Biopsy variability of lymphocytic infiltration in breast cancer subtypes and the ImmunoSkew score

Prediction value study of breast cancer tumor infiltrating lymphocyte levels based on ultrasound imaging radiomics

Objective

Construct models based on grayscale ultrasound and radiomics and compare the efficacy of different models in preoperatively predicting the level of tumor-infiltrating lymphocytes in breast cancer.

Materials and methods

This study retrospectively collected clinical data and preoperative ultrasound images from 185 breast cancer patients confirmed by surgical pathology. Patients were randomly divided into a training set (n=111) and a testing set (n=74) using a 6:4 ratio. Based on a 10% threshold for tumor-infiltrating lymphocytes (TIL) levels, patients were classified into low-level and high-level groups. Radiomic features were extracted and selected using the training set. The evaluation included assessing the relationship between TIL levels and both radiomic features and grayscale ultrasound features. Subsequently, grayscale ultrasound models, radiomic models, and nomograms combining radiomics score (Rad-score) and grayscale ultrasound features were established. The predictive performance of different models was evaluated through receiver operating characteristic (ROC) analysis. Calibration curves assessed the fit of the nomograms, and decision curve analysis (DCA) evaluated the clinical effectiveness of the models.

Results

Univariate analyses and multivariate logistic regression analyses revealed that indistinct margin (P<0.001, Odds Ratio [OR]=0.214, 95% Confidence Interval [CI]: 0.103-1.026), posterior acoustic enhancement (P=0.027, OR=2.585, 95% CI: 1.116-5.987), and ipsilateral axillary lymph node enlargement (P=0.001, OR=4.214, 95% CI: 1.798-9.875) were independent predictive factors for high levels of TIL in breast cancer. In comparison to grayscale ultrasound model (Training set: Area under curve [AUC] 0.795; Testing set: AUC 0.720) and radiomics model (Training set: AUC 0.803; Testing set: AUC 0.759), the nomogram demonstrated superior discriminative ability on both the training (AUC 0.884) and testing (AUC 0.820) datasets. Calibration curves indicated high consistency between the nomogram model's predicted probability of breast cancer TIL levels and the actual occurrence probability. DCA revealed that the radiomics model and the nomogram model achieved higher clinical net benefits compared to the grayscale ultrasound model.

Conclusion

The nomogram based on preoperative ultrasound radiomics features exhibits robust predictive capacity for the non-invasive evaluation of breast cancer TIL levels, potentially providing a significant basis for individualized treatment decisions in breast cancer.

Elasticity Values as a Predictive Modality for Response to Neoadjuvant Chemotherapy in Breast Cancer

Shear-wave elastography (SWE) is an effective tool in discriminating malignant lesions of breast and axillary lymph node metastasis in patients with breast cancer. However, the association between the baseline elasticity value of breast cancer and the treatment response of neoadjuvant chemotherapy is yet to be elucidated. Baseline SWE measured mean stiffness (E-mean) and maximum stiffness (E-max) in 830 patients who underwent neoadjuvant chemotherapy and surgery from January 2012 to December 2022. Association of elasticity values with breast pCR (defined as ypTis/T0), pCR (defined as ypTis/T0, N0), and tumor-infiltrating lymphocytes (TILs) was analyzed. Of 830 patients, 356 (42.9%) achieved breast pCR, and 324 (39.0%) achieved pCR. The patients with low elasticity values had higher breast pCR and pCR rates than those with high elasticity values. A low E-mean (adjusted odds ratio (OR): 0.620; 95% confidence interval (CI): 0.437 to 0.878; p = 0.007) and low E-max (adjusted OR: 0.701; 95% CI: 0.494 to 0.996; p = 0.047) were independent predictive factors for breast pCR. Low elasticity values were significantly correlated with high TILs. Pretreatment elasticity values measured using SWE were significantly associated with treatment response and inversely correlated with TILs, particularly in HR+HER2- breast cancer and TNBC.

Tumor Heterogeneity Confounds Lymphocyte Metrics in Diagnostic Lung Cancer Biopsies

CONTEXT.—

The immune microenvironment is involved in fundamental aspects of tumorigenesis, and immune scores are now being developed for clinical diagnostics.

OBJECTIVE.—

To evaluate how well small diagnostic biopsies and tissue microarrays (TMAs) reflect immune cell infiltration compared to the whole tumor slide, in tissue from patients with non-small cell lung cancer.

