the HER2-antibody trastuzumab and the patient's outcome. In this HER2 + patient cohort, our aim was to study the numbers of FoxP3 + regulatory TILs and CD8 + cytotoxic TILs, their correlations with CD68 + and CD163 + TAMs, and the prognostic and predictive value of the studied factors.

METHODS

We evaluated 139 non-metastatic HER2 + breast cancer patients operated between 2001 and 2008. The FoxP3+TIL count (FoxP3+TILs) was assessed using the hotspot method, and the CD8 + TIL count (CD8+mTILs) utilizing a digital image analysis from invasive margin areas. The ratios between CD8+mTILs and FoxP3+TILs as well as CD8+mTILs and TAMs were calculated.

RESULTS

FoxP3 + TILs and CD8 + mTILs correlated positively with each other (p<0.001). FoxP3+TILs had a positive correlation with CD68+and CD163+TAMs (p≤0.038), while CD8 + mTILs correlated only with CD68+TAMs (p<0.001). In the HER2 + and hormone receptor-positive Luminal B subgroup, high numbers of FoxP3+TILs were associated with shorter disease-free survival (DFS) (54% vs. 79%, p = 0.040). The benefit from adjuvant trastuzumab was extremely significant among patients with a high CD8 + mTILs/CD68 + TAMs ratio, with overall survival (OS) 84% vs. 33% (p = 0.003) and breast cancer-specific survival (BCSS) 88% vs. 48% (p = 0.009) among patients treated with or without trastuzumab, respectively.

CONCLUSION

In the HER2 + Luminal B subgroup, high FoxP3 + TILs were associated with shorter DFS. A high CD8 + mTILs/CD68 + TAMs ratio seems to associate with impressive efficacy of trastuzumab.

The tumor-stroma ratio and the immune microenvironment improve the prognostic prediction of pancreatic ductal adenocarcinoma

Tumor-infiltrating immune cells and fibroblasts are significant components of the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC), and they participate in tumor progression as closely as tumor cells. However, the relationship between the features of the TME and patient outcomes and the interactions among TME components are still unclear. In this study, we evaluated the PDAC TME in terms of the quantity and location of cluster of differentiation (CD)4⁺ T cells, CD8⁺ T cells, macrophages, stromal maturity, and tumor-stroma ratio (TSR), as evaluated by immunohistochemical staining of serial whole-tissue sections from 116 patients with PDAC. The density of T cells and macrophages (mainly activated macrophages) was significantly higher at the invasive margins (IMs) than at the tumor center (TC). CD4⁺ T cells were significantly association with all the other tumor-associated immune cells (TAIs) including CD8, CD68 and CD206 positive cells. Tumors of the non-mature (intermediate and immature) stroma type harbored significantly more CD8⁺ T cells at the IMs and more CD68⁺ macrophages at the IMs and the TC. The density of CD4⁺, CD8⁺, and CD206⁺ cells at the TC; CD206⁺ cells at the IMs; and tumor-node-metastasis (TNM) staging were independent risk factors for patient outcomes, and the c-index of the risk nomogram for predicting the survival probability based on the TME features and TNM staging was 0.772 (95% confidence interval: 0.713-0.832). PDAC harbored a significantly immunosuppressive TME, of which the IMs were the hot zones for TAIs, while cells at the TC were more predictive of prognosis. Our results indicated that the model based on the features of the TME and TNM staging could predict patient outcomes.

Automated Analysis of PD1 and PDL1 Expression in Lymph Nodes and the Microenvironment of Transmissible Tumors in Tasmanian Devils

The wild Tasmanian devil (Sarcophilus harrisii) population has suffered a devastating decline due to two clonal transmissible cancers. The first devil facial tumor 1 (DFT1) was observed in 1996, followed by a second genetically distinct transmissible tumor, the devil facial tumor 2 (DFT2), in 2014. DFT1/2 frequently metastasize, with lymph nodes being common metastatic sites. MHC-I downregulation by DFT1 cells is a primary means of evading allograft immunity aimed at polymorphic MHC-I proteins. DFT2 cells constitutively express MHC-I, and MHC-I is upregulated on DFT1/2 cells by interferon gamma, suggesting other immune evasion mechanisms may contribute to overcoming allograft and anti-tumor immunity. Human clinical trials have demonstrated PD1/PDL1 blockade effectively treats patients showing increased expression of PD1 in tumor draining lymph nodes, and PDL1 on peritumoral immune cells and tumor cells. The effects of DFT1/2 on systemic immunity remain largely uncharacterized. This study applied the open-access software QuPath to develop a semiautomated pipeline for whole slide analysis of stained tissue sections to quantify PD1/PDL1 expression in devil lymph nodes. The QuPath protocol provided strong correlations to manual counting. PD-1 expression was approximately 10-fold higher than PD-L1 expression in lymph nodes and was primarily expressed in germinal centers, whereas PD-L1 expression was more widely distributed throughout the lymph nodes. The density of PD1 positive cells was increased in lymph nodes containing DFT2 metastases, compared to DFT1. This suggests PD1/PDL1 exploitation may contribute to the poorly immunogenic nature of transmissible tumors in some devils and could be targeted in therapeutic or prophylactic treatments.Abbreviations: PD1: programmed cell death protein 1; PDL1: programmed death ligand 1; DFT1: devil facial tumor 1; DFT2: devil facial tumor 2; DFTD: devil facial tumor disease; MCC: Matthew's correlation coefficient; DAB: diaminobenzidine; ROI: region of interest.

