Intratumoral Tumor-infiltrating Lymphocytes Research Articles

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as a predictive biomarker for immune checkpoint inhibitors in biliary tract cancer.

Anti-PD-1/L1 has been demonstrated for its efficacy when combined with cytotoxic chemotherapy in randomized phase 3 trials for advanced biliary tract cancer (BTC). However, no biomarker predictive of benefit has been established for anti-PD-1/L1 in BTC. Here, we evaluated tumor-infiltrating lymphocytes (TILs) using artificial intelligence-powered immune phenotype (AI-IP) analysis in advanced BTC treated with anti-PD-1. Pre-treatment H&E-stained whole-slide images from 339 advanced BTC patients who received anti-PD-1 as second-line treatment or beyond, were utilized for AI-IP analysis and correlative analysis between AI-IP and efficacy outcomes with anti-PD-1. Next, data and images of BTC cohort from The Cancer Genome Atlas (TCGA) were additionally analyzed to evaluate the transcriptomic and mutational characteristics of various AI-IPs in BTC. Overall, AI-IPs were classified as inflamed (high intratumoral TIL [iTIL]) in 40 patients (11.8%), immune-excluded (low iTIL and high stromal TIL) in 167 (49.3%), and immune-deserted (low TIL overall) in 132 (38.9%). The inflamed IP group showed a significantly higher overall response rate compared to the non-inflamed IP groups (27.5% vs. 7.7%, P<0.001). Median overall survival and progression-free survival were significantly longer in the inflamed IP group than in the non-inflamed IP group (OS: 12.6 vs. 5.1 months, P=0.002; PFS: 4.5 vs. 1.9 months, P<0.001). In the analysis using TCGA cohort, the inflamed IP showed increased cytolytic activity scores and an interferon-gamma signature compared to the non-inflamed IP. AI-powered IP based on spatial TIL analysis was effective in predicting the efficacy outcomes in patients with BTC treated with anti-PD-1.

Evaluation of prognostic factors for oral tongue squamous cell carcinoma: Significance of intratumoral tumor-infiltrating lymphocytes, lymph node ratio, and depth of invasion.

132 Background: Oral tongue squamous cell carcinoma (SCC) is an aggressive malignancy with a variable prognosis. Identifying reliable prognostic factors is crucial for developing personalized treatment strategies and improving patient outcomes. This study examined the prognostic significance of clinicopathological factors in oral tongue SCC. Methods: A retrospective cohort study was conducted on 192 patients who underwent surgical resection at Asan Medical Center between 2010 and 2017. Clinicopathological data, including age at diagnosis, American Joint Committee of Cancer (AJCC) 8th edition stages, depth of invasion (DOI), extranodal extension (ENE), intratumoral and stromal (invasive front) tumor-infiltrating lymphocytes (TILs), lymphovascular invasion (LVI), margin status, metastatic-to-examined lymph nodes ratio (LNR), number of metastatic lymph nodes, perineural invasion (PNI), sex, size, tumor budding, tumor differentiation, tumor-to-stromal ratio (TSR), and worst pattern of invasion (WPOI) were analyzed. The total cohort, early-stage group, and late-stage group were analyzed separately. Results: Most variables showed significant associations with the survival rate. The multivariate Cox proportional hazard models for the total cohort showed significant results for intratumoral TILs, DOI grade, and LNR. However, other factors failed to show statistical significance. Intratumoral TIL was the only consistently potent factor for survival in all study groups. Conclusions: Our findings highlight the need for increased focus on the prognostic significance of intratumoral TILs. The DOI grade and LNR were also powerful prognostic factors, especially in late-stage tongue SCCs. Our data suggest that the prognostic significance of certain variables, such as the WPOI, may have been overestimated in the literature, thereby warranting a reassessment of the currently utilized prognostic markers in oral tongue SCC.

Neoadjuvant Chemotherapy Response in Triple-Negative Apocrine Carcinoma: Comparing Apocrine Morphology, Androgen Receptor, and Immune Phenotypes.

Apocrine differentiation and androgen receptor (AR) positivity represent a specific subset of triple-negative breast cancer (TNBC) and are often considered potential prognostic or predictive factors. To evaluate the response of TNBC to neoadjuvant chemotherapy (NAC) and to assess the impact of apocrine morphology, AR status, Ki-67 labeling index (Ki-67LI), and tumor-infiltrating lymphocytes (TILs). A total of 232 TNBC patients who underwent NAC followed by surgical resection in a single institute were analyzed. The study evaluated apocrine morphology and AR and Ki-67LI expression via immunohistochemistry from pre-NAC biopsy samples. Additionally, pre-NAC intratumoral TILs and stromal TILs (sTILs) were quantified from biopsies using a deep learning model. The response to NAC after surgery was assessed based on residual cancer burden. Both apocrine morphology and high AR expression correlated with lower Ki-67LI (P < .001 for both). Apocrine morphology was associated with lower postoperative pathologic complete response (pCR) rates after NAC (P = .02), but the difference in TILs between TNBC cases with and without apocrine morphology was not statistically significant (P = .09 for sTILs). In contrast, AR expression did not significantly affect pCR (P = .13). Pre-NAC TILs strongly correlated with postoperative pCR in TNBCs without apocrine morphology (P < .001 for sTILs), whereas TNBC with apocrine morphology demonstrated an indeterminate trend (P = .82 for sTILs). Although TIL counts did not vary significantly based on apocrine morphology, apocrine morphology itself was a more reliable predictor of NAC response than AR expression. Consequently, although apocrine morphology is a rare subtype of TNBC, its identification is clinically important.

The Comprehensive Characterization of B7-H3 Expression in the Tumor Microenvironment of Lung Squamous Cell Carcinoma: A Retrospective Study.