DESIGN.—

A TMA was constructed comprising tissue from surgical resection specimens of 58 patients with non-small cell lung cancer, with available preoperative biopsy material. Whole sections, biopsies, and TMA were stained for the pan-T lymphocyte marker CD3 to determine densities of tumor-infiltrating lymphocytes. Immune cell infiltration was assessed semiquantitatively as well as objectively with a microscopic grid count. For 19 of the cases, RNA sequencing data were available.

RESULTS.—

The semiquantitative comparison of immune cell infiltration between the whole section and the biopsy displayed fair agreement (intraclass correlation coefficient [ICC], 0.29; P = .01; CI, 0.03-0.51). In contrast, the TMA showed substantial agreement compared with the whole slide (ICC, 0.64; P < .001; CI, 0.39-0.79). The grid-based method did not enhance the agreement between the different tissue materials. The comparison of CD3 RNA sequencing data with CD3 cell annotations confirmed the poor representativity of biopsies as well as the stronger correlation for the TMA cores.

CONCLUSIONS.—

Although overall lymphocyte infiltration is relatively well represented on TMAs, the representativity in diagnostic lung cancer biopsies is poor. This finding challenges the concept of using biopsies to establish immune scores as prognostic or predictive biomarkers for diagnostic applications.

Evaluation of tumor-infiltrating lymphocytes and mammographic density as predictors of response to neoadjuvant systemic therapy in breast cancer

BACKGROUND

Response rates vary among breast cancer patients treated with neoadjuvant systemic therapy (NAST). Thus, there is a need for reliable treatment predictors. Evidence suggests tumor-infiltrating lymphocytes (TILs) predict NAST response. Still, TILs are seldom used clinically as a treatment determinant. Mammographic density (MD) is another potential marker for NAST benefit and its relationship with TILs is unknown. Our aims were to investigate TILs and MD as predictors of NAST response and to study the unexplored relationship between TILs and MD.

MATERIAL AND METHODS

We studied 315 invasive breast carcinomas treated with NAST between 2013 and 2020. Clinicopathological data were retrieved from medical records. The endpoint was defined as pathological complete response (pCR) in the breast. TILs were evaluated in pre-treatment core biopsies and categorized as high (≥10%) or low (<10%). MD was scored (a-d) according to the breast imaging reporting and data system (BI-RADS) fifth edition. Binary logistic regression and Spearman's test of correlation were performed using SPSS.

RESULTS

Out of 315 carcinomas, 136 achieved pCR. 94 carcinomas had high TILs and 215 had low TILs. Six carcinomas had no available TIL data. The number of carcinomas in each BI-RADS category were 37, 122, 112, and 44 for a, b, c, and d, respectively. High TILs were independently associated with pCR (OR: 2.95; 95% CI: 1.59-5.46) compared to low TILs. In the univariable analysis, MD (BI-RADS d vs. a) showed a tendency of higher likelihood for pCR (OR: 2.43; 95% CI: 0.99-5.98). However, the association was non-significant, which is consistent with the result of the multivariable analysis (OR: 2.51; 95% CI: 0.78-8.04). We found no correlation between TILs and MD (0.02; p = .80).

CONCLUSION

TILs significantly predicted NAST response. We could not define MD as a significant predictor of NAST response. These findings should be further replicated.

Core needle biopsies alter the amounts of CCR5, Siglec-15, and PD-L1 positivities in breast carcinoma

Core needle biopsies (CNB) are widely used to diagnose breast cancer, but the procedure is invasive and thus, it changes the tumor microenvironment. The purpose of this study is to see how the expression of three potentially anti-inflammatory molecules, namely, programmed death-ligand 1 (PD-L1), sialic acid-binding immunoglobulin-like lectin-15 (Siglec-15), and C-C chemokine receptor-5 (CCR-5), are expressed in CNB and surgical resection specimens (SRS). To do this, we compared the amounts of tumor-infiltrating lymphocytes and the levels of CCR5, Siglec-15, and PD-L1 in tumor cells and inflammatory cells as assessed by immunohistochemistry in CNB and the corresponding SRS of 22 invasive breast carcinomas of no special type and 22 invasive lobular carcinomas. The Siglec-15 H-score was higher in tumor cells in the SRS than in the CNB groups. There was no change in tumor cells CCR5 or PD-L1 between CNB and SRS. The positive inflammatory cell numbers for all markers rose between CNB and SRS, as did the amount of Tils. Furthermore, higher grade tumors and tumors with a high proliferation rate had more inflammatory cells that were positive for the markers and also more PD-L1+ tumor cells. Although changes in inflammatory cells can partly be attributed to the larger sample size of operation specimens, the differences also mirror a true change in the tumor microenvironment. The changes in inflammatory cells could be partly due to the need to restrict excess inflammation at the site of the biopsy.