QuPath Algorithm Accurately Identifies MLH1-Deficient Inflammatory Bowel Disease-Associated Colorectal Cancers in a Tissue Microarray

Current methods for analysing immunohistochemistry are labour-intensive and often confounded by inter-observer variability. Analysis is time consuming when identifying small clinically important cohorts within larger samples. This study trained QuPath, an open-source image analysis program, to accurately identify MLH1-deficient inflammatory bowel disease-associated colorectal cancers (IBD-CRC) from a tissue microarray containing normal colon and IBD-CRC. The tissue microarray (n = 162 cores) was immunostained for MLH1, digitalised, and imported into QuPath. A small sample (n = 14) was used to train QuPath to detect positive versus no MLH1 and tissue histology (normal epithelium, tumour, immune infiltrates, stroma). This algorithm was applied to the tissue microarray and correctly identified tissue histology and MLH1 expression in the majority of valid cases (73/99, 73.74%), incorrectly identified MLH1 status in one case (1.01%), and flagged 25/99 (25.25%) cases for manual review. Qualitative review found five reasons for flagged cores: small quantity of tissue, diverse/atypical morphology, excessive inflammatory/immune infiltrations, normal mucosa, or weak/patchy immunostaining. Of classified cores (n = 74), QuPath was 100% (95% CI 80.49, 100) sensitive and 98.25% (95% CI 90.61, 99.96) specific for identifying MLH1-deficient IBD-CRC; κ = 0.963 (95% CI 0.890, 1.036) (p < 0.001). This process could be efficiently automated in diagnostic laboratories to examine all colonic tissue and tumours for MLH1 expression.

Tertiary lymphoid structures in the primary tumor site of patients with cancer-associated myositis: A case-control study

Objective

To investigate histologic features of immunological components in the primary tumor site of patients with cancer-associated myositis (CAM) by focusing on tumor-infiltrating lymphocytes (TILs) and tertiary lymphoid structures (TLSs), which play major roles in antitumor immunity.

Methods

Cancer-associated myositis patients were selected from the single-center idiopathic inflammatory myopathy cohort based on the availability of primary tumor specimens obtained before the introduction of immunomodulatory agents. Control cancer subjects without CAM were selected from the cancer tissue repository at a ratio of 1:2 matched for demographics and cancer characteristics of CAM cases. A series of immunohistochemical analyses was conducted using sequential tumor sections. TLS was defined as an ectopic lymphoid-like structure composed of DC-LAMP⁺ mature dendritic cells, CD23⁺ follicular dendritic cells (FDCs) and PNAd⁺ high endothelial venules. TLS distribution was classified into the tumor center, invasive margin, and peritumoral area.

Results

Six CAM patients and 12 matched non-CAM controls were eligible for the study. There was no apparent difference in the density or distribution of TILs between the groups. TLSs were found in 3 CAM patients (50%) and 4 non-CAM controls (33%). TLSs were exclusively located at the tumor center or invasive margin in CAM cases but were mainly found in the peritumoral area in non-CAM controls. FDCs and class-switched B cells colocalized with follicular helper T cells were abundantly found in the germinal center-like area of TLSs from CAM patients compared with those from non-CAM controls.

Conclusion

The adaptive immune response within TLSs in the primary tumor site might contribute to the pathogenic process of CAM.