Lung squamous cell carcinoma (LSCC) is refractory to various therapies for non-small cell cancer; therefore, new therapeutic approaches are required to improve the prognosis of LSCC. Although immunotherapies targeting B7 family molecules were explored as treatments for several cancer types, the expression and significance of B7-H3 in the tumor microenvironment (TME) and its relationship with other immune checkpoint molecules have not yet been investigated in detail. We used high-throughput quantitative multiplex immunohistochemistry to examine B7-H3 expression in the TME. We investigated the relationship between B7-H3 expression and prognosis as well as changes in the TME with B7-H3 expression using 110 surgically resected pathological specimens retrospectively. We examined the correlation between B7-H3 and programmed cell death-ligand 1 (PD-L1) expression in single cells. High B7-H3 expression in tumor cells was associated with a better prognosis and a significant increase in the number of CD163+PD-L1+ macrophages. Quantitative analysis revealed that there is a positive correlation between B7-H3 and PD-L1 expression in tumor and stromal cells, as well as in intratumoral tumor-infiltrating lymphocytes and tumor-associated macrophages in the same cells. CD68+, CD163+, and CK+ cells with PD-L1+ phenotypes had higher B7-H3 expression compared to PD-L1- cells. Our findings demonstrate a correlation between B7-H3 and PD-L1 expression in the same cells, indicating that therapies targeting B7-H3 could provide additional efficacy in patients refractory to PD-L1-targeting therapies.

Clinical, histopathological, and molecular biomarkers in a multicentric cohort of Mexican women with triple-negative breast cancer.

e13152 Background: Triple negative breast cancer (TNBC) is a heterogeneous entity with a marked variation in biological behavior, treatment responses, and patient outcomes. Thus, the investigation of clinical, histopathological, and molecular biomarkers is essential to understand this variability and potentially inform more effective management approaches across different patient profiles. Methods: We conducted a retrospective multicenter study of women &gt;18 years diagnosed with TNBC between 2006 and 2021 in two Mexican centers. We systematically gathered clinical and histopathological data, including an assessment of H&amp;E-stained slides for histopathological features and tumor-infiltrating lymphocytes (TILs), alongside immunohistochemistry analyses for androgen receptors (AR), CD8, and doublecortin-like kinase 1 (DCLK1). Statistical analyses were conducted using R version 4.3.2. Results: In our cohort, comprising 289 patients, the average age at diagnosis was 49.13 years, with a median overall survival (OS) of 63 months and a 5-year OS rate of 55%. The distribution of clinical stages at diagnosis was as follows: I (n=12, 4.2%), II (n=94, 32.5%), III (n=130, 45.0%), and IV (n=53, 18.3%). CD8 expression was higher in patients with no recurrence compared to patients with stage IV at diagnosis (p&lt;0.001), and it decreased with advancing clinical stages. We also found statistically significant differences in OS between negative and positive CD8 expression, favoring the latter (5-year OS 51.8% vs. 72.2%, p=0.032). Disease-free survival (DFS) and OS also differed significantly between low (≤10%) and high (&gt;10%) stromal TILs, favoring the high expression group (5-year DFS 51.9% vs. 70.8%, p=0.0066; 5-year OS 50.1% vs. 70.3%, p=0.0018). CD8 levels positively correlated with stromal and intratumoral TILs. Positive AR expression (&gt;10%) was seen in 8.9% of cases, with no observed differences in DFS or OS according to negative or positive status (5-year DFS 56.0% vs. 72.2%, p=0.42; 5-year OS 55.0% vs. 60.3%, p=0.68). Finally, DCLK1 positivity (≥10%) was seen in 23% of cases, with no influence on survival (negative vs. positive status, 5-year DFS 58.5% vs. 53.8%, p=0.63; 5-year OS 54.6% vs. 58.1%, p=0.60). Conclusions: Our study underscores the prognostic significance of CD8 and TILs in predicting DFS and OS among TNBC patients. Notably, the expressions of AR and DCLK1 were not independently associated with survival, although their prognostic impact in combination with other biomarkers is still an area of active research. Overall, our findings advocate for a more detailed examination of the molecular characteristics of TNBC within our demographic, encompassing an expanded array of biomarkers and a thorough investigation of the tumor microenvironment.

Abstract PO5-25-03: Immune cell infiltrate profiles in primary Triple Negative Breast Cancer and co-relation with treatment response and survival outcomes

Abstract Introduction Tumor microenvironment (TME) in breast cancer is a heterogeneous landscape with multiple cell types, each modulating the tumor progression and the disease prognosis. These cell types include lymphocytes, RBCs, stromal cells, macrophages, cancer-associated fibroblasts (CAFs), and cancer stem cells. Each cell type in the TME influences tumor progression and clinical outcomes for patients in a good or bad way, depending on the interaction with tumor cells. Tumor-infiltrating lymphocytes (TILs) are shown to be prognostic for therapy response in many cancers in the western cohorts. Our recent study showed that a higher proportion of Indian TNBC patients had intra-tumoral TILs compared to Western cohorts, and these are predictive of better response to NACT and longer disease-free survival in patients, making it a distinct finding from Western reports. In the follow-up study, we are characterizing infiltrating immune cell subtypes and their comparative association with treatment response in TNBC patients. Results from preliminary analysis and comparative analysis between responders and non-responders will be presented here. We speculate that the pro- and anti-tumorigenic immune cell population and its spatial information would help us understand TME and its precise role in response to therapy. Methods A retrospective cohort of breast cancer patients from a single one-surgeon breast cancer clinic with a uniform treatment strategy was evaluated for this study. FFPE primary tissue samples with variable TILs scores (moderate to high), taken from patients who showed complete response to the NACT treatment (n=6) and non-responding group (n=8) determined by H&amp;E stained slides from our cohort, were further stained for immune cells (Pan-B cell, Pan-T cells, Pan-macrophages) and T cells (CD4; Helper T cell marker, CD8; Cytotoxic T cell marker), FOXP; Regularly CD4+ cell marker) and PanCK (Pan-tumor marker) and counterstained with DAPI for multiplex imaging. Multispectral images for these slides were obtained using the Leica Aperio Versa system. Parameters such as individual cell types of identification and scoring, spatial proximity to tumor cells, and individual cell types will be determined by HALO software using the High plex module. Results A total of 14 TNBC samples were stained for the T-cell subtypes panel and Immune cell subtype s panel to determine the TIME. DAPI stain was used for nuclear counting based the parameters such as threshold intensity, nuclear size, roundness, and aggressiveness. The cytoplasmic size was selected as 2um beyond the outside nuclear boundary. Using Halo-Indica software, around 50000-300000 cells/tissue were evaluated across all samples from mIF whole slide scans of biopsy samples. Cell count was validated by cross-checking individual ROIs and manual cell count using Fiji. A Highplex module was used to identify individual signal positivity for each marker based on threshold intensity and cell completeness percent. Preliminary data showed a higher proportion of CD8+ cells and macrophages population are spatially closer to the tumor cells in Responders compared to non-responders. Conclusion Immune profiles are distinct among responding and non-responding patients in the Indian TNBC cohort. The association of these profiles with long-term survival in patients and various clinical and pathological parameters will help us determine the clinical relevance of these profiles and identify distinct immune subgroups as prognostic in Indian TNBCs. Citation Format: Pooja Vaid, Devaki Kelkar, LS Shashidhara, C B Koppiker, Madhura Kulkarni. Immune cell infiltrate profiles in primary Triple Negative Breast Cancer and co-relation with treatment response and survival outcomes [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-25-03.