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.

Influences of intratumoral heterogeneity on assessment of tumor microenvironment in esophageal squamous cell carcinoma

The intratumoral heterogeneity (ITH) of the tumor microenvironment (TME) has yet to be addressed in esophageal squamous cell carcinoma (ESCC). Here, we studied the ITH of CD8 and PD-L1 status in ESCC, and examined the potential of the tumor surface for representing the TME. In total, 67 surgically resected clinical Stage II ESCC specimens were analyzed. The CD8-cell density, PD-L1 tumor proportion score (TPS), and combined positive score (CPS) were calculated in three (superficial, middle, and deep) areas of each specimen. ITH was quantified by distance-standardized coefficient variations of the three values. The CD8 and PD-L1 status of each area was dichotomized and tumor-surface capabilities for predicting the entire tumor status were estimated. Variables were compared according to the presence of neoadjuvant chemotherapy (NAC). The ITH, especially PD-L1 heterogeneity, differed markedly among specimens. The concordance rates of CD8 and PD-L1 (CPS and TPS) status among the three different areas were 71.6%, 74.6%, and 73.1%, respectively. The sensitivity and the specificity of the tumor surface for predicting the CD8 status of the whole tumor were high, especially in the NAC- group (both 1.0). The tumor surface also showed high capabilities for representing the whole PD-L1 status, while yielding moderate positive predictive values (0.70). The ITH degrees and predictive capabilities did not differ according to NAC. Taken together, the ITH of CD8 and PD-L1 differed among ESCC specimens, while not being markedly affected by NAC. The use of a biopsy specimen from the tumor surface might be feasible for TME evaluation.

Inter-observer agreement of tumor infiltrating lymphocytes in primary HER2-positive breast cancer and correlation between tissue microarray and full tumor-sections

Tumor infiltrating lymphocytes (TILs) have predictive and prognostic potential in HER2-positive breast cancer (HER2 + BC). Due to tumor heterogeneity, guidelines recommend evaluation on full tumor-sections over biopsies, but aren't clear regarding tissue microarrays (TMAs). Herein, we investigate the inter-observer agreement of TILs assessment in HER2 + BC on full-sections and TMAs using a standardized method. Two pathologists assessed TILs using HE full-sections and TMAs from 244 patients with HER2 + BC. TILs were assessed in 10% intervals; values <10% evaluated as 0%, 1% or 5%. Levels of agreement were evaluated using intraclass-coefficient (ICC), Kappa statistics and concordance analysis. For inter-observer agreement for full-sections, ICC was 0.93 (95% CI 0.89-0.95) and Kappa was 0.75, corresponding to acceptable and moderate agreement respectively. For TMAs, ICC was 0.73 (95% CI: 0.62-0.81) and Kappa 0.33, corresponding to unacceptable agreement. For association in matched TMA and full-sections, ICC was 0.64 (95% CI 0.55-0.71) and Lin's concordance correlation coefficient was 0.63 (95% CI 0.55-0.71), corresponding to unacceptable agreement. There is acceptable inter-observer agreement of TILs assessment on full-sections but not TMAs and discrepancy between full-sections and TMAs. TMA preparation must include consideration for representation of both entire tumor area and tumor-microenvironment to correctly define prognostic and predictive values of potential immuno-related biomarkers.

Quantification of tumor heterogeneity: from data acquisition to metric generation

Tumors are unique and complex ecosystems, in which heterogeneous cell subpopulations with variable molecular profiles, aggressiveness, and proliferation potential coexist and interact. Understanding how heterogeneity influences tumor progression has important clinical implications for improving diagnosis, prognosis, and treatment response prediction. Several recent innovations in data acquisition methods and computational metrics have enabled the quantification of spatiotemporal heterogeneity across different scales of tumor organization. Here, we summarize the most promising efforts from a common experimental and computational perspective, discussing their advantages, shortcomings, and challenges. With personalized medicine entering a new era of unprecedented opportunities, our vision is that of future workflows integrating across modalities, scales, and dimensions to capture intricate aspects of the tumor ecosystem and to open new avenues for improved patient care.