Radiomic models based on magnetic resonance imaging predict the spatial distribution of CD8+ tumor-infiltrating lymphocytes in breast cancer

Infiltration of CD8⁺ T cells and their spatial contexture, represented by immunophenotype, predict the prognosis and therapeutic response in breast cancer. However, a non-surgical method using radiomics to evaluate breast cancer immunophenotype has not been explored. Here, we assessed the CD8⁺ T cell-based immunophenotype in patients with breast cancer undergoing upfront surgery (n = 182). We extracted radiomic features from the four phases of dynamic contrast-enhanced magnetic resonance imaging, and randomly divided the patients into training (n = 137) and validation (n = 45) cohorts. For predicting the immunophenotypes, radiomic models (RMs) that combined the four phases demonstrated superior performance to those derived from a single phase. For discriminating the inflamed tumor from the non-inflamed tumor, the feature-based combination model from the whole tumor (RM-whole_FC) showed high performance in both training (area under the receiver operating characteristic curve [AUC] = 0.973) and validation cohorts (AUC = 0.985). Similarly, the feature-based combination model from the peripheral tumor (RM-peri_FC) discriminated between immune-desert and excluded tumors with high performance in both training (AUC = 0.993) and validation cohorts (AUC = 0.984). Both RM-whole_FC and RM-peri_FC demonstrated good to excellent performance for every molecular subtype. Furthermore, in patients who underwent neoadjuvant chemotherapy (n = 64), pre-treatment images showed that tumors exhibiting complete response to neoadjuvant chemotherapy had significantly higher scores from RM-whole_FC and lower scores from RM-peri_FC. Our RMs predicted the immunophenotype of breast cancer based on the spatial distribution of CD8⁺ T cells with high accuracy. This approach can be used to stratify patients non-invasively based on the status of the tumor-immune microenvironment.

Immune modulation by molecularly targeted photothermal ablation in a mouse model of advanced hepatocellular carcinoma and cirrhosis

Immunotherapy is a promising new treatment approach for hepatocellular carcinoma (HCC), but there are numerous barriers to immunotherapy in HCC, including an immunosuppressive microenvironment and the "immunotolerance" of the liver. Hyperthermia treatment modalities are standard of care for early stage HCC, and hyperthermia is known to have immunomodulatory effects. We have developed a molecularly targeted photothermal ablation (MTPA) technology that provides thermally tunable, tumor-specific heat generation. The purpose of this study was to evaluate the morphologic and immunologic effects of MTPA in an immunotherapy-resistant syngeneic mouse model of HCC in a background of toxin-induced cirrhosis. We found that the anatomic, cellular, and molecular features of this model recapitulate the characteristics of advanced human HCC. MTPA as a monotherapy and in combination with immune checkpoint therapy significantly increased intratumoral CD3+ and activated CD8+ T cells while decreasing regulatory T cells relative to control or immune checkpoint therapy alone based on immunohistochemistry, flow cytometry, and single cell RNA sequencing data. Furthermore, we identified evidence of MTPA's influence on systemic tumor immunity, with suppression of remote tumor growth following treatment of orthotopic tumors. The results of this study suggest that tumor-specific hyperthermia may help overcome resistance mechanisms to immunotherapy in advanced HCC.

Simultaneous and Spatially-Resolved Analysis of T-Lymphocytes, Macrophages and PD-L1 Immune Checkpoint in Rare Cancers

Penile, vulvar and anal neoplasms show an incidence lower than 0.5% of the population per year and therefore can be considered as rare cancers but with a dramatic impact on quality of life and survival. This work describes the experience of a Chilean cancer center using multiplexed immunofluorescence to study a case series of four penile cancers, two anal cancers and one vulvar cancer and simultaneous detection of CD8, CD68, PD-L1, Cytokeratin and Ki-67 in FFPE samples. Fluorescent image analyses were performed using open sources for automated tissue segmentation and cell phenotyping. Our results showed an objective and reliable counting of objects with a single or combined labeling or within a specific tissue compartment. The variability was below 10%, and the correlation between analytical events was 0.92-0.97. Critical cell phenotypes, such as TILs, PD-L1+ or proliferative tumor cells were detected in a supervised and unsupervised manner with a limit of detection of less than 1% of relative abundance. Finally, the observed diversity and abundance of the different cell phenotypes within the tumor microenvironment for the three studied tumor types confirmed that our methodology is useful and robust to be applicable for many other solid tumors.

Gorham-Stout case report: a multi-omic analysis reveals recurrent fusions as new potential drivers of the disease

Background

Gorham-Stout disease is a rare condition characterized by vascular proliferation and the massive destruction of bone tissue. With less than 400 cases in the literature of Gorham-Stout syndrome, we performed a unique study combining whole-genome sequencing and RNA-Seq to probe the genomic features and differentially expressed pathways of a presented case, revealing new possible drivers and biomarkers of the disease.