Abstract 7515: Enhancing immune checkpoint inhibitor efficacy with fulvestrant in estrogen receptor-positive breast cancer

Abstract Introduction: Breast cancer (BC) recurs decades after initial treatment that consists majority of the annual 43,000 BC deaths. Thus, Immune Checkpoint Inhibitor (ICI) therapy that bolster anti-cancer immunity is expected to improve long-term survival with reduced recurrence. Neoadjuvant ICI revolutionized management of triple negative breast cancer (TNBC); however, this represents only 5-7% of all BC cases, where estrogen receptor (ER)-positive subtype that consists of 70% of all BCs is not indicated due to less tumor-infiltrating lymphocytes (TILs). Using I-SPY2 trial we aim to investigate the potency of ER-alpha gene (ESR1) expression as a predictive biomarker, and whether the inhibition of the ER with fulvestrant enhances the efficacy of ICIs in ER+ BC. Methods:Total of 1157 BC patients from two independent cohorts (ISPY2 trial; n= 73, TCGA; n = 1084) were included, encompassing both clinical and transcriptomic profiles. The TIL score was determined using the xCell algorithm. Results:Using the transcriptome of the ISPY2 trial, we found that compared to ESR1 low expression patients, ESR1 high patients were associated with significantly lower pCR rates after neoadjuvant immunotherapy with ICI in whole cohort (n=71, pCR rate=30%, p&amp;lt;0.05) and HR+ subtype (n=50, pCR rate=20%, p&amp;lt;0.001), but not in triple-negative breast cancer (TNBC). ESR1 expression outperformed PD-1, PD-L1, and CTLA4 in Area Under the Curve (AUC) of the whole ISPY2 cohort (AUC=0.75, 0.68, 0.48, and 0.62, respectively), and further pronounced in HR+ BC (AUC=0.88, 0.73, 0.55, and 0.65, respectively), suggesting the potency of ESR1 expression as a predictive biomarker for ICI in HR+ BC. In agreement, ESR1 expression inversely correlated with the amount of intratumoral TILs consistently in both ISPY2 and TCGA cohorts in HR+ BC, but only in TCGA in whole cohort (all p&amp;lt;0.05). Among the intratumoral TILs, CD8+ T cell and M1 Macrophages were found to be less infiltrated in HR+ BC in TCGA. Given that ESR1 expression was associated with less intratumoral TILs and a poor response to ICI, we hypothesized that suppression of ER-alpha would enhance the effectiveness of ICI in HR+ BC in vitro. ER-alpha positive MCF7 cells were incubated with activated peripheral blood mononuclear cells with 1:1 ratio, and treated with 0.1 microgram of anti-PDL1, and 1nM of ER antagonist, fulvestrant, which demonstrated minimum cell killing. We found that ICI therapy with anti-PDL1 significantly decreased the cell viability of the MCF7 cells when ER-alpha expression was suppressed by fulvestrant, while activated peripheral blood mononuclear cells or anti-PDL1 alone or the combination did not exhibit any significant cell killing. Conclusion: We found that ESR1 expression is a predictive biomarker of ICI, and ER antagonist fulvestrant enhances the response of HR+ BC to ICI, suggesting that this combination could expand ICI indications to HR+ BC. Citation Format: Jun Arima, Kohei Chida, Masanori Oshi, Arya Mariam Roy, Kohei Taniguchi, Sang-Woong Lee, Kazuaki Takabe. Enhancing immune checkpoint inhibitor efficacy with fulvestrant in estrogen receptor-positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7515.

Prognostic value and distribution pattern of tumor infiltrating lymphocytes and their subsets in distant metastases of advanced breast cancer

BackgroundThere are significant correlations between the levels of tumor infiltrating lymphocytes (TILs) and the prognosis of primary breast cancer. While little is known about immunological mechanisms in the distant metastasis of advanced breast cancer. Patients and MethodsA total of 106 patients with advanced metastatic breast cancer were enrolled in this study between 2016 and 2022. Hematoxylin and eosin staining and immunohistochemistry were used to assess the densities of stromal TILs (sTILs), intratumoral TILs (iTILs) and invasive marginal TILs (imTILs) and CD4+, CD8+, CD20+, FOXP3+ TILs in the primary tumor and metastasis (bone, lung, liver, and distant lymph node) of advanced breast cancer. ResultsHigher levels of sTILs at metastatic sites were associated with better progression-free survival (PFS), postmetastasis survival (PMS) and overall survival (OS) (p = .026, .001 and .005, respectively). The levels of iTILs were significantly lower than those of sTILs and imTILs in both primary tumor (p< .001, both) and metastasis (p< .001, both). The level of CD4+ T cells was higher than those of CD8+ T cells and CD20+ B cells in both primary tumor (p < .001) and metastasis (p < .001). The levels of sTILs (p=0. 001) and imTILs (p< .001) in the primary tumor were generally higher than those in the metastasis. ConclusionThe levels of TILs and their subsets can predict the survival and prognosis of patients with advanced breast cancer. The distributions of TILs and their subsets are similar between the primary tumor and metastasis. The metastases have a lower degree of lymphocytes infiltration than its corresponding primary tumor.