Computational pathology reveals unique spatial patterns of immune response in H&E images from COVID-19 autopsies: preliminary findings

Purpose: We used computerized image analysis and machine learning approaches to characterize spatial arrangement features of the immune response from digitized autopsied H&E tissue images of the lung in coronavirus disease 2019 (COVID-19) patients. Additionally, we applied our approach to tease out potential morphometric differences from autopsies of patients who succumbed to COVID-19 versus H1N1. Approach: H&E lung whole slide images from autopsy specimens of nine COVID-19 and two H1N1 patients were computationally interrogated. 606 image patches ( ∼ 55 per patient) of 1024 × 882    pixels were extracted from the 11 autopsied patient studies. A watershed-based segmentation approach in conjunction with a machine learning classifier was employed to identify two types of nuclei families: lymphocytes and non-lymphocytes (i.e., other nucleated cells such as pneumocytes, macrophages, and neutrophils). Based off the proximity of the individual nuclei, clusters for each nuclei family were constructed. For each of the resulting clusters, a series of quantitative measurements relating to architecture and density of nuclei clusters were calculated. A receiver operating characteristics-based feature selection method, violin plots, and the t-distributed stochastic neighbor embedding algorithm were employed to study differences in immune patterns. Results: In COVID-19, the immune response consistently showed multiple small-size lymphocyte clusters, suggesting that lymphocyte response is rather modest, possibly due to lymphocytopenia. In H1N1, we found larger lymphocyte clusters that were proximal to large clusters of non-lymphocytes, a possible reflection of increased prevalence of macrophages and other immune cells. Conclusion: Our study shows the potential of computational pathology to uncover immune response features that may not be obvious by routine histopathology visual inspection.

The role of tumor heterogeneity in immune-tumor interactions

The development of cancer stems from genetic instability and changes in genomic sequences, and hence, the heterogeneity exhibited by tumors is integral to the nature of cancer itself. Tumor heterogeneity can be further altered by factors that are not cancer cell intrinsic, i.e., by the microenvironment, including the patient's immune responses to tumors and administered therapies (immunotherapies, chemotherapies, and/or radiation therapies). The focus of this review is the impact of tumor heterogeneity on the interactions between immune cells and the tumor, taking into account that heterogeneity can exist at several levels. These levels include heterogeneity within an individual tumor, within an individual patient (particularly between the primary tumor and metastatic lesions), among the subtypes of a specific type of cancer, or within cancers that originate from different tissues. Because of the potential for immunity (either the natural immune system or via immunotherapeutics) to halt the progression of cancer, major clinical significance exists in understanding the impact of tumor heterogeneity on the associations between immune cells and tumor cells. Increased knowledge of why, whether, and how immune-tumor interactions occur provides the means to guide these interactions and improve outcomes for patients.

Shortwave infrared emitting multicolored nanoprobes for biomarker-specific cancer imaging in vivo

BACKGROUND

The ability to detect tumor-specific biomarkers in real-time using optical imaging plays a critical role in preclinical studies aimed at evaluating drug safety and treatment response. In this study, we engineered an imaging platform capable of targeting different tumor biomarkers using a multi-colored library of nanoprobes. These probes contain rare-earth elements that emit light in the short-wave infrared (SWIR) wavelength region (900-1700 nm), which exhibits reduced absorption and scattering compared to visible and NIR, and are rendered biocompatible by encapsulation in human serum albumin. The spectrally distinct emissions of the holmium (Ho), erbium (Er), and thulium (Tm) cations that constitute the cores of these nanoprobes make them attractive candidates for optical molecular imaging of multiple disease biomarkers.

METHODS

SWIR-emitting rare-earth-doped albumin nanocomposites (ReANCs) were synthesized using controlled coacervation, with visible light-emitting fluorophores additionally incorporated during the crosslinking phase for validation purposes. Specifically, HoANCs, ErANCs, and TmANCs were co-labeled with rhodamine-B, FITC, and Alexa Fluor 647 dyes respectively. These Rh-HoANCs, FITC-ErANCs, and 647-TmANCs were further conjugated with the targeting ligands daidzein, AMD3100, and folic acid respectively. Binding specificities of each nanoprobe to distinct cellular subsets were established by in vitro uptake studies. Quantitative whole-body SWIR imaging of subcutaneous tumor bearing mice was used to validate the in vivo targeting ability of these nanoprobes.