Case presentation

We present a case report of a white 45-year-old female patient with marked bone loss of the left humerus associated with vascular proliferation, diagnosed with Gorham-Stout disease. The analysis of whole-genome sequencing showed a dominance of large structural DNA rearrangements. Particularly, rearrangements in chromosomes seven, twelve, and twenty could contribute to the development of the disease, especially a gene fusion involving ATG101 that could affect macroautophagy. The study of RNA-sequencing data from the patient uncovered the PI3K/AKT/mTOR pathway as the most affected signaling cascade in the Gorham-Stout lesional tissue. Furthermore, M2 macrophage infiltration was detected using immunohistochemical staining and confirmed by deconvolution of the RNA-seq expression data.

Conclusions

The way that DNA and RNA aberrations lead to Gorham-Stout disease is poorly understood due to the limited number of studies focusing on this rare disease. Our study provides the first glimpse into this facet of the disease, exposing new possible therapeutic targets and facilitating the clinicopathological diagnosis of Gorham-Stout disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01277-x.

Developing image analysis methods for digital pathology

The potential to use quantitative image analysis and artificial intelligence is one of the driving forces behind digital pathology. However, despite novel image analysis methods for pathology being described across many publications, few become widely adopted and many are not applied in more than a single study. The explanation is often straightforward: software implementing the method is simply not available, or is too complex, incomplete, or dataset‐dependent for others to use. The result is a disconnect between what seems already possible in digital pathology based upon the literature, and what actually is possible for anyone wishing to apply it using currently available software. This review begins by introducing the main approaches and techniques involved in analysing pathology images. I then examine the practical challenges inherent in taking algorithms beyond proof‐of‐concept, from both a user and developer perspective. I describe the need for a collaborative and multidisciplinary approach to developing and validating meaningful new algorithms, and argue that openness, implementation, and usability deserve more attention among digital pathology researchers. The review ends with a discussion about how digital pathology could benefit from interacting with and learning from the wider bioimage analysis community, particularly with regard to sharing data, software, and ideas. © 2022 The Author. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Immune Checkpoint Inhibitors in Triple Negative Breast Cancer: The Search for the Optimal Biomarker

Triple negative breast cancer (TNBC) is a high-risk and aggressive malignancy characterized by the absence of estrogen receptors (ER) and progesterone receptors (PR) on the surface of malignant cells, and by the lack of overexpression of human epidermal growth factor 2 (HER2). It has limited therapeutic options compared to other subtypes of breast cancer. There is now a growing body of evidence on the role of immunotherapy in TNBC, however much of the data from clinical trials is conflicting and thus, challenging for clinicians to integrate the data into clinical practice. Landmark phase III trials using immunotherapy in the early-stage neoadjuvant setting concluded that the addition of immunotherapy to chemotherapy improved the pathologic complete response (pCR) rate compared to chemotherapy with placebo while others found no significant improvement in pCR. Phase III trials have investigated the utility of immunotherapy in previously untreated metastatic TNBC, and these studies have similarly arrived at inconsistent conclusions. Some studies showed no benefit while others demonstrated a clinically significant improvement in overall survival in the PD-L1 positive population. It is not yet clear which biomarkers are most useful, and assays for these biomarkers have not been standardized. Given the often serious and severe side effects of immunotherapy, it is important and necessary to identify predictive biomarkers of response and resistance in order to enhance patient selection. In this review, we will discuss both the challenges of traditional biomarkers and the opportunities of emerging biomarkers for patient selection.

Assessing Tumor-Infiltrating Lymphocytes in Breast Cancer: A Proposal for Combining Immunohistochemistry and Gene Expression Analysis to Refine Scoring

Scoring of tumor-infiltrating lymphocytes (TILs) in breast cancer specimens has gained increasing attention, as TILs have prognostic and predictive value in HER2+ and triple-negative breast cancer. We evaluated the intra- and interrater variability when scoring TILs by visual inspection of hematoxylin and eosin-stained tissue sections. We further addressed whether immunohistochemical staining of these sections for immune cell surface markers CD45, CD3, CD4, and CD8 and combination with nanoString nCounter® gene expression analysis could refine TIL scoring. Formalin-fixed paraffin-embedded and fresh-frozen core needle biopsies of 12 female and treatment-naive breast cancer patients were included. Scoring of TILs was performed twice by three independent pathologists with a washout period of 3 days. Increasing intra- and interrater variability was observed with higher TIL numbers. The highest reproducibility was observed on tissue sections stained for CD3 and CD8. The latter TIL scores correlated well with the TIL scores obtained through nanoString nCounter® gene expression analysis. Gene expression analysis also revealed 104 and 62 genes that are positively and negatively related to both TIL scores. In conclusion, integration of immunohistochemistry and gene expression analysis is a valuable strategy to refine TIL scoring in breast tumors.