Predicting Neoadjuvant Treatment Response in Triple-Negative Breast Cancer Using Machine Learning.

Neoadjuvant chemotherapy (NAC) is the standard treatment for early-stage triple negative breast cancer (TNBC). The primary endpoint of NAC is a pathological complete response (pCR). NAC results in pCR in only 30-40% of TNBC patients. Tumor-infiltrating lymphocytes (TILs), Ki67 and phosphohistone H3 (pH3) are a few known biomarkers to predict NAC response. Currently, systematic evaluation of the combined value of these biomarkers in predicting NAC response is lacking. In this study, the predictive value of markers derived from H&E and IHC stained biopsy tissue was comprehensively evaluated using a supervised machine learning (ML)-based approach. Identifying predictive biomarkers could help guide therapeutic decisions by enabling precise stratification of TNBC patients into responders and partial or non-responders. Serial sections from core needle biopsies (n = 76) were stained with H&E and immunohistochemically for the Ki67 and pH3 markers, followed by whole-slide image (WSI) generation. The serial section stains in H&E stain, Ki67 and pH3 markers formed WSI triplets for each patient. The resulting WSI triplets were co-registered with H&E WSIs serving as the reference. Separate mask region-based CNN (MRCNN) models were trained with annotated H&E, Ki67 and pH3 images for detecting tumor cells, stromal and intratumoral TILs (sTILs and tTILs), Ki67+, and pH3+ cells. Top image patches with a high density of cells of interest were identified as hotspots. Best classifiers for NAC response prediction were identified by training multiple ML models and evaluating their performance by accuracy, area under curve, and confusion matrix analyses. Highest prediction accuracy was achieved when hotspot regions were identified by tTIL counts and each hotspot was represented by measures of tTILs, sTILs, tumor cells, Ki67+, and pH3+ features. Regardless of the hotspot selection metric, a complementary use of multiple histological features (tTILs, sTILs) and molecular biomarkers (Ki67 and pH3) resulted in top ranked performance at the patient level. Overall, our results emphasize that prediction models for NAC response should be based on biomarkers in combination rather than in isolation. Our study provides compelling evidence to support the use of ML-based models to predict NAC response in patients with TNBC.

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes for prediction of prognosis in resected colon cancer

Tumor-infiltrating lymphocytes (TIL) have been suggested as an important prognostic marker in colorectal cancer, but assessment usually requires additional tissue processing and interpretational efforts. The aim of this study is to assess the clinical significance of artificial intelligence (AI)-powered spatial TIL analysis using only a hematoxylin and eosin (H&E)-stained whole-slide image (WSI) for the prediction of prognosis in stage II–III colon cancer treated with surgery and adjuvant therapy. In this retrospective study, we used Lunit SCOPE IO, an AI-powered H&E WSI analyzer, to assess intratumoral TIL (iTIL) and tumor-related stromal TIL (sTIL) densities from WSIs of 289 patients. The patients with confirmed recurrences had significantly lower sTIL densities (mean sTIL density 630.2/mm2 in cases with confirmed recurrence vs. 1021.3/mm2 in no recurrence, p < 0.001). Additionally, significantly higher recurrence rates were observed in patients having sTIL or iTIL in the lower quartile groups. Risk groups defined as high-risk (both iTIL and sTIL in the lowest quartile groups), low-risk (sTIL higher than the median), or intermediate-risk (not high- or low-risk) were predictive of recurrence and were independently associated with clinical outcomes after adjusting for other clinical factors. AI-powered TIL analysis can provide prognostic information in stage II/III colon cancer in a practical manner.

The Value of Tumor Infiltrating Lymphocytes (TIL) for Predicting the Response to Neoadjuvant Chemotherapy (NAC) in Breast Cancer according to the Molecular Subtypes.

The antitumor host immune response is an important factor in breast cancer, but its role is not fully established. The role of tumor infiltrating lymphocytes (TIL) as an immunological biomarker in breast cancer has been significantly explored in recent years. The number of patients treated with neoadjuvant chemotherapy (NAC) has increased and the identification of a biomarker to predict the probability of pCR (pathological complete response) is a high priority. We evaluated 334 cases of BC treated with NAC followed by surgical resection from 2020-2022 at the Ist Clinic of Oncological Surgery, Oncological Institute "Prof Dr I Chiricuta" Cluj Napoca. Of the above, 122 cases were available for histological evaluation both in pre-NAC biopsy and post-NAC resection tissue. Evaluation of biopsy fragments and resection parts were performed using hematoxylin eosin (H&E). The TIL evaluation took place according to the recommendations of the International TIL Working Group (ITILWG). There was a strong association between elevated levels of pre-NAC TIL. At the same time, there is a statistically significant correlation between stromal TIL and tumor grade, the number of lymph node metastases, the molecular subtype and the number of mitoses (p < 0.005). Intratumoral TIL showed a significant correlation with tumor size, distant metastasis, molecular subtype, number of mitosis, stage and lymph node metastasis (p < 0.005). We also demonstrated that high pre-NAC STIL represents a strong predictive marker for pCR. This study reveals the role of TIL as a predictive biomarker in breast cancer not only for the well-established TNBC (triple negative breast cancer) and HER2+ (Her2 overexpressed) subtypes but also in Luminal A and B molecular subtypes. In this scenario, the evaluation of sTIL as a novel predictive and therapy-predicting factor should become a routinely performed analysis that could guide clinicians when choosing the most appropriate therapy.

The Peritumoral CD8+/FOXP3+ Cell Ratio Has Prognostic Value in Triple-negative Breast Cancer.