RESULTS

Each of the three ligand-functionalized nanoprobes showed significantly higher uptake in the targeted cell line compared to untargeted probes. Increased accumulation of tumor-specific nanoprobes was also measured relative to untargeted probes in subcutaneous tumor models of breast (4175 and MCF-7) and ovarian cancer (SKOV3). Preferential accumulation of tumor-specific nanoprobes was also observed in tumors overexpressing targeted biomarkers in mice bearing molecularly-distinct bilateral subcutaneous tumors, as evidenced by significantly higher signal intensities on SWIR imaging.

CONCLUSIONS

The results from this study show that tumors can be detected in vivo using a set of targeted multispectral SWIR-emitting nanoprobes. Significantly, these nanoprobes enabled imaging of biomarkers in mice bearing bilateral tumors with distinct molecular phenotypes. The findings from this study provide a foundation for optical molecular imaging of heterogeneous tumors and for studying the response of these complex lesions to targeted therapy.

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.

Levels of different subtypes of tumour-infiltrating lymphocytes correlate with each other, with matched circulating lymphocytes, and with survival in breast cancer

Purpose

Breast cancer tumour-infiltrating lymphocytes associate with clinico-pathological factors, including survival, although the literature includes many conflicting findings. Our aim was to assess these associations for key lymphocyte subtypes and in different tumour compartments, to determine whether these provide differential correlations and could, therefore, explain published inconsistencies. Uniquely, we also examine whether infiltrating levels merely reflect systemic lymphocyte levels or whether local factors are predominant in recruitment.

Methods

Immunohistochemistry was used to detect tumour-infiltrating CD20+ (B), CD4+ (helper T), CD8+ (cytotoxic T) and FoxP3+ (regulatory T) cells in breast cancers from 62 patients, with quantification in tumour stroma, tumour cell nests, and tumour margins. Levels were analysed with respect to clinico-pathological characteristics and matched circulating levels (determined by flow-cytometry).

Results

CD4+ lymphocytes were the most prevalent subtype in tumour stroma and at tumour edge and CD8+ lymphocytes were most prevalent in tumour nests; FoxP3+ lymphocytes were rarest in all compartments. High grade or hormone receptor negative tumours generally had significantly increased lymphocytes, especially in tumour stroma. Only intra-tumoural levels of CD8+ lymphocytes correlated significantly with matched circulating levels (p < 0.03), suggesting that recruitment is mainly unrelated to systemic activity. High levels of stromal CD4+ and CD20+ cells associated with improved survival in hormone receptor negative cases (p < 0.04), while tumour nest CD8+ and FoxP3+ cells associated with poor survival in hormone receptor positives (p < 0.005).

Conclusions

Lymphocyte subtype and location define differential impacts on tumour biology, therefore, roles of tumour-infiltrating lymphocytes will only be unravelled through thorough analyses that take this into account.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-05757-5) contains supplementary material, which is available to authorized users.

Tumor Infiltrating Lymphocytes and CD8+ T Cell Subsets as Prognostic Markers in Patients with Surgically Treated Laryngeal Squamous Cell Carcinoma

To evaluate the prognostic significance of tumor infiltrating lymphocytes (TILs) and of CD8+ T-cell subsets in patients with surgically treated laryngeal squamous cell carcinoma (LSCC), LSCC from 283 patients were examined. TIL density was morphologically assessed on whole sections. CD8+ cell counts/mm² were evaluated on multiple tissue microarray cores per tumor (median counts for high/low CD8+/mm²). TIL density and CD8+ counts weakly correlated with each other (Spearman's rho = 0.348). Heterogeneous CD8+ counts/mm² were demonstrated in 28% of the tumors. In univariate analysis, a significant interaction was observed between CD8 expression and nodal status with respect to outcome; in node-positive patients, those with high CD8+ tumors had 77% lower risk of relapse (interaction p < 0.001) and 74% lower risk for death (interaction p = 0.002) compared to patients with low CD8+ tumors. In multivariate analysis, higher TIL density independently conferred lower risk for relapse in the entire cohort (HR 0.87; 95% CI 0.77-0.98; Wald's p = 0.017) and in node-positive patients (HR 0.41; 95% CI 0.23-0.75; p = 0.003) and, similarly, for death (p = 0.025 and p = 0.003, respectively). High CD8+ was not a significant independent prognostic marker in any analysis setting. The assessment of CD8+ infiltrates does not seem to offer additional prognostic information over the morphologically assessed TIL density. It also appears that the favorable prognostic impact of higher TIL density and CD8+ infiltrates mostly concerns node-positive but not node-negative disease. If validated in larger node-positive cohorts, these findings are worth considering for the diagnostic development of immune cell infiltrates in LSCC.