Integrin αvβ6 as a Target for Tumor-Specific Imaging of Vulvar Squamous Cell Carcinoma and Adjacent Premalignant Lesions

Surgical removal of vulvar squamous cell carcinoma (VSCC) is associated with significant morbidity and high recurrence rates. This is at least partially related to the limited visual ability to distinguish (pre)malignant from normal vulvar tissue. Illumination of neoplastic tissue based on fluorescent tracers, known as fluorescence-guided surgery (FGS), could help resect involved tissue and decrease ancillary mutilation. To evaluate potential targets for FGS in VSCC, immunohistochemistry was performed on paraffin-embedded premalignant (high grade squamous intraepithelial lesion and differentiated vulvar intraepithelial neoplasia) and VSCC (human papillomavirus (HPV)-dependent and -independent) tissue sections with healthy vulvar skin as controls. Sections were stained for integrin αvβ6, CAIX, CD44v6, EGFR, EpCAM, FRα, MRP1, MUC1 and uPAR. The expression of each marker was quantified using digital image analysis. H-scores were calculated and percentages positive cells, expression pattern, and biomarker localization were assessed. In addition, tumor-to-background ratios were established, which were highest for (pre)malignant vulvar tissues stained for integrin αvβ6. In conclusion, integrin αvβ6 allowed for the most robust discrimination of VSCCs and adjacent premalignant lesions compared to surrounding healthy tissue in immunohistochemically stained tissue sections. The use of an αvβ6 targeted near-infrared fluorescent probe for FGS of vulvar (pre)malignancies should be evaluated in future studies.

Kinomics platform using GBM tissue identifies BTK as being associated with higher patient survival

BTK is a dominant bioactive kinase expressed within both cancer and immune cells of GBM tissue. Complex cell co-cultures might better model the impact of kinase inhibitors as therapeutics in GBM.

Better understanding of GBM signalling networks in-vivo would help develop more physiologically relevant ex vivo models to support therapeutic discovery. A “functional proteomics” screen was undertaken to measure the specific activity of a set of protein kinases in a two-step cell-free biochemical assay to define dominant kinase activities to identify potentially novel drug targets that may have been overlooked in studies interrogating GBM-derived cell lines. A dominant kinase activity derived from the tumour tissue, but not patient-derived GBM stem-like cell lines, was Bruton tyrosine kinase (BTK). We demonstrate that BTK is expressed in more than one cell type within GBM tissue; SOX2-positive cells, CD163-positive cells, CD68-positive cells, and an unidentified cell population which is SOX2-negative CD163-negative and/or CD68-negative. The data provide a strategy to better mimic GBM tissue ex vivo by reconstituting more physiologically heterogeneous cell co-culture models including BTK-positive/negative cancer and immune cells. These data also have implications for the design and/or interpretation of emerging clinical trials using BTK inhibitors because BTK expression within GBM tissue was linked to longer patient survival.

Breast Cancer Heterogeneity

Breast tumor heterogeneity is a major challenge in the clinical management of breast cancer patients. Both inter-tumor and intra-tumor heterogeneity imply that each breast cancer (BC) could have different prognosis and would benefit from specific therapy. Breast cancer is a dynamic entity, changing during tumor progression and metastatization and this poses fundamental issues to the feasibility of a personalized medicine approach. The most effective therapeutic strategy for patients with recurrent disease should be assessed evaluating biopsies obtained from metastatic sites. Furthermore, the tumor progression and the treatment response should be strictly followed and radiogenomics and liquid biopsy might be valuable tools to assess BC heterogeneity in a non-invasive way.