Compelling data has demonstrated the prognostic significance of tumor-infiltrating lymphocytes (TILs) in triple-negative breast cancer (TNBC), a subtype generally associated with a poor clinical outcome but highly heterogeneous in nature. There have been limited studies investigating the importance of subsets of T cells in TILs. Further, the significance of intratumoral versus peritumoral TILs remains controversial. We examined the prognostic value of tumor-associated CD8+ cytotoxic T cells and FOXP3+ regulatory T cells in 35 chemotherapy-naive TNBC cases with a tumor-host interface in the tissue sections. The CD8+ and FOXP3+ cell count was expressed by immunoreactive cells per high-power field in an average of 10 high-power fields. There was a wide range of CD8+ and FOXP3+ T cells within the peritumoral and intratumoral stroma. Both CD8+ and FOXP3+ TILs were significantly higher at the former location as compared with the latter (P<0.0001 and 0.003, respectively). The numbers of CD8+ and FOXP3+ T cells, either within peritumoral or intratumoral stroma, were not significantly associated with distant relapse-free or disease-specific survival. However, the peritumoral CD8+/FOXP3+ ratio of TILs was significantly associated with prolonged relapse-free survival (P=0.04) and disease-specific survival (P=0.02). This association was not observed with the CD8+/FOXP3+ ratio of intratumoral TILs. These observations suggest that the immunologic balance in the tumor microenvironment might determine antitumor immunity. Further, the peritumoral TILs appear to play a more important role in the progression of TNBC when compared with the intratumoral TILs, thus reaffirming the necessity of revisiting the method for the assessment of TILs.

Artificial intelligence (AI)-powered HER2 quantification continuous score (QCS) and tumor microenvironment (TME) analysis in HER2-amplified metastatic colorectal cancer (mCRC) treated with pertuzumab plus trastuzumab.

34 Background: Pertuzumab plus trastuzumab (per-/tra-) has shown clinical benefits in patients (pts) with HER2-amplified mCRC, but still there is an unmet need of biomarkers to optimize treatment decisions. In this study, we applied AI-powered whole-slide image (WSI) analyzers, to investigate the association of HER2 QCS and TME with clinical outcomes of per-/tra- in pts with HER2-amplified mCRC enrolled in TRIUMPH, a phase II study. Methods: TRIUMPH is a multicenter phase II study to evaluate the efficacy of per-/tra- in pts with mCRC with HER2 amplification confirmed by tumor tissue or circulating tumor DNA (ctDNA) analysis. HER2 immunohistochemistry (IHC) and H&amp;E-stained WSIs from 30 pts enrolled in TRIUMPH were included in the analysis. AI-powered WSI analyzers, Lunit SCOPE HER2 and Lunit SCOPE IO (Lunit, Republic of Korea) detects tumor cells (TC) by HER2 staining intensity (negative, 1+, 2+, or 3+) in HER2-WSI, and detects various class of cells including tumor-infiltrating lymphocytes (TIL), macrophages and fibroblasts in H&amp;E-WSI, respectively. Immune-excluded score (IES) was defined as the proportion of high stromal TIL but low intratumoral TIL area in all analyzable TME. Tumor response was measured by RECIST v1.1, and the primary endpoint was progression-free survival (PFS) assessed by the investigators. Results: All 30 tumor samples had proven HER2-amplification by either HER FISH or ctDNA analysis. The concordance rate between pathologists and AI to examine HER2 IHC was 86.7% (26/30), AI-powered HER2 QCS showed the proportion of HER2 3+ TC was widely distributed (median 73.9%; min-max 11.9%-98.9%) in the samples with HER2 3+ assessed by pathologists. Objective response rates (ORR) of per-/tra- in the whole set and a subgroup of HER2 IHC 3+ assessed by pathologists were 26.7% (8/30) and 34.8% (8/23), respectively. AI-powered HER2 QCS enabled enrichment of responders, as a subgroup of HER2 3+ QCS ≥ 50%, which is a higher cutoff than ASCO/CAP guideline (10%), had 42.1% (8/19) ORR, since all 8 responders harbored HER2 3+ QCS ≥ 50%. PFS and overall survival (OS) were significantly favorable in HER2 3+ QCS ≥ 50% group compared to &lt; 50% group (median PFS [mPFS] 4.4 vs 1.4 m, hazard ratio [HR] 0.12 [95% CI, 0.04-0.38], p = 0.0000994; median OS [mOS] 16.5 vs 4.1 m, HR 0.13 [95% CI, 0.05-0.38], p = 0.000117, respectively). Interestingly, IES and the densities of macrophages and fibroblasts within cancer stroma were correlated with poor response to per-/tra-. Among HER2 3+ QCS ≥ 50% group, 5 pts with high IES (≥ 54%), macrophage density (≥ 26.3/mm2), and fibroblast density (≥ 1790/mm2) had ORR 0%, mPFS 1.3 m, and mOS 4.5 m. Conclusions: AI-powered HER2 QCS and TME analysis may provide additional information to precisely predict per-/tra- response in HER2-positive mCRC.

Intratumoral Tumor Infiltrating Lymphocytes (TILs) are Associated With Cell Proliferation and Better Survival But Not Always With Chemotherapy Response in Breast Cancer.

To investigate the clinical relevance of intratumoral tumor infiltrating lymphocytes (TILs) in breast cancer as measured by computational deconvolution of bulk tumor transcriptomes. Commonly assessed TILs, located in tumor stroma without direct contact with cancer cells (stromal TILs), correlate with breast cancer treatment response and survival. The clinical relevance of intratumoral TILs has been less studied partly due to their rarity; however, they may have nonnegligible effects given their direct contact with cancer cells. In all, 5870 breast cancer patients from TCGA, METABRIC, GSE96058, GSE25066, GSE163882, GSE123845, and GSE20271 cohorts were analyzed and validated. The intratumoral TIL score was established by the sum of all types of lymphocytes using the xCell algorithm. This score was the highest in triple-negative breast cancer (TNBC) and the lowest in the ER-positive/HER2-negative subtype. It correlated with cytolytic activity and infiltrations of dendritic cells, macrophages, and monocytes, and uniformly enriched immune-related gene sets regardless of subtype. Intratumoral TIL-high tumors correlated with higher mutation rates and significant cell proliferation on biological, pathological, and molecular analyses only in the ER-positive/HER2-negative subtype. It was significantly associated with pathological complete response after anthracycline- and taxane-based neoadjuvant chemotherapy in about half of the cohorts, regardless of the subtype. Intratumoral TIL-high tumors correlated with better overall survival in HER2-positive and TNBC subtypes consistently in 3 cohorts. Intratumoral TILs estimated by transcriptome computation were associated with increased immune response and cell proliferation in ER-positive/HER2-negative and better survival in HER2-positive and TNBC subtypes, but not always with pathological complete response after neoadjuvant chemotherapy.