The adequacy of tissue microarrays in the assessment of inter- and intra-tumoural heterogeneity of infiltrating lymphocyte burden in leiomyosarcoma

The characterisation and clinical relevance of tumour-infiltrating lymphocytes (TILs) in leiomyosarcoma (LMS), a subtype of soft tissue sarcoma that exhibits histological heterogeneity, is not established. The use of tissue microarrays (TMA) in studies that profile TIL burden is attractive but given the potential for intra-tumoural heterogeneity to introduce sampling errors, the adequacy of this approach is undetermined. In this study, we assessed the histological inter- and intra-tumoural heterogeneity in TIL burden within a retrospective cohort of primary LMS specimens. Using a virtual TMA approach, we also analysed the optimal number of TMA cores required to provide an accurate representation of TIL burden in a full tissue section. We establish that LMS have generally low and spatially homogenous TIL burdens, although a small proportion exhibit higher levels and more heterogeneous distribution of TILs. We show that a conventional and practical number (e.g. ≤3) of TMA cores is adequate for correct ordinal categorisation of tumours with high or low TIL burden, but that many more cores (≥11) are required to accurately estimate absolute TIL numbers. Our findings provide a benchmark for the design of future studies aiming to define the clinical relevance of the immune microenvironments of LMS and other sarcoma subtypes.

Impact of Tumor and Immunological Heterogeneity on the Anti-Cancer Immune Response

Metastatic tumors are the primary cause of cancer-related mortality. In recent years, interest in the immunologic control of malignancy has helped establish escape from immunosurveillance as a critical requirement for incipient metastases. Our improved understanding of the immune system's interactions with cancer cells has led to major therapeutic advances but has also unraveled a previously unsuspected level of complexity. This review will discuss the vast spatial and functional heterogeneity in the tumor-infiltrating immune system, with particular focus on natural killer (NK) cells, as well as the impact of tumor cell-specific factors, such as secretome composition, receptor-ligand repertoire, and neoantigen diversity, which can further drive immunological heterogeneity. We emphasize how tumor and immunological heterogeneity may undermine the efficacy of T-cell directed immunotherapies and explore the potential of NK cells to be harnessed to circumvent these limitations.

Evaluation of phospho-histone H3 in Asian triple-negative breast cancer using multiplex immunofluorescence

PURPOSE

We used multiplex immunofluorescence (mIF) to determine whether mitotic rate represents an independent prognostic marker in triple-negative breast cancer (TNBC). Secondary aims were to confirm the prognostic significance of immune cells in TNBC, and to investigate the relationship between immune cells and proliferating tumour cells.

METHODS

A retrospective Asian cohort of 298 patients with TNBC diagnosed from 2003 to 2015 at the Singapore General Hospital was used in the present study. Formalin-fixed, paraffin-embedded breast cancer samples were analysed on tissue microarrays using mIF, which combined phospho-histone H3 (pHH3) expression with cytokeratin (CK) and leukocyte common antigen (CD45) expression to identify tumour and immune cells, respectively.

RESULTS

Multivariate analysis showed that a high pHH3 index was associated with significantly improved overall survival (OS; p = 0.004), but this was not significantly associated with disease-free survival (DFS; p = 0.22). Similarly, multivariate analysis also revealed that a pHH3 positive count of > 1 cell per high-power field in the malignant epithelial compartment was an independent favourable prognostic marker for OS (p = 0.033) but not for DFS (p = 0.250). Furthermore, a high CD45 index was an independent favourable prognostic marker for DFS (p = 0.018), and there was a significant positive correlation between CD45 and pHH3 index (Spearman rank correlation coefficient, 0.250; p < 0.001).

CONCLUSIONS

Mitotic rates as determined by pHH3 expression in epithelial cells are significantly associated with improved survival in TNBC. mIF analysis of pHH3 in combination with CK and CD45 could help clinicians in prognosticating patients with TNBC.

Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non-Small Cell Lung Cancer

PURPOSE

The presence of a high degree of tumor-infiltrating lymphocytes (TIL) has been proven to be associated with outcome in patients with non-small cell lung cancer (NSCLC). However, recent evidence indicates that tissue architecture is also prognostic of disease-specific survival and recurrence. We show a set of descriptors (spatial TIL, SpaTIL) that capture density, and spatial colocalization of TILs and tumor cells across digital images that can predict likelihood of recurrence in early-stage NSCLC.