Whole-Slide Image Analysis of Human Pancreas Samples to Elucidate the Immunopathogenesis of Type 1 Diabetes Using the QuPath Software

Type 1 diabetes is a chronic disease of the pancreas characterized by the loss of insulin-producing beta cells. Access to human pancreas samples for research purposes has been historically limited, restricting pathological analyses to animal models. However, intrinsic differences between animals and humans have made clinical translation very challenging. Recently, human pancreas samples have become available through several biobanks worldwide, and this has opened numerous opportunities for scientific discovery. In addition, the use of new imaging technologies has unraveled many mysteries of the human pancreas not merely in the presence of disease, but also in physiological conditions. Nowadays, multiplex immunofluorescence protocols as well as sophisticated image analysis tools can be employed. Here, we described the use of QuPath—an open-source platform for image analysis—for the investigation of human pancreas samples. We demonstrate that QuPath can be adequately used to analyze whole-slide images with the aim of identifying the islets of Langerhans and define their cellular composition as well as other basic morphological characteristics. In addition, we show that QuPath can identify immune cell populations in the exocrine tissue and islets of Langerhans, accurately localizing and quantifying immune infiltrates in the pancreas. Therefore, we present a tool and analysis pipeline that allows for the accurate characterization of the human pancreas, enabling the study of the anatomical and physiological changes underlying pancreatic diseases such as type 1 diabetes. The standardization and implementation of these analysis tools is of critical importance to understand disease pathogenesis, and may be informative for the design of new therapies aimed at preserving beta cell function and halting the inflammation caused by the immune attack.

Transcriptomic and Immunophenotypic Characterization of Tumor Immune Microenvironment in Squamous Cell Carcinoma of the Oral Tongue

The tumor immune microenvironment of oral tongue squamous cell carcinoma may be accountable for differences in clinical behavior, particularly between different age groups. We performed RNA expression profiling and evaluated tumor infiltrating lymphocytes (TILs) and their T-cell subsets in order to assess the functional status of oral tongue squamous cell carcinoma tumor microenvironment and detect potentially clinically useful associations. Archival surgical pathology material from sixteen oral tongue squamous cell carcinoma patients was microscopically evaluated for TIL densities. RNA was extracted from macrodissected whole tumor sections and normal controls and RNA expression profiling was performed by the NanoString PanCancer IO 360 Gene Expression Panel. Immunostains for CD4, CD8 and FOXP3 were evaluated manually and by digital image analysis. Oral tongue squamous cell carcinomas had increased TIL densities, numerically dominated by CD4 + T cells, followed by CD8 + and FOXP3 + T cells. RNA expression profiling of tumors versus normal controls showed tumor signature upregulation in inhibitory immune signaling (CTLA4, TIGIT and PD-L2), followed by inhibitory tumor mechanisms (IDO1, TGF-β, B7-H3 and PD-L1). Patients older than 44 years showed a tumor microenvironment with increased Tregs and CTLA4 expression. Immunohistochemically assessed CD8% correlated well with molecular signatures related to CD8 + cytotoxic T-cell functions. FOXP3% correlated significantly with CTLA4 upregulation. CTLA4 molecular signature could be predicted by FOXP3% assessed by immunohistochemistry (R2 = 0.619, p = 0.026). Oral tongue squamous cell carcinoma hosts a complex inhibitory immune microenvironment, partially reflected in immunohistochemically quantified CD8 + and FOXP3 + T-cell subsets. Immunohistochemistry can be a useful screening tool for detecting tumors with upregulated expression of the targetable molecule CTLA4.

Blood Immunosenescence Signatures Reflecting Age, Frailty and Tumor Immune Infiltrate in Patients with Early Luminal Breast Cancer

Simple Summary

Treating older patients with (breast) cancer is a major challenge. On the one hand, older persons are more vulnerable to side effects of therapy, and over-treatment should be avoided. On the other hand, under-treatment (which is common in the elderly) can lead to worse survival and quality of life as well. Benefits of therapy and risk of (sometimes life threatening) toxicity should be carefully balanced. There is an urgent need for robust markers that reflect the body’s biological age and could aid in outlining optimal individual treatment regimens. Here we investigated whether age/frailty and characteristics of the tumor immune infiltrate are mirrored in specific blood biomarker combinations. Several three-biomarker panels were able to categorize patients quite efficiently, especially in terms of their clinical frailty status.

Abstract

Background: Immune/senescence-related host factors play a pivotal role in numerous biological and pathological process like aging, frailty and cancer. The assessment of these host factors via robust, non-invasive, and easy-to-measure blood biomarkers could improve insights in these processes. Here, we investigated in a series of breast cancer patients in which way single circulating biomarkers or biomarker panels relate to chronological age, frailty status, and tumor-associated inflammatory microenvironment. Methods: An extensive panel of blood immune/senescence markers and the tumor immune infiltrate was studied in young, middle-aged, and old patients with an early invasive hormone-sensitive, HER2-negative breast cancer. In the old group, clinical frailty was estimated via the G8-scores. Results: Several three-blood biomarker panels proved to be able to separate old chronological age from young age very efficiently. Clinically more important, several three-blood biomarker panels were strongly associated with clinical frailty. Performance of blood biomarker panels for prediction of the tumor immune infiltrate was lower. Conclusion: Immune/senescence blood biomarker panels strongly correlate with chronological age, and clinically more importantly with frailty status in early breast cancer patients. They require further investigation on their ability to provide a more complete picture on clinical frailty status and direct personalized therapy in older persons.