Association of tumor-infiltrating lymphocytes (TILs) with clinicopathologic characteristics and prognosis in young women with HR+/HER2- breast cancer (BC).

505 Background: Increased TILs are associated with better prognosis in triple-negative BC, including in patients (pts) age &lt; 40. However, the role of TILs remains unclear in HR+/HER2- BC and little data exist in young pts, in whom immune microenvironment could be altered by age-related host/tumor differences. We assessed the extent and composition of immune infiltration in HR+ tumors of young women and correlated with clinicopathologic features and survival outcomes. Methods: From a prospective cohort study of women with BC diagnosed age ≤40, we identified those with stage I-III HR+/HER2- BC and available pre-treatment (tx) tumor tissue. Multiplexed immunofluorescence was used to quantify cytotoxic T (CD8+), T helper (Th, CD3+CD8-), T regulatory (Tregs, FOXP3+CD3+) and exhausted T (PD1+CD8+) cells in stroma and tumor. Univariate analyses tested associations between clinicopathologic variables and immune markers by high or low expression, divided based on median. High vs. low TILs were evaluated in Cox regression analyses for invasive breast cancer-free survival (iBCFS), distant disease-free survival (DDFS) and overall survival (OS). Results: In 390 pts, median age was 37 years (21-40), most had grade 2 (51%), T1 (65%), N0 (63%) tumors and 67% received adjuvant chemotherapy. Black pts (n = 17) had higher expression of stromal CD8+ ( P= .010), FOXP3+CD3+ ( P= .027) and PD1+CD8+ TILs ( P= .043); intratumoral TILs did not differ by race. Older age (36-40) was associated with high expression of CD8+ ( P= .033) and PD1+CD8+ TILs ( P= .031) within stroma and CD3+CD8- TILs within tumor ( P= .046). Grade 3 tumors had higher stromal and intratumoral expression of CD3+CD8- ( P= .002; P&lt; .001) and FOXP3+CD3+ TILs ( P= .020; P&lt; .001). No differences in TILs were seen according to recency of pregnancy, BRCA1/2 status or T/N stage. Over a median follow up of 8 years, 85 iBCFS events, 64 DDFS events and 37 deaths occurred. High stromal expression of CD3+CD8- TILs was associated with better iBCFS (HR 0.49, P= .002) and DDFS (HR 0.57, P= .046), which remained significant when adjusted for T/N stage, grade and chemotherapy (iBCFS HR 0.41, P&lt; .001; DDFS HR 0.45, P= .008). High stromal expression of CD3+CD8- and FOXP3+CD3+ TILs was associated with better OS (HR 0.47, P= .038) and iBCFS (HR 0.58, P= .018), respectively, on adjusted analyses only. High intratumoral expression of CD3+CD8- and FOXP3+CD3+ TILs was associated with better iBCFS (HR 0.59, P= .025; HR 0.63, P= .043) after adjustment only. Conclusions: The distribution of TIL subtypes in young women’s HR+ BC varied according to race, age and grade. High stromal and intratumoral expression of Th and Tregs was associated with improved BC outcomes. Characterization of immune cell subsets could help refine the prognostic value of TILs in HR+ BC, particularly in young pts who may benefit from individualized escalated/de-escalated tx strategies.

Dynamic change of immune phenotype assessed by artificial intelligence (AI)-powered analysis of tumor-infiltrating lymphocytes (TILs) during neoadjuvant durvalumab with or without tremelimumab (D+/-T) in head and neck squamous cell carcinoma (HNSCC).

2578 Background: The results of a phase II trial evaluating preoperative durvalumab with or without tremelimumab (D+/-T) in resectable HNSCC (NCT03737968) suggest that the neoadjuvant immunotherapy is associated with pathologic tumor regression with manageable safety profiles. Here, we applied AI-powered spatial TIL analyzer, Lunit SCOPE IO, to tumor specimens of the patients included in the trial to assess the impact of spatial TIL density and inflamed immune phenotype (IIP) on immunotherapy responses. Methods: H&amp;E-stained whole-slide images (WSIs) of pre- and post-treatment tumor specimens from HNSCC pts enrolled in the aforementioned D+/-T trial were collected. Patients with locally advanced but operable HNSCC were randomly assigned in 1:1 to receive a single dose of D (1,500mg) or D+T (1,500mg+75mg) followed by surgery, at Severance Hospital in Seoul, Korea. Lunit SCOPE IO was used to segment tumor epithelium and stroma to identify and quantify intratumoral TIL (iTIL) and stromal TIL. IIP was defined as the proportion of high iTIL area more than 33.3% of analyzable area. Clinical data and the combined positive scores (CPS) of PD-L1 were also collected. Results: A total of 39 paired tumor samples of pre- and post-treatment WSI (23 from D+T and 16 from D) were included. Overall, tumor regression grade 2 (TRG2, ≥ 50% of tumor regression) was achieved in 15.4% (6/39) pts, and downstaging after treatment was achieved in 35.9% (14/39) pts. By pre-treatment WSIs, 38.5% (15/39) samples were classified as IIP, and subgroups of D+T and D had 34.8% (8/23) and 43.8% (7/16), respectively. In the D+T arm, the proportions of TRG2 were 25% (2/8) in IIP versus 13.3% (2/15) in non-IIP, whereas D arm had 28.6% (2/7) TRG2 in IIP, but no TRG2 in non-IIP (0/9), respectively. Comparing the WSI of pre- and post- D+/-T samples, the proportion of IIP was significantly increased to 66.7% from 38.5 ( p = 0.015). The increase in IIP proportion was prominent in the D+T arm (34.8% to 69.6%, p = 0.043), but not in the D arm (43.8% to 62.5%, p = 0.37). Similarly, PD-L1 CPS increased after therapy, especially in the D+T group (mean CPS 6.0 to 20.7, p = 0.009). Interestingly, pts who remained non-IIP in both pre- and post-treatment (25.6%, 10/39) had significantly poor prognosis compared to the others, as the 12-month disease-free survival (DFS) rate was 50.0% vs 93.1% (median DFS 13.4m vs not reached, hazard ratio [HR] 4.26, 95% confidence interval [CI] 1.32-13.8, p = 0.009). This prognostic impact was prominent in the D+T arm (HR 6.75, 95% CI 1.49-30.6, p = 0.004). Conclusions: Neoadjuvant durvalumab +/- tremelimumab promotes dynamic change toward inflamed immune phenotype, resulting in favorable clinical outcomes. Resistance mechanism of stand-still-non-inflamed patients even on D+/-T should be further investigated. Clinical trial information: NCT03737968 .