EXPERIMENTAL DESIGN

The association between recurrence in early-stage NSCLC and SpaTIL features was explored on 301 patients across four different cohorts. Cohort D1 (n = 70) was used to identify the most prognostic SpaTIL features and to train a classifier to predict the likelihood of recurrence. The classifier performance was evaluated in cohorts D2 (n = 119), D3 (n = 112), and D4 (n = 112). Two pathologists graded each sample of D1 and D2; intraobserver agreement and association between manual grading and likelihood of recurrence were analyzed.

RESULTS

SpaTIL was associated with likelihood of recurrence in all test sets (log-rank P < 0.02). A multivariate Cox proportional hazards analysis revealed an HR of 3.08 (95% confidence interval, 2.1-4.5, P = 7.3 × 10-5). In contrast, agreement among expert pathologists using tumor grade was moderate (Kappa = 0.5), and the manual TIL grading was only prognostic for one reader in D2 (P = 8.0 × 10-3).

CONCLUSIONS

A set of features related to density and spatial architecture of TILs was found to be associated with a likelihood of recurrence of early-stage NSCLC. This information could potentially be used for helping in treatment planning and management of early-stage NSCLC.See related commentary by Peled et al., p. 1449.

Changes of Tumor Infiltrating Lymphocytes after Core Needle Biopsy and the Prognostic Implications in Early Stage Breast Cancer: A Retrospective Study

PURPOSE

The purpose of this study was to investigate the changes of tumor infiltrating lymphocytes (TILs) between core needle biopsy (CNB) and surgery removed sample (SRS) in early stage breast cancer patients and to identify the correlating factors and prognostic significance of TILs changes.

Materials and Methods

A retrospective study was carried out on 255 patients who received CNB and underwent surgical resection for invasive breast cancer. Stromal TILs levels of CNB and SRS were evaluated respectively. Tumors with ≥50% stromal TILs were defined as lymphocyte-predominant breast cancer (LPBC). Clinicopathological variables were analyzed to determine whether there were factors associated with TILs changes. Log-rank tests and Cox proportional hazards models were used to analyze the influences of TILs and TILs changes on survival.

RESULTS

SRS-TILs (median, 10.0%) were significant higher than CNB-TILs (median, 5.0%; p<0.001). Younger age (<60 years, p=0.016) and long surgery time interval (STI, ≥4 days; p=0.003) were independent factors correlating with higher TILs changes. CNB-LPBC patients showed better breast cancer-free interval (BCFI, p=0.021) than CNB-non-LPBC (CNB-nLPBC) patients. Patients were categorized into four groups according to the LPBC change pattern from CNB to SRS: LPBC→LPBC, LPBC→nLPBC, nLPBC→LPBC, and nLPBC→nLPBC, with estimated 5-year BCFI 100%, 100%, 69.7%, and 86.0% (p=0.016). nLPBC→LPBC pattern was an independent prognostic factor of worse BCFI (hazard ratio, 2.19; 95% confidence interval, 1.06 to 4.53; p=0.035) compared with other patterns.

CONCLUSION

TILs were significantly higher in SRS than in CNB. Higher TILs changes were associated with younger age and long STI. Changing from nLPBC to LPBC after CNB indicated a worse BCFI, which needs further validation.

Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer

Background

We sought to investigate associations between dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) features and tumor-infiltrating lymphocytes (TILs) in breast cancer, as well as to study if MRI features are complementary to molecular markers of TILs.

Methods

In this retrospective study, we extracted 17 computational DCE-MRI features to characterize tumor and parenchyma in The Cancer Genome Atlas cohort (n = 126). The percentage of stromal TILs was evaluated on H&E-stained histological whole-tumor sections. We first evaluated associations between individual imaging features and TILs. Multiple-hypothesis testing was corrected by the Benjamini-Hochberg method using false discovery rate (FDR). Second, we implemented LASSO (least absolute shrinkage and selection operator) and linear regression nested with tenfold cross-validation to develop an imaging signature for TILs. Next, we built a composite prediction model for TILs by combining imaging signature with molecular features. Finally, we tested the prognostic significance of the TIL model in an independent cohort (I-SPY 1; n = 106).