Quantitative systems pharmacology model predictions for efficacy of atezolizumab and nab-paclitaxel in triple-negative breast cancer

Background

Immune checkpoint blockade therapy has clearly shown clinical activity in patients with triple-negative breast cancer, but less than half of the patients benefit from the treatments. While a number of ongoing clinical trials are investigating different combinations of checkpoint inhibitors and chemotherapeutic agents, predictive biomarkers that identify patients most likely to benefit remains one of the major challenges. Here we present a modular quantitative systems pharmacology (QSP) platform for immuno-oncology that incorporates detailed mechanisms of immune–cancer cell interactions to make efficacy predictions and identify predictive biomarkers for treatments using atezolizumab and nab-paclitaxel.

Methods

A QSP model was developed based on published data of triple-negative breast cancer. With the model, we generated a virtual patient cohort to conduct in silico virtual clinical trials and make retrospective analyses of the pivotal IMpassion130 trial that led to the accelerated approval of atezolizumab and nab-paclitaxel for patients with programmed death-ligand 1 (PD-L1) positive triple-negative breast cancer. Available data from clinical trials were used for model calibration and validation.

Results

With the calibrated virtual patient cohort based on clinical data from the placebo comparator arm of the IMpassion130 trial, we made efficacy predictions and identified potential predictive biomarkers for the experimental arm of the trial using the proposed QSP model. The model predictions are consistent with clinically reported efficacy endpoints and correlated immune biomarkers. We further performed a series of virtual clinical trials to compare different doses and schedules of the two drugs for simulated therapeutic optimization.

Conclusions

This study provides a QSP platform, which can be used to generate virtual patient cohorts and conduct virtual clinical trials. Our findings demonstrate its potential for making efficacy predictions for immunotherapies and chemotherapies, identifying predictive biomarkers, and guiding future clinical trial designs.

Digital Pathology Analysis Quantifies Spatial Heterogeneity of CD3, CD4, CD8, CD20, and FoxP3 Immune Markers in Triple-Negative Breast Cancer

Overwhelming evidence has shown the significant role of the tumor microenvironment (TME) in governing the triple-negative breast cancer (TNBC) progression. Digital pathology can provide key information about the spatial heterogeneity within the TME using image analysis and spatial statistics. These analyses have been applied to CD8+ T cells, but quantitative analyses of other important markers and their correlations are limited. In this study, a digital pathology computational workflow is formulated for characterizing the spatial distributions of five immune markers (CD3, CD4, CD8, CD20, and FoxP3) and then the functionality is tested on whole slide images from patients with TNBC. The workflow is initiated by digital image processing to extract and colocalize immune marker-labeled cells and then convert this information to point patterns. Afterward invasive front (IF), central tumor (CT), and normal tissue (N) are characterized. For each region, we examine the intra-tumoral heterogeneity. The workflow is then repeated for all specimens to capture inter-tumoral heterogeneity. In this study, both intra- and inter-tumoral heterogeneities are observed for all five markers across all specimens. Among all regions, IF tends to have higher densities of immune cells and overall larger variations in spatial model fitting parameters and higher density in cell clusters and hotspots compared to CT and N. Results suggest a distinct role of IF in the tumor immuno-architecture. Though the sample size is limited in the study, the computational workflow could be readily reproduced and scaled due to its automatic nature. Importantly, the value of the workflow also lies in its potential to be linked to treatment outcomes and identification of predictive biomarkers for responders/non-responders, and its application to parameterization and validation of computational immuno-oncology models.

Age-related remodelling of the blood immunological portrait and the local tumor immune response in patients with luminal breast cancer

Objectives

Aging is associated with altered immune function and chronic low-grade inflammation, referred to as immunosenescence. As breast cancer is an age-related disease, the impact of aging on tumor immune responses may have important consequences. However, effects of immunosenescence on breast tumor immune infiltration remain largely unknown.

Methods

This exploratory study investigated a broad panel of immune/senescence markers in peripheral blood and in the tumor microenvironment of young, middle-aged and old patients diagnosed with early invasive luminal (hormone-sensitive, HER2-negative) breast cancer. In the old group, G8-scores were computed as a correlate for clinical frailty.