Relationship between tumor microenvironment (TME)-based histomic TGFβ signature (TGFBs), stromal fibroblast recruitment, and exclusion of immune cells as immunotherapy resistance mechanisms.

2585 Background: TGF-beta activates fibroblasts within the TME and may be associated with poor response to immunotherapy.However, objective and reliable assessment of the TGFBs by gene expression profiling (GEP) is challenging. Using H&amp;E whole-slide images (WSI) from The Cancer Genome Atlas (TCGA), we developed an artificial intelligence (AI) model to predict a normalized TGFBs, applying it to real-world datasets (RWDs) of advanced solid tumor patients treated with immunotherapy. Methods: The TGFBs was defined using the mean GEP values of the 'Hallmark TGF-beta signaling' gene set. H&amp;E WSIs of 23 carcinoma types from TCGA (n=6,945) were used to discover the association of the TGFBs with various cell types, including fibroblasts and tumor-infiltrating lymphocytes (TILs) detected by an AI model, Lunit SCOPE IO (AI-1). Another custom AI model (AI-2) to predict TGFBs was developed by integrating self-supervised and supervised features and other semantic content extracted by AI-1 with multilayered perceptron classifiers. TGFBs prediction scores from the AI-2 were applied to 5 different RWDs containing 1,792 immunotherapy-treated patients (&gt; 16 primary tumor types). The immune-excluded phenotype (IEP) was defined by high stromal TIL and low intratumoral TIL density. Results: In the TCGA dataset, TGFBs and fibroblast density detected by AI-1 were closely correlated (R=0.19, p&lt;0.001) compared to other cell types, with both highest in pancreatic adenocarcinoma (PAC)(median [interquartile range, IQR] 0.73 [0.66-0.80], 1306 [985-1588]/mm2, respectively) and CMS4 colorectal cancer (0.61 [0.54-0.67], 868 [582-1128]/mm2) compared to other cancers (0.57 [0.47-0.66], 577 [295-890]/mm2). The AI-2 predicted TGFBs with area-under-the-curve of 0.781 on cross-validation within the TCGA dataset. The TGFBs of immunotherapy-treated RWDs were inferred from their corresponding H&amp;E WSI, with scores comparable to those from the TCGA (0.42 [0.16-0.60] vs 0.58 [0.48-0.67]), with PAC having the highest TGFBs (0.65 [0.45-0.77]) in the RWD as well. Interestingly, TGFBs inferred scores and fibroblast density were significantly correlated (R=0.7, p&lt;0.001) in the RWD and also significantly correlated with the IEP (0.52 [0.30-0.66]) compared to other immune phenotypes (0.42 [0.16-0.60], p&lt;0.001). In the RWD, patients with inferred TGFBs in the upper 75% quartile had a poor clinical response to immunotherapy (objective response rate: 15.1% vs 20.7%, median progression-free survival 3.0 m vs 4.0 m, hazard ratio 1.21, 95% confidence interval 1.07-1.36, p=0.002). Conclusions: TGFBs is closely correlated with fibroblast density within the TME and may confer resistance to immunotherapy. Unique morphologic features of the TGFBs can be captured by AI, enabling scalable application to various datasets for clinical and translational research.

Artificial intelligence (AI) –powered spatial analysis of macrophages in tumor microenvironment and its association with interferon-gamma (IFNG) signature and immune phenotype (IP) in pan-cancer dataset.

2621 Background: Macrophages are known to play a crucial role in cancer progression, but few studies have reported macrophage spatial distribution and its association with genomic signatures and tumor-infiltrating lymphocytes (TIL). Here, we applied an AI-powered Whole Slide Image (WSI) analyzer in The Cancer Genome Atlas (TCGA) pan-cancer dataset to show correlation between specific localization of macrophage and anti-tumor activity, which is reflected by IFNG signature and IP based on spatial TIL density. Methods: For spatial macrophage analysis in TCGA pan-cancer dataset, we used Lunit SCOPE IO, an AI-powered H&amp;E WSI analyzer, which identifies and quantifies various classes of cells such as tumor cell, macrophage, and TIL within cancer or stroma area. IPs were defined as follows: inflamed IP (IIP) as high intratumoral TIL (iTIL) and stromal TIL (sTIL); immune-excluded IP (IEP) as low iTIL and high sTIL; immune-desert IP (IDP) as low TIL overall. The immune cell profiling and quantification of the IFNG signature score were analyzed by using CIBERSORT and RSEM. Results: In TCGA dataset (N = 7,402), median macrophage density in total TME area (tMP) was 19.9 /mm2 (interquartile range [IQR] 9.0-44.9), and it was highly enriched in lung adenocarcinoma (median 65.1, IQR 34.3-110.0), lung squamous cell carcinoma (61, 32.4-101.3), and head and neck squamous cell carcinoma (39.4, 19.6-77.3). Based on IP classification, tMP was highly enriched in IIP (37.8, 18.7-73.8) compared to IEP (25.5, 13.8-48.6) and IDP (8.9, 4.4-17.1). Interestingly, spatial analysis showed that intratumoral macrophage density (iMP) in IIP was highly enriched compared to the others (mean fold change 2.57) and the difference of stromal macrophage density (sMP) among IPs was relatively smaller (mean fold change x1.85). Classified into four groups based on median values of iMP and sMP, high-iMP/high-sMP group had the highest proportion of IIP (47.3% vs 18.7%, p &lt; 0.001), whereas low-iMP/high-sMP group had the highest one of IEP (54.9% vs 32.3%, p &lt; 0.001) compared to the others, respectively. Moreover, the high-iMP/high-sMP group had the highest level of IFNG signature score among 4 groups (x2.13 times higher, p &lt; 0.001). Notably, both iMP and sMP were significantly correlated with CD68 expression (rho 0.292 and 0.287) but CSF1R expression was more strongly correlated with iMP (rho 0.259) compared to sMP (rho 0.078). Conclusions: IIP, IFNG signature, and CSF1R expression are more strongly correlated with intratumoral macrophage density versus stromal macrophage density, suggesting a relationship between macrophage location and function in the TME warranting further investigation.