Results

Four imaging features were significantly associated with TILs (P < 0.05 and FDR < 0.2), including tumor volume, cluster shade of signal enhancement ratio (SER), mean SER of tumor-surrounding background parenchymal enhancement (BPE), and proportion of BPE. Among molecular and clinicopathological factors, only cytolytic score was correlated with TILs (ρ = 0.51; 95% CI, 0.36–0.63; P = 1.6E-9). An imaging signature that linearly combines five features showed correlation with TILs (ρ = 0.40; 95% CI, 0.24–0.54; P = 4.2E-6). A composite model combining the imaging signature and cytolytic score improved correlation with TILs (ρ = 0.62; 95% CI, 0.50–0.72; P = 9.7E-15). The composite model successfully distinguished low vs high, intermediate vs high, and low vs intermediate TIL groups, with AUCs of 0.94, 0.76, and 0.79, respectively. During validation (I-SPY 1), the predicted TILs from the imaging signature separated patients into two groups with distinct recurrence-free survival (RFS), with log-rank P = 0.042 among triple-negative breast cancer (TNBC). The composite model further improved stratification of patients with distinct RFS (log-rank P = 0.0008), where TNBC with no/minimal TILs had a worse prognosis.

Conclusions

Specific MRI features of tumor and parenchyma are associated with TILs in breast cancer, and imaging may play an important role in the evaluation of TILs by providing key complementary information in equivocal cases or situations that are prone to sampling bias.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1039-2) contains supplementary material, which is available to authorized users.

Comparison of tumor-infiltrating lymphocytes of breast cancer in core needle biopsies and resected specimens: a retrospective analysis

PURPOSE

Neoadjuvant chemotherapy (NAC) is being increasingly used to treat locally advanced breast cancer and to conserve the breast. In triple-negative breast cancer and HER2-positive breast cancer, a high density of tumor-infiltrating lymphocytes (TILs) is an important predictor of NAC response. Thus far, it remains unclear whether the TIL scores in core needle biopsies (CNBs) are closely representative of those in the whole tumor section in resected specimens. This study aimed to evaluate the concordance between the TIL scores of CNBs and resected specimens of breast cancer.

METHODS

A total of 220 matched pairs of CNBs and resected specimens of breast cancer were included. Stromal TILs were scored on slides stained with hematoxylin and eosin. Clinicopathologic parameters and the agreement of the TIL scores between CNBs and resected specimens were statistically analyzed.

RESULTS

The average TIL score was approximately 4.4% higher for the resected specimens than for the CNBs. When the tumors were divided into two groups according to a 60% TIL score cut-off (low and intermediate TIL vs. high TIL), 8.2% showed discordance between the CNB and resected specimen. The overall intraclass correlation coefficient (ICC) value of the TIL score was 0.895 (95% confidence interval, 0.864-0.920, P < 0.001), and all molecular subtypes showed ICC values over 0.8 (P < 0.001). The ICC values were > 0.9 when ≥ 5 cores were included in the CNBs. Tumors with discordant TILs were characterized by histologic grade III, ER negativity, high proliferative index, and HER2 and triple-negative subtypes. A high proliferative index was an independent risk factor for TIL discordance.

CONCLUSIONS

The TIL score in CNB specimens is a reliable value that reflects the TIL status of the entire tumor in resected specimens of breast cancer. More than five CNB cores may accurately predict the TIL score of the entire tumor.

Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma

The goal of this study is to use computational pathology to help guide the development of human-based prognostic H&E biomarker(s) suitable for research and potential clinical use in lung squamous cell carcinoma (SCC). We started with high-throughput computational image analysis with tissue microarrays (TMAs) to screen for histologic features associated with patient overall survival, and found that features related to stromal inflammation were the most strongly prognostic. Based on this, we developed an H&E stromal inflammation (SI) score. The prognostic value of the SI score was validated by two blinded human observers on two large cohorts from a single institution. The SI score was found to be reproducible on TMAs (Spearman rho = 0.88 between the two observers), and highly prognostic (e.g. hazard ratio = 0.32; 95% confidence interval: 0.19-0.54; p-value = 2.5 × 10-5 in multivariate analyses), particularly in comparison to established histologic biomarkers. Guided by downstream molecular/biomarker correlation studies starting with TCGA cases, we investigated the hypothesis that epithelial PD-L1 expression modified the prognostic value of SI. Our research demonstrates that computational pathology can be an efficient hypothesis generator for human pathology research, and support the histologic evaluation of SI as a prognostic biomarker in lung SCCs.

Sampling strategies to capture single-cell heterogeneity

Advances in single-cell technologies have highlighted the prevalence and biological significance of cellular heterogeneity. A critical question researchers face is how to design experiments that faithfully capture the true range of heterogeneity from samples of cellular populations. Here we develop a data-driven approach, illustrated in the context of image data, that estimates the sampling depth required for prospective investigations of single-cell heterogeneity from an existing collection of samples.