Results

Significant age-related changes in plasma levels of several inflammatory mediators (IL-1α, IP-10, IL-8, MCP-1, CRP), immune checkpoint markers (Gal-9, sCD25, TIM-3, PD-L1), IGF-1 and circulating miRs (miR-18a, miR-19b, miR-20, miR-155, miR-195 and miR-326) were observed. Shifts were observed in distinct peripheral blood mononuclear cell populations, particularly naive CD8⁺ T-cells. At the tumor level, aging was associated with lower total lymphocytic infiltration, together with decreased abundance of several immune cell markers, especially CD8. The relative fractions of cell subsets in the immune infiltrate were also altered. Clinical frailty was associated with higher frequencies of exhausted/senescent (CD27^-CD28^- and/or CD57⁺) terminally differentiated CD8⁺ cells in the blood and with increased tumor infiltration by FOXP3⁺ cells.

Conclusion

Aging and frailty are associated with profound changes of the blood and tumor immune profile in luminal breast cancer, pointing to a different interplay between tumor cells, immune cells and inflammatory mediators at higher age.

Assessment of stromal tumor infiltrating lymphocytes and immunohistochemical features in invasive micropapillary breast carcinoma with long-term outcomes

PURPOSE

We studied the long-term outcomes of invasive micropapillary carcinoma (IMPCs) of the breast in relation to stromal tumor infiltrating lymphocytes (sTILs), prognostic biomarkers and clinicopathological features.

METHODS

Stage I-III IMPCs treated with upfront surgery at our institution (January 2000 and December 2016) were included. Central pathology review was performed and sTILs (including zonal distribution and hot spot analysis) and tumor-associated plasma cells (TAPC) were evaluated. Expression of P53, BCL2, FOXP3, and WT1, which are variably linked to breast cancer prognosis, was measured by immunohistochemistry using tissue microarrays. Time-to-event endpoints were distant recurrence free interval (DRFI) and breast cancer-specific survival (BCSS).

RESULTS

We included 111 patients of whom 59% were pure IMPCs. Standard clinicopathological features were comparable between pure and non-pure IMPCs. Overall, the mean sTILs level was 20% with higher proportion of sTILs present at the invasive front. There were no significant differences between pure- and non-pure IMPCs in sTILs levels, nor in the spatial distribution of the hot spot regions or in the distribution of TAPC. Higher sTILs correlated with worse DRFI (HR = 1.55; p = 0.0172) and BCSS (HR = 2.10; p < 0.001).

CONCLUSIONS

Clinicopathological features, geographical distribution of sTILs and TAPC are similar between pure and non-pure IMPCs. Despite a high proportion of grade 3 tumors and lymph node involvement, we observed a low rate of distant recurrences and breast cancer-related death in this cohort of stage I-III IMPCs treated with primary surgery. Caution in interpretation of the observed prognostic correlations is required given the very low number of events, warranting validation in other cohorts.

TILs Immunophenotype in Breast Cancer Predicts Local Failure and Overall Survival: Analysis in a Large Radiotherapy Trial with Long-Term Follow-Up

AIM

To determine the prognostic significance of the immunophenotype of tumour-infiltrating lymphocytes (TILs) within a cohort of breast cancer patients with long-term follow-up.

METHODS

Multiplexed immunofluorescence and automated image analysis were used to assess the expression of CD3, CD8, CD20, CD68, Fox P3, PD-1 and PD-L1 in a clinical trial of local excision and radiotherapy randomised to a cavity boost or not (n = 485, median follow-up 16 years). Kaplan-Meier and Cox multivariate analysis (MVA) methodology were used to ascertain relationships with local recurrence (LR), overall survival (OS) and disease-free survival (DFS). NanoString BC360 gene expression panel was applied to a subset of luminal patients to identify pathways associated with LR.

RESULTS

LR was predicted by low CD8 in MVA in the whole cohort (HR 2.34, CI 1.4-4.02, p = 0.002) and luminal tumours (HR 2.19, CI 1.23-3.92, p = 0.008) with associations with increased stromal components, decreased Tregs (FoxP3), inflammatory chemokines and SOX2. Poor OS was associated with low CD20 in the whole cohort (HR 1.73, CI 1.2-2.4, p = 0.002) and luminal tumours on MVA and low PD-L1 in triple-negative cancer (HR 3.44, CI 1.5-7, p = 0.003).

CONCLUSIONS

Immunophenotype adds further prognostic data to help further stratify risk of LR and OS even in TILs low-luminal tumours.