Prediction of clinicopathological features, multi-omics events and prognosis based on digital pathology and deep learning in HR+/HER2- breast cancer.

Breast cancer has the highest incidence and mortality rates among women worldwide. Hormone receptor (HR)+/human epidermal growth factor receptor 2 (HER2)- breast cancer is the most common molecular subtype, accounting for 50-79% of breast cancers. Deep learning has been widely used in cancer image analysis, especially for predicting targets related to precise treatment and patient prognosis. However, studies focusing on therapeutic target and prognosis predicting in HR+/HER2- breast cancer are lacking. This study retrospectively collected hematoxylin and eosin (H&E)-stained slides of HR+/HER2- breast cancer patients between January 2013 and December 2014 at Fudan University Shanghai Cancer Center (FUSCC) and scanned to generate whole-slide images (WSIs). Then, we built a deep-learning-based workflow to train and validate model to predict clinicopathological features, multi-omics molecular features and prognosis; the area under the curve (AUC) of the receiver operating characteristic (ROC) and the concordance index (C-index) of the test set were used to assess model effectiveness. A total of 421 HR+/HER2- breast cancer patients were included in our study. Regarding clinicopathological features, grade III could be predicted with an AUC of 0.90 [95% confidence interval (CI): 0.84-0.97]. Regarding somatic mutations, TP53 and GATA3 mutation could be predicted with AUCs of 0.68 (95% CI: 0.56-0.81) and 0.68 (95% CI: 0.47-0.89), respectively. Regarding gene set enrichment analysis (GSEA) pathways, the G2-M checkpoint pathway was predicted with an AUC of 0.79 (95% CI: 0.69-0.90). Regarding markers of immunotherapy response, intratumoral tumor-infiltrating lymphocytes (iTILs), stromal tumor-infiltrating lymphocytes (sTILs), CD8A, and PDCD1 were predicted with AUCs of 0.78 (95% CI: 0.55-1.00), 0.76 (95% CI: 0.65-0.87), 0.71 (95% CI: 0.60-0.82), and 0.74 (95% CI: 0.63-0.85), respectively. In addition, we found that the integration of clinical prognostic variables and deep features of images can improve the stratification of patient prognosis. Using a deep-learning-based workflow, we developed models to predict the clinicopathological features, multi-omics features and prognosis of patients with HR+/HER2- breast cancer using pathological WSIs. This work may contribute to efficient patient stratification to promote the personalized management of HR+/HER2- breast cancer.

Abstract 2032: Intratumoral tumor infiltrating lymphocytes is associated with cell proliferation and better survival but not with response to chemotherapy

Abstract Introduction: Abundance of tumor infiltrated lymphocytes (TILs) in the peripheral region of tumor assessed pathologically is associated with improved response to chemotherapy and better prognosis in Her2+ and triple-negative breast cancer (TNBC). Since recent progress in bioinformatics has allowed for computational deconvolution of bulk tumor, we investigated the clinical relevance of intratumoral TILs in primary breast cancer and response to neoadjuvant chemotherapy (NAC). Methods: A total of 4139 bulk tumor RNA sequencing data were analyzed for the association of high intratumoral TILs with clinicopathologic factors and biology in primary breast cancer cohorts of TCGA and SCAN-B. Total of 1719 bulk samples from three other cohorts (GSE163882, GSE25066, and GSE194040) were utilized to investigate the association between pathologic complete response rate (pCR) to neoadjuvant chemotherapy and intratumoral TILs. Results: Among several deconvolution algorithms, the sum of xCell lymphocytes was chosen to estimate intratumoral TIL since it correlated the strongest with multiple signals that represent lymphocytes. The cohorts were divided into high or low TIL tumor by median cut-off, and number of TILs in high-TIL ER+/Her2- was roughly the same as that of low-TIL TNBC. As expected, high TILs were associated with better disease specific survival in Her2+ and TNBC subtypes consistently in TCGA and SCAN-B cohorts. Immune-related gene sets were uniformly enriched to high TIL tumors regardless of subtype, and the difference in cytolytic activity by TILs were the largest in TNBC. Macrophages, dendritic cells, lymphatic and blood endothelial cells were infiltrated in TIL high tumors. Thus, estimated intra-tumor TILS showed similar immune-related characteristics with pathology-assessed TILs. However, ER+/Her2- was most strongly correlated with cell proliferation biologically, pathologically, and molecular biologically. High TIL was significantly associated with higher mutation related scores only in ER+HER2-. Unexpectedly, intratumoral TILs and all the types of lymphocytes showed low AUC for predicting pCR to NAC (AUC &amp;lt; 0.6). Gene expression-based scores generated by LASSO model showed low AUC in all the cohorts neither (AUC &amp;lt; 0.65). Conclusion: Transcriptomic signature of Intratumoral TILs is associated with cell proliferation in ER+HER2- breast cancer and better survival in HER2+ breast cancer and TNBC but is not as consistently associated with response to neoadjuvant chemotherapy as pathologically assessed TILs. Citation Format: Rongrong Wu, Masanori Oshi, Mariko Asaoka, Masayuki Nagahashi, Li Yan, Yasuo Miyoshi, Takashi Ishikawa, Kazuaki Takabe. Intratumoral tumor infiltrating lymphocytes is associated with cell proliferation and better survival but not with response to chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2032.